A Phase 1, First-In-Human, Dose Escalation Study Of Jnj-80038114, A Psmaxcd3 Bispecific Antibody, In Participants With Metastatic Castration-Resistant Prostate Cancer, Andrew Hudson, Anuradha Jayaram, Benjamin Garmezy, Nicholas Zorko, Kevin Zarrabi, Ligi Mathews, Brent Rupnow, Mengjie Li, Debopriya Ghosh, Karen Urtishak, Peter Francis, Sherry Wang, Edward Attiyeh, Johann De Bono

Department of Medical Oncology Faculty Papers

PURPOSE: Prostate-specific membrane antigen (PSMA) has been identified as a therapeutic target for metastatic castration-resistant prostate cancer (mCRPC). The recent success of radioligands targeting PSMA spurred development of new PSMA-targeting agents including immunotherapy. JNJ-80038114 is a bispecific antibody that binds PSMA on tumor cells and CD3 on T cells to induce anti-tumor activity.

METHODS: This was a phase 1, open-label, multicenter study of JNJ-80038114 in participants with mCRPC and ≥ 1 prior systemic therapy. JNJ-80038114 was administered subcutaneously every 3 weeks (Q3W), starting at 0.1 mg. The primary endpoint was safety. Secondary endpoints included pharmacokinetics (PK), immunogenicity, and prostate-specific antigen …

Affect Regulation In The Context Of Sexual And Gender Minority Stress: A Scoping Review Protocol, Daphne Y. Liu, Benjamin A. Swerdlow, Shao Yuan Chong, Nadia Kako, Alex Rubin, Nicholas S. Perry

Psychology: Faculty Scholarship

Objective

To provide a broad, comprehensive picture of affect regulation in the context of sexual and gender minority stress, this scoping review aims to identify and synthesize methods, methodologies, and available evidence pertinent to emotion regulation and coping in the context of minority stress among sexual and gender minority (SGM) people.

Introduction

SGM people face disproportionately high rates of mental health problems due to experiences of minority stress and lack of social safety. Theories and growing evidence suggest that affect regulation plays a critical role in SGM people’s well-being in the face of minority stress. Researchers have largely studied emotion …

Task-Optimized Brain Parcellations Reveal Latent Functional Organization For Enhanced Connectivity-Based Neuroimaging Classification, Andrew Hannum, Mario A. Lopez

Computer Science: Faculty Scholarship

Brain parcellation schemes are fundamental to neuroimaging, yet general-purpose atlases may obscure the specific functional architecture relevant to a given cognitive task or clinical condition. This reflects a growing consensus that the “optimal” brain map is context-dependent. Here, we introduce a novel framework that validates this principle by generating task-optimized human brain parcellation maps directly from supervised learning objectives. Our method defines functional parcels by grouping brain regions based on the similarity of their contributions to a classifier's decision boundary for a specific goal (e.g., cognitive state decoding or clinical group separation). This approach prioritizes a region's discriminative role over …

Towards A Unified Gating Scheme For The Cnbd Ion Channel Family, Jenna L Lin, Baron Chanda

2020-Current year OA Pubs

Cyclic nucleotide-binding domain (CNBD) channels are critical components of numerous bioelectrical processes, including cardiac pacemaking, neuronal signaling, phototransduction in the eye, and stomatal regulation in plants. While members of this channel family share a conserved overall structure, they exhibit striking differences in voltage sensitivity. Hyperpolarization-activated cyclic nucleotide-gated channels are activated by membrane hyperpolarization, whereas ether-à-go-go channels open upon depolarization. Mutagenesis and chimeragenesis studies have revealed that some mutants display bipolar gating behavior-remaining closed at intermediate membrane potentials but capable of opening in response to both hyperpolarization and depolarization. Remarkably, in certain cases, just a few mutations are sufficient to reverse …

