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- All Subjects: Biology
- Genre: Masters Thesis
- Creators: Arizona State University
- Status: Published
Description
Increasingly, college courses have transitioned from traditional lecture to student-centered active learning, creating more opportunities for students to interact with each other in class. Recent studies have indicated that these increased interactions in active learning can create situations where students’ identities are more salient, which could result in novel challenges for students with marginalized identities. Christianity has been shown to be a marginalized identity in the context of undergraduate biology courses, but it is unknown whether Christian students experience challenges in their interactions with other students in class. The social psychology framework of concealable stigmatized identity (CSI) was used to explore the experiences of Christian students during peer interactions in undergraduate biology courses. Thirty students were interviewed, and most felt their religious identity was salient during peer interactions in biology. Students also reported that they have more opportunities to reveal their religious identity in courses that incorporate peer discussion than in courses that do not. Students claimed that revealing their religious identity to their peers could be beneficial because they could find other religious students in their courses, grow closer with their peers, and combat stereotypes about religious individuals in science. Though most students anticipated stigma, which caused some students to choose not to reveal their religious identities, comparatively few had experienced stigma during peer interactions in their college biology courses, and even fewer had experienced stigma from peers who knew they were religious. These findings indicate that it be may important to teach students how to be culturally competent to reduce Christian students’ anticipated and experienced stigma in active learning courses.
ContributorsEdwards, Baylee Anne (Author) / Brownell, Sara E. (Thesis advisor) / Barnes, M. Elizabeth (Committee member) / Sterner, Beckett (Committee member) / Cooper, Katelyn M. (Committee member) / Arizona State University (Publisher)
Created2022
Description
Bouteloua eriopoda (Torr.) Torr., also known as black grama, is a perennial bunchgrass native to arid and semiarid ecosystems in the southwestern region of North America. As a result of anthropogenic climate change, this region is predicted to increase in aridity and experience more frequent extreme drought and extreme wet years. This change in precipitation will no doubt affect black grama; however, few studies have investigated how the specific structural components of this grass will respond. The purpose of this study was to examine the effects of years since start of treatment and annual precipitation amount on tiller and stolon densities, and to test for interaction between the two predictor variables. Additionally, the effects of annual precipitation on ramets and axillary buds were investigated. By using 36 experimental plots that have been receiving drought, irrigated, or control treatments since 2007, tiller density was the most responsive component to both annual precipitation amount and years since start of treatment. Years since start of treatment and annual precipitation amount also had a statistically significant interaction, meaning the effect of precipitation amount on tiller density differs depending on how many years have passed since treatments began. Stolon density was the second-most responsive component; the predictor variables were found to have no statistically significant interaction, meaning their effects on stolon density are independent of one another. Ramet density, ramets per stolon, and axillary bud metabolic activity and density were found to be independent of annual precipitation amount for 2021. The results indicate that multiple-year extreme wet and multiple-year extreme dry conditions in the Southwest will both likely reduce tiller and stolon densities in black grama patches. Prolonged drought conditions reduced tiller and stolon production in black grama because of negative legacies from previous years. Reduced production during prolonged wet conditions could be due to increased competition between adjacent plants.
ContributorsSutter, Bryce Madison (Author) / Sala, Osvaldo E (Thesis advisor) / Makings, Elizabeth (Committee member) / Wojciechowski, Martin F (Committee member) / Arizona State University (Publisher)
Created2022
Description
Drosophila melanogaster, as an important model organism, is used to explore the mechanism which governs cell differentiation and embryonic development. Understanding the mechanism will help to reveal the effects of genes on other species or even human beings. Currently, digital camera techniques make high quality Drosophila gene expression imaging possible. On the other hand, due to the advances in biology, gene expression images which can reveal spatiotemporal patterns are generated in a high-throughput pace. Thus, an automated and efficient system that can analyze gene expression will become a necessary tool for investigating the gene functions, interactions and developmental processes. One investigation method is to compare the expression patterns of different developmental stages. Recently, however, the expression patterns are manually annotated with rough stage ranges. The work of annotation requires professional knowledge from experienced biologists. Hence, how to transfer the domain knowledge in biology into an automated system which can automatically annotate the patterns provides a challenging problem for computer scientists. In this thesis, the problem of stage annotation for Drosophila embryo is modeled in the machine learning framework. Three sparse learning algorithms and one ensemble algorithm are used to attack the problem. The sparse algorithms are Lasso, group Lasso and sparse group Lasso. The ensemble algorithm is based on a voting method. Besides that the proposed algorithms can annotate the patterns to stages instead of stage ranges with high accuracy; the decimal stage annotation algorithm presents a novel way to annotate the patterns to decimal stages. In addition, some analysis on the algorithm performance are made and corresponding explanations are given. Finally, with the proposed system, all the lateral view BDGP and FlyFish images are annotated and several interesting applications of decimal stage value are revealed.
