• Molecular Strategies to Distinguish Key Subphenotypes in Sarcoidosis

      Garcia, Joe G. N.; Casanova, Nancy Gonzalez; Gomez, Jorge; Culver, Melanie; Bime, Christian; Sun, Xiaoguang (The University of Arizona., 2020)
      Sarcoidosis is a multisystemic disease of unknown etiology and unpredictable course, characterized by histopathological conglomerates of inflammatory cells defined as granulomas. These lesions however are non-pathognomonic, and in the absence of an identifiable etiologic agent, there are not specific diagnostic test for sarcoidosis. Despite the variable course of sarcoidosis, the lungs are affected in 90 percent of the cases. Approximately 25-30% of sarcoidosis patients progress to a complicated phenotype with progressive disease, leading to pulmonary fibrosis and organ dysfunction with increased mortality. These cases are in desperate need for biomarkers, conventional sarcoidosis biomarkers have proven to be insufficiently sensitive for implementation in routine clinical care. In this dissertation, I focused on the use of alternate strategies for biomarkers development utilizing genomic base approaches based on high-throughput molecular assays to characterize genotype, gene expression, and epigenetics that define sarcoidosis subphenotypes. Our results demonstrated that the integration of expression quantitative loci (eQTL) studies increase the power of Genome-wide association studies (GWAS). We identified SNPs that were associated to complicated sarcoidosis in African Americans (AA) and in European Americans (EA), and then we validated these SNPs by Massarray. Furthermore, at the transcript level, we identified the Peripheral Mononuclear Cells (PBMCs) responses to TNF-α exposure, a cytokine involved in the initiation of granulomas and progression of fibrosis in sarcoidosis and identified a differential dysregulation in pathways unique to complicated sarcoidosis. At the transcriptome level, we profiled microdisected granulomas from lung and lymph nodes, and identified a hub of genes that were dysregulated only in sarcoidosis in both compartments. Additionally, we compared the genomic profile of these granulomas in Sarcoidosis vs Tuberculosis (TB) and Coccidioidomycosis. We corroborated that some genes previously suggested as potential sarcoidosis markers were also present in fungal or mycobacterium granulomas, pointing to a common mechanistic origin. We also demonstrated a strong similarity at the transcriptional level between Sarcoidosis and TB. The contribution of the epigenetic mechanisms to the clinical presentation of sarcoidosis was assessed through DNA methylation analysis, complicated sarcoidosis reveled a hypo-methylated pattern in genes within HLA complex while the miRNA analysis derived a molecular signature consisting of 17 protein-coding genes, potentially regulated by 8 miRNAs dysregulated in complicated sarcoidosis.
    • Exploring the Predictability Power of Arizona's College and Career Readiness Indicators on College Enrollment Rates: A Multiple Regression Analysis

      López, Francesca; Burns McOmber, Eve Marie; Koyama, Jill; Henry, Kevin (The University of Arizona., 2020)
      Arizona’s most recent implementation of the A-F policy provides a unique opportunity to explore the relationship of various college and career readiness indicators (CCRI) on the impact of college enrollment rates. These CCRI incorporate various components of a school’s college-going culture that often fall to school counselors to design and implement within the school. Unfortunately, scholars find that school counselors do not have the time (McClafferty, McDonough, & Nunez 2002; McDonough, 1997; McKillip, Rawls, & Barry, 2012), in part because they are overburdened with excessive student caseloads (McClafferty, McDonough, & Nunez 2002; McDonough, 1997; McKillip, Rawls, Barry, 2012), and excessive administrative responsibilities to adequately support the college navigation process (Corwin & Tierney, 2007; McKillip, Rawls, Barry, 2012). Moreover, scholars have found that counselors often lack the prerequisite training (Corwin & Tierney, 2007) and policy support (Dahir, 2004). Furthermore, the extant literature is almost devoid of school counseling outcome research (Dahir, 2004; Whiston & Sexton, 1998). Research that reveals the support structures, advising needs or how to best use limited counselor time in order to support students is essential for successful evidence-based practices. The objective of this study is to examine the predictive power of various components of Arizona’s A-F CCRI on Title 1 high school’s college enrollment rates in southern Arizona. The secondary goal of this study is to analyze the available data to determine if specific CCRI components or combination of components have stronger impacts on college enrollment. These results may then be utilized to inform school counselors and administrators on the best methods to support their underserved student populations. Data was analyzed using multiple regression to determine the predictive nature of the selected indicators on the enrollment rates of students. Results indicate that of the indicators analyzed, meeting all 16 Arizona Board of Regents Program of Study Requirements and sections passed on the ACT had significant positive relationships with post-secondary enrollment rates. However, contrary to expectations the Number of College Classes Credit was Earned had a significant negative relationship with post-secondary enrollment rates. An (2013) and (Taylor, 2015) stated in their literature reviews that research on the effects of dual enrollment credit is still minimal however the consensus is that there is college access and completion benefits. These research findings indicate this relationship warrants deeper investigation. The findings have relevance for informing counselors and administrators on ways to support first-generation and underserved student populations. Counselors as advocates for students are ideally situated to act as critical advocates to support these students and protect student agency as schools work to maximize the points in all categories of the CCRI measures. Furthermore, a number of potential follow-up studies may further expand the existing literature and support counselors in making evidenced based policy implementation recommendations.
    • Increasing Pneumoccal Vaccination Rates Among Patients 65 Years and Older in a Retail Clinic