A Probabilistic Modeling Analysis Of The Longitudinal Immune Response To Infection And Vaccination Across Demographic Groups And Pulmonary Symptoms, James O'Hanlon, Kaitlyn Sullivan, Lyndsey M. Muehling, Glenda Canderan, Jie Sun, Judith A. Woodfolk, Jeffrey M. Wilson, Rayanne A. Luke

Spora: A Journal of Biomathematics

Antibody and cytokine kinetics describe the dynamic response to immune events such as infection and vaccination. These dynamics are not fully understood, and mathematical characterization may help explain variability across demographic groups and pulmonary symptoms post-acute infection. We fit time-dependent probability models to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data to obtain distributions of longitudinal antibody response and cytokine values. To assess differences between groups, an overlap metric is applied to the modeled response curves. Our antibody models suggest significant differences between male and female populations and demonstrate deficient antibody responses of less-healthy groups such as smokers. Our cytokine …

Optimal Intervention Strategies In Age-Structured Sirvd Model: Epidemiological And Economic Analysis Of Covid-19 In Korea, Joon Chun, Melisa Hendrata

Spora: A Journal of Biomathematics

This study employed an age-structured Susceptible-Infected-Recovered-Vaccinated-Deceased (SIRVD) model to design optimal COVID‑19 intervention strategies by integrating epidemiological dynamics with economic costs. Using empirical data from South Korea, we estimated transmission parameters and analyzed quarantine-based non-pharmaceutical interventions (NPIs) alongside targeted vaccination scenarios. Our results indicated that a stronger form of mild NPI (upper range of Level I), when combined with targeted vaccination that prioritized seniors, achieved substantial reductions in infection peaks and overall economic burden. These findings underscore the effectiveness of age-specific strategies in epidemic management and offer critical insights for policymakers seeking balanced, resource-efficient approaches.

Exploring The Role Of Occupational Therapy In The Delivery Of Trauma-Informed Services To Hospital-Based Clients Ot, Frank Czuba

Journal of Applied Disciplines

Hospitalization can traumatize clients and impact overall health outcomes, leading to increased hospital readmission rates and resulting in a negative impact for both clients and providers. Limited information exists regarding how hospital-based occupational therapists evaluate and address trauma, even though incorporating trauma-informed principles into professional practice can enhance the occupational therapy process. The study explored the comprehension and perceived significance of trauma-informed tenets among occupational therapists delivering services in hospital-based settings. A quantitative research study with an exploratory design was implemented to explore how occupational therapists (OT) understand and utilize trauma-informed practices with their clients in a hospital setting. An …

Physiologically Based Pharmacokinetic Modeling Of Acetaminophen In A Preterm Neonate Population, Sonia Sharma

Selected Full-Text Dissertations 2020-

Extremely preterm neonates are a pharmacologically vulnerable group due to their immature organ function and rapid developmental changes, which complicate optimal drug dosing. This thesis introduces a comprehensive physiologically based pharmacokinetic (PBPK) model for acetaminophen (APAP) tailored to this population, incorporating mechanistic ontogeny equations for key sulfotransferase (SULT) enzymes SULT1A1, SULT1A3, SULT1B1, and SULT2A1 developed from a unique dataset of pediatric liver samples. The PBPK model was calibrated and validated using observed pharmacokinetic data from neonates, infants, and children, demonstrating high predictive accuracy across developmental stages. By applying virtual twin simulations, the model was used on a nationwide children's hospital …

Aura: An Ai-Powered Multimodal Prototype For Adaptive Apraxia Of Speech Therapy And Communication Support, Omotayo Omoyemi, Rachel K. Johnson

Speech-Language Pathology Faculty Publications

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and …

Examining The Association Between Ddt Exposure And Parkinson’S Disease, Hodges Mccathern

Undergraduate Honors Theses

Dichlorodiphenyltrichloroethane, commonly known as DDT, was an organochlorine pesticide widely used in the mid-20th century. It is highly stable and resistant to degradation, leading to its long-term presence in the environment. This chemical bioaccumulates in ecosystems and in human tissue, particularly adipose tissue, raising concerns about chronic exposure. Emerging research links DDT exposure to adverse neurological outcomes, including increased risk for neurodegenerative disorders such as Parkinson’s Disease. Mechanistically, DDT and its metabolites may disrupt dopaminergic neurons, induce oxidative stress, and interfere with mitochondrial function, contributing to neurotoxicity. Understanding the environmental fate of DDT and its bioaccumulative properties is essential for …

