Physical Sciences and Mathematics Commons^™

Asthma Prevalence Among United States Population Insights From Nhanes Data Analysis, Sarya Swed, Bisher Sawaf, Feras Al-Obeidat, Wael Hafez, Amine Rakab, Hidar Alibrahim, Mohamad Nour Nasif, Baraa Alghalyini, Abdul Rehman Zia Zaidi, Lamees Alshareef, Fadel Alqatati, Fathima Zamrath Zahir, Ashraf I. Ahmed, Mulham Alom, Anas Sultan, Abdullah Almahmoud, Agyad Bakkour, Ivan Cherrez-Ojeda

All Works

Asthma is a prevalent respiratory condition that poses a substantial burden on public health in the United States. Understanding its prevalence and associated risk factors is vital for informed policymaking and public health interventions. This study aims to examine asthma prevalence and identify major risk factors in the U.S. population. Our study utilized NHANES data between 1999 and 2020 to investigate asthma prevalence and associated risk factors within the U.S. population. We analyzed a dataset of 64,222 participants, excluding those under 20 years old. We performed binary regression analysis to examine the relationship of demographic and health related covariates with …

Highly Toxic Aβ Begets More Aβ, Merc M. Kemeh, Noel Lazo

Chemistry

No abstract provided.

Identifying Phytoremediation Performing Plant Species That Can Be Utilized In The Improvement Of Heavy Metal Contaminated Soils, Ashley Clark*, Samuel Mutiti

Graduate Research Showcase

Heavy metal pollution is a problem associated with industrialization and development. Two major metals that are commonly mined and can enter the environment, which can jeopardize communities’ health, are copper (Cu) and lead (Pb). There are different options for reducing heavy metal pollution in the environment via remediation efforts, including physical, chemical, and biological methods. However, physical and chemical remediation can be costly and labor-intensive, making them unsuitable for regions that do not have the funds to utilize these practices. Biological remediation is a more cost-conservative practice that has been shown in many studies to be effective in the gradual …

An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient …

Grey Relational Analysis And Canonical Correlation Analysis Of Air Pollution In Three Kentucky Counties, Sarah Hartman

Masters Theses & Specialist Projects

Air pollution is a crucial factor that affects both the environment and public health. Various methods are available for assessing air quality and pollution levels, such as regression models, principal component analysis, and factor analysis tools. However, some of these methods present issues in multicollinearity and the nature of collected data. It is important to recognize that air pollution data is often uncertain, incomplete, and contains limited valid data points. Weather conditions and economic activities are also factors that can affect air pollution. With growing communities in Kentucky (KY), it is essential to address these factors as the state has …

Synthesis Of Gold Nanoparticles Via Pulsed Liquid Ablation For Use In The Photodynamic Therapy Of Bacteria, Justice Ben Yosef

Masters Theses & Specialist Projects

With the ever-increasing threat of antibiotic resistant bacteria, alternative treatment methods have been developed including photodynamic therapy (PDT). Within the PDT process, photosensitizers are used to generate reactive oxygen species (ROS) and facilitate the cell termination process. This work lays the conceptual foundation for the functionalization of the photosensitizer methylene blue (MB) with gold nanoparticles (AuNPs) and INF-55 as a potential inhibitor of the AcrAB-TolC efflux pump to enhance the effectivity of the PDT process.

AuNPs were synthesized using pulsed laser ablation in an aqueous citrate solution. Both nanosecond and picosecond pulse durations, as well as both 532 nm and …

Scholars Day 2024 Program Of Events, Carl Goodson Honors Program

Scholars Day

This is the program of events for the 2023 Scholars Day Conference, where undergraduates across disciplines present their scholarly and creative works.