      Love, Rene; Carroz, Minnerva; Daly, Patricia; Rothers, Janet (The University of Arizona., 2020)
      Background: Despite the significant morbidity and mortality associated with pneumococcal disease, the national vaccination rates for pneumococcal vaccine for patients 65 years and older fall below the Healthy People goal of 2020. In recent years, there is a growing trend in the use of retail health clinics in the country. These retail health clinics can be an avenue to close the gap in the delivery of pneumococcal vaccination. The purpose of this project is to assess the baseline knowledge of retail health providers and their perception of barriers to pneumonia vaccinations. In addition, a program called The Four Pillars on Immunization Toolkit was implemented to increase pneumococcal immunization rates in a retail health clinic. Purpose: This project explored the baseline knowledge of the providers and the perceived barriers regarding the delivery of pneumococcal vaccination. Furthermore, The Four Pillars on Immunization Toolkit was utilized to increase immunization in a retail health clinic. Methods: The baseline knowledge and perception of barriers to delivering the pneumonia vaccination was assessed via an online survey. To increase the pneumococcal vaccination, the participants were educated on the Four Pillars on Immunization Toolkit before actual implementation. Results: The scores on the knowledge section of the survey ranged from 9% to 81%. These results indicated that providers working in the retail health setting could benefit from pneumococcal vaccination education. The results on the perception of barriers showed that providers working the retail clinics face barriers that prevent the recommendation or the giving of pneumococcal vaccination. In addition, the use of the Four Pillars on Immunization toolkit indicated a 10 % increase in pneumococcal vaccination rate when compared to the previous year. Conclusion: The result indicated that providers working in the retail clinic are generally knowledgeable about pneumonia vaccination; however, there is a gap noted on certain knowledge questions. In addition, providers noted barriers that prevent the recommendation or the giving of the pneumonia vaccination in this setting. The results suggested the use of the Four Pillars on Immunization Toolkit could be used as a tool in a retail clinic to improve delivery of important immunizations.
    • Geographic and Racial Disparities in Mortality of Dialysis Patients

      Calhoun, Elizabeth A.; Mohan, Prashanthinie; Roy-Chaudhury, Prabir; Barraza, Leila Fs; Gilliland, Stephen (The University of Arizona., 2020)
      BACKGROUND: The incidence rate and hospitalization rate for patients with End Stage Renal Disease (ESRD) vary across different counties in the U.S. Little information is available on how geography can impact patient mortality through county health status and gaps in supply and demand for hemodialysis services. METHODS: This is a retrospective cohort study where adult patients who initiated in-center hemodialysis between 2007 and 2016 and recorded in the United States Renal Data System (USRDS) were assessed for survival time and mortality rate. The primary exposure variable in Aim 1 was the overall county health status (Most Healthy vs Least Healthy) based on the health factor ranks published by County Health Rankings & Roadmap (CHR&R). The primary exposure variable for Aim 2 was the supply-demand gap for hemodialysis services as measured by the patient-station ratio for each county. The primary exposure variable for Aim 3 was the change in the number of dialysis stations between 2011 and 2016 for each county. Kaplan-Meier estimate used to compute the median survival time and Cox regression analysis was used to compute the hazard rate (HR) for mortality after adjusting for various confounders. RESULTS: Most Healthy counties in the U.S. are likely to be larger urban counties with predominantly white and older patients. On the contrary, Least Healthy counties are comparatively more rural and smaller counties with a higher percentage of African American population, more unemployed and Medicaid patients. Patients residing in Most Healthy counties (HR = 0.899, 95% CI 0.825,0.979) had a lower hazard rate (HR) for mortality compared to patients living in Least Healthy Counties (p value = 0.0143). In Aim 2, counties in Category 1 (counties with no hemodialysis stations), Category 2.1 (underutilized HD stations with population <50,000) and Category 2.2 (underutilized HD stations with population 50,000) had higher HR compared to the reference Category 3. However, when stratified by age and race, the HR was statistically significant for Blacks only for Category 2.2 for all age groups (HR = 1.11, 95% CI 1.06,1.16) and for Whites for Category 1 (aged 40 – 79; HR=1.1) and Category 2.2 (aged 65 – 79; HR=1.11). In Aim 3, counties with No Change had a marginally higher hazard rate (HR=1.04, 95% CI 1.02, 1.07) compared to counties with an increase in dialysis stations. Race was a significant confounder but not an effect modifier to this association (p-value 0.2942). CONCLUSION: County health status and lack of hemodialysis facilities affects survival of ESRD patients. Additionally, patients residing in some suburban counties or smaller metros had a higher hazard rate for mortality despite excess supply of dialysis stations. It is important for care providers and local health officials to understand the health factor profile and spatial distribution of dialysis stations in their county to help ESRD patients navigate barriers to care, reduce rates of dialysis withdrawal, and improve mortality outcomes.
    • Statistical Methods for Improving Low Frequency Variant Calling in Cancer Genomics

      Gutenkunst, Ryan; Mannakee, Brian; Roe, Denise; Bedrick, Edward; Padi, Megha; McEvoy, Justina (The University of Arizona., 2020)
      Cancer is not a single disease, but a family of genomic diseases characterized by a set of initiating genomic variants accumulated in a single cell that allows that cell to begin dividing uncontrollably. Tumors grow by cell division, and each cell division generates a new set of variants that are passed along to its offspring. As a result, at the time of diagnosis a typical tumor of approximately 100,000,000 cells contains hundreds of millions of genomic variants, whose frequency in the population is a function of the time that they arose. Mutation accumulation through both inheritance and de novo variant production results in a final tumor in which the vast majority of variants are present at low frequency. Current methods used to identify variants have difficulty identifying low frequency variants. Here I will describe two algorithms aimed at improving low frequency variant calling in two settings. Patient-Derived Xenografts (PDXs) serve as avatars for individual patient disease as well as invaluable models for studying basic cancer biology. Molecular character- ization of PDXs is common, but the extensive homology between human and mouse genes present special challenges in sequencing tumors grown in mice. In Chapter 2 I describe an algorithm and R implementation called MAPEX that allows labs study- ing PDXs to use commercial sequencing technologies and locally filter false positive variants caused by sequence homology. Detecting somatic mutations within tumors is key to understanding treatment re- sistance, patient prognosis, and tumor evolution. In Chapter 3 I present BATCAVE (Bayesian Analysis Tools for Context-Aware Variant Evaluation), which extends cur- rent state-of-the-art statistical models for tumor variant calling. I also present an R implementation of the algorithm, and show using simulations that the BATCAVE algorithm improves variant detection.
    • Cancer Capacity and Resources in Rural Arizona

