Matching Items (91)
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Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of

Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not

Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress. In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Evolution is a key feature of undergraduate biology education: the AmericanAssociation for the Advancement of Science (AAAS) has identified evolution as one of the five core concepts of biology, and it is relevant to a wide array of biology-related careers. If biology instructors want students to use evolution to address scientific challenges post-graduation,

Evolution is a key feature of undergraduate biology education: the AmericanAssociation for the Advancement of Science (AAAS) has identified evolution as one of the five core concepts of biology, and it is relevant to a wide array of biology-related careers. If biology instructors want students to use evolution to address scientific challenges post-graduation, students need to be able to apply evolutionary principles to real-life situations, and accept that the theory of evolution is the best scientific explanation for the unity and diversity of life on Earth. In order to help students progress on both fronts, biology education researchers need surveys that measure evolution acceptance and assessments that measure students’ ability to apply evolutionary concepts. This dissertation improves the measurement of student understanding and acceptance of evolution by (1) developing a novel Evolutionary Medicine Assessment that measures students’ ability to apply the core principles of Evolutionary Medicine to a variety of health-related scenarios, (2) reevaluating existing measures of student evolution acceptance by using student interviews to assess response process validity, and (3) correcting the validity issues identified on the most widely-used measure of evolution acceptance - the Measure of Acceptance of the Theory of Evolution (MATE) - by developing and validating a revised version of this survey: the MATE 2.0.
ContributorsMisheva, Anastasia Taya (Author) / Brownell, Sara (Thesis advisor) / Barnes, Elizabeth (Committee member) / Collins, James (Committee member) / Cooper, Katelyn (Committee member) / Sterner, Beckett (Committee member) / Arizona State University (Publisher)
Created2023
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People with disabilities are underrepresented in the Science, Technology, Engineering, and Math (STEM) workforce (NSF, 2016). One way to increase representation of people with disabilities in STEM fields is by supporting students with disabilities (SWDs) at the undergraduate level. In undergraduate education in the United States, SWDs represent approximately 19%

People with disabilities are underrepresented in the Science, Technology, Engineering, and Math (STEM) workforce (NSF, 2016). One way to increase representation of people with disabilities in STEM fields is by supporting students with disabilities (SWDs) at the undergraduate level. In undergraduate education in the United States, SWDs represent approximately 19% of the undergraduate community (U.S. Census Bureau, 2021). However, SWDs have lower graduation and retention rates. This is particularly true for STEM majors, where SWDs make up about 9% of the STEM community in higher education. The AAC&U has defined a list of High-Impact Practices (HIPs), which are active learning practices and experiences that encourage deep learning by promoting student engagement, and could ultimately support student retention (AAC&U). To date, student-centered disability research has not explored the extent to which SWDs participate in HIPs. We hypothesized that SWDs are less likely than students without disabilities to be involved in HIPs and that students who identify as having severe disabilities would participate in HIPs at lower rates. In this study, we conducted a national survey to examine involvement in HIPs for students with disabilities in STEM. We found that disability status significantly affects the probability of participation in undergraduate research, but is not a significant factor for participation in most other HIPs. We also found that self-reported severity of disability did not significantly impact participation in HIPs, though we observed trends that students reporting higher severity generally reported lower participation in HIPs. Our open-ended responses did indicate that SWDs still faced barriers to participation in HIPs.
ContributorsPais, Danielle (Author) / Brownell, Sara (Thesis director) / Cooper, Katelyn (Committee member) / Barrett, The Honors College (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-05
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Description

There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and

There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and anxiety. No studies have examined the relationship between active learning and undergraduate depression. To address this gap in the literature, we conducted hour-long exploratory interviews with 29 students with depression who had taken active learning science courses across six U.S. institutions. We probed what aspects of active learning practices exacerbate or alleviate depressive symptoms and how students’ depression affects their experiences in active learning. We found that aspects of active learning practices exacerbate and alleviate students’ depressive symptoms, and depression negatively impacts students’ experiences in active learning. The underlying aspects of active learning practices that impact students’ depression fall into four overarching categories: inherently social, inherently engaging, opportunities to compare selves to others, and opportunities to validate or invalidate intelligence. We hope that by better understanding the experiences of undergraduates with depression in active learning courses we can create more inclusive learning environments for these students.