Apigenin Alleviates Autistic-Like Stereotyped Repetitive Behaviors And Mitigates Brain Oxidative Stress In Mice, Petrilla Jayaprakash, Dmytro Isaev, Keun-Hang Susan Yang, Rami Beiram, Murat Oz, Bassem Sadek

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Studying the involvement of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in neuropsychiatric brain disorders such as autism spectrum disorder (ASD) has gained a growing interest. The flavonoid apigenin (APG) has been confirmed in its pharmacological action as a positive allosteric modulator of α7-nAChRs. However, there is no research describing the pharmacological potential of APG in ASD. The aim of this study was to evaluate the effects of the subchronic systemic treatment of APG (10–30 mg/kg) on ASD-like repetitive and compulsive-like behaviors and oxidative stress status in the hippocampus and cerebellum in BTBR mice, utilizing the reference drug aripiprazole (ARP, 1 …

Health And Healthcare: Designing For The Social Determinants Of Health And Blue Zones In North Nashville, Rebecca Tonguis, Honor Thomas, Olivia Hobbs

Belmont University Research Symposium (BURS)

Owned by North Nashville’s First Community Church, a now empty site in the Osage-North Fisk neighborhood of North Nashville has been identified as a potential site for a new location of The Store, in addition to a community-centric architectural development based on the social determinants of health and informed by the principles behind Blue Zones, the locations with the highest lifespans in the world. Opened by Brad Paisley and Kimberly Williams-Paisley, The Store is a free grocery store that “allow[s] people to shop for their basic needs in a way that protects dignity and fosters hope”, for which North Nashville …

Accurate Characterization Of Binding Kinetics And Allosteric Mechanisms For The Hsp90 Chaperone Inhibitors Using Ai-Augmented Integrative Biophysical Studies, Chao Xu, Xianglei Zhang, Lianghao Zhao, Gennady M. Verkhivker, Fang Bai

Mathematics, Physics, and Computer Science Faculty Articles and Research

The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure–kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate …

Simultaneous Extraction And Quantitative Analysis Of S-Methyl-L-Cysteine Sulfoxide, Sulforaphane And Glucosinolates In Cruciferous Vegetables By Liquid Chromatography Mass Spectrometry, Armaghan Shafaei, Caroline R. Hill, Jonathan M. Hodgson, Lauren C. Blekkenhorst, Mary C. Boyce

Research outputs 2022 to 2026

Sulfur containing compounds including glucosinolates (GLS), sulforaphane (SFN) and S-methyl-L-cysteine sulfoxide (SMCSO) have been proposed to be partly responsible for the beneficial health effects of cruciferous vegetables. As such, greater understanding of their measurements within foods is important to estimate intake in humans and to inform dietary intervention studies. Herein is described a simple and sensitive method for simultaneous analysis of 20 GLS, SFN and SMCSO by liquid chromatography mass spectrometry. Analytes were effectively retained and resolved on an Xbridge C18 column. Detection can be achieved using high resolution or unit resolution mass spectrometry; the latter making the method more …

Β-Sheets Mediate The Conformational Change And Allosteric Signal Transmission Between The Aslov2 Termini, Sian Xiao, Mayar Terek Ibrahim, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Avena sativa phototropin 1 light-oxygen-voltage 2 domain (AsLOV2) is a model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change begins with the unfolding of the N-terminal A'α helix in the dark state followed by the unfolding of the C-terminal Jα helix. The light state is characterized by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets are identified as crucial components for mediating allosteric signal transmission between the two termini. Through combined experimental and computational investigations, the Hβ …

Exploring The Design Of Low-End Technology To Increase Patient Connectivity To Electronic Health Records, Rens Kievit, Abdullahi Abubakar Kawu, Mirjam Van Reisen, Dympna O'Sullivan, Lucy Hederman

Conference papers

The tracking of the vitals of patients with long term health problems is essential for clinicians to determine proper care. Using Patient Generated Health Data (PGHD) communicated remotely allows patients to be monitored without requiring frequent hospital visits. Issues might arise when the communication of data digitally is difficult or impossible due to a lack of access to internet or a low level of digital literacy as is the case in many African countries. The VODAN-Africa project (van Reisen et al., 2021) started in 2020 and has greatly increased the capabilities of clinics in different countries in both Africa and …

Navigating Through Chaos, Hoong Chuin Lau

Asian Management Insights

How AI and optimisation models can strengthen supply chain resilience.

Identifying Rural Health Clinics Within The Transformed Medicaid Statistical Information System (T-Msis) Analytic Files, Katherine Ahrens Mph, Phd, Zachariah Croll, Yvonne Jonk Phd, John Gale Ms, Heidi O'Connor Ms

Rural Health Clinics

Researchers at the Maine Rural Health Research Center describe a methodology for identifying Rural Health Clinic encounters within the Medicaid claims data using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files.