ContributorsPan, Cheng (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Farin, Gerald (Committee member) / Arizona State University (Publisher)
Created2012
Description
Structural Equation Modeling (SEM) is a multivariate analysis methodology that could potentially be utilized to examine the barrier effect that river systems have on genetic differentiation. In this project, river systems are split into the variables of Daily Average Discharge, Average River Width, and Seasonality measurements and regressed onto the genetic differentiation, measured as Fst. This data was collected from the USGS database (U.S. Geological Survey, 2020), sequencing files from differing literature, or Google Earth measurements. Different Structural Equation Modeling models are used to model different system structures as well as compare it to more traditional methodologies like Generalized Linear Modeling and Generalized Linear Mixed Modeling. Ultimately results were limited by the small sample size, however, interesting patterns still emerged from the models. The SE models indicate that Discharge plays a primary role in the genetic differentiation of adjacent river populations. In addition to this, the results demonstrate how quantification of indirect effects, particularly those relating to discharge, give more informative interpretations than traditional multivariate statistics alone. These findings prompt further investigations into this potential methodology.
ContributorsMaag, Garett (Author) / Dolby, Greer A. (Thesis advisor) / Kusumi, Kenro (Thesis advisor) / Stokes, Maya F. (Committee member) / Barly, Anthony (Committee member) / Arizona State University (Publisher)
Created2023
Description
Globally, land use change is the primary driver of biodiversity loss (IPBES, 2019). Land use change due to agricultural expansion is driving bird species to the brink of extinction in the Peruvian Amazon rainforest. Agriculture is one of the primary threats to bird species in the region, and agroforestry is being pursued in some communities as a potential solution to reduce agriculture's impacts on species, as agroforestry provides improved habitat for wildlife while also enabling livelihoods for people. Understanding how anthropogenic land use choices affect imperiled species is an important prerequisite for conservation policy and practice in the region. In this thesis, I develop a spatial model for quantifying expected threat abatement from shifting agricultural land use choices towards agroforestry. I used this model explored how agricultural land use impacts imperiled bird species in the Peruvian Amazon. My approach builds on the species threat abatement and restoration (STAR) metric to make the expected consequences of reducing agricultural threats spatially explicit. I then analyzed results of applying the metric to alternative scenarios with and without agroforestry conversion. I found that agroforestry could result in up to 18.68% reduction in mean bird projected population decline. I found that converting all terrestrial agriculture in the Peruvian Amazon to agroforestry could produce a benefit of up to 83% to imperiled birds in the region in terms of improvement in Red List status. This use of the STAR metric to model alternative scenarios presents a novel usage for the STAR metric and a promising approach to understand how to address terrestrial biodiversity challenges efficiently and effectively.
ContributorsPoe, Katherine (Author) / Iacona, Gwen (Thesis advisor) / Gerber, Leah (Thesis advisor) / Mair, Louise (Committee member) / Arizona State University (Publisher)
Created2023
Modeling Spatial Competition and Adaptive Therapy Protocols in Three-Dimensional Vascularized Tumors
Description
In contrast to traditional chemotherapy for cancer which fails to address tumor heterogeneity, raises patients’ levels of toxicity, and selects for drug-resistant cells, adaptive therapy applies ideas from cancer ecology in employing low-dose drugs to encourage competition between cancerous cells, reducing toxicity and potentially prolonging disease progression. Despite promising results in some clinical trials, optimizing adaptive therapy routines involves navigating a vast space of combina- torial possibilities, including the number of drugs, drug holiday duration, and drug dosages. Computational models can serve as precursors to efficiently explore this space, narrowing the scope of possibilities for in-vivo and in-vitro experiments which are time-consuming, expensive, and specific to tumor types. Among the existing modeling techniques, agent-based models are particularly suited for studying the spatial inter- actions critical to successful adaptive therapy. In this thesis, I introduce CancerSim, a three-dimensional agent-based model fully implemented in C++ that is designed to simulate tumorigenesis, angiogenesis, drug resistance, and resource competition within a tissue. Additionally, the model is equipped to assess the effectiveness of various adaptive therapy regimens. The thesis provides detailed insights into the biological motivation and calibration of different model parameters. Lastly, I propose a series of research questions and experiments for adaptive therapy that CancerSim can address in the pursuit of advancing cancer treatment strategies.