Ocular Surface Disease Following Lasik And Cataract Surgery: A Review Of Their Interrelated Complications, Matthew D. Spangler, Nila Kirupaharan, John D. Sheppard

Department of Ophthalmology Faculty Publications

Background: Ocular surface disease is a multifactorial condition that is very commonly caused by dry eye disease (DED). Ophthalmic procedures intended to improve visual outcomes, laser-assisted in situ keratomileusis (LASIK) and cataract surgery, can paradoxically cause or exacerbate underlying ocular surface disease. This results in worsening vision and quality of life.

Areas covered: This review examines the pathophysiological mechanisms contributing to ocular surface disease development following LASIK and cataract surgery. Both procedures are associated with the transection of corneal nerves, leading to decreased tear production, surface instability, altered neurotrophin production, and impairment of the blink reflex. Furthermore, these incisional procedures …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Ai-Assisted Surface-Enhanced Raman Spectroscopy For Cardiovascular Diagnostics: From Plasmonic Materials To Clinical Translation, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. …

Gender, And Socioeconomic Status In School-Based Speech-Language Pathology Decision-Making For Adolescents With Traumatic Brain Injury: A Critically Appraised Topic, Geneva Renee Toledo

Selected Full-Text Master Theses 2021-

Purpose: Adolescents are at greater risk for traumatic brain injury (TBI), and TBI-related symptoms may contribute to disciplinary actions that increase their risk of entering the school-toconfinement pipeline. Given the disproportionate representation of racially marginalized male adolescents within this pipeline, this critically appraised topic (CAT) examined how race, gender, and socioeconomic status may influence school-based speech-language pathology (SLP) services and clinical decision-making following TBI. Method: A structured search of five electronic databases was conducted to identify studies examining speech-language pathologists’ (SLPs’) clinical decision-making and management of adolescents with TBI in relation to race, gender, and socioeconomic status. Relevant studies were …

Antagonistic Effects Of Glucagon And Insulin On 5-Fluorouracil Efficacy In Colorectal Cancer, Gabriel M. Randolph, Andrea Florian

SPARK Symposium Presentations

Prior research on the combined effects of insulin and glucagon with low-dose chemotherapy in cancer treatment has yielded contradictory conclusions. Insulin potentiation therapy (IPT), a longstanding but understudied approach, is broadly claimed to enhance chemotherapeutic efficacy; however, it has also been characterized as pseudoscience lacking physiological merit. Adding further complexity, glucagon, insulin's antagonist hormone, has been shown to produce anti-cancer effects when combined with chemotherapeutic agents. The present study aims to observe the individual effects of both hormones on colorectal cancer cells in combination with 5-Fluorouracil (5-FU), to clarify their respective roles in combination therapy. Through the modulation of both …

Chemotherapy Exposure Alters Heart Rate In Daphnia Magna: A Rapid Model For Evaluating Cardiotoxicity, Leland B. Wythoff, Andrea Florian

SPARK Symposium Presentations

Chemotherapy agents such as 5-Fluorouracil and Oxaliplatin are commonly employed in the management of various types of cancer. However, they have been implicated as causative factors of various side effects related to the heart. Drug-induced cardiotoxicity in rapid preclinical models could be employed as an effective tool for the identification of adverse effects. Daphnia magna is a small aquatic organism that is frequently employed in toxicological tests due to its transparent body that allows direct observation of physiological activities such as heart rates.