Background: There is limited information on the extent to which Rural Health Clinics (RHC) provide pediatric and pregnancy-related services to individuals enrolled in state Medicaid/CHIP programs. In part this is because methods to identify RHC encounters within Medicaid claims data are outdated.

Methods: We used a 100% sample of the 2018 Medicaid Demographic and Eligibility and Other Services Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files for 20 states …

Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo

Research Collection School Of Computing and Information Systems

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-modal data can be effectively used to improve the segmentation accuracy of regions of interest by analyzing both spatial and temporal information. In this study, we propose a dual-path segmentation model for multi-modal medical images, named TranSiam. Taking into account that there is a significant diversity between the different modalities, TranSiam employs two parallel CNNs to extract the features which are specific to …

Eyris: From The Lab To The Market, Steven Miller, David Gomulya, Mahima Rao-Kachroo

Asian Management Insights

Singapore’s trailblazer AI algorithm for detecting diabetes-related eye diseases. Can you imagine getting the results of your eye disease screening within minutes rather than days? This capability is what EyRIS, a Singapore-based start-up that uses the AI (Artificial Intelligence)-driven Singapore Eye LEsion Analyzer (SELENA+) algorithm to screen for diabetes-related eye diseases, set out to productise and commercialise.

Purification And Isolation Of Α-Chloro-Β-Lactone Precursor Molecules, Matthew Ellis

ASPIRE 2024

This research investigates the synthesis of α-chloro-β-lactone molecules, focusing on the production, isolation, and purification of two precursor compounds from chloroacetic acid and substituted benzaldehydes. While multiple methods were explored, including EDC, DIC, and DCC catalysis, DCC proved to be most effective in producing higher yields. However, challenges in purification arose due to the formation of byproducts, particularly with DCC, prompting further investigation for efficient extraction and purification techniques. DCC, however, shows a promising route for α-chloro-β-lactone synthesis, despite purification complexities.

Chatgpt Can Offer Satisfactory Responses To Common Patient Questions Regarding Elbow Ulnar Collateral Ligament Reconstruction, William Johns, Alec Kellish, Dominic Farronato, Michael G. Ciccotti, Sommer Hammoud

Rothman Institute Faculty Papers

PURPOSE: To determine whether ChatGPT effectively responds to 10 commonly asked questions concerning ulnar collateral ligament (UCL) reconstruction.

METHODS: A comprehensive list of 90 UCL reconstruction questions was initially created, with a final set of 10 "most commonly asked" questions ultimately selected. Questions were presented to ChatGPT and its response was documented. Responses were evaluated independently by 3 authors using an evidence-based methodology, resulting in a grading system categorized as follows: (1) excellent response not requiring clarification; (2) satisfactory requiring minimal clarification; (3) satisfactory requiring moderate clarification; and (4) unsatisfactory requiring substantial clarification.

RESULTS: Six of 10 ten responses were …

Analyzing The Ramifications Of Climate Change On Mental Health, Salvatore A. Medori

CAFE Symposium 2024

When thinking about the vast array of impacts that the climate crisis has on humanity, there are many things that come to mind, but mental health impacts are likely not one of them. Even though research demonstrates that mental effects from any form of disaster far exceed the physical health implications mental health impacts of the largest disaster facing humanity since the Second World War are rarely considered at all, let alone when solutions are being created. This has led to a hidden crisis emerging underneath an even larger crisis, with serious consequences for most individuals across the globe. The …

A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei

Computer Science Faculty Publications

The most common eye infection in people with diabetes is diabetic retinopathy (DR). It might cause blurred vision or even total blindness. Therefore, it is essential to promote early detection to prevent or alleviate the impact of DR. However, due to the possibility that symptoms may not be noticeable in the early stages of DR, it is difficult for doctors to identify them. Therefore, numerous predictive models based on machine learning (ML) and deep learning (DL) have been developed to determine all stages of DR. However, existing DR classification models cannot classify every DR stage or use a computationally heavy …

Computational Study Of Binding Of Oseltamivir To Neuraminidase Mutants Of Influenza A Virus, Muhammad Arba, Sri Wahyuli, Setyanto Tri Wahyudi, Amir Karton, Chun Wu

