Diseases Commons^™

Ethnic Disparities In Hba1c And Hypoglycemia Among Youth With Type 1 Diabetes: Beyond Access To Technology, Social Deprivation And Mean Blood Glucose, J. Pemberton, Zhide Fang, Stuart Chalew, S. Uday

School of Public Health Faculty Publications

Introduction The UK national pediatric diabetes audit reports higher HbA1c for children and young people (CYP) with type 1 diabetes (T1D) of Black ethnicity compared with White counterparts. This is presumably related to higher mean blood glucose (MBG) due to lower socioeconomic status (SES) and less access to technology. We aimed to determine if HbA1c ethnic disparity persists after accounting for the above variables. Research design and methods A retrospective analysis of participants who received structured education in continuous glucose monitoring (CGM) use was conducted at a tertiary center. HbA1c was paired with glucose metrics from 90-day CGM data. The …

Congenital Rickets, Melissa Intriago

Mako: NSU Undergraduate Student Journal

No abstract provided.

Multiparametric Mri Along With Machine Learning Predicts Prognosis And Treatment Response In Pediatric Low-Grade Glioma, Anahita Fathi Kazerooni, Adam Kraya, Komal Rathi, Meen Chul Kim, Arastoo Vossough, Nastaran Khalili, Ariana Familiar, Deep Gandhi, Neda Khalili, Varun Kesherwani, Debanjan Haldar, Hannah Anderson, Run Jin, Aria Mahtabfar, Sina Bagheri, Yiran Guo, Qi Li, Xiaoyan Huang, Yuankun Zhu, Alex Sickler, Matthew R Lueder, Saksham Phul, Mateusz Koptyra, Phillip Storm, Jeffrey Ware, Yuanquan Song, Christos Davatzikos, Jessica Foster, Sabine Mueller, Michael J Fisher, Adam Resnick, Ali Nabavizadeh

Department of Neurosurgery Faculty Papers

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free …

Estimating Per-Infection Cost And Burden For Dengue And Zika As A Function Of Antibody-Dependent Enhancement, Christopher M. Kribs

Mathematics Faculty Publications - Archive

The complex immune interactions produced by the tetravalent dengue vaccine Dengvaxia have foregrounded the important role of antibody-dependent enhancement (ADE) in dengue infection. Some evidence exists that ADE may extend beyond the four dengue serotypes to Zika, a closely related flavivirus transmitted by the same mosquito species as dengue, and may also account for the increased severity of some cases. Estimates of the public health impact of dengue vaccination may then need to include its effects on the transmission of Zika in addition to dengue. This study gathers primary references to build estimates of per-case economic cost and disease burden …

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 …

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. …

Effects Of Round-Up On The Environment, Sandra J. Marcu

Journal of Earth and Life Science

Many people around the world have used and still currently use Roundup but are unaware of the effects it has on the environment. Roundup is a spray on application weedkiller that is widely used around the world today both residentially and commercially. It enables its user to grow a garden or a field of crops with a no-tilling approach to eliminate weeds. It is a well-known and popular choice for killing weeds that has been around since the mid 1970’s (Oca, 2017). John Franz, a Monsanto scientist discovered that glyphosate (main ingredient in Roundup) was an herbicide or weedkiller, and …

Alpha-Synuclein Interaction With Gedunin, Tony Matundura Nyabayo

Graduate Theses/Dissertations

Parkinson’s disease (PD) and other Proteinopathies develop when α-synuclein misfolds and aggregates into toxic amyloids. While existing treatments for PD are primarily focused on managing its symptoms, a viable solution for slowing down the progress of Parkinson’s disease involves targeting the toxic α-synuclein amyloids. Gedunin, a natural inhibitor of heat shock protein 90, has been extensively used to treat malaria. Also, recent research investigations have shed light on its potential beyond malaria therapy, indicating that Gedunin may offer a possible solution for treating a variety of neurodegenerative diseases. Using plate-based assays, we examined how Gedunin influences α-synuclein fibrillation and its …

Rwanda's Natural Remedies: A Fresh Look At The Fight Against Malaria, Leandre Nsabimana Ndisanze

