Medicine and Health Sciences Commons^™

Bridging The Gap From Preschool To Primary: From Policy To Practice, Aimee O'Connor, Cóilín O’ Braonáin

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Editorial, Anne M. Friel, Brigid Hooban, Therese Montgomery, Anne Marie O'Brien, Cormac Quigley, Edel Mcneela, Eva Campion, James Walshe, Sinead Loughran

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Insecticide Resistance Profile In Nashville Culex Spp. Mosquito Populations, Ellie Sebaugh, Zachary Bement, Abelardo Moncayo, Darlene Panvini

Science University Research Symposium (SURS)

Mosquitoes may develop resistance to insecticides used by control programs, potentially increasing population density and the risk of mosquito-borne diseases. Culex spp. mosquitos are the primary vector of West Nile Virus (WNV), the leading cause of mosquito-borne disease in the United States and a reportable disease in Tennessee. Resistance profiles were constructed for two insecticides, permethrin and malathion, in a Culex spp. population from Nashville, Tennessee. Adult female mosquitoes were live-captured using gravid traps and tested using the Centers of Disease Control and Prevention (CDC) bioassay protocol to assess resistance or susceptibility. Three inhibitors were also included to identify metabolic …

Substituted Piperidines As (Alpha4)3(Beta2)2 Nicotinic Acetylcholine Receptor Positive Allosteric Modulators: In Vitro Pharmacology, Nataly Sanchez, Josue Gaona, Wilder Felix, Nathalia Menegasso, Brisa Cea, Ganesh Thakur, Ayman K. Hamouda

School of Medicine Student Publications and Presentations

Nicotinic acetylcholine receptors (nAChRs) play a crucial role in the pathogenesis of neurodegenerative diseases such as Parkinsonʼs disease (PD). In PD, degeneration of dopaminergic and cholinergic neurons impairs neurotransmitter release, leading to cognitive and motor dysfunction. Current treatments provide only symptomatic relief, highlighting the need for novel therapeutic strategies. The (α4)₃(β2)₂ subtype of nAChRs is expressed on affected neurons, making it a promising druggable target for enhancing neurotransmitter release and providing neuroprotection. To explore the therapeutic potential of positive allosteric modulators (PAMs) of (α4)₃(β2)₂ nAChRs, we evaluated chemical derivatives of CMPI [3-(2-chlorophenyl)-5-(5-methyl-1-(piperidin-4-yl)-1H-pyrazol-4-yl)isoxazole]. We used two-electrode voltage-clamp recordings from Xenopus laevis …

Spatio-Temporal Dynamics Of Malaria Vector Niche Overlaps In Africa, Eric Ali Ibrahim, John Odindi, Mark Wamalwa, Henri E.Z. Tonnang

All Peer-Reviewed Publications

Malaria remains a significant public health challenge in sub-Saharan Africa, with transmission heightened by the dynamics of primary and secondary mosquitoes infected with Plasmodium parasites. Regions where both vector types co-exist face heightened likelihood of intensified malaria transmission. Hence, understanding vectors' ecological interactions, especially their niche overlaps in geographic or environmental space, is crucial for targeted malaria control and elimination strategies. We employed a dynamic cellular automata (CA) model to map niche overlaps among primary (Anopheles gambiae complex, An. funestus group) and secondary (An. pharoensis, An. coustani) malaria vectors across African, using open-access environmental and vector occurrence datasets sourced from …

Climate-Driven Potential For Tularemia In East Africa: Skill Testing And Ecological Consistency Of A Transferred Risk Model, Komi Mensah Agboka, Allan Muohi Ngángá, Bonoukpoè Mawuko Sokame, Steve Soh Bernard Baleba, Tobias Landmann, Elfatih M. Abdel-Rahman, Chrysantus M. Tanga, Souleymane Diallo

All Peer-Reviewed Publications

Tularemia, a neglected zoonosis, remains underreported in Africa despite growing concern over its climate-driven expansion. This study aims to quantify the specific contribution of climate to tularemia risk using a climate attribution framework. We trained a Least Squares Dummy Variable (LSDV) fixed-effects panel model on United States (U.S.) county-level tularemia incidence data from 2011–2020 (n = 500, R² = 0.90), incorporating only climatic predictors: cumulative temperature, cumulative precipitation, and their respective variabilities. The climate-only model explained 86% of variance in the training data, demonstrating strong climate influence on tularemia disease dynamics. We then applied the model to East Africa, using …

Causal Predictive Modeling Of Survival Of Lung And Bronchus Cancer Patients Diagnosed During 2010–2011 In Texas, Zeinab Mohamed, Sidketa Fofana, Everardo Cobos, Manish K. Tripathi, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Background: Lung and Bronchus cancer is the most fatal type of cancer in the United States. According to the American Cancer Society, there were more than 127,000 deaths from lung cancer in 2023. Lung cancer care cost 23.8 billion dollars in 2020. In Texas, only 22.8% of lung cancer patients survived 5 years or more past diagnosis based on 2012-2018 data.

Aim: This study evaluates the survival length of lung and bronchus cancer patients in Texas using advanced statistical and machine learning methods applied to an 11-year cohort study from Surveillance, Epidemiology, and End Results Program. It also quantifies the …

Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam

USF Tampa Graduate Theses and Dissertations

According to the World Health Organization (WHO), mosquitoes are the deadliest animals on Earth, responsible for more human deaths annually than any other species. Mosquito-borne illnesses continue to pose severe risks to global health. In 2015 alone, there were an estimated 214 million malaria cases worldwide. Similarly, a 2016 report from the Centers for Disease Control and Prevention (CDC) revealed that Puerto Rico’s Department of Health received over 62,500 suspected cases of Zika, with 29,345 confirmed positive cases. In 2019, Southeast Asia experienced its worst dengue outbreak in recorded history. Of the approximately 4,500 mosquito species distributed across 34 genera, …

10.27.2025 Ored Connect, Liz Williamson

ORED Newsletter

ORED Field Fest

OTC Director Candidates

14th International Conference On Business, Technology And Innovation 2025, University For Business And Technology - Ubt

UBT International Conference

Welcome to IC – UBT 2025

UBT Annual International Conference is the 14th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make …

2025 Celebration Of Scholarship, Creativity, And Engagement, Todd Bruns, Jaime Pedigo, Jennifer Smith, Patty Watson, Heather Wohltman, Amanda Wolf

Programs

Each year, Eastern Illinois University proudly recognizes the outstanding achievements of our faculty in research, creativity, and engagement. This collection of accomplishments reflects the dedication of an engaged faculty committed to excellence and the continual pursuit of knowledge. Many of these successes were made possible through meaningful collaboration with our students, who contribute as co-authors, research assistants, and partners in bringing ideas to life. Some of these professional milestones represent years of effort, demonstrating remarkable persistence and determination. We offer our heartfelt congratulations on this wide range of achievements, which bring distinction to our departments, colleges, and the University as …

Enhancing Cyberattack Resiliency Through The Radiotherapy Backup And Recovery Dashboard Tool, Justin Pijanowski, Eric Nguyen, Yasin Abdulkadir, Justin Hink, Yevgeniy Vinogradskiy, James Lamb

Department of Radiation Oncology Faculty Papers

PURPOSE: Radiation Oncology departments impacted by recent cyberattacks were unable to access data backups or their Record and Verify (R&V) system and therefore faced challenges to resume patient treatments in a timely manner. We present a novel software tool that backs-up critical radiotherapy treatment information and displays essential information for on-treatment patients in an intuitive and accessible dashboard allowing clinics to continue radiotherapy treatments. The purpose of this report is to describe implementation details, challenges, and share open-source code to facilitate radiation oncology clinics' efforts to develop tools to improve cyberattack resiliency.

METHODS: The Radiotherapy Backup and Recovery Dashboard Tool …

Adverse Childhood Experiences, Positive Childhood Experiences, And Digital Media Use Among Children And Adolescents In The United States, Elizabeth L. Crouch, Emma Boswell, Monique J. Brown Ph.D., Kevin J. Bennett

Publications

No abstract provided.

