Medicine and Health Sciences Commons^™

The Effect Of Temperature And Salinity On Margalefidinium Polykrikoides Group Iii Va, Usa Strain Growth, Eduardo Pérez-Vega, Margaret R. Mulholland, Katherine E. Crider, Kimberly E. Powell, P. Dreux Chappell, Alexander Bochdansky

OES Faculty Publications

Margalefidinium polykrikoides is a cosmopolitan dinoflagellate that blooms in coastal waters. Despite genomic evidence that it belongs to Group III and so closely related to isolates from Puerto Rico, Malaysia, North America, and Central America, M. polykrikoides blooms in the Chesapeake Bay at warmer temperatures and lower salinities than in coastal ecosystems occupied by its closest relatives. In this study, the effect of temperature and salinity on the growth rate and total cell yield of an M. polykrikoides VA culture isolate were examined and compared with environmental observations made during M. polykrikoides blooms in the Chesapeake Bay. M. polykrikoides group …

Revealing Spatiotemporal Neural Activation Patterns In Electrocorticography Recordings Of Human Speech Production By Mutual Information, Julio Kovacs, Dean Krusienski, Minu Maninder, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

Background

Spatiotemporal mapping of neural activity during continuous speech production has been traditionally approached using correlation coefficient (CC) analysis between cortical signals and speech recordings. A prior study employed this approach using electrocorticography (ECoG) data from participants who underwent invasive intracranial monitoring for epilepsy. However, CC cannot detect nonlinear relationships and is dominated by the correspondence between periods of silence and of non-silence.

New Method

We introduce the mutual information (MI) measure, which can capture both linear and nonlinear dependencies. We validated CC and MI on the sub-second spatiotemporal brain activity recorded during continuous speech tasks. To refine the results, …

An Analytical Model Of Motion Artifacts In A Measured Arterial Pulse Signal—Part Ii: Tactile Sensors, Md Mahfuzur Rahman, Subodh Toraskar, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

This paper, the second of two parts, presents an analytical model of motion artifacts (MA) in measured pulse signals by a tactile sensor, which contains a deformable microstructure sitting on a substrate. While the tissue-contact-sensor (TCS) stack and the sensor are both treated as a 1DOF (degree-of-freedom) system, tissue–sensor contact joins their mass together to form a 1DOF system with springs and dampers on both sides. MA on the sensor substrate causes baseline drift and time-varying system parameters (TVSP) of the TCS stack simultaneously. An analytical model is developed to mathematically relate baseline drift and TVSP to a measured pulse …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Identifying Intangible And Biocultural Heritage Elements Toward Environmental Understanding: Engaging Stakeholders Through Art, Martha B. Lerski

Publications and Research

Grounded in a case study in Barbuda in the Caribbean, this research examines sustainability from the perspective of what arts and heritage can contribute to community engagement and local and broader understandings about the environment. This article documents a growing body of literature recognizing the role of arts and culture, including local knowledge and traditional ecological knowledge (TEK), in climate change endeavors. Art and TEK present expansive world views. Contextual information situates research done on the island of Barbuda pre- and post-Hurricane Irma. Visual arts workshops engaged community members in mixed methods research. Results documented cultural elements, particularly intangible and …

Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce …

Lead Bioaccessibility And Commonly Measured Soil Characteristics (Detroit, Mi, Usa) Phase Ii, Conor T. Gowan, Sabrina R. Good, Allison R. Harris, Patrick Crouch, Shawn P. Mcelmurry

Open Data at Wayne State

Urban soil contaminated with anthropogenic sources of Pb is a major contributor to child Pb exposure. To assess the Pb risk in urban areas, composite samples were collected from 142 voluntary privately owned 142 residential parcels in Detroit, Hamtramck, and Highland Park, Michigan. Samples were collected at two time periods, before and after treatment applied for those denoted as treatment sites. Samples were collected from areas covered with turf grass on the parcels from the front, middle and rear sections. Soils were collected with a bulb planter at approximately 10cm depth and were cleaned with a tap water-Liquinox detergent solution …

Association Between Lifetime Interpersonal Violence And Post– Covid-19 Condition Among Women In Kentucky, 2020-2022, Ayşe Güler, Heather M. Bush, Katie Schill, Nurlan Kussainov, Ann L. Coker

Biostatistics Faculty Publications

Objective: The COVID-19 pandemic increased the risk of interpersonal violence. We investigated the association between lifetime interpersonal violence experience and risk of post–COVID-19 condition (the persistence of symptoms of COVID-19 and severity of health problems associated with COVID-19 that last a few weeks, months, or years) among women with lifetime interpersonal violence experience.   Methods: Women participants aged ≥18 years in Kentucky’s Wellness, Health & You—COVID-19 study completed online quantitative surveys about the impacts of the pandemic, developing COVID-19, and symptoms of post–COVID-19 condition. We conducted cross-sectional analyses estimating rate ratios of developing COVID-19 and symptoms of post–COVID-19 condition during the …

Temporal Network Analysis Of Comorbidities Among People With Hiv In South Carolina, Yunqing Ma, Matthew Lohman Ph.D., Monique J. Brown Ph.D., Mph, Yichen Li, Xiaoming Li Ph.D., Bankole Olatosi Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Introduction: People with HIV experience a high rate of comorbidities that can complicate their health outcomes. Understanding the prevalence, interrelationships and temporal development of these comorbidities is crucial for improving health management and quality of life for people with HIV. Methods: We used a population-based cohort extracted from statewide electronic health record (EHR) data in South Carolina (SC), including 18 649 people with HIV who survived at least 1 year after HIV diagnosis between January 1, 2005, and December 31, 2020. Comorbidities and organ systems were classified using ICD-10 codes. Network analysis was performed to assess the closeness centrality among …

A Vision Transformer Based Assistive System For Dermatological Diagnosis In Systemic Lupus Erythematosus, Syeda Lamima Farhat

All Graduate Theses, Dissertations, and Other Capstone Projects

Systemic Lupus Erythematosus (SLE) is a complex and often underdiagnosed autoimmune disease that affects multiple organs and presents with a wide range of symptoms-ranging from fatigue and joint pain to life-threatening organ damage. One of its most visible and diagnostically significant indicators is the Butterfly Malar Rash (BMR), a distinctive facial rash that often resembles other common dermatological conditions like rosacea, acne, eczema, and fifth disease. This overlap can lead to misdiagnosis or delayed detection, especially in busy clinical environments. To assist dermatologists in distinguishing BMR from similar facial rashes, this study explores the development of an AI-powered image classification …

Program And Proceedings: Nebraska Academy Of Sciences 1880–2025, 145th Anniversary Year, One Hundred-Thirty-Fifth Annual Meeting

Nebraska Academy of Sciences: Programs and Proceedings

Program

Aeronautics and Space Science

Biological and Medical Sciences

Biology

Chemistry

Earth Sciences

Science Education

Anthropology

Applied Science and Technology

Physics and Engineering

Forensic Sciences

Ecology, Sustainability, and Environmental Science

Maiben Lecture: Mary Ann Vinton, "State of the Academy"

Friends of Science Awards: David Crouse and Daniel Sitzman

Predicting Lung Cancer Severity Using Machine Learning Algorithms: Enhanced By Statistical Analysis, Esin Bilgin

Theses, Dissertations and Culminating Projects

Cancer is a serious and severe cause seen in every region of the world and severely affects the quality of life and life span. Among the various types of cancer, lung cancer is one of the most critical, having a fatal impact on life. While medical imaging techniques, laboratory results, and biomarkers play a significant role in diagnosis and prognosis, clinical studies are also crucial in monitoring the progression of cancer and identifying diagnostic and prognostic factors. The findings demonstrate satisfactory accuracy, and the analysis incorporates statistical data with machine learning techniques. These findings play a pivotal role in supporting …

Quantitative Preventive Approaches To Diabetes: Mathematical Modeling And Analysis, Rushi P. Bhatt

Theses, Dissertations and Culminating Projects

The rising prevalence of diabetes presents a pressing global health concern, necessitating effective control strategies. This study aims to construct a mathematical model to analyze the influence of diverse factors on blood sugar levels, with a focus on identifying optimal methods for maintaining healthy glucose levels. Employing ordinary differential equations (ODE), the model investigates variables including leptin resistance, fat mass, glucose, insulin resistance, beta cell mass, daily physical activity, and dietary intake. Utilizing parameter estimates from existing literature, the model’s framework is established, and simulation results elucidate the intricate interplay between lifestyle choices and blood glucose dynamics. Furthermore, the model …

Understanding The Challenges And Satisfaction Among The Medical Professional Preceptors, Cornelia Ko

West Chester University Doctoral Projects

This study evaluates the Penn Medicine Family Medicine Clerkship program through a mixed-methods approach, exploring the challenges and factors influencing the satisfaction of medical professional preceptors when precepting students. A quantitative survey with 54 preceptor participants reveals the top challenges preceptors face: workload, conflicts with patient care, and limited clinical space. Despite this, there is strong support for the program, with 89% of preceptors enjoying the role and 85% expressing willingness to continue to precept for the next three years. Finally, data analysis shows no statistical correlation between preceptor motivation with gender, ethnicity, age group, years of serving, or total …

Circadian Variation In Mgmt Promoter Methylation And Expression Predicts Sensitivity To Temozolomide In Glioblastoma, Maria F. Gonzalez-Aponte, Yitong Huang, William A. Leidig, Tatiana Simon, Omar H. Butt, Marc D. Ruben, Albert H. Kim, Joshua B. Rubin, Erik D. Herzog, Olivia J. Walch

Mathematics Sciences: Faculty Publications

Purpose Recent studies show that glioblastoma (GBM) is more sensitive to temozolomide (TMZ) in the morning. In cells, inhibiting O6-Methylguanine-DNA-Methyltransferase (MGMT) abolished time-dependent TMZ efficacy, suggesting that circadian regulation of this DNA repair enzyme underlies daily TMZ sensitivity. Here, we tested the hypotheses that MGMT promoter methylation and protein abundance vary with time-of-day in GBM, resulting in daily rhythms in TMZ efficacy.

Methods We assessed daily rhythms in MGMT promoter methylation in GBM in vitro and retrospectively analyzed MGMT methylation status in human GBM biopsies collected at different times of day. Next, we measured MGMT and BMAL1 protein …

Machine Learning Models For Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages And Treatments Using The Surveillance, Epidemiology, And End Results (Seer) Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pancreatic cancer is among the most lethal malignancies, with poor prognosis and limited survival despite treatment advances. Accurate survival modeling is critical for prognostication and clinical decision-making. This study had three primary aims: (1) to determine the best-fitting survival distribution among patients diagnosed and deceased from pancreatic cancer across stages and treatment types; (2) to construct and compare predictive risk classification models; and (3) to evaluate survival probabilities using parametric, semi-parametric, non-parametric, machine learning, and deep learning methods for Stage IV patients receiving both chemotherapy and radiation. Methods: Using data from the SEER database, parametric models (Generalized Extreme Value, …

Understanding Physiological Responses For Intelligent Posture Detection Using Wearable Technology, Chaitanya Vardhini Anumula, Tanvi Banerjee, Anuradha Oak

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

This study investigates the physiological impact of Iyengar yoga at the pose-level using EmbracePlus wearable smartwatch, for data recording and personalized yoga pose detection for tracking.

Generative Ai (Gan & Vae) In Motion Sickness Research, Harigovind Harikumar, Tomojit Ghosh

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

No abstract provided.

A Systematic Study Of Freezing Behavior In Earthworms In Response To Auditory And Vibratory Stimuli, Navjot Singh, A. Burton, Dragana Ivkovich Claflin

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

While earthworms have largely been studied for their role in eliminating toxic metals from soil, less is known about their behavior overall. Previous work from our lab found that a predator-like auditory stimulus (grunting) reliably induced fear-related freezing behavior (Worthen et al., 2024). The present studies further explore earthworm behaviors in response to audio-vibratory stimuli. In Experiment 1, we manipulated amplitude levels and speaker location to examine the parameters needed to reliably induce a freezing fear response to the grunting sound. It was hypothesized that when the speaker was touching the apparatus and producing an added mechanical vibration, there would …

Motion Artifacts (Ma) At-Rest In Measured Arterial Pulse Signals: Time-Varying Amplitude In Each Harmonic And Non-Flat Harmonic-Ma Coupled Baseline, Md Mahfuzur Rahman, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Motion artifacts (MA) cause great variability in a measured arterial pulse signal, and treatment of MA solely as a baseline drift (BD) fails to eliminate its effect on the measured signal. This paper presents a study on the effect of MA at rest (< 0.7 Hz) on measured arterial pulse signals using a microfluidic-based tactile sensor. By taking full account of the dynamic behavior of the transmission path from the true pulse signal in an artery to a measured pulse signal at the sensor, the tissue-contact-sensor (TCS) stack, an analytical model of MA in a measured pulse signal is developed. In this model, the TCS stack is treated as a 1DOF system for its dynamic behavior; MA is quantified as the displacement (i.e., BD) and time-varying system parameters (TVSP) of the TCS stack. The mathematical expression of MA in a measured pulse signal reveals that while BD remains as low-frequency additive noise, TVSP causes time-varying harmonics in a measured pulse signal. Further time-frequency analysis (TFA) of measured pulse signals validates the existence of TVSP and, for the first time, reveals its effect on a measured pulse signal: time-varying amplitude in each harmonic and non-flat harmonic-MA-coupled baseline.