ContributorsShah, Sanjana Saurin (Author) / Daymude, Joshua J (Thesis advisor) / Forrest, Stephanie (Committee member) / Maley, Carlo C (Committee member) / Arizona State University (Publisher)
Created2023
Description
Riparian ecosystems comprise less than 2% of the landscape in the arid western U.S. yet provide habitat and resources to over half of arid-land wildlife species, including a broad diversity of anurans (frogs and toads). I surveyed anurans using passive acoustic monitoring to capture spring advertisement calls in wilderness area tributaries of the Verde River, Arizona, USA. In the spring and summer of 2021 and 2022, 13-29 autonomous recording units (ARUs) were deployed along perennial, intermittent, and ephemeral reaches across eight headwater streams. I characterized stream reaches based on the percent of pool, riffle, run, and side channel habitat within 100 meters of each ARU. I quantified substrate, discharge at 95% exceedance probability, flow width, and canopy cover at each site. To relate anuran occupancy and relative habitat use to environmental and hydrological variables, I evaluated acoustic data using single-species occupancy and Royle-Nichols and N-mixture (relative habitat use) models. Four species were detected in this study: canyon treefrog (Hyla arenicolor), red-spotted toad (Anaxyrus punctatus), Woodhouse’s toad (Anaxyrus woodhousii), and non-native American bullfrog (Lithobates catesbeianus), with canyon treefrog being the most ubiquitous species observed. Occupancy of canyon treefrog was greater at perennial and intermittent sites compared to ephemeral sites, and presence of pool was the most important driver of canyon treefrog occupancy and relative habitat use. Notably, this study did not detect several species with historical records in the middle Verde River watershed, including Arizona toad (Anaxyrus microscaphus) and Northern leopard frog (Lithobates pipiens). Given climate change-related flow declines and intensifying demands for water in the Southwest, maintaining stream flows that provide consistent and suitable hydroregimes for anuran breeding and larval development is of increasing importance. Determining habitat use and flow regimes necessary to support anuran populations can aid in prioritization of conservation actions related to water management and predict how changes in water availability may impact stream-breeding anurans.
ContributorsHuck, Margaret (Author) / Bateman, Heather L (Thesis advisor) / Albuquerque, Fabio S (Thesis advisor) / Lewis, Jesse S (Committee member) / Arizona State University (Publisher)
Created2023
Description
Hydration status serves as an essential pillar of human health. Adequate hydration reduces cardiovascular strain, improves the body's ability to thermoregulate, stabilizes mood, and may reduce the risk of physiologic diseases like that of diabetes and urolithiasis. While many studies have shown the importance of adequate fluid intake on hydration status, very few have investigated the influence of dietary food moisture on hydration status. This study collected daily food diaries, daily fluid diaries, and spot urine samples over a 24hr period from 694 participants in Northwest Arkansas participating in the HYBISKUS study. Fluid and food diaries were logged in NDSR and analyzed using JMP while combined spot urine samples were analyzed using a freezing point depression osmometer to retrieve 24hr urine osmolality. Urine osmolality data was extracted from 24hr urine samples and used as the hydration status biomarker for study participants. The average contributions of water from fluids and foods in participants was 79.3 ±9.6% and 20.7 ±9.5% respectively. This study found that dietary food moisture has a significant effect on hydration status in adults with no specific macronutrient groups take precedence over any others in regard to dietary food moisture contributions. These results suggest that there are legitmate reasons to consider dietary food moisture intake when water intake recommendations are made for adults attempting to optimize health or prepare for physical exercise.
