Click on this link to download the full high-definition interactive pdf for AJUR Volume 20 Issue 4 (March 2024) or https://doi.org/10.33697/ajur.2024.100
Links to individual manuscripts, abstracts, and keywords are provided below.
p.3. On Sample Size Needed for Block Bootstrap Confidence Intervals to Have Desired Coverage Rates
Mathew Chandy, Elizabeth D. Schifano, & Jun Yan
https://doi.org/10.33697/ajur.2024.101
ABSTRACT: Block bootstrap is widely used in constructing confidence intervals for parameters estimated from stationary time series. Theoretically, the method should provide valid confidence intervals as the length of the time series goes to infinity. In practice, however, it is necessary to know how large of a finite sample is required for block bootstrap confidence intervals to work well. This study aims to answer this question in a simple simulation setting where the data are generated from a first-order autoregressive process. The empirical coverage rates of several commonly used bootstrap confidence intervals for the mean, standard deviation, and the lag-1 autocorrelation coefficient are compared. A quite large sample is found necessary for the intervals to have the right coverage rates even when estimating a simple parameter like the mean. Some block bootstrap methods could fail when estimating the lag-1 autocorrelation. It is surprising that the coverage property even deteriorates as the sample size increases with some commonly used block bootstrap confidence intervals including the percentile intervals and bias-corrected intervals. KEYWORDS: Autocorrelation; Bias-Correction; Centering; Dependent Data; Percentile; Resampling; Simulation; Time Series
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p.17. Faculty Opinions of AI Tools: Text Generators and Machine Translators
Mahlet Yitages & Akie Kasai
https://doi.org/10.33697/ajur.2024.102
ABSTRACT: Artificial Intelligence (AI) tools recently became a prominent concern in higher education classrooms. Many teachers have implemented the technology into their assignments, while others are strictly against this technology’s use for assignments. Either way, students have found ways to use it in their academic careers. Though research on the power of AI in the workplace exists, research is lacking in its appropriate use in higher education. Universities need to define AI’s role on campus and establish guidelines on how these tools may or may not be used and how faculty can recognize misuse, specifically related to academic integrity. This study aimed to determine how faculty view AI as a part of undergraduate literature, language, and linguistics programs. From the interview study, common themes emerged, including implementation, academic integrity, the human aspect of linguistics, and the future of AI writing tools. Interviewed faculty also stated that those in higher education must tread carefully through this strong intersection between technology and the arts to use AI responsibly, strategically, and ethically. KEYWORDS: Artificial Intelligence (AI); Artificial General Intelligence (AGI); Linguistics; Higher Education; ChatGPT; Machine Translation; Academic Integrity; Ethics
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p.29. The Predicted Structure of a Thermophilic Malate Synthase
Shaelee Nielsen, Jantzen Orton, & Bruce R. Howard
https://doi.org/10.33697/ajur.2024.103
ABSTRACT: This project aims to solve the structure of the crenarchaeal Sulfolobus acidocaldarius enzyme malate synthase. Other known malate synthase enzymes have been found to require a magnesium ion in the active site to carry out catalytic activities, but a study reported that S. acidocaldarius malate synthase does not require magnesium. This suggests a novel mechanism for this enzyme. Additionally, the mature S. acidocaldarius protein is approximately 100 residues larger than any other structurally characterized malate synthase. It has also been reported to form a dimer, while previously solved structures have only displayed monomeric, trimeric, and hexameric arrangements. We plan to determine the structure experimentally. However, major advances in the accuracy of protein structure prediction were made recently by AlphaFold, an artificial intelligence system developed by DeepMind, which has revolutionized the field and has largely solved the protein folding problem. A similar AI system, RoseTTAFold, developed by David Baker’s lab at the University of Washington, has been publicly available. Here, we report our analysis of the structure of this protein, predicted using both of these algorithms and of a predicted structural model for the dimeric form of the enzyme using ClusPro. Our results strongly support a conserved catalytic mechanism requiring magnesium, which is common with all previously solved malate synthase isoforms. KEYWORDS: Glyoxylate Cycle; Malate synthase; Protein Prediction; Thermophile; Sulfolobus acidocaldarius; Magnesium; AlphaFold; RoseTTAFold
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p.39. The Impact of Narratives on Healthcare Decision-Making in Online Discourse
Zayd Almaya & Tom Mould
https://doi.org/10.33697/ajur.2024.104