Inferred Global Dense Residue Transition Graphs From Primary Structure Sequences Enable Protein Interaction Prediction Via Directed Graph Convolutional Neural Networks, Islam A. Ebeid, Haoteng Tang, Pengfei Gu

Computer Science Faculty Publications

Introduction: Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct sequence embeddings from Protein Language Models (PLMs) or apply Graph Neural Networks (GNNs) to 3D protein structures, the main focus of this study is to investigate less computationally intensive alternatives. This work introduces a novel framework for the downstream task of PPI prediction via link prediction.

Methods: We introduce a two-stage graph representation learning framework, ProtGram-DirectGCN. First, we developed ProtGram, a novel approach that models a protein's primary structure as a hierarchy of …

10.20.2025 Ored Connect, Liz Williamson

ORED Newsletter

• OTC Director Candidate Forum
• ORED Small Grants Program RFP

Large Language Models As Information Providers For Appropriate Antimicrobial Use: Computational Text Analysis And Expert-Rated Comparison Of Chatgpt, Claude And Gemini, Marcello Di Pumpo, Maria Rosaria Gualano, Danilo Buonsenso, Francesca Raffaelli, Daniele Donà, Vittorio Maio, Patrizia Laurenti, Walter Ricciardi, Leonardo Villani

College of Population Health Faculty Papers

OBJECTIVES: Antimicrobial resistance is a critical public health threat. Large language models (LLMs) show great capability for providing health information. This study evaluates the effectiveness of LLMs in providing information on antibiotic use and infection management.

METHODS: Using a mixed-method approach, responses to healthcare expert-designed scenarios from ChatGPT 3.5, ChatGPT 4.0, Claude 2.0 and Gemini 1.0, in both Italian and English, were analysed. Computational text analysis assessed readability, lexical diversity and sentiment, while content quality was assessed by three experts via DISCERN tool.

RESULTS: 16 scenarios were developed. A total of 101 outputs and 5454 Likert-scale (1-5) scores were obtained …

Tableau Part Ii - October 2025, Rubab Shahzad

Day Family Research Lab Workshop Series

Part Two of Introduction to Tableau. Learn to make cool visualizations using Tableau. A hands-on opportunity where we will go over calculated fields, hierarchies, unions, dashboards, and stories.

Prior experience with Tableau is recommended

10.13.2025 Ored Connect, Liz Williamson

ORED Newsletter

• ORED Small Grants Program RFP
• Mississippi Impact Grants RFP
• Contest to Promote Lab Practices
• Field Fest
• AAAS Membership for Faculty, Staff, and Students 

Discriminative Accuracy Of Cha2ds2-Vasc Score, And Development Of Predictive Accuracy Model Using Machine Learning For Ischemic Stroke Risk In Cardiac Amyloidosis And Atrial Fibrillation, Waqas Ullah, Abhinav Nair, Eric Warner, Salman Zahid, Mansoor Rahman, Palwasha Khan, Indranee Rajapreyar, Sridhara S. Yaddanapudi, M. Chadi Alraies, Said Ashraf, Jeffery Van Hook, Yegeny Brailovsky

Department of Medicine Faculty Papers

BACKGROUND: CHA2DS2-VASc score in cardiac amyloidosis (CA) with atrial fibrillation (AF) is believed to underestimate ischemic stroke risk, necessitating a better predictive model.

METHODS: Data were obtained from the National Readmission Database (NRD). Outcomes between CA-AF and no-CA-AF were compared using multivariate regression analysis to calculate adjusted odds ratios (aORs). AutoScore, an interpretable machine learning framework, was used to develop a stroke risk prediction model, and its predictive accuracy was evaluated with an area under the curve (AUC) using the receiver operating characteristic analysis.

RESULTS: A total of 11,860,804 (CA-AF 22,687 (0.19%) and no-CA-AF 11,838,117) patients were identified from 2015 …

Ophthoacr (Ophthalmology Automated Chart Review): An Ai-Powered Tool For Complete Automation Of Ophthalmology Chart Reviews And Cohort Data Analysis, Karen M. Chen, Kevin W. Chen, Vlad Diaconita, Stanley Chang, Leejee H. Suh