ContributorsAraghi, Tala (Author) / Cooper, Katelyn (Thesis director) / Brownell, Sara (Committee member) / Busch, Carly (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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Mounting evidence suggests that gender biases favoring men and racial biases favoring whites and Asians contribute to the underrepresentation of women and underrepresented minorities (URM) in science, technology, engineering, and mathematics (STEM). Systemic issues caused by gender and racial biases create barriers that prevent women and URM from entering STEM

Mounting evidence suggests that gender biases favoring men and racial biases favoring whites and Asians contribute to the underrepresentation of women and underrepresented minorities (URM) in science, technology, engineering, and mathematics (STEM). Systemic issues caused by gender and racial biases create barriers that prevent women and URM from entering STEM from the structure of education to admission or promotions to higher-level positions. One of these barriers is unconscious biases that impact the quality of letters of recommendation for women and URM and their success in application processes to higher education. Though letters of recommendation provide a qualitative aspect to an application and can reveal the typical performance of the applicant, research has found that the unstructured nature of the traditional recommendation letter allows for gender and racial bias to impact the quality of letters of recommendation. Standardized letters of recommendation have been implemented in various fields and have been found to reduce the presence of bias in recommendation letters. This paper reviews the trends seen across the literature regarding equity in the use of letters of recommendation for undergraduates.
ContributorsKolath, Nina (Author) / Brownell, Sara (Thesis director) / Goodwin, Emma (Committee member) / Barrett, The Honors College (Contributor) / School of Criminology and Criminal Justice (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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This work focuses on a novel approach to combine electrical current with cyanobacterial technology, called microbial electrophotosynthesis (MEPS). It involves using genetically modified PSII-less Synechocystis PCC 6803 cells to avoid photoinhibition, a problem that hinders green energy. In the work, a cathodic electron delivery system is employed for growth and

This work focuses on a novel approach to combine electrical current with cyanobacterial technology, called microbial electrophotosynthesis (MEPS). It involves using genetically modified PSII-less Synechocystis PCC 6803 cells to avoid photoinhibition, a problem that hinders green energy. In the work, a cathodic electron delivery system is employed for growth and synthesis. Photoinhibition leads to the dissipation energy and lower yield, and is a major obstacle to preventing green energy from competing with fossil fuels. However, the urgent need for alternative energy sources is driven by soaring energy consumption and rising atmospheric carbon dioxide levels. When developed, MEPS can contribute to a carbon capture technology while helping with energy demands. It is thought that if PSII electron flux can be replaced with an alternative source photosynthesis could be enhanced for more effective production. MEPS has the potential to address these challenges by serving as a carbon capture technology while meeting energy demands. The idea is to replace PSII electron flux with an alternative source, which can be enhanced for higher yields in light intensities not tolerated with PSII. This research specifically focuses on creating the initiation of electron flux between the cathode and the MEPS cells while controlling and measuring the system in real time. The successful proof-of-concept work shows that MEPS can indeed generate high-light-dependent current at intensities up to 2050 µmol photons m^‒2 s^‒1, delivering 113 µmol electrons h^‒1 mg-chl^‒1. The results were further developed to characterize redox tuning for electron delivery of flux to the photosynthetic electron transport chain and redox-based kinetic analysis to model the limitations of the MEPS system.
ContributorsLewis, Christine Michelle (Author) / Torres, César I (Thesis advisor) / Fromme, Petra (Thesis advisor) / Woodbury, Neal (Committee member) / Hayes, Mark (Committee member) / Arizona State University (Publisher)
Created2023
Description

Mental health conditions can impact college students’ social and academic achievements. As such, students may disclose mental illnesses on medical school applications. Yet, no study has investigated to what extent disclosure of a mental health condition impacts medical school acceptance. We designed an audit study to address this gap. We

Mental health conditions can impact college students’ social and academic achievements. As such, students may disclose mental illnesses on medical school applications. Yet, no study has investigated to what extent disclosure of a mental health condition impacts medical school acceptance. We designed an audit study to address this gap. We surveyed 99 potential admissions committee members from at least 43 unique M.D.-granting schools in the U.S. Participants rated a fictitious portion of a medical school application on acceptability, competence, and likeability. They were randomly assigned to a condition: an application that explained a low semester GPA due to a mental health condition, an application that explained a low semester GPA due to a physical health condition, or an application that had a low semester GPA but did not describe any health condition. Using ANOVAs, multinomial regression, and open-coding, we found that committee members do not rate applications lower when a mental health condition is revealed. When asked about their concerns regarding the application, 27.0% of participants who received an application that revealed a mental health condition mentioned it as a concern; 14.7% of participants who received an application that revealed a physical health condition mentioned it as a concern. Committee members were also asked about when revealing a mental health condition would be beneficial and when it would be detrimental. This work indicates that medical school admissions committee members do not exhibit a bias towards mental health conditions and provides recommendations on how to discuss mental illness on medical school applications.