Faculty Scholarship for the College of Science & Mathematics

Oseltamivir (OTV), which targets the neuraminidase (NA) of Influenza A virus (IAV), has been reported to develop resistance. Here, we performed a computational study on the binding modes of OTV in the wild-type and popular mutants of IAV NA (E119A, E119D, E119G, H274Y, I117T, I117V, I117V-E119A, K150N, N294S, R292K, V116A, and Y252H). The Arg118, Glu119, Asp151, Arg152, Glu276, Arg292, and Arg371 were identified as crucial interacting residues with the drug. The energy decomposition analysis showed that with few exceptions, the dispersion interaction is the dominant interaction, followed by the charge-transfer and polarization interactions. The affinities for OTV were greatly reduced …

Predictive Algorithm For Surgery Recommendation In Thoracolumbar Burst Fractures Without Neurological Deficits, Charlotte Dandurand, Nader Fallah, Cumhur F. Öner, Richard J. Bransford, Klaus Schnake, Alex R. Vaccaro, Lorin M. Benneker, Emiliano Vialle, Gregory D. Schroeder, Shanmuganathan Rajasekaran, Mohammad El-Skarkawi, Rishi M. Kanna, Mohamed Aly, Martin Holas, Jose A. Canseco, Sander Muijs, Eugen Cezar Popescu, Jin Wee Tee, Gaston Camino-Willhuber, Andrei Fernandes Joaquim, Ory Keynan, Harvinder Singh Chhabra, Sebastian Bigdon, Ulrich Spiegel, Marcel F. Dvorak

Department of Orthopaedic Surgery Faculty Papers

STUDY DESIGN: Predictive algorithm via decision tree.

OBJECTIVES: Artificial intelligence (AI) remain an emerging field and have not previously been used to guide therapeutic decision making in thoracolumbar burst fractures. Building such models may reduce the variability in treatment recommendations. The goal of this study was to build a mathematical prediction rule based upon radiographic variables to guide treatment decisions.

METHODS: Twenty-two surgeons from the AO Knowledge Forum Trauma reviewed 183 cases from the Spine TL A3/A4 prospective study (classification, degree of certainty of posterior ligamentous complex (PLC) injury, use of M1 modifier, degree of comminution, treatment recommendation). Reviewers' regions …

Analysis Of The Outer Retinal Bands In Abca4 And Prph2-Associated Retinopathy Using Oct, Rachael C. Heath Jeffery, Johnny Lo, Jennifer A. Thompson, Tina M. Lamey, Terri L. Mclaren, John N. De Roach, Lauren N. Ayton, Andrea L. Vincent, Abhishek Sharma, Fred K. Chen

Research outputs 2022 to 2026

Purpose: To evaluate the outer retinal bands using OCT in ABCA4- and PRPH2-associated retinopathy and develop a novel imaging biomarker to differentiate between these 2 genotypes. Design: Multicenter case-control study. Participants: Patients with a clinical and genetic diagnosis of ABCA4- or PRPH2-associated retinopathy and an age-matched control group. Methods: Macular OCT was used to measure the thickness of the outer retinal bands 2 and 4 by 2 independent examiners at 4 retinal loci. Main Outcome Measures: Outcome measures included the thicknesses of band 2, band 4, and the band 2/band 4 ratio. Linear mixed modeling was used to make comparisons …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …

Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao

School of Medicine Faculty Publications

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum’s de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were …

De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …

Virgin Coconut Oil (Vco) Supplementation Relieves Symptoms And Inflammation Among Covid-19 Positive Adults: A Single-Blind Randomized Trial, Imelda Angeles-Agdeppa, Jacus S. Nacis, Fabian M. Dayrit, Keith V. Tanda

Chemistry Faculty Publications

A clinical study conducted in 2020 showed that virgin coconut oil (VCO) has been found effective in the rapid relief of COVID-19 symptoms and normalization of the C-reactive protein (CRP) concentration among probable and suspected cases of COVID-19. This present study aimed to validate those results and to evaluate the effects of VCO among COVID-19 patients through a 28-day randomized, single-blind trial conducted among 76 SARS-CoV-2 RT-PCR (reverse transcription-polymerase chain report)-confirmed adults, with VCO given as a COVID-19 adjunct therapy. The results showed that VCO recipients were free from symptoms and had normal CRP concentrations by day 14. In comparison, …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong

Computer Science Faculty Publications

Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …