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Investigating the Role of ILV1 on Stress Response in Saccharomyces cerevisiae
Get PDFSaccharomyces cerevisiae, a model organism within molecular genetics, is also known for its broad role within baking, brewing, biofuel, and pharmaceutical industries. An unpublished study at The University of Tennessee at Chattanooga observed decreased cell viability in an ILV1 Knockout strain of S. cerevisiae when exposed to environmental stressors. A subsequent study at The University of Tennessee at Chattanooga found expression levels of the candidate genes to be significantly altered within the ILV1 Knockout strain relative to the BY4743 Wildtype strain, demonstrating the reality of a pleiotropic role within ILV1. Now, this study aims to further investigate this peculiar characteristic of ILV1 and role on stress response in S. cerevisiae by analyzing eight candidate genes involved in various metabolic processes. Two strains of S. cerevisiae, a BY4743 Wildtype and ILV1 Knockout, were subjected to identical stress conditions (salinity, osmotic, oxidative, and heat) and RNA was individually extracted from each trial of yeast cells, converted into cDNA, and analyzed through quantitative Real Time Polymerase Chain Reaction (qRT-PCR). The results of this study demonstrate minimal significant variation in candidate gene expression levels between the ILV1 Knockout and the BY4743 Wildtype strains. These results do not entirely support the pleiotropic nature of ILV1 and instead challenge the pleiotropic hypothesis of ILV1, warranting further investigation into the nature of ILV1
The effect of catalyst choice on biodiesel yield and quality using waste cooking oil as a feedstock
Get PDFBiodiesel is one current area of interest as a replacement for traditional diesel fuel. Benefits of biodiesel include that it can be derived from renewable resources, and it possesses properties similar to that of traditional diesel fuel. Biodiesel is often produced through a catalyzed transesterification process, which involves the use of a catalyst to aid in the conversion of triglycerides into alkyl esters. A method called the transesterification double step process (TDSP) was researched and used in this project due to the success seen using this method for the conversion of waste cooking oil to biodiesel. In this project, four basic catalysts were used at two different reaction temperatures to produce biodiesel, with waste cooking oil being used as the feedstock of interest. New cooking oil was also used to produce biodiesel under the same conditions used for the conversion of waste cooking oil. Three experiments were performed for each set of unique reaction conditions, for a total of 48 experiments conducted. Various testing methods were used for characterization of the final biodiesel products, with results allowing for the relationships between biodiesel quality and catalyst choice, temperature, and feedstock to be determined
Larry Sultan: Photography\u27s Role in Shaping Perceptions
Get PDFThis paper and presentation provide an overview and analysis of photographer, Larry Sultan. They explore his background and career providing insights into his practice and projects. The 2 main projects discussed are titled Pictures From Home and The Valley.https://scholar.utc.edu/global-contemporary-artists/1027/thumbnail.jp
Toward explainable machine learning methods for stroke patient outcomes in Tennessee
No full textStroke is one of the leading causes of long-term disability and death in the United States. Stroke patients often face severe health consequences, significantly impacting their lives and placing a substantial financial burden on their families and the wider healthcare system. Therefore, reliable predictions of various patient outcomes, such as early hospital readmission, length of stay (LOS) in the hospital, and risk of mortality, can help patients and healthcare providers in various aspects. Furthermore, successful modeling of such phenomena can help identify the influential factors affecting the patient outcomes, and, by this, improve the quality of care for patients. In this research, we have combined statistical analysis and machine learning (ML) algorithms to enhance the prediction of three patient outcomes — i.e. 30-day readmission, LOS, and mortality — for stroke patients in Tennessee. Since typically such a dataset is imbalanced, due to a small fraction of those events, various ML algorithms, suitable for imbalanced data, such as XGBoost, LightGBM, and CatBoost, were employed in this work. To further improve the performance of the models, various data-level approaches were used to overcome the imbalanced nature of the data. These methods include cluster centroids, NearMiss, and Instant Hardness Threshold. It was shown that such a combination of data modification, especially with under-sampling methods, and suitable ML algorithms can lead to high model performance, measured in terms of Recall and other metrics. Furthermore, based on the features of the data available in our work, using SHAP explainable ML method, the influential factors affecting these outcomes were identified; higher age and mostly the vital signs at the time of admission play an important role in LOS. For 30-day readmission peripheral artery disease, sleep disorders, as well as prescribed medicine such as anticoagulant and antibiotic agents were among the most influential features. For mortality, static patient health conditions were the most influential factors. A simple Graphical User Interface (GUI) was also developed for one of the LOS outcomes, which can be extended to other outcomes, to demonstrate the capability of this work for practical applications
Elementary teachers\u27 perception of preparedness for the elementary science classroom