ContributorsAbraham, Anna (Author) / Brownell, Sara (Thesis director) / Cooper, Katelyn (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2022-05
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Similar-identity role models, including instructors, can benefit science undergraduates by enhancing their self-efficacy and sense of belonging. However, for students to have similar-identity role models based on identities that can be hidden, instructors need to disclose their identities. For concealable stigmatized identities (CSIs) – identities that can be hidden and

Similar-identity role models, including instructors, can benefit science undergraduates by enhancing their self-efficacy and sense of belonging. However, for students to have similar-identity role models based on identities that can be hidden, instructors need to disclose their identities. For concealable stigmatized identities (CSIs) – identities that can be hidden and carry negative stereotypes – the impersonal and apolitical culture cultivated in many science disciplines likely makes instructor CSI disclosure unlikely. This dissertation comprises five studies I conducted to assess the presence of instructor role models with CSIs in undergraduate science classrooms and evaluate the impact on undergraduates of instructor CSI disclosure. I find that science instructors report CSIs at lower rates than undergraduates and typically keep these identities concealed. Additionally, I find that women instructors are more likely to disclose their CSIs to students compared to men. To assess the impact of instructor CSI disclosure on undergraduates, I report on findings from a descriptive exploratory study and a controlled field experiment in which an instructor reveals an LGBTQ+ identity. Undergraduates, especially those who also identify as LGBTQ+, benefit from instructor LGBTQ+ disclosure. Additionally, the majority of undergraduate participants agree that an instructor revealing an LGBTQ+ identity during class is appropriate. Together, the results presented in this dissertation highlight the current lack of instructor role models with CSIs and provide evidence of student benefits that may encourage instructors to reveal CSIs to undergraduates and subsequently provide much-needed role models. I hope this work can spark self-reflection among instructors to consider revealing CSIs to students and challenge the assumption that science environments should be devoid of personal identities.
ContributorsBusch, Carly Anne (Author) / Cooper, Katelyn (Thesis advisor) / Brownell, Sara (Thesis advisor) / Collins, James (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2024
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Education through field exploration is fundamental in geoscience. But not all students enjoy equal access to field-based learning because of time, cost, distance, ability, and safety constraints. At the same time, technological advances afford ever more immersive, rich, and student-centered virtual field experiences. Virtual field trips may be the only

Education through field exploration is fundamental in geoscience. But not all students enjoy equal access to field-based learning because of time, cost, distance, ability, and safety constraints. At the same time, technological advances afford ever more immersive, rich, and student-centered virtual field experiences. Virtual field trips may be the only practical options for most students to explore pedagogically rich but inaccessible places. A mixed-methods research project was conducted on an introductory and an advanced geology class to explore the implications of learning outcomes of in-person and virtual field-based instruction at Grand Canyon National Park. The study incorporated the Great Unconformity in the Grand Canyon, a 1.2 billion year break in the rock record; the Trail of Time, an interpretive walking timeline; and two immersive, interactive virtual field trips (iVFTs). The in-person field trip (ipFT) groups collectively explored the canyon and took an instructor-guided inquiry hike along the interpretive Trail of Time from rim level, while iVFT students individually explored the canyon and took a guided-inquiry virtual tour of Grand Canyon geology from river level. High-resolution 360° spherical images anchor the iVFTs and serve as a framework for programmed overlays that enable interactivity and allow the iVFT to provide feedback in response to student actions. Students in both modalities received pre- and post-trip Positive and Negative Affect Schedules (PANAS). The iVFT students recorded pre- to post-trip increases in positive affect (PA) scores and decreases in negative (NA) affect scores, representing an affective state conducive to learning. Pre- to post-trip mean scores on concept sketches used to assess visualization and geological knowledge increased for both classes and modalities. However, the iVFT pre- to post-trip increases were three times greater (statistically significant) than the ipFT gains. Both iVFT and ipFT students scored 92-98% on guided-inquiry worksheets completed during the trips, signifying both met learning outcomes. Virtual field trips do not trump traditional in-person field work, but they can meet and/or exceed similar learning objectives and may replace an inaccessible or impractical in-person field trip.
ContributorsRuberto, Thomas (Author) / Semken, Steve (Thesis advisor) / Anbar, Ariel (Committee member) / Brownell, Sara (Committee member) / Arizona State University (Publisher)
Created2018