      Calhoun, Elizabeth A.; Lent, Adrienne; Jacobs, Elizabeth T.; Barraza, Leila (The University of Arizona., 2020)
      Background: Cancer is the second leading cause of death in the U.S. Rural urban cancer disparities exist nationally and in Arizona. Previous studies on the availability of rural cancer services are cancer-specific, limited to specific points along the cancer care continuum (e.g., screening, diagnosis, or treatment), or require updating to capture the current landscape as it relates to rural health. This study explored the following three aims: 1) Describe the availability of cancer capacity and services for breast, cervical, colorectal and lung cancer across the cancer care continuum in low populous counties in Arizona; 2) Evaluate the association between breast cancer capacity and resources with breast cancer incidence and mortality; and 3) Provide policy recommendations focused on increasing capacity and resources in low populous, rural counties in Arizona. Methods: For Aim 1, a cancer capacity and resources survey was developed and distributed to healthcare organizations operating outside of Arizona’s largest population centered counties, Maricopa and Pima. Numbers of healthcare providers were pulled from the Center for Medicare and Medicaid Services. Numbers of clinical sites and healthcare providers were converted to county-level per capita rates. Rural Urban Continuum (RUC) codes were used to designate county metropolitan status. County demographic information from the U.S. Census Bureau, income data from the US Bureau of Economic Analysis, and unemployment rates from the US Department of Labor were included. Descriptive statistics were used to summarize the results. A student’s t-test was used to evaluate differences between rural and urban counties. For Aim 2, the Arizona Department of Health Services Cancer Registry provided county level cancer incidence and death rates from 2010 through 2016. Linear regression was used to evaluate the association between rural status and breast cancer capacity and services with breast cancer incidence and mortality rates. For Aim 3, current US federal and state level policies focused on increasing the rural workforce were reviewed. Results: Out of Arizona’s 15 counties, 13 were represented. Six were urban (RUC codes 1 – 3) and seven were rural (RUC codes 4 – 7). Urban counties had a larger average population (216,773) than rural counties (49,507) (p-value = 0.01). Rural counties had more per capita clinical sites (20.4) than urban counties (8.9) (p-value = 0.02). Rural counties had more per capita cervical cancer screening sites (18.9) than urban counties (7) (p-value = 0.02) and rural counties had more per capita colorectal cancer screening sites (15.7) than urban counties (2.5) (p-value = 0.02). Urban counties had more per capita gastroenterologists (2.2) than rural counties (0) (p-value = 0.02) and urban counties had more per capita pathologists (1.0) than rural counties (0) (p-value = <0.01). Rural counties had zero medical oncologists. Per capita, rural counties with RUC codes 4 and 6 had hematology and oncology physicians (0.3, 2.5) and radiologists (2.8, 6.0) but those with RUC code 7 had zero. Although not significantly different, rural counties with RUC code 6 had three times as many per capita registered nurses (306.7) than urban counties (90.8). Rural county status was associated with a decrease in breast cancer incidence (β = -20.1, 95% CI: -37.2, 3.1). There was no association between breast cancer incidence and county per capita sites providing breast cancer screening (β = -8.8, 95% CI: -23.9, 6.9), diagnosis (β = -5.2, 95% CI: -22.2, 11.7), treatment (β = -6.5, 95% CI: -23.2, 10.2), and all three services (β = -8.0, 95% CI: -23.9, 7.9) or county per capita primary care physicians (β = 0.0, 95% CI: -0.54, 0.48), hematology oncology physicians (β = -0.9, 95% CI: -15.7, 13.8), medical oncology physicians (β = 35.2, 95% CI: -22.7, 93.0), OBGYN physicians (β = -0.5, 95% CI: -4.2, 3.2), radiologists (β = -0.2, 95% CI: -6.8, 6.4), and surgeons (β = 1.6, 95% CI: -3.1, 6.3). In the unadjusted model, rural RUC codes four (β = -24.1, 95% CI: -41.8, -6.4) and six (β = -32.6, 95% CI: -53.0, -12.2) were associated with breast cancer incidence. There was no association between breast cancer incidence and RUC code 7 (β = -1.8, 95% CI: -22.3, 18.6). In the model adjusted for race (percent of the county population that’s Hispanic) and Ethnicity (percent of the county population that’s American Indian and Alaska Native), RUC codes four (β = -19.0, 95% CI: -37.7, -0.4) and six (β = -32.6, 95% CI: -56.0, -7.9) were associated with breast cancer incidence. There was no association between breast cancer mortality and rural county status (β = -1.1, 95% CI: -7.7, 5.6), county per capita sites providing breast cancer screening (β = -0.2, 95% CI: -4.2, 3.8), diagnosis (β = 0.4, 95% CI: -3.8, 4.6), treatment (β = 0.4, 95% CI: -3.9, 4.6), all three services (0.2, -3.9, 4.3) or county per capita primary care physicians (β = 0.0, 95% CI: -0.1, 0.0), hematology oncology physicians (β = -1.6, 95% CI: -5.3, 2.1), medical oncology physicians (β = -0.9, 95% CI: -17.2, 15.3), OBGYN physicians (β = -0.6, 95% CI: -1.5, 0.3), radiologists (β = -0.7, 95% CI: -2.4, 1.0), and surgeons (β = -0.1, 95% CI: -1.4, 1.2). Conclusions: While rural counties may have more physical infrastructure, they lack specialists integral to providing cancer services. Non-physician clinical providers may be more prevalent in rural areas and represent opportunities for improving cancer care. Compared to urban counties, rural county status was associated with lower breast cancer incidence rates but not associated with breast cancer death. The number of sites delivering breast cancer services and physicians were not associated with breast cancer incidence or mortality at the county level. Other factors may contribute to rural urban differences in breast cancer incidence. Federal and state level policies have been effective in increasing the rural healthcare workforce. However, opportunities for improving rural cancer care through policies and programs exist. Improved data collection and availability from state level workforce data and the FDA mammography database can help improve cancer capacity research. Increased exposure to rural locations during residency, transformation of GME payment, and expansion of loan repayment and scholarship programs may help increase the number of specialists delivering cancer care in rural Arizona and nationally. Increased training opportunities and the scope of work expansions for non-physician clinicians and advanced practice providers may help improve the delivery of cancer prevention and treatment services in rural areas that lack specialist physicians. Future research should explore these factors as well as the association between cancer capacity and resources at a more local level since Arizona counties can be a heterogeneous unit of observation.
    • Examining the Differences in Reading Performance Between Students Who Were Retained Versus Struggling Readers Promoted in Early Grades