Get PDFThis dissertation explores the perception of preparedness among elementary teachers to effectively teach three-dimensional science lessons as advocated by the Next Generation Science Standards. A mixed methods approach combining qualitative interviews with quantitative analysis was employed to gain a full understanding of variables that are related to teachers feeling prepared for the classroom and what aspects of teacher preparation and professional experience are areas of success or areas of growth in terms of implementing effective science instruction in a large school district in southeastern Tennessee. Findings revealed teachers completing a full semester of student teaching perceived themselves to be significantly more prepared for the science classroom than those teachers who only completed a partial semester of student teaching. Teacher experience, science methods courses completed, effectiveness of teacher preparation program, and science content knowledge were not shown to have a relationship with teacher perception of preparation for the elementary science classroom. Teachers identified several strengths in teacher preparation programs including firsthand experiences, exemplar professors, and courses designed around education students. On the other hand, weaknesses were identified in teacher preparation programs including limited science coursework, professor limitations, and overall limited preparation for the science classroom. Teachers identified weak preparation in three-dimensional, inquiry-based science in their preparation programs. Ideas to improve teacher preparation were highlighted including a need to focus more heavily on the new science standards, time to create science lessons with colleagues, more time to observe effective science lessons, and more opportunities to teach science lessons in the classroom. In the professional world, teachers identified more time to collaborate with peers, more effective professional development, and a rise in the importance of science teaching as ways to increase teacher preparation for the science classroom. These results indicate a need to revise teacher preparation programs and preparation in the professional world to increase student achievement in elementary science
Spaced out: an exploration of potential ADHD strategies and the Tennessee Comprehensive Assessment Program
Get PDFThe study investigated how implementing academic and behavioral strategies can improve outcomes for students with ADHD by addressing their challenges with cognitive and executive functioning, which impact academic and social skills. Students with ADHD often experience coexisting conditions like anxiety and depression, and they face difficulties in traditional education systems designed for neurotypical learners. Accommodations such as extended time, preferential seating, and breaking tasks into smaller steps are helpful but insufficient. Other strategies included providing digital and written notes, using graphic organizers, incorporating movement, and offering instant rewards to maintain focus and engagement. The research questions focused on the effectiveness of strategies by gender, their impact on academic performance, and the students’ perceptions of the interventions. The study aimed to increase understanding of ADHD in education, contribute to more inclusive practices, and reduce stigmas surrounding ADHD diagnosis and treatment. The study involved a total of 41students from a high school in rural Appalachia of Southeast Tennessee. Five of the 41 students had documented ADHD. The study used a mixed-methods case study design and examined the relationship between these strategies and student achievement on the TCAP English I Practice Test in writing and reading comprehension. It also explored gender differences in ADHD presentation and how these might have influenced the effectiveness of strategies. After conducting Chi-Square tests, results indicated no statistical significance for RQ 1-4. However, for RQ 5, using a paired samples t-test and a two-way ANOVA, it was found students with ADHD scored lower on the self-perception posttest when compared to their peers without ADHD. RQ 6’s qualitative findings indicated students’ positive perceptions of the teacher’s academic and behavioral strategies used, such as communication tools, organizational aids, and classroom management techniques. Even though there were no statistically significant quantitative results, the findings contributed to the understanding of inclusive teaching practices and improving support for neurodivergent learners. Moreover, this research sought to reduce stigma surrounding ADHD by promoting awareness, improving outcomes, and providing students with coping mechanisms for adulthood
The Need for Standards in Autonomous Driving: Exploring Ethical and Social Implications in the Successful Deployment of Autonomous Cars
Get PDFAutonomous driving incorporates applications and algorithms of AI to enable self-driving vehicles as viable transportation options across the country. Self-driving vehicles may provide advantages over human-driven vehicles in several ways, including cost savings, accessibility to transportation, efficiency, convenience, and reduced traffic. However, there are still challenges due to the added lack of cybersecurity issues, laws, and ethical factors to consider in gaining public trust. Ethical issues such as choosing how to respond to accidents and algorithms for safety decisions are factors in the progression of autonomous vehicles for many companies. Since a gap exists in research and development for ethical and other issues, the purpose of the study is to explore the challenges and problems related to safety and reliability, regulatory and legal issues, technological changes and ethical challenges, scalability, public perception and acceptance, and data security and privacy concerns. The scope of this paper is largely focused on the technical and ethical concerns related to the creation and usage of autonomous cars. This study intends to uncover the gaps in legislation, public opinion, and industry readiness through a data-driven survey of UTC students, case studies, and an examination of recent literature and provide solutions based on this research
Pacific Islander Mental Health: A Literature Review
Get PDFMental health among Pacific Islanders remains an underexplored area in research. This review aims to synthesize existing research on the mental health status of Pacific Islanders, focusing on mental health risk factors and mental health service utilization. A systematic search across APA PsychInfo spanning from 2015 to 2024 yielded 11 relevant articles, which were subsequently analyzed and synthesized. Findings suggest that Pacific Islanders experience unique stressors, including, racial discrimination, socioeconomic disparities, and cultural stigma surrounding mental health. However, there is a disparity in culturally sensitive assessment tools and interventions tailored specifically to this population. Future research should prioritize phenomenological methods, culturally informed assessments, and community-based interventions to better understand and address the mental health implications of Pacific Islanders. Practitioners, clinicians, counselors, and researchers should work together to develop culturally competent approaches that promote mental wellness and reduce disparities among Pacific Islander populations
Assessing a police department\u27s reliance on the National Integrated Ballistic Information Network (NIBIN) to solve shooting cases: Can NIBIN increase shooting clearance rates?