ContributorsKleinschmidt, Hunter (Author) / Kavouras, Stavros SK (Thesis advisor) / Sweazea, Karen KS (Committee member) / Katsanos, Christos CK (Committee member) / Arizona State University (Publisher)
Created2019
Description
Mast cells, components of the immune system, promote allergic symptoms such as itching, sneezing, and increased intestinal motility. Although mast cells have a detrimental role in allergies, they might have unrecognized physiological functions. Indeed, mast cells have been reported to protect against lethal envenomation. I hypothesized that mast cells have a protective role in the defense against toxins. Because toxin-induced diarrheal diseases are one of the top five causes of mortality in children worldwide (induced by cholera toxin, for example), I tested the role of mast cells in sensing relevant dietary toxins. My goals were to a) establish an in vitro model of mast cell activation using foodborne toxins and b) determine the mast cell transcriptional programs induced by these toxins. To establish the in vitro model, I generated mast cells from murine bone marrow precursors and cultured them in mast cell-specific media for 5 weeks. Mature mast cells were then stimulated with toxins from phylogenetically distinct origins. I found that, surprisingly, no toxin was able to induce significant cell death, even after 24h of culturing, suggesting that mast cells are resistant to the toxic effects of these compounds. To assess mast cell activation, I quantified the levels of TNF-α 6h after toxin exposure. None of the toxins were able to induce TNF-α production by mast cells, suggesting that toxins might not induce inflammation in mast cells. However, I found that mast cells induced expression of activation-related transcripts like Il1b, Tpsab1, Alox5, Egr1, Tnfa and Hdc in response to cholera toxin, when compared with controls. Mast cells stimulated with retrorsine induced the expression of Tph1, Alox5, Il1b and Hdc. Deoxynivalenol induced Ltc4, Il6, Tpsab1, Tnfa, Hdc, and Alox5 while okadaic acid induced Il6, Tnfa, Tph1, Alox5, Egr1, Il1b and Hdc expression. Aconitine only induced Il6, Hdc, and Tpsab1. Lastly, Ochratoxin A induced expression of Il1b, Il6, Tpsab1, Egr1 and Hdc. Altogether, these results suggest that mast cells directly sense and respond to food toxins, which was unknown. How exactly mast cells contribute to toxin defenses will be crucial to investigate as they impact both toxin-induced and inflammatory diseases.
ContributorsGalarza, Mayka (Author) / Borges Florsheim, Esther (Thesis advisor) / Lucas, Alexandra (Committee member) / Mana, Miyeko (Committee member) / Arizona State University (Publisher)
Created2023
Description
Programmed cell death plays an important role in a variety of processes that promote the survival of the host organism. Necroptosis, a form of programmed cell death, occurs through a signaling pathway involving receptor-interacting serine-threonine protein kinase 3 (RIPK3). In response to vaccinia virus infection, necroptosis is induced through DNA-induced activator of interferon (DAI), which activates RIPK3, leading to death of the cell and thereby inhibiting further viral replication in host cells. DAI also localizes into stress granules, accumulations of mRNAs that have stalled in translation due to cellular stress. The toxin arsenite, a canonical inducer of stress granule formation, was used in this project to study necroptosis. By initiating necroptosis with arsenite and vaccinia virus, this research project investigated the roles of necroptosis proteins and their potential localization into stress granules. The two aims of this research project were to determine whether stress granules are important for arsenite- and virus-induced necroptosis, and whether the proteins DAI and RIPK3 localize into stress granules. The first aim was investigated by establishing a DAI and RIPK3 expression system in U2OS cells; arsenite treatment or vaccinia virus infection was then performed on the U2OS cells as well as on U2OSΔΔG3BP1/2 cells, which are not able to form stress granules. The second aim was carried out by designing fluorescent tagging for the necroptosis proteins in order to visualize protein localization with fluorescent microscopy. The results show that arsenite induces DAI-dependent necroptosis in U2OS cells and that this arsenite-induced necroptosis likely requires stress granules. In addition, the results show that vaccinia virus induces DAI-dependent necroptosis that also likely requires stress granules in U2OS cells. Furthermore, a fluorescent RIPK3 construct was created that will allowfor future studies on protein localization during necroptosis and can be used to answer questions regarding localization of necroptosis proteins into stress granules. This project therefore contributes to a greater understanding of the roles of DAI and RIPK3 in necroptosis, as well as the roles of stress granules in necroptosis, both of which are important in research regarding viral infection and cellular stress.
ContributorsGogerty, Carolina (Author) / Jacobs, Bertram (Thesis advisor) / Langland, Jeffrey (Committee member) / Jentarra, Garilyn (Committee member) / Arizona State University (Publisher)
Created2021