Synthesis And Design Of Clpp Activators As Novel Antibiotics, Schyler Odum

Theses and Dissertations (ETD)

Purpose. Design and synthesize novel compounds to treat Staphylococcus aureus infections by targeting the dysregulation of the Casein Protease P, ClpP. Methods. Utilize established chemical methods to synthesize ureadepsipeptides, small-molecule ClpP activators, and ureadepsipeptide hybrids. Assess their effectiveness by using minimum inhibitory concentration assays and in vitro biochemical assays for ClpP activation. Explore their potential as antibiotics through mitochondrial toxicity tests, glucose/galactose assays, and biophysical measurements related to metabolism and clearance, including thermal shift and surface plasmon resonance assays. Results. Synthesized and tested 33 novel compounds, comprising a total of 80 synthetic steps. Conclusion. The three-part conclusion from the dissertation …

Understanding The Impact Of The Medicaid Expansion On Hospital Length Of Stay And Emergency Department Use In Kentucky, Cameron Bushling

Theses and Dissertations--Epidemiology and Biostatistics

Three related analyses were performed to try to understand the immediate effects of Medicaid expansion on hospital systems in Kentucky. Medicaid expansion led to a large, sudden increase in the number of individuals eligible for various health care needs. This sudden increase in demand for health services lead to initial hypotheses regarding hospitals’ ability to handle this demand. The first analysis examined hospital average length of stay (LOS) using a linear mixed-effects model. Length of stay was modeled longitudinally between 2013 and 2015 to determine if significant changes in the slope of LOS could be detected after expansion (2014). Separate …

Changes In Cancer Diagnosis And Survival In The United States During The Covid-19 Pandemic, Justin T. Burus

Theses and Dissertations--Epidemiology and Biostatistics

The COVID-19 Pandemic led to global societal disruptions as political leaders and public health authorities attempted to control the spread of the newly discovered SARS- CoV-2 virus. While these measures were designed to lessen morbidity and mortality from a novel pathogen, their impact was also felt in many other, often unintended ways. The purpose of this dissertation is to use cancer surveillance research methods to examine the association between COVID-19 Pandemic-related disruptions and changes in the normal diagnosis and care of cancer in the United States.

The first two studies of this dissertation analyzed reductions in cancer diagnoses in the …

Enhancing Public Health Surveillance: Development And Validation Of Machine Learning Models For Suspected Opioid Overdose Detection In Emergency Medical Services Data, Peter J. Rock

Theses and Dissertations--Clinical and Translational Science

The ongoing opioid overdose crisis in the United States requires timely and accurate surveillance systems to inform public health responses. Traditional public health surveillance methods rely on hospital discharge data and death certificates, which suffer from significant reporting delays and miss cases where patients refuse hospital transportation. Emergency Medical Services (EMS) data presents a promising alternative with advantages in timeliness and case ascertainment but lacks validated definitions for suspected opioid overdose (SOO).

This dissertation addresses this critical gap through the development, validation, and fairness assessment of machine learning models with natural language processing (ML-NLP) for identifying SOOs in EMS data. …

Development And Characterization Of Polysaccharide-Based Controlled Drug Delivery Platforms, Amanda Pepler

Open Access Dissertations

Drug delivery research focuses on overcoming challenges in patient treatment. Most therapeutics are delivered systemically through oral or intravenous routes. However, these administration methods are often inefficient due to therapeutic hydrophobicity, poor bioavailability, and liver metabolic clearance, necessitating frequent dosing. When treatment plans require frequent dosing, patients experience significant fluctuations in therapeutic concentration in the bloodstream, which can increase adverse side effects. These factors contribute to low patient compliance. Therefore, the core focus of drug delivery research is to develop new administration routes for therapeutics. Drug delivery systems (DDS) that can target therapeutics to a localized region offer advantages over …