      Perfect, Michelle M.; Potter, Ashley McClung; Kirkpatrick, Jennifer B.; Lopez, Francesca A. (The University of Arizona., 2020)
      Background and Objectives: Research has shown that retention is not an effective form of intervention and can often delay identification of learning disabilities and increase chances for school dropout. Students can also be retained due to high stakes testing results, most states require students to pass the third grade state reading assessment in order to be promoted to fourth grade. Often students later diagnosed with learning disabilities have been retained. Curriculum based measures (CBMs) are used to help identify reading difficulties at earlier ages for the purposes of interventions. This study compared reading growth, second grade reading scores, and third grade state assessment outcomes between retained and promoted students. Methods: The current study utilized an existing data set from a school district in southern Arizona that uses CBMs to help identify students for interventions and identification through a Response to Intervention (RTI) process. The sample consisted of 176 students who had scores of <40 letter sounds in a minute on a kindergarten reading CBM. The main dependent variables were second grade oral reading fluency (ORF) score, second grade ORF growth, and third grade reading assessment level. Growth was calculated using a slope formula of spring score minus fall score divided by the number of weeks in between. Independent variables included retention status, special education status, sex, free and reduced lunch at the student’s school. Results: Analyses showed that the retained group (Mdn=22) scored significantly lower on letter sound fluency (LSF) than those promoted (Mdn=33), U=13.968, p<.000. In first grade, those who had been retained (Mdn=31) performed significantly lower than those who had not been retained (Mdn=49) on their Spring word identification fluency (WIF) score and were more likely to be in the frustrational range (<50 words in a minute) than expected by chance on the Spring administration U=10.520, p<.001. Further analysis showed that those who were retained (Mdn=33) did not score significantly different on the Fall ORF probe than those not retained (Mdn=34), U=.269, p=.604, two-tailed. Based on a linear regression, no significant differences were observed between the groups for second grade Spring ORF, F (3,172) =.671, p = .571, R2 = .012. Again using a linear regression, no significant contributions to second grade ORF growth were found, F(3,162) = 1.63, p = .185), R2= .029. Significant unique contributions were made by special education status and Spring ORF, 2(12, N= 92) = 82.020, Nagelkerke R2= .302, p = .004 using a multinomial regression model to determine risk factors for students falling into the Minimally Proficient category on the state assessment. Conclusion: Significant differences were observed between the retained and promoted groups in kindergarten and 1st grade. No observable differences were observed between the groups in second grade. Retention was not a significant contributor to third grade state assessment category; however, Spring ORF score was. At the end of second grade, 23 (13.06%) out of the original 176 continued to be in the frustrational range. Eleven out of these 23 students scored into the Minimally Proficient category on their state standardized assessment and all but one were identified as receiving special education services. Of the 36 students in the Minimally Proficient category on the state test, 18 were not identified as receiving special education services.
    • Diagnostic Biosensors for Detection of Blood-Derived Biomarkers

      Yoon, Jeong-Yeol; Ulep, Tiffany-Heather; Galbraith, David W.; Zenhausern, Frederic; Kim, Minkyu (The University of Arizona., 2020)
      Standard diagnostic tools used from patient samples, specifically from blood draws, require specialized equipment, personnel, and facilities. Conventional techniques can often be very laborious and time consuming due to required sample preparation. The evident delay from sample collection to a patient’s result immensely impacts their outcome. The aims of this research are to design diagnostic biosensors that decrease time-to-results, minimize reagent and sample handling, and incorporate automated simple optical transduction and user interfaces for the detection of blood-derived biomarkers. Specifically, four biosensing detection mechanisms performed on 3 different point-of-care platforms will be discussed. First is a static loop-mediated isothermal amplification (LAMP) of nucleic acid aqueous droplet on a silicone chip platform immersed in mineral oil. The target-of-interest is a nucleic acid sequence as a biomarker for antibiotic resistant bacteria. The biosensing technique used related changes in interfacial tension (IFT) at the water-oil interface by measuring the change in contact angle (geometrical-effects) over time. Initially the system was characterized as a linear response in relation to concentration of bacteria in a buffer system down to the limit of detection (LOD) of 100 CFU per uL. Subsequently, with the addition of bacterial infected blood sample models, the system became a binary assay (i.e. yes or no) as low as 10 CFU per uL within 10 min of reaction. Secondly, a two-layered, paper microfluidic chip was utilized to quantify cancer cells from a buffy coat sample matrix by two detection mechanisms: 1) on-chip particle enumeration via smartphone microscope and 2) capillary flow dynamics via smartphone video processing. The assay resulted in a LOD as low as 1 cell per uL for the on-chip imaging aspect of platform and 0.1 cell per uL for the capillary flow analysis within 13 to 22s post application of blood sample. Lastly, the same concepts previously described in the first platform utilizes changes in IFT due to amplicon presence in an aqueous solution immersed in mineral oil. An emulsion LAMP platform was investigated to determine the relation between angle-dependent light scatter intensity (based off Mie scatter theory) and nucleic acid amplification progression. The phenomenon attributing to changes in light scatter intensities is due to the interfacial changes occurring in the emulsion droplets, where amplicon amount increases the IFT decreases, resulting in smaller diameter emulsions. Changes in light scatter intensity within 3 min of the reaction shows statistical difference in comparison to no target control (NTC) for 10^3 CFU per uL of bacteria dosed into aqueous sample. These four detection mechanisms and three platforms offer but a few alternatives as biosensing methods for blood-derived diagnostic biosensors.
    • Networks of Transformative Resistance: How Community College Educators Support Students with an Undocumented Status

      Cabrera, Nolan; Matera, Matthew Thomas; Muñoz, Susana M.; Deil-Amen, Regina; Rhoades, Gary (The University of Arizona., 2020)
      Students with an undocumented or DACA status continue to fight for access to higher education across the U.S. Their struggle is particularly courageous in Arizona, where these student populations are forced to pay nonresident tuition and subjected to laws that separate, detain, and deport immigrants with an undocumented status. Student Services Professionals (SSPs) at community colleges, where most students with an undocumented status attend, can support or block these student populations from accessing college because of their roles in recruitment, orientation, and retention. In contrast to literature that centers educators’ individual work to support students with an undocumented or DACA status, I seek to understand how community college SSPs use social networks to support these student populations in Arizona. I conducted a qualitative case study design that centered SSPs’ social networks. I grounded my methodological approach in Social Network Analysis (SNA) which helped visualize individuals and strength of relations in SSPs’ networks. I used the Critical Agency Network Model (Kiyama, Lee, & Rhoades, 2012) and concept of transformational resistance (Solórzano & Delgado Bernal, 2001) in the conceptual framework that guided my research. My findings indicate that to be in a network which supports students with an undocumented or DACA status, network actors must show visible and explicit support for the students. Networks are built among actors who have strong ties based on trust and a shared resistance to policies harming these student populations. Networks, especially with actors external to the college, offered places of support, care, and knowledge sharing for SSPs. The more SSPs were engaged in transformative resistance efforts in their networks, the lower they perceived their personal risk in supporting students with an undocumented or DACA status.
    • Regional Atmospheric Dynamics of Water on Mars