Pomona Senior Theses

Malaria remains one of the most devastating parasitic diseases globally, disproportionately affecting sub-Saharan Africa, where Rwanda continues to face high transmission rates and rising resistance to conventional interventions. Despite decades of control efforts, the emergence of drug-resistant Plasmodium falciparum and insecticide-resistant Anopheles mosquitoes threatens to reverse recent gains. This research responds to the urgent need for sustainable and culturally relevant alternatives by exploring the therapeutic potential of Rwandan traditional medicinal plants. These indigenous remedies, long used by local healers, offer an underexplored reservoir of bioactive compounds that may provide the basis for novel antimalarial drugs.

The central hypothesis of this …

Skinrisk Ai, Spencer Simms

Williams Honors College, Honors Research Projects

SkinRisk AI is an exploration of the opportunities for implementing machine learning (ML) and artificial intelligence (AI) in the medical technology field, specifically in the early detection of skin cancer. This project presents the design, development, and evaluation of a mobile application that allows users to capture images of skin lesions and receive a machine learning assisted risk assessment. The system combines a convolutional neural network (CNN) for image analysis with an intuitive mobile app built using Flutter, FastAPI, and Supabase to deliver real time screening.

Motivated by the rising skin cancer rates and importance of early detection, SkinRisk AI …

Biomechanics Of The Atherosclerotic Lipidome: (Un)Expected Statin Interactions And Membrane Remodelling, Ethan M. Fong

Pomona Senior Theses

Statins interact with lipid membranes in ways that shape their pharmacokinetics, off-target effects, and pleiotropic actions, yet these interactions' mechanical and biophysical consequences remain poorly understood. This thesis employs a combination of surface plasmon resonance (SPR), quartz crystal microbalance with dissipation monitoring (QCM-D), and rheological modelling to characterize how representative statins intercalate within biomimetic supported lipid bilayers (SLBs) of healthy and diseased composition. SPR reveals that lipophilic statins exhibit higher apparent affinities and slower dissociation kinetics, especially in cholesterol- and anionic lipid-rich membranes. QCM-D analyses demonstrate that statins alter membrane mass, dissipation, and interfacial stiffness in a statin- and membrane-dependent …

Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim

Mathematics & Statistics Faculty Publications

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are prevalent neurodegenerative disorders among the elderly, leading to cognitive decline and motor impairments. As the population ages, the prevalence of these neurodegenerative disorders is increasing, providing motivation for active research in this area. However, most studies are conducted using brain imaging, with relatively few studies utilizing voice data. Using voice data offers advantages in accessibility compared to brain imaging analysis. This study introduces a novel ensemble-based classification model that utilizes Mel spectrograms and Convolutional Neural Networks (CNNs) to distinguish between healthy individuals (NM), AD, and PD patients. A total of 700 voice …

Generating Real-World Evidence In Early Alzheimer's Disease: Considerations For Applying The Target Trial Emulation Framework To Study The Safety Of Anti-Amyloid Therapies, Xiaojuan Li, Sonal Singh, Bahareh Rasouli, Jennifer Lyons, Noelle M. Cocoros, Richard Platt, Ivan Abi-Elias, Jerry H. Gurwitz

Department of Medicine Faculty Publications

Anti-amyloid beta monoclonal antibodies (anti-Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinical trials. However, whether findings from these trials are generalizable to the real world is uncertain. We need reliable evidence on the real-world safety of these treatments to inform decision making for clinicians, patients, and caregivers. Using lecanemab as an exemplar, we outline the key considerations in designing and implementing an observational study on safety and utilization outcomes using …

Computational Approaches For Diagnosing Neurological Impairments And Restoring Functional Movement, Serhii Bahdasariants

Graduate Theses, Dissertations, and Problem Reports (ETD)

Movement is the primary means by which the nervous system converts intention into interaction with the environment. Voluntary limb motion enables standing, walking, reaching, and grasping—actions that underpin self‑care, communication, and economic participation. When diseases or injuries disrupt the pathways that couple neural commands to muscle forces—whether through cortical stroke, spinal cord injury, or peripheral nerve damage—mechanical outcomes such as weakness, loss of coordination, and ultimately reduced mobility emerge. These impairments cascade into secondary complications, increased dependence on caregivers, and diminished quality of life. Quantifying how the lesion alters the mechanics of movement is therefore essential for designing targeted interventions …