Predicting Mental Health Disparities Using Machine Learning For African Americans In Southeastern Virginia, Ismail El Moudden, Michael C. Bittner, Matvey V. Karpov, Isaac O. Osunmakinde, Akosua Acheamponmaa, Breshell J. Nevels, Mamadou T. Mbaye, Tonya L. Fields, Karthiga Jordan, Messaoud Bahoura

Department of Obstetrics & Gynecology Faculty Publications

This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18–85) in Southeastern Virginia (2016–2020), we found Mood Affective Disorders were most prevalent (41.66%), followed by Schizophrenia Spectrum and Other Psychotic Disorders. Females predominantly experienced mood disorders, with patient ages typically ranging from late thirties to mid-forties. Medicare coverage was notably high among schizophrenia patients, while emergency admissions and comorbidities significantly impacted total healthcare charges. Machine learning models, including gradient boosting, random forest, neural networks, logistic regression, and Naive Bayes, were validated through 100 repeated 5-fold cross-validations. …

Training Set Augmentation And Harmonization Enables Radiomic Models To Detect Early Onset Of Lung Cancer, Claire Huchthausen, Menglin Shi, Gabriel L.A. Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

Radiomics-based machine learning models have the potential to detect lung cancer at inception from CT scans and transform patient outcomes. Low malignancy rates in early-development pulmonary nodules (PNs) and variable image acquisition hinder development of clinically applicable radiomics-based early detection models. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We first trained machine learning models to predict PN malignancy using radiomic features from scans of early-development benign and malignant PNs (n = 187) harmonized using ComBat. Observing near-chance performance, we augmented training with later-development benign and malignant PNs (n = 225). We evaluated …

A Happy Medium?: Using Image Generators To Explore Solution-Focused Art Therapy’S Miracle Question, Daniel A. Hernried

Art Therapy | Master's Theses

This mixed methods, randomized, single-session study tested whether integrating text-to-image generations into Solution-Focused Brief Art Therapy alters therapeutic rapport and short-term outcomes relative to traditional artmaking materials. Participants were assigned by coin flip to create using either a text-to-image generator or convention media (23 per group), completing immediate and three-day follow-ups. Alliance was measured using DREAM (Dimensions of Regard, Empathy, and Authenticity Metric), and problems were rated pre/post; groups did not differ significantly on DREAM total or facets, and both modalities produced reliable pre-to-post reductions in problem severity. At the same time, process differences were pronounced: the AI condition showed …

Asymmetric Synthesis Of The Hiv Protease Inhibitor Tmc-126 And An Anti-Malarial Agent Via A Titanium Tetrachloride Mediated Asymmetric Glycolate Aldol Addition Reaction. Redefining The Curtius Rearrangement Reaction Via Dehomologation Of Carboxylic Acids Bearing Alpha-Leaving Groups, Kweku Amaning Affram

Theses and Dissertations

Acquired Immune Deficiency Syndrome (AIDS) and malaria are two devastating infectious diseases caused by HIV and Plasmodium parasites. AIDS is caused by HIV-1 and HIV-2, transmitted through sexual contact, blood transfusions, needle sharing, and perinatal routes. Malaria, caused by plasmodium parasites through mosquito bites. Today, millions of people around the world have been infected with HIV and malaria and much research has been done to treat it. However, despite advancements in therapeutic options, these diseases remain a significant global health threat, particularly in developing countries due to the emergence of drug-resistant strains for both HIV and malaria complicating eradication efforts. …

A Spine-Specific Lexicon For The Sentiment Analysis Of Interviews With Adult Spinal Deformity Patients Correlate With Sf-36, Sf-36, And Odi Scores: A Pilot Study Of 25 Patients, Ross Gore, Michael M. Safaee, Christopher J. Lynch, Christopher P. Ames

VMASC Publications

Classic health-related quality of life (HRQOL) metrics are cumbersome, time-intensive, and subject to biases based on the patient’s native language, educational level, and cultural values. Natural language processing (NLP) converts text into quantitative metrics. Sentiment analysis enables subject matter experts to construct domain-specific lexicons that assign a value of either negative (−1) or positive (1) to certain words. The growth of telehealth provides opportunities to apply sentiment analysis to transcripts of adult spinal deformity patients’ visits to derive a novel and less biased HRQOL metric. In this study, we demonstrate the feasibility of constructing a spine-specific lexicon for sentiment analysis …