School of Medicine Faculty Publications

Purpose: Retrospective chart reviews in ophthalmology are essential for gaining clinical insights, but they remain labor-intensive and prone to error. Despite digitization through electronic health records, extracting and interpreting lengthy, unstructured patient histories remains challenging, particularly in ophthalmology, which relies heavily on both imaging and text-based reports. We introduce OphthoACR, a Health Insurance Portability and Accountability Act-compliant artificial intelligence (AI)-powered tool for automated chart review and cohort analyses in ophthalmology. Methods: OphthoACR was applied to extract 16 variables of increasing task difficulty from the complete chart histories of 91 patients who underwent secondary intraocular lens surgery at the Columbia University …

Investigating The Organs At Risk (Oar) Received Dose During Prostate Cancer Therapy Using Intensity Modulated Radiation Therapy (Imrt) And 3d Conformal Radiotherapy (3dcrt): A Comparison Study, Talib Abdulwahid, Hussein Mraity, Mustafa Al-Aseebee, Zeyad Al-Dulaimi, Ali Abid Abojassim

Chulalongkorn Medical Journal

Radiotherapy domain is known to impose undesired risk of radiation to normal tissue surrounding the tumor. So, the treatment planning systems are developing with time to introduce a perfect treatment. Organs at risks surrounding prostate tumors are sensitive to high doses of radiation. This study is aimed at comparing the efficiency of the three-dimensional conformal radiotherapy (3DCRT) and intensity-modulated radiation therapy (IMRT) techniques during the treatment of prostate cancer. A cross-sectional study was performed in Middel Euphrate Csancer Center, Najaf , Iraq. A 25 patients with prostate tumor were enrolled. They underwent CT scans from imaging then treated with x-ray …

10.06.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Field Fest
• AAAS Membership
• MIG Application Opportunity
• Contest to Promote Safe Lab Practices

Research On Identification And Evaluation Method Of Medical Experts' Expertise Domains In Online Health Community Based On Knowledge Graph, Yunjiang Xi, Qian Zhang, Man Li, Juan Yu

Journal of Scientific Information Research

[Purpose/significance] This study aims to identify the expertise domains of medical experts, and evaluates their domain levels to provide a basis for community expert recommendation.

[Method/process] This study utilized the improved OneRel model to structure community historical Q&A into entity relation triples. Then used the knowledge graph triples to test the consistency between the medical knowledge in the community Q&A and the domain knowledge, and finally obtained the doctor's domain levels by aggregating in each expertise domain.

[Result/conclusion] Using the data example from xywy.com website, 214 doctors in the community were ranked in terms of their average level of expertise …

Topoimages: Incorporating Local Topology Encoding Into Deep Learning Models For Medical Image Classification, Pengfei Gu, Hongxiao Wang, Yejia Zhang, Huimin Li, Chaoli Wang, Danny Z. Chen

Computer Science Faculty Publications

Topological structures in image data, such as connected components and loops, play a crucial role in understanding image content (e.g., biomedical objects). Despite remarkable successes of numerous image processing methods that rely on appearance information, these methods often lack sensitivity to topological structures when used in general deep learning (DL) frameworks. In this paper, we introduce a new general approach, called TopoImages (for Topology Images), which computes a new representation of input images by encoding local topology of patches. In TopoImages, we leverage persistent homology (PH) to encode geometric and topological features inherent in image patches. Our main objective is …

Adipose Tissue Estrogen Receptor-Alpha Overexpression Ameliorates High-Fat Diet–Induced Adipose Tissue Inflammation, Marion C. Hope, Christian A. Unger, M. Chase Kettering, Cassidy E. Socia, Ahmed K. Aladhami, Barton C. Rice, Darya S. Niamira, Ben P. Wiznitzer, Diego Altomare Ph.D., William E. Cotham, Reilly T. Enos

Faculty Publications

Context

We created an innovative mouse model that enables inducible overexpression of estrogen receptor-alpha (ERα), specifically in adipose tissue (Adipo-ERα↑). Objective

We aimed to investigate how elevated Adipo-ERα↑ influences the development of high-fat diet (HFD)-induced obesity in both male and female mice. Methods

Male and female Adipo-ERα↑ mice and littermate controls were fed a low-fat diet (LFD) or HFD for 13 weeks. Adipo-ERα↑ was induced at the initiation of dietary treatment. Body morphology and composition, hepatic lipid accumulation, glucose tolerance, fasting insulin concentrations, and adipose tissue mRNA profiling were assessed. Liquid chromatography–mass spectrometry was used to determine circulating and adipose …