Surgical Delay-Associated Mortality Risk Varies By Subtype In Loco-Regional Breast Cancer Patients In Seer-Medicare, Macall Leslie Salewon, Rashmi Pathak, William Dooley, Ronald Squires, Hallgeir Rui, Inna Chervoneva, Takemi Tanaka

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

Substantial evidence supports that delay of surgery after breast cancer diagnosis is associated with increased mortality risk, leading to the introduction of a new Commission on Cancer quality measure for receipt of surgery within 60 days of diagnosis for non-neoadjuvant patients. Breast cancer subtype is a critical prognostic factor and determines treatment options; however, it remains unknown whether surgical delay-associated breast cancer-specific mortality (BCSM) risk differs by subtype. This retrospective cohort study aimed to assess whether the impact of delayed surgery on survival varies by subtype (hormone [HR] + /HER2 -, HR -/HER2 -, and HER2 +) in patients with …

Artificial Intelligence In Fetal And Pediatric Echocardiography, Alan Wang, Tam T Doan, Charitha Reddy, Pei-Ni Jone

Faculty, Staff and Students Publications

Echocardiography is the main modality in diagnosing acquired and congenital heart disease (CHD) in fetal and pediatric patients. However, operator variability, complex image interpretation, and lack of experienced sonographers and cardiologists in certain regions are the main limitations existing in fetal and pediatric echocardiography. Advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offer significant potential to overcome these challenges by automating image acquisition, image segmentation, CHD detection, and measurements. Despite these promising advancements, challenges such as small number of datasets, algorithm transparency, physician comfort with AI, and accessibility must be addressed to fully integrate AI …

Measurement Of Breast Artery Calcification Using An Artificial Intelligence Detection Model And Its Association With Major Adverse Cardiovascular Events, Suzanne Rose, Josette Hartnett, Zachary Estep, Daniyal Ameen, Shweta Karki, Edward Schuster, Rebecca Newman, David Hsi

Department of Medicine Faculty Papers

Breast artery calcification (BAC) obtained from standard mammographic images is currently under evaluation to stratify risk of major adverse cardiovascular events in women. Measuring BAC using artificial intelligence (AI) technology, we aimed to determine the relationship between BAC and coronary artery calcification (CAC) severity with Major Adverse Cardiac Events (MACE). This retrospective study included women who underwent chest computed tomography (CT) within one year of mammography. T-test assessed the associations between MACE and variables of interest (BAC versus MACE, CAC versus MACE). Risk differences were calculated to capture the difference in observed risk and reference groups. Chi-square tests and/or Fisher's …

Feasibility Of Large Language Models For Ceus Li-Rads Categorization Of Small Liver Nodules In Patients At Risk For Hepatocellular Carcinoma, Jiayan Huang, Rui Yang, Xiaotong Huang, Keyu Zeng, Yan Liu, Jun Luo, Andrej Lyshchik, Qiang Lu

Department of Radiology Faculty Papers

BACKGROUND: Large language models (LLMs) offer opportunities to enhance radiological applications, but their performance in handling complex tasks remains insufficiently investigated.

PURPOSE: To evaluate the performance of LLMs integrated with Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) in diagnosing small (≤20mm) hepatocellular carcinoma (sHCC) in high-risk patients.