Get PDFOften, police response to shooting incidents lacks the investigative leads needed for successful follow-up and prosecution. This may result from a lack of surveillance video or witnesses investigators rely on to solve such cases quickly. To overcome these obstacles, law enforcement has turned to forensic science to provide police with the information and clues to be successful. Ballistic evidence is one such tool that can provide police with detailed information regarding linked shooting cases that can help identify possible new witnesses, surveillance videos, potential suspects and criminal groups, motive, and account for the number of firearms used at the scene. This is all made possible with access to the National Integrated Ballistic Information Network (NIBIN) database, which is overseen by the Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF). Though such a database is useful, law enforcement agencies that do not have access must rely on consolidated state or local labs for ballistic evidence processing. This results in delayed lab reports by weeks or even months, failing to provide the timely information investigators need. To overcome such delays, police departments across the United States have begun purchasing the technology to enter and compare ballistic evidence in the NIBIN database in hopes of identifying other linked shooting cases. Based on previous research, this may not always mean the agency will obtain timely information if they fail to have a plan to push NIBIN leads generated, when there is a match, out to investigators whose job is to follow up on such information. This study examined one department’s use of the NIBIN database for leads and how investigators used them as part of the investigative process. Using a mixed-methods research approach, data was obtained from the agency and investigators to determine if the agency saw a reduction in fatal and nonfatal shootings and improved clearance rates after becoming a NIBIN site compared to previous periods when they did not have direct access to the NIBIN database. Furthermore, information obtained from investigators sought to understand their perceptions of using the NIBIN database as a tool in the investigative process
Transcription factors and regulatory proteins in the control of eukaryotic gene expression
No full textTranscription factors (TFs) function as precision switches that integrate signaling inputs, chromatin state, and protein homeostasis to control gene expression. This thesis unites three interconnected research themes: (1) mechanistic studies of the ubiquitin-proteasome system (UPS) in regulating eukaryotic TFs, focusing on polymerase-associated Factor 1 (Paf1) and TATA-box binding protein-associated factor 2 (Taf2); (2) identification of biomarker genes within odor-related TF networks; and (3) integration of published undergraduate research linking molecular regulation, bioinformatics, and synthetic biology. These themes are purposefully structured so that mechanistic insight into TF control sets up network-level discovery and, in turn, motivates applied and translational directions. In Part 1, we examined the UPS-mediated regulation of Paf1 and Taf2. While UPS is known to control their stability, its precise mechanisms and transcriptional dependency were unclear. Our results showed that Paf1 abundance remains unchanged upon α-amanitin-induced transcriptional inhibition, suggesting that UPS regulation may occur independently of transcription and may reflect protein quality control rather than transcription-coupled degradation. Having established transcription-independent UPS effects on Paf1, we next asked whether a parallel, ligase-specific mechanism might govern Taf2. For Taf2, we screened 30 of 60 known yeast E3 ligases but did not identify a specific ligase, indicating the need for broader screening to pinpoint its regulator. Building on these mechanistic findings, we moved from protein-level regulation to system-level patterns by interrogating TF-centered networks computationally. In Part 2, we used computational approaches to identify biomarker genes within odor-related TF networks. Through Gene Expression Omnibus (GEO) dataset analysis, Adenylate Cyclase 3 (ADCY3) emerged as a key dysregulated olfactory-related gene in kidney and colorectal cancers. Functional pathway analysis revealed that ADCY3 modulates tumor progression through cyclic adenosine monophosphate (cAMP) signaling via protein kinase A (PKA), exchange protein directly activated by cAMP (EPAC), and cAMP response element–binding protein (CREB) pathways, highlighting its potential as a potential therapeutic target. The identification of ADCY3-linked signaling as a candidate driver of phenotype provided a natural bridge to integrative, application-oriented studies. Part 3 synthesizes findings from three of our recent publications, demonstrating the integration of molecular and bioinformatics strategies to address biomedical and environmental challenges. The first study identified TOP2A as a prognostic biomarker and a compound from Andrographis paniculata as a promising therapeutic candidate for kidney and liver cancers. The second study examined farnesoid X receptor (FXR) agonists in regulating kinase pathways in non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), emphasizing their therapeutic significance. The third introduced PlastiCRISPR, a CRISPR-based system enabling microbial plastic degradation, showcasing the potential of genome editing for environmental applications. Together, these studies provide a cohesive framework for dissecting transcription factor regulation and translating molecular signatures into actionable biomarkers, bridging fundamental molecular biology with applied biomedical and environmental research