The purpose of the study was to evaluate the effect of various concentrations of 5-Fluorouracil and Oxaliplatin …

Comparative Machine Learning Models For Disease Risk Prediction, Mercy Mawusi Agbley

Theses, Dissertations and Capstones

Accurate prediction of disease outcomes is crucial for improving clinical decision-making and enabling early intervention. This study compares the performance of various statistical and machine learning models for clinical risk prediction using two healthcare datasets: diabetic retinopathy and heart disease. The models assessed include Logistic Regression, LASSO, k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Neural Networks, Random Forests, Gradient Boosting Machines (GBM), and a stacked ensemble model. Prior to modeling, datasets were split into train and test sets. Standardization was applied to numeric features whilst categorical features were one-hot encoded. These transformations were later applied to the test set. Principal …

A Hybrid Response Surface Methodology And Machine Learning Framework For Quantifying Effects Of Physicochemical Parameters On Pfas Distribution, Harsh V. Patel, Jazmin Green, Hyoshin Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Predicting PFAS adsorption across diverse adsorbents and environmental matrices remains challenging because adsorbent physicochemical properties, PFAS molecular descriptors, and operational conditions simultaneously influence adsorption. This study develops and evaluates a unified hybrid modeling framework that integrates Response Surface Model (RSM) with machine-learning algorithms to quantify how six key variables, surface area, Log K_ow, pH_pzc, pK_a, log dose, and log-initial concentration, affect PFAS distribution coefficients (Log K_d). A data set of more than 1000 adsorption observations spanning 15 PFAS compounds, multiple adsorbent types, and a broad operational range was compiled and preprocessed using …

Metabolic Syndrome Beyond Diagnostic Criteria: Population-Scale Integrative Metabolomics Characterization, Marwa Talal

Theses and Dissertations

Background: Metabolic syndrome (MetS) is a complex cluster of interrelated metabolic abnormalities associated with elevated cardiometabolic risk. While diagnosis is based on well-established five clinical criteria, these may overlook early or atypical metabolic alterations. Large-scale metabolomic profiling offers an opportunity to identify biochemical signatures of MetS beyond diagnostic bias and to evaluate their relative importance across different presentations of the syndrome.

Methods: Data from 117,147 UK Biobank participants were analyzed in a cross-sectional design. High-throughput NMR quantified 75 circulating metabolites, for. Univariate analyses, MetS subtype stratification, and elastic net models with SHAP interpretation were applied to assess feature …

Modélisation Spatiotemporelle De La Maladie De Lyme : Évaluation Du Risque D'Exposition Chez Les Travailleurs En Plein Air Au Québec, Mathieu Varin, Alberto Quezada Garcia, Gilles Joanisse, Virginie Millien, Batistin Bour, Bilel Chalghaf, Kirsten Crandall, François Milord, Jade Savage

Rapports de recherche scientifique

La maladie de Lyme, transmise par la tique à pattes noires, devient un problème de plus en plus important au Québec. Depuis 2009, les cas humains ont fortement augmenté, surtout dans le sud de la province. Les changements climatiques et les transformations du territoire issues des activités humaines favorisent la présence des tiques et de leurs hôtes, ce qui augmente le risque pour les personnes qui travaillent à l’extérieur.

Ce projet avait pour but de mieux comprendre où et quand ce risque est le plus élevé afin d’aider à protéger les travailleurs. Pour y arriver, nous avons combiné :

• des …

Reply To: S. N. Katkuri Et Al. And H. Liu Et Al. On Early And Sustained Improvements In Sense Of Smell With Tezepelumab Treatment In Patients With Chronic Rhinosinusitis With Nasal Polyps (Waypoint), Joaquim Mullol, Joseph K. Han, Tanya M. Laidlaw, Claire Hopkins, Anju T. Peters, Oliver Pfaar, Martin Desrosiers, Stella E. Lee, Andrew P. Lane, Claudia Chen, Yun Chon, Sandhia S. Ponnarambil, Andrew Foster, Andrew W. Lindsley, Christopher S. Ambrose

Department of Otolaryngology (ENT) Faculty Publications

[Introduction] We thank Dr. S. N. Katkuri, Dr. H. Liu, and their coauthors [1, 2] for their interest in our recent publication describing the improvements in loss of smell symptoms with tezepelumab versus placebo in patients with uncontrolled chronic rhinosinusitis with nasal polyps (CRSwNP) in the WAYPOINT trial (NCT04851964) [3]. We are grateful for the authors' feedback on the clinical significance of the data presented and their appreciation of the consistency observed across a range of baseline clinical characteristic and demographic subgroups.