MATERIALS AND METHODS: From November 2014 to December 2023, high-risk HCC patients with untreated small (≤20mm) focal liver lesions (sFLLs), were included in this retrospective study. ChatGPT-4.0, ChatGPT-4o, ChatGPT-4o mini, and Google Gemini were integrated with imaging features from structured CEUS LI-RADS reports to assess their diagnostic performance for sHCC. …

Artificial Intelligence-Based Methodologies For Early Diagnostic Precision And Personalized Therapeutic Strategies In Neuro-Ophthalmic And Neurodegenerative Pathologies, Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

SKMC Student Presentations and Publications

Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer's disease, Parkinson's disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques-Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging-in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and …

Comparing Multivalent Cross-Linked Sodium Alginate/ Montmorillonite Beads Containing Curcumin Or Cayenne Pepper As Drug Carriers And Their Antimicrobial Resistance, Shionainn Traynor, Shubham Sharma

SURE Journal: Science Undergraduate Research Experience Journal

The aim of the following work was to investigate and compare curcumin and cayenne pepper in microbeads composed of sodium alginate (SA) crosslinked with montmorillonite (MMT) to act as drug carriers and their antimicrobial resistance. The microbeads were prepared through ion-exchange in multivalent solutions of CaCl₂, MgCl₂ and AlCl₃. The microbeads were characterized by Scanning Electron Microscopy (SEM), Energy Dispersive X-ray analysis (EDX) and the time required for intercalation of curcumin and cayenne pepper with MMT. Simulated intestinal fluid (pH 7.3) and gastric fluid (pH 1.2) at 37°C were used for comparison in swelling studies. …

Mathematical Modelling Of Disease Outbreak, Favour Christian, Matthew Molloy

SURE Journal: Science Undergraduate Research Experience Journal

Establishing a model framework for more research necessitates a thorough understanding of the causes, distribution, prevalence, and evolution of infectious illnesses. The main mathematical concept used in this modelling simulation is ordinary differential equations (ODEs). The purpose of this study was to investigate the significance of the many criteria linked to a zombie virus spread. The zombie framework provides an accessible and relatively simple representation of the nature of infectious disease spread, allowing for tractable assumptions and the development of more complex situations.

The models are designed around a zombie outbreak in which the zombie virus is spread through a …

Editorial - Sure Journal Vol 6, Anne M. Friel, Eva Campion, Sinead Loughran

SURE Journal: Science Undergraduate Research Experience Journal

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Design, Synthesis, And Nmr-Guided Characterization Of A Targeted Covalent Inhibitor-Like Molecule Against Ivyp1 From P. Aeruginosa, Samuel Taylor Moore

Master's Theses

Multi-drug resistance poses a serious threat to future generations and historical antibiotic pipelines; consequently, the medical and economic burdens associated with treating multidrug-resistant bacteria are substantiated. In this context, P. aeruginosa (PA) emerges as one of the most significant healthcare challenges, being a leading cause of resistance-associated mortality worldwide. Despite modern efforts to combat these poor outcomes, drug-resistant cases continue to rise, and the need for novel antibiotic treatment is apparent. To this end, we investigated relevant resistance mechanisms and past antibiotic targets within PA, and in doing so, we identified relationships between peptidoglycan biology and a periplasmic protein, Inhibitor …

Rings Of Power: Controlling Sod Mimic Activity By The Addition Of Pyridine Rings Within The Pyridinophane Scaffold, Katherine J. Smith, Timothy M. Schwartz, David M. Freire, Cameron Bowers, Sarah K. Dunn, Jackson F. Bonnell, Magy A. Mekhail, Giridhar Akkaraju, Kayla N. Green

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Superoxide dismutase enzymes are a major defense against superoxide, which is a potent reactive oxygen species. Misregulation of reactive oxygen species and subsequent neuronal damage are etiological hallmarks of neurodegenerative disease. Macrocyclic small molecules have offered inroads toward functional SOD1 mimics. Herein, we report a series of five tetra-aza macrocyclic ^RPy₂N₂ ligands, varied by 4-position substitution of the pyridine ring with both electron-donating (R = OMe) and withdrawing groups (R = Cl, I, and CF₃) to offer the first comparison to well-studied ^RPyN₃ congeners and other mimics in the literature. New ligands …

A Latent Class Assessment Of Healthcare Access Factors And Disparities In Breast Cancer Care Timeliness, Matthew Dunn, Didong Li, Marc Emerson, Caroline Thompson, Hazel Nichols, Sarah Van Alsten, Mya Roberson, Stephanie Wheeler, Lisa Carey, Terry Hyslop, Jennifer Elston Lafata, Melissa Troester

Kimmel Cancer Center Faculty Papers

BACKGROUND: Delays in breast cancer diagnosis and treatment lead to worse survival and quality of life. Racial disparities in care timeliness have been reported, but few studies have examined access at multiple points along the care continuum (diagnosis, treatment initiation, treatment duration, and genomic testing).