ABSTRACT: This study examines first what type of evidence is most influential in online discussions for patients when making decisions about their health and second how people deploy, interpret, and react to stories in these online discussions to better understand the role and importance of narrative in the medical field. Data was gathered on the platform Reddit using the subreddit r/melanoma for a duration of two weeks. 242 posts were collected and analyzed. Using a combination of grounded theory and coding criteria from sociologist and narrative scholar Francesca Polletta, a code book was developed and applied to all 242 posts to assess narrative impact and engagement. Results demonstrate that evidence based on past experiences and factual information were the most persuasive. Additionally, stories yielded greater discussion, greater empathetic connections, and greater positive responses from online discussants than other forms of evidence. Further, those positive responses indicate that patients seeking medical advice were more likely to express agreement with the advice when it was offered with a story. Given these results, greater attention should be paid to narratives shared in online communities, particularly considering the levels of misinformation and disinformation found online and the evolving relationships between doctors and patients where authority is no longer so easily assumed. KEYWORDS: Narrative; Personal Experience; Fact; Evidence; Persuasion; Medical Decision-Making; Social Media
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p.53. Elongation Factor P is Required for Processes Associated with Acinetobacter Pathogenesis
Dylan Kostrevski & Anne Witzky
https://doi.org/10.33697/ajur.2024.105
ABSTRACT: Antibiotic resistance is one of the world’s fastest-growing and most prevalent problems today. The influx of antibiotics within our environment from inadequate antibiotic stewardship has led to a surge of drug-resistant microorganisms. The CDC has classified Carbapenem-resistant Acinetobacter (CRA) as an urgent threat within this crisis. New drug development is imperative to combat infections caused by drug-resistant pathogens such as CRA. Bacterial translation, the process of protein synthesis by the ribosome, is a common target for new antibiotic development. Elongation factor P (EF-P) is a universally conserved translation factor required for antibiotic resistance in many bacteria. In this study, we assessed the importance of EF-P in processes associated with Acinetobacter pathogenesis. In the absence of EF-P, Acinetobacter baylyi displays decreased biofilm formation, surface-associated motility, and resistance to beta-lactams and carbapenems. This data holds hope for future drug development targeting EF-P in pathogens closely related to A. baylyi. KEYWORDS: Acinetobacter baylyi; Translation; Ribosome; Elongation Factor P; Polyproline; Biofilm; Surface Associated Motility; Antibiotic Resistance
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p.63. Measurement System for Compliance in Tubular Structures
Ave Kludze, Anthony R. D’Amato, & Yadong Wang
https://doi.org/10.33697/ajur.2024.106
ABSTRACT: Tubular structures such as blood vessels, intestines, and the trachea are common in various life forms. This paper describes a measurement system to test the mechanical compliance of tubular structures. The novelty of the system lies in its hardware and software. Here we use vascular graft as an example to demonstrate the utility of the system. A fully synthetic vascular graft would ideally mimic the mechanical and architectural properties of a native blood vessel. Therefore, mechanical testing of the graft material under physiological pressure is crucial to characterizing its potential in vivo performance. The device operates through a low-cost Arduino-based control system that simulates and measures cyclic fluid pressure changes over time and a laser micrometer that measures diameter changes with pressure. This system is low-cost, assuming one already has access to a laser micrometer. In contrast to previous methods, this system offers a simple, low-cost, and customizable option to measure compliance and is equipped with data acquisition/analysis programs. These programs include a MATLAB application that processes and synchronizes Arduino Uno pressure signals and LabChart Pro diameter readings. Lastly, this paper explains the hardware and software of the measurement system. The system is beneficial for testing the pressure-diameter relationship of tubular structures of varying sizes and materials. KEYWORDS: Tubular Structures; Compliance; Data Acquisition System; Physiological Pressure; Diameter Change; Arduino Uno; LabChart Pro; MATLAB
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p.77. Fibroblast Embedded 3D Collagen as a Potential Tool for Epithelial Wound Repair
Claire Behning, Lia Kelly, Emma Smith, Yizhe Ma, & Louis Roberts
https://doi.org/10.33697/ajur.2023.107
ABSTRACT: Collagen is a functional biomaterial with many applications, including wound healing. 3D collagen hydrogels mimic an in vivo cell culture experience used in cell survival and growth studies. In experimentally examining human cells under contact with 3D collagen, it is possible to understand the role of collagen in human epithelial tissue repair. This study explored the growth and attachment response of human MCF-7 cells when exposed to 3D collagen by investigating if the presence of NIH/3T3 fibroblasts embedded within the collagen should produce an increased wound-healing response. 3D collagen and fibroblast presence were able to be analyzed in tandem with a “sandwich-like” configuration of the gels to determine how these variables impact or improve the tissue repair response in MCF-7 cells. Examinations in growth, attachment, viability, and migration patterns demonstrated that MCF-7 repair response may be increased when in contact with NIH/3T3 embedded 3D collagen without impairing viability. Most notably, results from the migration assay revealed that MCF-7 cells migrate the most when covered by and adhered to cellular 3D collagen. Fibroblast-embedded collagen on top of and below MCF-7 cells exceeded quantitative assessment to near confluency, whereas less than 50 counted cells per image migrated without any top collagen layering. The continuation of these methods could involve in vivo experiments that incorporate live animal models to determine if these results will continue to extend to live tissue. KEYWORDS: Collagen; 3D Collagen; Fibroblasts; Wound Healing; Hydrogels; Tissue Repair; Migration
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