Use Of Tezepelumab For Chronic Rhinosinusitis With Nasal Polyps By Eosinophilic Endotype: Waypoint Post-Hoc Analysis, Shigeharu Fujieda, Nobuyoshi Otori, Joseph K. Han, Tadataka Yabuta, Claudia Chen, Claudio Marchese, Andrews Foster, Sandhia S. Ponnarambil, Yun Chan, Brian J. Lipworth

Department of Otolaryngology (ENT) Faculty Publications

Background

The phase 3 WAYPOINT study (NCT04851964) reported that tezepelumab improved outcomes in patients with chronic rhinosinusitis with nasal polyps (CRSwNP), including nasal polyp size, nasal congestion, and sinonasal symptoms, and reduced the need for surgery and systemic corticosteroids (SCS).

Objective

To evaluate the efficacy and safety of tezepelumab across Japanese Epidemiological Survey of Refractory Eosinophilic Chronic Rhinosinusitis-defined eosinophilic chronic rhinosinusitis (ECRS) subgroups.

Methods

Adults with severe CRSwNP were randomized to tezepelumab 210 mg or placebo every 4 weeks. Coprimary end points were the change from baseline to week 52 in total Nasal Polyp Score and the biweekly mean Nasal …

Real-World Anti-Amyloid Therapy Beyond Traditional Symptomatic Populations: A Longitudinal Case Series, Jayoung Han, Yuan Fang, Darlingtina Esiaka, Olufunmilola Abraham

Mathematics & Statistics Faculty Publications

Introduction: Anti-amyloid monoclonal antibodies are approved as disease-modifying therapies for early Alzheimer’s disease (AD), but real-world evidence remains limited, particularly among individuals treated during preclinical or minimally symptomatic stages. This study characterized clinical and biomarker trajectories among anti-amyloid therapy recipients across disease stages.

Method: We conducted a longitudinal retrospective case series of three biomarker-positive individuals from the Alzheimer’s Disease Neuroimaging Initiative who received lecanemab or donanemab. Clinical, cognitive, cerebrospinal fluid, plasma biomarker, and amyloid PET data were examined.

Results: In all three cases, most of the observation period preceded anti-amyloid therapy initiation. Clinical trajectories varied by biomarker profile and treatment …

Influence Of Motion Artifacts On Instantaneous Frequency Based Heart Rate Variability Of Arterial Pulse Signals Measured By A Tactile Sensor: An Analytical Study, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Objective: Heart rate variability (HRV), quantified via the instantaneous frequency (IF) of arterial pulse signals, is a key indicator of cardiovascular (CV) regulation. This study presents a theoretical and experimental investigation of how motion artifacts (MA) influence IF-and thus HRVmeasured with a tactile sensor, emphasizing underlying mechanisms rather than population-level validation. Approach: Building on a previously developed single-degree-of-freedom (SDOF) model of the tissue-contact-sensor (TCS) stack between the sensor and the artery, MA is represented as low-frequency baseline drift and time-varying system parameters (TVSP) of the TCS stack. Analytical expressions quantify the effect of MA on the IF of each harmonic …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Evaluating The Effectiveness Of Scenario-Based Virtual Escape Rooms To Improve Student Confidence In Dosage Calculations, Jennifer A. Cuevas

Theses

Abstract

Background: Accurate dosage calculations (DCs) are critical for patient safety, as medication errors contribute to approximately 7,000-9,000 preventable deaths annually. Nearly 30% of nursing students exhibit weakness in foundational mathematical skills, and a significant confidence gap exists: 70% feel confident in mathematical abilities, yet only 45% feel confident in clinical application, necessitating innovative educational interventions.