Smarter Disease Detection From Electronic Health Record Data: An End-To-End Ai-Augmented Pipeline For Computable Phenotyping, Dylan Owens

Statistical Science Theses and Dissertations

Electronic Health Records (EHR) contain a wealth of structured and unstructured patient data that can be leveraged for computable phenotyping, the process of algorithmically identifying patient cohorts with specific diseases or conditions. Traditional rule-based phenotyping approaches, while interpretable, often struggle with scalability, portability across institutions, and effective use of unstructured clinical narratives. Recent advances in large language models (LLMs) present new opportunities for synthesizing complex free-text information into concise, clinically meaningful representations. However, integrating LLMs into phenotyping workflows requires careful design to maintain transparency, interpretability, and measurable uncertainty—features essential for clinical adoption and downstream applications such as decision support.

We …

Spatiotemporal Modeling Of Maternal Mortality In South Carolina 2018-2023, Leah Wood, Ray Bai, Emily Mann

Senior Theses

Maternal death serves as a public health indicator due to fact that it is considered preventable with the availability of modern biomedicine, however, it persists broadly throughout the United States. Current literature outlines national trends in maternal mortality with complicating, preexisting conditions, and structural upstream factors often cited as being the largest contributors to increased risk. This study utilizes publicly available, county-level data for maternal death in addition to demographic and descriptive data in order to estimate maternal mortality rates in each of South Carolina’s 46 counties from 2018 to 2023. In order to address sparsity in the outcome variable …

Use Of Modified Z-Domain Peptides To Specifically Label The Constant Region Of Immunoglobulin G And Vegf, Madeline Allen

Department of Chemistry: Dissertations, Theses, and Student Research

Antibodies are increasingly being used in medicinal therapies due to their ability to specifically bind to a target antigen. This fundamental behavior of antibodies has been used as a key component in drug development to address common problems with traditional drug molecules such as off-targeting, fast drug clearance, and low efficacy. This thesis provides some background into how antibodies can be used as potential treatments for a few diseases. Chapter 1 begins with an overview of the human immune system, and the role antibodies play within it. Then, the variety of ways in which antibodies can be used as medicinal …

Persistent Chemicals In Particulate Matter (Pm) Near A Hazardous Waste Thermal Treatment Facility, Chuqi Guo, Martine E. Mathieu-Campbell, Thomas Blanchard, Lavrent Khachatryan, Md Abdullah Al-Mamun, Qingzhao Yu, Myron Lard, Oluwafeyikemi Ogunmusi, Brenda Vallee, Wilma Subra, Iriel Edwards, David Malone, Slawo Lomnicki, Stephania A. Cormier, Jennifer Richmond-Bryant

School of Public Health Faculty Publications

Colfax, an overburdened community in central Louisiana, hosts the last commercially-operated open-burn/open-detonation (OB/OD) hazardous waste thermal treatment facility in the United States. Until December 2023 when their permit disallowed OB/OD, the facility processed military waste, fireworks, propellants, soils excavated from Superfund sites, and other hazardous materials. This community-engaged study measured ambient fine particulate matter (PM2.5), environmentally persistent free radicals (EPFRs), polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), and metals using two high-volume PM2.5 samplers deployed 1.2 mi and 9.0 mi from the facility from April, 2022 through February, 2023. Elevated PM2.5 concentrations were recorded at both sites during spring and summer 2022. …

The Science Of Sound: Studying The Cognitive, Emotional, And Physiological Effects Of Frequency, Genre, And Music, Jett Yarborough

Senior Honors Theses

Music influences emotion, physiology, and cognition, yet little is known about how the frequency it is tuned to affects these influences. Prior research has shown that music tuned to 432 Hz can reduce stress, lower blood pressure, and improve sleep. My colleagues and I conducted two studies to investigate this. Our research found that music tuned to 432 Hz promotes a significant increase in memory retention and induces a state of focus and relaxation. These results suggest that shifting from the standard tuning frequency of 440 Hz to 432 Hz could have a profoundly positive impact on our daily lives. …