      McEwen, Alfred S.; Rafkin, Scot C.R.; Leung, Cecilia Wai See; Kahre, Melinda A.; Yelle, Roger V.; Castro, Christopher L.; Byrne, Shane (The University of Arizona., 2020)
      The investigation of water on Mars continues to be a quintessential objective in planetary exploration since water represents a critical link to Mars’ past and present climate, geology, and its potential for habitability. Direct observations of water at the regional scale is limited, and the distribution and behavior of water in the planetary boundary layer remains an outstanding question. The research in this dissertation investigates the radiative and dynamical processes governing the regional water cycle on Mars. Using global and mesoscale atmospheric models, simulations of the regional water circulation revealed a highly non-homogeneous local distribution of water that is strongly modulated by diurnal transport. Terrain-following air parcels forced along the slopes of the Tharsis volcanoes and the steep canyon walls of Valles Marineris significantly impact the local water concentration and the associated conditions for cloud formation in these regions. An investigation of water ice fogs inside Valles Marineris showed significant variability between the local atmospheric environment inside versus outside the canyon. Formation of water ice clouds is possible in Valles Marineris, but their formation is highly influenced by radiative feedbacks forced by the thermal properties of the underlying surface. An evaluation of the potential influences of the atmosphere on recurring slope lineae (RSL) activity revealed an upper limit of ~1 µm per sol for the quantity of water that can be extracted from the atmosphere through deliquescence. Ongoing efforts to understand how regional atmospheric dynamics govern the distribution of water in the planetary boundary layer represent a significant step towards a comprehensive understanding of the water cycle on Mars.
    • Water Resources, Tiered Institutions, and Rural-Urban Land Use in Coupled Social-Ecological Dryland Systems: Evidence from the Sonoran Desert

      Scott, Christopher A.; Lee, Ryan Hawken; Breshears, David D.; Marsh, Stuart E.; Megdal, Sharon B. (The University of Arizona., 2020)
      A number of complex sustainable development challenges beset the 21st century. Central among them are how to address climatic, landscape, and human driven impacts on water resources in a manner that adequately supports both environmental health and human prosperity. Dryland water resources management, in both rural and urban contexts, underscores how complex this challenge is due to human and natural processes coupling into social-ecological systems to exert reciprocal feedbacks upon another. Addressing this challenge requires tools to assess and understand social and ecological interlinkages so that institutional and technological interventions to improve water governance and management can be identified. Results, analysis, and discussion from three dryland studies (Appendices A, B, and C) located in rural and urban Sonoran Desert locations, reinforce how complex are the challenges and pressing is the need for solutions in social-ecological systems. We also find and show that collaborative decision-making between institutions and stakeholders is the primary mechanism whereby humans are able to respond to with programs, policies, and actions able to deal with the dual pressure on water resources posed by climate change and heightened demand while reconciling economic efficiency, social equity, and environmental sustainability. Social-ecological assessment and response are two parts of the adaptive management process, and are both specific components of the three presented studies. Each study’s social-ecological assessment shows that vulnerability is not homogenous, and defined spatio-temporally, as well as by socio-demographics. This finding is an additional challenge to effective response, management, and mitigation of climate change, landscape change, and water insecurity. In particular: Appendix A uses the water-energy nexus and case examples from Tajikistan and Mexico, to show that (a) poorly articulated multi-tiered institutional arrangements coupled with failure to generate truly participatory interaction of stakeholders lead to water insecurity, (b) the livelihoods of vulnerable populations are threatened when users experience water insecurity that is created or exacerbated when tiered- institutions neglect users’ signals by failure to respond with actions that promote sound resource management or mitigate livelihood threats, and (c) water and livelihood security would be improved by adaptive actions targeted at user-defined causes of water insecurity and coordination between local resource users and institutions at multiple levels. Appendix B uses an interdisciplinary set of methods to show that rangeland productivity, surface-water reaches, and aquifers in Sonora, Mexico’s Río San Miguel Watershed are reduced to critical levels, agrarian livelihoods endangered, and within this dynamic that downstream locations are less resilient and water secure than operations upstream. Partnerships and cooperation amongst ranchers, sub-watersheds, and institutions are amongst the management and policy interventions available to prepare for or mitigate the developing social-ecological crisis in the watershed. Appendix C looks at challenges and potential solutions to documented disparity in participation between low-income versus median- income households in rainwater harvesting (RWH) programs in Tucson, Arizona to show that (a) Hispanic minority, low- income communities experience a disproportionate lack of tree canopy and higher urban temperatures compared to residents of other areas of the city, (b) both social and ecological factors are at cause for the inequitable, imbalanced racial/ethnic distribution of high heat risk in the city, and (c) that tiered-institutions, namely, NGOs and focal points historically embedded in socio-ecologically vulnerable communities, are key to developing and mediating greening and sustainable urban development processes to address the challenge. The lessons learned from the three studies highlight barriers, challenges, and best-practices that are valuable for sustainable water management, climate adaptation, and development in other groundwater-reliant economies, rural-urban dryland systems, climatic regions, or natural resource regimes.
    • Solar Desalination in Arid Lands

      Angel, J. Roger P.; Peon Anaya, Rodolfo; Marsh, Stuart E.; Zuniga-Teran, Adriana A.; Koshel, Richard J. (The University of Arizona., 2020)
      Freshwater consumption has already exceeded natural replenishment in many parts of the world. With a constant population growth, this unbalance does nothing but to accelerate. Being agriculture the largest water consumer, food production will be extremely challenging in the future; particularly in the most arid regions of the world. Migration to the cities will continue, and by the year 2050 about half of world’s population will live within 200 kilometers of the coast. This situation will undoubtedly make of seawater desalination an attractive alternative. However practically all desalination techniques are energy-intensive and produce large volumes of saline waste; both with potential environmental implications. To date, less than 1% of the roughly 20,000 desalination plants worldwide are powered by renewable energy directly, the reminder relies on fossil-fuels or the power grid (which also heavily relies on non-renewable energy sources in most countries). In this context, a growth in global desalination capacity, will also mean an increase in global CO2 emissions. In addition, current waste management by most desalination plants essentially consists of returning brine back to the environment. Therefore, an increase in desalination capacity in coastal areas, will also add to the stressors of marine ecosystems; which already include over-exploitation, pollution and climate change. With the objective of exploring sustainable desalination alternatives for the future, this work performed a literature review of large-scale solar thermal desalination, their integration to concentrating solar power plants and its potential implementation in the Sonoran Desert. In addition, this work proposed and mathematically evaluated a hybrid desalination unit (HDU) powered by high concentration photovoltaics with thermal collection capability for remote non-serviced homes at the Navajo Nation. As discussed in this work, the combination of solar power tower plants with thermal desalination can provide electricity and water at the same time cost-competitively and with a possibility of zero-liquid discharge (ZLD). It is also shown that this technological integration has the potential to secure water and electricity for Arizona, through binational desalination plants in the Sea of Cortez, with minimal environmental impact. In addition, experimental results from modeling the proposed HDU show that these units can offer potable water at nearly half the cost of hauling it at the Navajo Nation. Furthermore, it is shown that these units can double the amount of water available, offer ZLD, deliver a surplus of electric power and provide the means for growing food all year round.
    • Bullying Among Adolescents in Secondary Schools in Trinidad & Tobago

      Sulkowski, Michael; Bauman, Sheri; Jones, Marlon Byron; Yoon, Jina; Greenberg, Jeff (The University of Arizona., 2020)
      There is a dearth of existing research on the phenomenon of bullying among children in Trinidad and Tobago and the Caribbean region. This study used a cross-sectional design and convenience sampling to examine the frequency of various types of bullying (verbal, physical, relational, homophobic) among 489 adolescents (11-16 years of age) in seven secondary schools in Trinidad and Tobago. It was hypothesized that Trinidad and Tobago adolescents experienced more bullying than the global average (as so defined by the Global Bullying Database), and that verbal bullying was more prevalent than physical aggression. It was also hypothesized that participants would demonstrate low compassionate empathy for bully victims, that female participants would report more relational victimization than males, and that there would be a significant relationship between peer victimization, anxiety, and depression. Findings revealed that bullying rates in Trinidad and Tobago were lower than the global average, but within the expected range for the Caribbean region. Participants reported significantly more verbal bullying than physical bullying, with boys experiencing more homophobic teasing than girls. Girls reported significantly more relational victimization than boys. Low compassionate empathy attitudes towards victims of bullying were more prevalent, with a majority of participants sharing the belief that victims needed to learn to stand up for themselves. This study also found a strong relationship between bullying, anxiety, and depression, with male and female participants being at similar risk for poor mental health outcomes.
    • Thermoacoustic Thermometry Assisted Focused Microwave Therapy

      Xin, Hao; Saraswat, Srishti; Witte, Russell S.; Dvorak, Steven L. (The University of Arizona., 2020)
      In recent years, there has been a progressive trend towards minimally invasive methods with less morbidity and better cosmetic appearance for treating breast cancer. Non-invasive focused microwave therapy (FMT) is a cutting-edge approach for treating breast cancer that employs an array of antennas to focus electromagnetic energy deep into tissue at microwave frequencies. FMT offers better penetration and larger ablation zones (> 2 cm) than interstitial laser therapy (ILT), radiofrequency ablation (RFA), and cryoablation. In addition, because FMT depends on tissue dielectric properties, microwaves preferentially heat and damage high-water content breast carcinomas instead of healthy breast tissue. We develop and evaluate a focused microwave therapy (FMT) system and integrate it with thermoacoustic thermometry (TAT) for mapping temperature, quantifying the heat zone and guiding the delivery of focused heat. The thesis showcases the development of actual antenna arrays to transmit microwave power while the excitation signals are derived from the time-reversal (TR) beamforming algorithm to generate power distributions and thermal profiles in the patient-specific breast models. The first study based on 2D antenna arrays and patient-specific breast models demonstrates a nuanced analysis of the intricacies of the TR beamforming algorithm. Time reversal beamforming performs significantly well within a heterogeneous non-dissipative environment. An improved FMT approach for breast cancer treatment, overcoming the limitations of previously analyzed techniques, is also introduced. In this approach, a multi-ring 3D array is developed and FMT simulation is conducted in a 3D environment that allows targeting microwave power to tumors located at various locations by using a fixed antenna array. A figure of merit is identified which demonstrates significant improvement from 2D to 3D time reversal in heterogeneous breast as compared to homogeneous breast model. A proof of concept prototype is then developed for validating the time-reversal beamforming algorithm. The experimental system is implemented in two phases, where the first phase corresponds to a 4-element one-ring prototype, and the second phase is the three-dimensional multi-ring array of 32 patch antennas operating at the ISM frequency band (915 MHz). Additionally, to control thermal dosage at tumor location, while maintaining normal temperatures in healthy tissue and monitoring the progress during treatment, Thermoacoustic Thermometry (TAT) assisted FMT prototype is developed.
    • Machine Learning and Additive Manufacturing Based Antenna Design Techniques

      Xin, Hao; Sharma, Yashika; Dvorak, Steven L.; Roveda, Janet Meiling; Zhang, Hao Helen (The University of Arizona., 2020)
      This dissertation investigates the application of machine learning (ML) techniques to additive manufacturing (AM) technology with the ultimate goal of tackling the universal antenna design challenges and achieving automated antenna design for a broad range of applications. First, we investigate the implementation and accuracy of few modern machine learning techniques including, least absolute shrinkage and selection operator (lasso), artificial neural networks (ANN) and k-nearest neighbor (kNN) methods, for antenna design optimization for antennas. The automated techniques provide an efficient, flexible, and reliable framework to identify optimal design parameters for a reference dual-band double T-shaped monopole antenna to achieve favorite performance in terms of its dual bandwidth. We first provide a brief background for these techniques and then explain how these techniques can be used to optimize the performance of the referenced antenna. Then the accuracy of these techniques is tested by doing a comparative analysis with HFSS simulations as well. After obtaining encouraging results from the primitive work mentioned above, we implement ML techniques for the optimization of a more complex 3D-printed slotted waveguide antenna. The design has more design parameters that are be tuned and, also multiple performance parameters, including bandwidth, realized gain, sidelobe level, and back lobe level, are optimized. This is a higher-dimensional and non-linear problem. Hence, we use an artificial neural network for this work. Next, we demonstrate the advantages and challenges of using ML techniques compared to heuristic optimization techniques. We apply ML techniques first for ‘modeling’ that refers to prediction of the performance curve (e.g., reflection coefficient w.r.t. frequency, gain plots in a given plane, etc.) for a given design of antenna with particular set of design parameters and then use it for obtaining ‘optimization’ results that refers to searching the value of the design parameters that can give optimized results for a particular goal (e.g., specific frequency band of operation, maximum gain, minimum sidelobe level, etc.). To explain modeling using ML-techniques, we use two antenna examples in this work, first is the modeling of the reflection coefficient curve with respect to frequency for a planar patch antenna when its shape changes from square to circular and second is the modeling of gain response of a monopole antenna when it is loaded with 3D-printed dielectric material. To explain the optimization process, we use the behavioral model obtained in the second antenna example, and find the design parameter values that are capable of providing single-beam, and multiple-beam radiation. The performance of ML is compared with a heuristic technique like genetic algorithm for this work and the benefits of using ML over GA are mentioned in this work. One of the prototypes that can provide a 3-beam radiation pattern is manufactured and its fabrication process and measurement results are also presented in this work. The ultimate goal of this research work is to overcome universal antenna design challenges and achieving automated antenna design for a broad range of applications. With this work, ML models are built to find the relationship between design parameters and antenna performance parameters analytically, thus requiring only analytical calculations instead of time-consuming numerical simulations for different design goals. This is useful for applications such as IoT, which involve a large number of antenna designs with different goals and constraints. ML techniques help build such behavioral models for antennas automatically from data which is beneficial for fully exploring the vast design degrees of freedom offered by AM.
    • A Nonparametric Multiple Imputation Approach for Survival Data Subject to Informative Censoring

      Hsu, Chiu-Hsieh; O'Connor, Patrick Anthony; Roe, Densie; Hu, Chencheng; Pogreba-Brown, Kristen (The University of Arizona., 2020)
      Most existing survival analysis methods work under the assumption that censoring times are independent of failure times. When censoring is informative of failure times, those methods will produce biased survival estimates. We have developed a nonparametric multiple imputation approach that uses the estimated correlation between failure and censoring times to impute missing failure times for every censored observation. A sensitivity analysis shows the efficacy of the imputation approach by comparing survival estimates of the imputed data sets to estimates from data where all failure times are known. Dependence between the failure and censoring data is then induced using a shared frailty model. Parametric assumptions of failure and censoring times are applied allowing for the dependence parameter to be estimated using the EM algorithm. The dependence parameter is used to create an imputing risk set for each censored observation. A Kaplan-Meier survival curve is then fit to the imputing risk set to impute a failure time from this set for the censored observation. Traditional Kaplan-Meier estimation is performed on the imputed data sets to estimate survival. The method is then extended using a Cox proportional hazards model to include auxiliary variables in the dependence parameter estimation. Simulations along with results using the ACTG-175 clinic trial HIV data set are presented for each approach.
    • Using Motivational Interviewing for Medication Adherence in Patients with Schizophrenia Spectrum Disorders

      Badger, Terry; Tellers, Ashlyn; Kahn-John, Michelle; Gallagher, Shawn (The University of Arizona., 2020)
      Schizophrenia spectrum disorders are psychiatric illnesses that have a high incidence of patients not adhering to their antipsychotic medications. There are multiple factors that contribute to medication nonadherence in patients with a schizophrenia spectrum disorders. Nonadherence with antipsychotic medications can cause poor patient outcomes for patients with these psychiatric illnesses. There is evidence to support that the therapeutic communication intervention, motivational interviewing, can improve medication adherence in patients with schizophrenia spectrum disorders. This quality improvement project used a pre- and post-test design to assess medication adherence pre- and post-intervention. The main outcome of this project was to improve the patient outcome, medication adherence. This project included a study sample of two participants that met inclusion criteria. Patient A’s pre-intervention medication adherence rating scale (MARS) score was 7 out of 10 and Patient B’s score was 4 out of 10. The higher the score on the MARS, the more favorable medication adherence. Patient A was unable to receive a therapeutic session of motivational interviewing because he was acutely psychotic and paranoid. Patient B received one face-to-face motivational interview session and behavioral changes were discussed on how to maintain medication adherence. The one-month follow up post- intervention could not be completed due to appointments being rescheduled by the patients and provider. The post-intervention MARS were not completed and motivational interviewing was unable to be evaluated for effectiveness. Despite the lack of result findings on medication adherence, administering the MARS and utilizing motivational interviewing offered insight about the patient’s beliefs and feelings about their antipsychotic medication. It is recommended for future projects to expand the PDSA cycle to recruit more participants and fully implement the study protocol. Keywords: motivational interviewing, medication adherence, schizophrenia spectrum disorders, and therapeutic communication.
    • When Land Becomes Property: Promises and Pitfalls of Land Titling for Indigenous Guarani and Campesinos in Northern Paraguay