METHODS AND FINDINGS: The Carolina Breast Cancer Study (CBCS) Phase 3 is a population-based, case-only cohort (n = 2,998, 50% black) of patients with invasive breast cancer diagnoses (2008 to 2013). We used latent class analysis (LCA) to group participants based on patterns of factors within 3 separate domains: socioeconomic status ("SES"), "care barriers," and …

D101n: A Unique And Ill-Understood Familial Als-Related Sod1 Mutant, Analisa Lott

Honors Program Theses and Research Projects

Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease, with 90% of documented cases considered sporadic and about 10% showing a hereditary link; such cases are deemed as familial ALS (fALS). Superoxide dismutase (SOD), a copper-zinc binding enzyme that protects cells from damaging free radicals, has been linked to fALS with certain toxic gain of function mutations, such as the D101N mutant. The human SOD1 D101N mutant has been shown to be associated with rapidly progressing neurodegeneration yet is less prone to aggregation than similar mutants, but its deviation from wild-type (WT) SOD1 remains misunderstood.

Objective: Although the D101N …

Exploring Post-Covid-19 Health Effects And Features With Advanced Machine Learning Techniques, Muhammad N. Islam, Md S. Islam, Nahid H. Shourav, Iftiaqur Rahman, Faiz A. Faisal, Md M. Islam, Iqbal H. Sarker

Research outputs 2022 to 2026

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and …

A Shared Mechanism For Tnp-Atp Recognition By Members Of The P2x Receptor Family, Xiao-Bo Ma, Chen-Xi Yue, Yan Liu, Yang Yang, Jin Wang, Xiao-Na Yang, Li-Dong Huang, Michael X Zhu, Motoyuki Hattori, Chang-Zhu Li, Ye Yu, Chang-Run Guo

Faculty, Staff and Student Publications

P2X receptors (P2X1-7) are non-selective cation channels involved in many physiological activities such as synaptic transmission, immunological modulation, and cardiovascular function. These receptors share a conserved mechanism to sense extracellular ATP. TNP-ATP is an ATP derivative acting as a nonselective competitive P2X antagonist. Understanding how it occupies the orthosteric site in the absence of agonism may help reveal the key allostery during P2X gating. However, TNP-ATP/P2X complexes (TNP-ATP/human P2X3 (hP2X3) and TNP-ATP/chicken P2X7 (ckP2X7)) with distinct conformations and different mechanisms of action have been proposed. Whether these represent species and subtype variations or experimental differences remains unclear. Here, we show …

Pediatric Renal Cell Carcinoma (Prcc) Subpopulation Environmental Differentials In Survival Disadvantage Of Black/African American Children In The United States: Large-Cohort Evidence, Laurens Holmes, Phatismo Masire, Arieanna Eaton, Robert Mason, Mackenzie Holmes, Justin William, Maura Poleon, Michael Enwere

College of Population Health Faculty Papers

OBJECTIVE: Renal cell carcinoma (RCC) is a rare but severe and aggressive pediatric malignancy. While incidence is uncommon, survival is relatively low with respect to acute lymphocytic leukemia (ALL), AML, lymphoma, ependymoma, glioblastoma, and Wilms Tumor. The pediatric renal cell carcinoma (pRCC) incidence, cumulative incidence (period prevalence), and mortality vary by health disparities' indicators, namely sex, race, ethnicity, age at tumor diagnosis, and social determinants of health (SDHs) as well as Epigenomic Determinants of Health (EDHs). However, studies are unavailable on some pRCC risk determinants, such as area of residence and socio-economic status (SES). The current study aimed at assessing …

Early Ctdna Kinetics As A Dynamic Biomarker Of Cancer Treatment Response, Aaron Li, Emil Lou, Kevin Leder, Jasmine Foo

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.