Purpose: The purpose of this project was to implement and evaluate a scenario-based virtual escape room intervention to enhance undergraduate nursing students' confidence in DCs.

Methods: Grounded in Kolb’s experiential learning theory, this online asynchronous intervention engaged students through concrete experience, reflective observation, abstract …

Optimized Nano-Bilosomes Loaded Ocular Insert As A Promising Approach For Boosting Voriconazole Ocular Bioavailability: In-Vitro, Microbiological, And In-Vivo Assessments, Eman Gomaa

Nanotechnology Research Centre

The eye possesses numerous physiological barriers that significantly limit the absorption of administered drugs, as only < 5 % get through. These barriers restrict drug bioavailability, often necessitating multiple dosing, which can lead to poor patient compliance. The study goal is to efficiently incorporate Voriconazole (VRC), a wide-spectrum antifungal candidate with a short half-life, into stable, biocompatible, non-irritating bile salt nanoparticles (Bilosomes, BLOs) to enhance its ocular delivery. Bilosomes were prepared by the ethanol injection method. Experimental (33) Box–Behnken Design (BBD) was employed; the amount of bile salt, cholesterol, and span-60 were chosen as independent variables, while entrapment efficiency (EE%), cumulative VRC release (Q8h), particle size (PS), zeta potential (ZP), and polydispersity index (PDI) were the dependent variables. The formula of optimization showed EE% (59.04 ± 1.88 %), cumulative release after 8 h (81.35 ± 0.69 %), PS (222.53 ± 2.04 nm), ZP (−72.53 ± 1.75 mV), and PDI (0.225 ± 0.03). It was chemically characterized using DSC and FTIR. Its spherical arrangement was confirmed using TEM. For ophthalmic application, the optimized formula was included in ocular inserts to extend ocular residence time while minimizing dosing frequency. The optimal VRC-loaded bilosomal ocular insert met the acceptable physicochemical criteria, was sterilized using UV radiation for conducting microbiological assay, in-vivo study, and pharmacokinetic analysis. For safety evaluation, an eye irritation study and histopathological examination were conducted. The results confirmed its effectiveness as evidenced by a significantly larger inhibition zone and 8.39-fold enhancement in VRC bioavailability compared to its suspension. These findings support the potential of bilosomes-loaded ocular insert as an effective ocular delivery of VRC.

Previsit Ai: A Retrieval-Augmented Generation For Patient Readiness In Clinical Encounters, Rolande Umuhoza

All Graduate Theses, Dissertations, and Other Capstone Projects

With healthcare systems under growing pressure from rising patient volumes and shrinking consultation windows, improving how patients communicate with physicians has become essential to delivering quality care. Yet patients routinely arrive at appointments unable to clearly describe their symptoms, recall their medical history, or articulate concerns, contributing to miscommunication, diagnostic inefficiency, and pre-visit anxiety. This study introduces PreVisit AI, a conversational system designed to address this gap through structured, knowledge-based patient preparation. The system is built on a Retrieval-Augmented Generation (RAG) architecture combining HuggingFace sentence embeddings (all-MiniLM-L6-v2), a Chroma vector store, and Google’s Gemini language model over a curated seven-document …

Enhancing Hospital Length Of Stay Using Ai Agent Modular Capabilities, Dami Fred

Theses and Dissertations

Hospital Length of Stay (LOS) analysis is essential for managing hospital efficiency and financial performance, yet the analytical depth required remains inaccessible to many organizations due to technical and resource constraints. This thesis introduces the AI Agent Modular Capabilities (AIAM) framework, which decomposes LOS analysis into discrete, codifiable capabilities integrated into a single skill activatable with one prompt. Seven AI Agent Modular Capabilities were developed using a Work Breakdown Structure and tested against a simulated hospital scenario across three successive skill versions. Results demonstrate that the packaged AIAM skill produces comprehensive, consistent, multi-section LOS analyses from a single interaction, outperforming …