      Green, Linda B.; Tusing, Cari; Vásquez León, Marcela; Sheridan, Thomas E. (The University of Arizona., 2020)
      This dissertation examines how rural people in Northern Paraguay manage land and navigate land titling in order to stake claims to land and property, particularly under continuing processes of settler colonialism. Land title in Paraguay is touted as the key to securing land and livelihoods for campesinos and indigenous people. Through a multi-sited ethnography, I challenge this assumption by showing that the title implementation is irregular and slow; title itself does not guarantee possession nor guard against dispossession; and title requires a certain ideal-type community in order to be achieved. Titling reorders rural people’s relationships to land as collective or individual lots are granted or held in suspension, and reorders rural people’s relationships to each other as they contest or cooperate on claims. I investigate the grinding precarity of rural livelihoods that both campesinos and indigenous people confront in ethnographic detail, focusing on the intersection of rural landowners including Paraguayan and Brasiguayo elites, campesinos, and indigenous peoples’ concepts of land rights and property. I find that despite legal mechanisms to title land, lasting settler colonial categorizations reproduce unequal material differences in land access and livelihoods. At the same time, communities are able to assert certain forms of autonomy by leveraging legal concepts of property and ownership. I argue that land title is a fraught opportunity, with both promises and pitfalls for marginalized communities.
    • Basin-Scale Aquifer Characterization: Theory and Application

      Yeh, Tian-Chyi Jim; Wang, Yu-Li; Ferre, Paul A.; Guo, Bo (The University of Arizona., 2020)
      Groundwater is one of important water resources for the socio-economic development of a community. Its reserve, distribution, and movement are mainly controlled by the subsurface hydraulic characteristics. For management of the groundwater resources, mathematical models of groundwater dynamics have been used for estimation, prediction, and scenario analysis. The accuracy of these analyses relies on the detailed knowledge of the subsurface hydraulic characteristic distributions. However, a reliable evaluation of groundwater resources remains intractable due to multi-scale variability of the subsurface characteristics and our limited ability to characterize it over a large groundwater basin. This difficulty thus hinders adequate assessments of water sustainability, and in turn, impedes the development of community. In order to overcome this difficulty, a new generation of basin-scale aquifer characterization method must be developed. My dissertation is to explore and develop the new generation of basin-scale aquifer characterization approach. The dissertation is composed of three parts. In, the first part, we investigate the feasibility of utilizing river stage fluctuation as spatial and temporal varying excitation sources to characterize the basin-scale aquifers. The wavelet analysis is first conducted to investigate the temporal characteristics of groundwater level, precipitation, and stream stage. The results of the analysis show that variations of groundwater level and stream stage are highly correlated over seasonal and annual periods while that between precipitation is less significant. Subsequently, spatial cross-correlation between seasonal variations of groundwater level and river stage data is analyzed. It is found that the correlation contour map reflects the pattern of sediment distribution of the fan. This finding is further substantiated by the cross-correlation analysis using both noisy and noise-free groundwater and river stage data of a synthetic aquifer, where aquifer heterogeneity is known exactly. The ability of river stage tomography is then tested with these synthetic data sets to estimate hydraulic diffusivity (D) distribution. Finally, the river stage tomography is applied to the alluvial fan. The results of the application reveal that the apex and southeast of the alluvial fan are regions with relatively high D and the D values gradually decrease toward the shoreline of the fan. In addition, D at northern alluvial fan is slightly larger than that at southern. These findings are consistent with the geologic evolution of this alluvial fan. In the second part of the dissertation, we investigate the effects of different types of river stage variation and the monitoring network design on the large-scale aquifer characterization. It evaluates the spatiotemporal cross-correlation between the observed head and D parameters in heterogeneous aquifers under static and migrating periodic excitations with different frequencies and other factors, and a moving single excitation along a river boundary. Results of the cross-correlation analysis are verified by estimating the parameters in a synthetic heterogeneous aquifer under these excitations. For assuring the statistical significance of the results based on a single realization, Monte Carlo experiments of estimating the parameters with these excitations are conducted. The experiments also explore the relationship between the resolution of the estimated parameters and the distance from the excitation to the observation wells, the frequency, and amplitude of the excitation, and the mean diffusivity of the aquifer. In addition, the relationship between the resolution of the estimates and monitoring network spatial density is investigated. Finally, the usefulness of moving single excitations, effects of frequencies of the periodic excitations under different situations, the density of monitoring network in term of correlation scale, and the ergodicity issue corresponding to the number of observation and size of simulation domain are discussed. In the third part, we evaluate the capability of periodic excitations with different frequencies and multi-frequency to estimate hydraulic transmissivity and storage coefficient fields in heterogeneous aquifers. The residual flux and residual storage presented in the stochastic groundwater flow model are examined by the unconditional and conditional effective approaches. Afterward, the first order approximation and the singular value decomposition are substantiated to quantify the similarity and dissimilarity of amplitude and phase shift of unconditional flux and storage under different pumping frequencies. The result of the cross-correlation analysis is verified by estimating the parameters in a set of synthetic heterogeneous aquifers. The Monte Carlo experiment is required for assuring the statistical significance of the results. These resulting data and the reanalyzing data from previous studies lead us to a conclusion that the heads induced by pumping with different frequencies or multi-frequency carry the same information about the heterogeneity. Finally, the parameter (e.g., hydraulic conductivity and specific storage) and state variable (e.g., water level and flow fields) ergodicities emphasize the importance of dense monitoring network and cost-effective data collection procedure on the resolution of delineating heterogeneity.
    • Innovative Methods for Outcome-Based Pricing of Treatments from the US Payer Perspective (The Six Delta Platform)

      Abraham, Ivo; Alkhatib, Nimer; Ramos, Kenneth; Erstad, Brian; McBride, Ali; Slack, Marion; Bhattacharjee, Sandipan (The University of Arizona., 2020)
      An independent group of researchers from the Center for Health Outcomes and PharmacoEconomic Research (HOPE), University of Arizona, has committed to designing, validating, and disseminating a platform of transparent methodologies for pricing of treatments that could potentially be used for outcome-based contracting from the US payer perspective. In brief, the suggested pricing methodology uses a multidimensional price assessment in which six dimensions (also termed δ) are used to provide price variations. Two-time horizons for assessing these 6 δs are considered, comprising two δs based on long-term assessments and four δs based on short-term assessments (Figure 1). Individually, each of these six δs is designed to use different scenarios for creating price variations (also termed dispersions) at the dimensional level. The price variations in each δ are simulated by Monte Carlo Simulation (MCS) methods to generate a price at the dimensional level (i.e., the dimension-specific price, DSP), and a price when all dimensions are integrated (i.e., the average of all dimensional prices, ADP). A proof-of-concept for the six pricing δs is provided for osimertinib in the treatment of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation.