Medicine and Health Sciences Commons^™

Hypertensive Disorders Of Pregnancy And Perinatal Outcomes: Two Prospective Cohort Studies Of Nulliparous Women In India And Tanzania, Andrea B. Pembe, Pratibha Dwarkanath, Amani Kikula, John Michael Raj, Nandita Perumal Phd, Heavenlight A. Paulo, Rajalakshmi M, Christopher P. Duggan, Honorati M. Masanja, Nandini Chopra, Mary M. Sando, Tinku Thomas, Cara A. Yelverton, Alfa Muhihi, Anura V. Kurpad, Wafaie E. Fawzi, Blair J. Wylie, Christopher R. Sudfeld

Faculty Publications

Introduction Hypertensive disorders of pregnancy (HDP) have been linked with increased risk for maternal and offspring complications in high-income settings. However, in resource-limited settings, studies with robust measurement of HDP, including severity and timing, and perinatal outcomes are limited.

Methods We analysed data from two prospective cohorts of nulliparous women in India (n=10 570 pregnancies) and Tanzania (n=10 299 pregnancies) who were enrolled in calcium supplementation trials and had blood pressure and proteinuria assessments throughout pregnancy and at the time of labour and delivery. Generalised estimating equations were used to assess the relationship between HDP severity categories (gestational hypertension, preeclampsia …

Multiscale Modeling Of Drug-Induced Liver Injury From Organ To Lobule, Alon Malka-Markovitz, Stelian Camara Dit Pinto, Mohammed Cherkaoui, Steven M Levine, Sharmila Anandasabapathy, Gagan K Sood, Sadhna Dhingra, Gao Yujia, John M Vierling, Nicolas R Gallo

Center for Medical Ethics and Health Policy Staff Publications

Drug-induced liver injury poses significant challenges in drug development and in clinical care. This study builds on prior work developing a Human Liver Virtual Twin by creating a Multiscale Computational Fluid Dynamics framework that integrates patient-specific anatomical data to predict acetaminophen-induced liver injury as a demonstration of its capability. The model bridges vascular, lobular, and cellular scales to simulate dynamic blood flow, drug transport, and injury mechanisms that accurately reflect clinically observed spatial heterogeneity. Results demonstrate accurate blood flow dynamics, predictions of hepatocellular damage, and a scalable framework for studying spatial heterogeneity applicable to other hepatic pathologies. This work establishes …

Association Between Dietary Inflammatory And Antioxidant Potential And Systemic Inflammatory And Oxidative Status With The Risk And Severity Of Coronary Artery Disease, Zahara Namkhah, Elham Alipoor, Manhnaz Salmani, Negar Ebrahimi, Monireh Ahmadpanahi, Ali Vasheghani-Farahani, Mehdi Yaseri, Michael David Wirth, Longgang Zhao, James Hébert Scd, Javad Hosseinzadeh-Attar

Faculty Publications

Background and aims

Unhealthy diets have pro-inflammatory properties that have been shown to contribute to coronary artery disease (CAD). The dietary inflammatory index (DII®) and the dietary antioxidant quality score (DAQS) quantify the anti-/pro-inflammatory and antioxidant potential of a diet. This study aims to investigate the association between the energy-adjusted DII (E-DIITM), DAQS, oxidant/anti-oxidant biomarkers, and CAD risk and severity.

Methods and results

This cross-sectional study investigated 158 participants for the presence and severity of CAD based on coronary angiography. E-DII and DAQS scores, malondialdehyde (MDA), total oxidant status (TOS), glutathione peroxidase (GPX) activity, total antioxidant capacity (TAC) and conventional …

A Community-Based Study To Investigate Persistent Ambient Odors In Childs Park, Fl, Gennaro Saliceto

USF Tampa Graduate Theses and Dissertations

For many years, residents in Childs Park, Saint Petersburg, Florida, have reported unpleasant odors. Although there have been prior efforts to address the issue, the odors continue to be a concern for the community, who worry about possible health implications. This research aimed to equip residents with information to address the issue by identifying the presence of airborne pollutants that generate odors, quantifying the concentrations of toxic organic pollutants, and exploring the sources and environmental conditions that contribute to odors and their perception.

To accomplish these aims, the study utilized different methods. First, two walking measurement campaigns were conducted to …

Proceedings Of The Cuny Games Conference 11.0, Robert O. Duncan, Grace Axler-Diperte, Joe Bisz, Christina Boyle, Devorah Kletenik, Carolyn Stallard

Publications and Research

The CUNY Games Conference combines workshops, idea exchanges, interactive participant presentations, playtesting, and playing tabletop games into a one-day online event to promote and discuss game-based learning. The conference focuses on creative pedagogy, such as playful learning activities or games, that teachers can use in the classroom every day. The conference is online and features interactive presentations by attendees, informal idea exchange sessions, and workshops by the conference organizers.

Early Diagnosis And Detection Of Skin Cancer Using Deep Neural Network Models And Feature Extraction From Pre-Trained Cnns, Sahil Khanna

Harrisburg University Dissertations and Theses

Skin cancer is one of the most common and lethal cancer types. While accurate diagnosis at an early stage is essential for skin cancer treatment it remains difficult to achieve in many regions due to lack of sufficient dermatologists and proper diagnostic equipment. Prior studies show Convolutional Neural Network (CNN) models excel at skin lesion classification and consistently achieve better results than standard diagnostic practices. However, the focus of many studies remains confined to image-based learning while neglecting useful patient metadata that could improve prediction accuracy. This research project created a specialized CNN model to classify skin lesions and evaluated …

Temporal Modeling And Forecasting Of Blood Glucose Dynamics In Individuals With Diabetes Mellitus, Mj Ruff

University Honors Theses

People living with Diabetes Mellitus face significant health risks, including an increased likelihood of heart disease, stroke, and fluctuations in blood glucose levels. The unpredictable nature of glucose levels can lead to dangerous conditions such as ketoacidosis and hypoglycemia. This study employs advanced time series analysis tools to forecast the glucose levels for an individual diagnosed with Type 1 Diabetes Mellitus.

Forecasting Influenza Rates Using Machine Learning: A Study Of Chatgpt's Predictive Accuracy, Sara Saleh

University Honors Theses

This study evaluates ChatGPT's ability to forecast influenza rates, such as the number of flu cases, hospitalizations, and death during peak season periods using CDC data, and comparing forecasts against actual results to calculate statistical accuracy and consistency. Influenza forecasting is essential for public health planning, but traditional methods may not always provide timely or accurate predictions. In this research study, ChatGPT was utilized to predict the influenza rates for the following week based on the previous week's data obtained from the FluView surveillance system. The predicted rates were compared to the actual influenza rates to assess the model's overall …

Ensemble-Based Binding Free Energy Profiling And Network Analysis Of The Kras Interactions With Darpin Proteins Targeting Distinct Binding Sites: Revealing Molecular Determinants And Universal Architecture Of Regulatory Hotspots And Allosteric Binding, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS allostery remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to dissect how engineered DARPin proteins K27, K55, K13, and K19 engage KRAS through diverse molecular mechanisms ranging from effector mimicry to conformational restriction and allosteric modulation. Mutational scanning across all four DARPin systems identifies a core set of evolutionarily constrained residues …

Motionteller: Multi-Modal Integration Of Wearable Time-Series With Llms For Health And Behavioral Understanding, Aiwei Zhang, Arvind Pillai, Andrew Campbell, Nicholas C. Jacobson

Computer Science Senior Theses

As wearable sensing becomes increasingly pervasive, a key challenge remains: how can we generate natural language summaries from raw physiological signals such as actigraphy - minute-level movement data collected via accelerometers? In this work, we introduce MotionTeller, a generative framework that natively integrates minute-level wearable activity data with large language models (LLMs). MotionTeller combines a pretrained actigraphy encoder with a lightweight projection module that maps behavioral embeddings into the token space of a frozen decoder-only LLM, enabling free-text, autoregressive generation of daily behavioral summaries.

We construct a novel dataset of 54,383 ⟨actigraphy, text⟩ pairs derived from real-world NHANES recordings, and …

Detecting Physical Activity Using Wearable Sensor Data, Dipok Deb

Data Science and Data Mining

This study focuses on detecting physical activity using wearable sensor data, specifically distinguishing between walking and running. A dataset comprising accelerometer and gyroscope readings is used to train and evaluate various machine learning models, including logistic regression, random forest, k-nearest neighbors, naïve Bayes, and XGBoost. Extensive preprocessing, such as creating lag features and rolling statistics, is performed to enhance temporal data representation. The models are evaluated using metrics like accuracy, precision, recall, and F1 score. Incorporating lag and rolling features significantly improves model performance, with logistic regression achieving perfect scores across all metrics. These findings demonstrate the effectiveness of enhanced …

Biomarker-Guided Imaging And Ai-Augmented Diagnosis Of Degenerative Joint Disease, Rahul Kumar, Kyle Sporn, Aryan Borole, Akshay Khanna, Chirag Gowda, Phani Paladugu, Alex Ngo, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

Department of Medicine Faculty Papers

Degenerative joint disease remains a leading cause of global disability, with early diagnosis posing a significant clinical challenge due to its gradual onset and symptom overlap with other musculoskeletal disorders. This review focuses on emerging diagnostic strategies by synthesizing evidence specifically from studies that integrate biochemical biomarkers, advanced imaging techniques, and machine learning models relevant to osteoarthritis. We evaluate the diagnostic utility of cartilage degradation markers (e.g., CTX-II, COMP), inflammatory cytokines (e.g., IL-1β, TNF-α), and synovial fluid microRNA profiles, and how they correlate with quantitative imaging readouts from T2-mapping MRI, ultrasound elastography, and dual-energy CT. Furthermore, we highlight recent developments …

Arts-Based Sustainability: From New York To Malawi, Martha B. Lerski

Publications and Research

Recognizing that libraries serve multiple constituencies and subject areas, this chapter documents and advocates for development of transdisciplinary arts-based research (ABR) and culture-related projects linked to environmental challenges. Libraries contribute collections and spaces, as well as the research of library and information scientists. Libraries are currently among invisible contributors to sustainability planning and services. The chapter will link this invisibility to the value of what visual arts refer to as negative space elements in subjects ranging from traditional ecological knowledge to environmental science. Library collections, projects, and research contribute to education for sustainable development (ESD) as required to achieve the …

Molecular Insights Into The Role Of Estrogen Receptor Beta In Ecdysterone Mediated Anabolic Activity, Syeda Sumayya Tariq, Madiha Sardar, Muhammad Shafiq, Hendrick Heinz, Mohammad Nur-E-Alam, Aftab Ahmad, Zaheer Ul-Haq

Pharmacy Faculty Articles and Research

Ecdysterone, often dubbed a “natural steroid,” has garnered significant attention among athletes for its reputed growth-promoting and anabolic properties. Unlike synthetic anabolic steroids, which are classified as controlled substances, ecdysteroids remain largely unregulated in many countries and are widely marketed as dietary supplements. Notably, ecdysterone has been included in the World Anti-Doping Agency (WADA) monitoring program, highlighting its potential impact on athletic performance and raising questions about its regulation. Emerging evidence indicates that, unlike traditional anabolic steroids that act primarily via the Androgen Receptor (AR), ecdysterone’s anabolic effects may be mediated through Estrogen Receptors (ERs), particularly Estrogen Receptor beta (ERβ). …

Tailoring Evaluations Of Chronic Rhinosinusitis: Understanding Sleep And Its Effect On Memory Through Actigraphy, Donyea Moore, Rachel Nolte, Yitong Pepper Huang, Shreya Maharana, Pavan Nataraj, Bichun Ouyang, Mahboobeh Mahdavinia

Mathematics Sciences: Faculty Publications

Background/Objectives: Chronic rhinosinusitis (CRS) is a persistent inflammatory condition of the sinonasal mucosa lasting for at least three months. For patients, CRS-related sleep disturbances can significantly disrupt circadian rhythms, leading to further health complications such as cognitive impairment. Despite the well-documented sleep disturbances associated with CRS, there is limited research on objective assessment methods. Additionally, the severity of these issues can vary among patients. This study aims to assess sleep quality and timing in CRS patients and investigate their impact on cognition, providing guidance for personalized and tailored assessment and management of CRS. Methods: Our case–control study compares sleep patterns …

Graduate School Blog - June 2025, Cynthia Haynes

UofM Grad School Blog

The June 2025 edition of the UofM Graduate School Blog helps prospective and current students make informed financial decisions with Part 1 of the Graduate School Cost Guide, breaking down tuition structures such as per-credit hour versus flat-rate models, highlighting UofM’s tuition cap for in-state students, and explaining key university fees and cost differences between online and on-campus formats. The blog also features Brianna Reilly, a Doctor of Musical Arts graduate from New York, who shares how a graduate assistantship and her passion for music education led her to continue at UofM through the pandemic. Additional resources include an …

Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher

Master's Theses

Neuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization …

Computerized Diagnostic Decision Support Systems-Isabel Pro Versus Chatgpt-4 Part Ii, Joe M Bridges, Xiaoqian Jiang, Michael Ige, Oluwatoniloba Toyobo

Faculty, Staff and Student Publications

Objective: Does a Tree-of-Thought prompt and reconsideration of Isabel Pro's differential improve ChatGPT-4's accuracy; does increasing expert panel size improve ChatGPT-4's accuracy; does ChatGPT-4 produce consistent outputs in sequential requests; what is the frequency of fabricated references?

Materials and methods: Isabel Pro, a computerized diagnostic decision support system, and ChatGPT-4, a large language model. Using 201 cases from the New England Journal of Medicine, each system produced a differential diagnosis ranked by likelihood. Statistics were Mean Reciprocal Rank, Recall at Rank, Average Rank, Number of Correct Diagnoses, and Rank Improvement. For reproducibility, the study compared the initial expert panel run …

Transforming The Future Of Health: Building Learning Health Systems Across The Globe, Sandra Yankah, Robert Saunders, Mark L. Tykocinski, Claudia Salzberg, Jonathan Gonzalez-Smith, Rachel Bonesteel, Cameron Joyce, Charles Kahn, Mark Mcclellan, Eyal Zimlichman

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Health care has faced disruptions over the past 5 years, including a global pandemic, supply chain interruptions, workforce shifts, and the introduction of new artificial intelligence (AI) tools. Health care organizations continue to leverage the learning health system (LHS) concept to adapt to these challenges through iterative feedback loops. The Future of Health (FOH), an international community of over 50 senior health leaders that focuses on shared challenges across international health systems, collaborated with the Duke-Margolis Institute for Health Policy in a consensus-building process with FOH members to identify opportunities for action in an LHS. Key areas for action identified …

Predictors Of Nursing Students' Stress, Anxiety, And Depression During The Covid-19 Pandemic In A Hispanic-Serving University In South Texas: A Cross-Sectional Study, Maria I. Diaz, Eleftherios Gkioulekas, Nancy Nadeau

School of Mathematical & Statistical Sciences Faculty Publications

Background: In nursing education, there have been several studies on the impact of the COVID-19 pandemic on the ability of nursing students to cope while in nursing school.

Purpose statement: The goal of this study is to assess undergraduate nursing students' support mechanisms as predictors of stress, anxiety, and depression during the COVID-19 pandemic within a Hispanic-serving institution in South Texas.

Methods: Across-sectional design was used in this study. An online survey using self-reported questionnaires was used to gather data from an undergraduate nursing student cohort during the Fall 2021 semester. Linear regression was used to identify the predictors of …

What References Are Chatgpt, Gemini, Copilot, And Perplexity Providing For Consumer Health Questions?, Ivan Portillo, Scott Johnson, Catherine Johnson

Library Presentations, Posters, and Audiovisual Materials

No abstract provided.

Residential Factors Associated With Mental Health In United States Veterans, Air Force Military, And Air Force Employees, Andrew J. Hoisington, Christopher A. Stamper, Molly Penzenik, Meredith Reitter, Elizabeth J. Kovacs, Nazanin H. Bahraini, Lisa A. Brenner

Faculty Publications

Individuals in Westernized countries spend most of their time indoors. However, exploration of residential building factors that may influence occupants’ mental health is limited in scientific literature. The purpose of this study was to explore investigator's perceived areas of importance in residences to mental health via survey methods. To that end, we administered the Housing, Occupancy, Materials, and Environment (HOME) survey to assess factors that may influence mental health to those working in the United States (US) Air Force (n = 230) or past military members, US Veterans (n = 180). Self-reported mental health surveys were also administered to the …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Field Journal: The Excluded Middle, Carrie E. Kouts

Masters Theses

What does it look like to engage with organisms and landscapes at the periphery of anthropocentric value structures? How does one break the internalized myth that the “built” environment is excluded from the natural world? When does a hyper-mobile and hyper-commodified society confront the exponential crisis of animal death? Within this series of journal entries, field notes, collection observations, weird prose, and sensory musings, one will find questions on the nature of being human and the complex narratives of care we encounter in a world shared with more-than-humans. Each handwritten vignette and photograph from daily life weaves a non-linear and …

Artificial Intelligence Use In Medical Education: Best Practices And Future Directions, Rasheed A. M. Thompson, Yash B. Shah, Francisco Aguirre, Courtney Stewart, Costas D. Lallas, Mihir S. Shah

Department of Urology Faculty Papers

PURPOSEOF REVIEW: This review examines the various ways artificial intelligence (AI) has been utilized in medical education (MedEd)and presents ideas that will ethically and effectively leverage AI in enhancing the learning experience of medical trainees.

RECENT FINDINGS: AI has improved accessibility to learning material in a manner that engages the wider population. It has utility as a reference tool and can assist academic writing by generating outlines, summaries and identifying relevant reference articles. As AI is increasingly integrated into MedEd and practice, its regulation should become a priority to prevent drawbacks to the education of trainees. By involving physicians in …

Socioeconomic Disparities In Breast Cancer Survival: Examining Potential Mediator Role Of Oncotype Dx(Odx) Test And Stage At Diagnosis Among Hr+/Her2- Breast Cancer Women, Pratibha Shrestha, Qingzhao Yu, Edward S. Peters, Edward Trapido, Mei Chin Hsieh, Tekeda Ferguson, Quyen D. Chu, Xiao Cheng Wu

School of Public Health Faculty Publications

Background: Women with a lower socioeconomic status (SES) have an increased risk of dying from breast cancer (BC) than those with a higher SES. The association of SES with BC survival may be partially mediated by factors such as Oncotype DX (ODX) testing and stage at diagnosis. This study aims to examine SES disparities in survival among HR+/HER2- BC women and to quantify the mediating effects of the ODX test and stage. Methods: We used data from the Louisiana Tumor Registry to identify women aged 20–90 years diagnosed with stage I–II in 2011–2014 and stage I–III in 2015–2017 HR+/HER2- BC …

Are Cycles Of Neural Activity The Algorithm Of The Brain?, Edwin Omondi Onyango

Computer Science Senior Theses

We propose that precisely timed neural activity cycles can serve as structural primitives for memory and computation in a system that exhibits associative learning like the brain. Inspired by biologically grounded mechanisms such as calcium-dependent plasticity, spike-timing-dependent learning, and phase-sensitive excitability, we construct a spiking neural network model in which repeated temporal coincidences drive the formation of self-sustaining activity loops. These cycles, once formed, persist as dynamic memory traces: not stored as static weights, but as reverberating patterns that replay in time when these loops are restarted. We show that noise alone fails to induce stable structure, but even sparse, …

American Society Of Hematology/International Society On Thrombosis And Haemostasis 2024 Updated Guidelines For Treatment Of Venous Thromboembolism In Pediatric Patients, Paul Monagle, Muayad Azzam, Rachel Bercovitz, Marisol Betensky, Rukhmi Bhat, Tina Biss, Brian Branchford, Leonardo R. Brandão, Anthony K.C. Chan, Vincent E.S. Faustino, Julie Jaffray, Sophie Jones, Hassan Kawtharany, Bryce A. Kerlin, Nicole Kucine, Riten Kumar, Christoph Male, Marie Claude Pelland-Marcotte, Leslie Raffini, Chittalsinh Raulji, Sarah E. Sartain, Clifford M. Takemoto, Cristina Tarango, C. Heleen Van Ommen, Maria C. Velez, Sara K. Vesely, John Wiernikowski, Suzan Williams, Hope P. Wilson, Et Al

School of Medicine Faculty Publications

Background: The American Society of Hematology (ASH) guidelines on treatment of pediatric venous thromboembolism (VTE) were published in 2018. In the last 6 years, there has been a 10-fold increase in the number of children involved in VTE treatment trials. Objective: The ASH Committee on Quality and Guidelines agreed to update the pediatric guidelines in conjunction with the International Society on Thrombosis and Haemostasis (ISTH). These ASH/ISTH evidence-based guidelines are intended to support patients, clinicians, and other health care professionals in the management of pediatric patients with VTE. Methods: ASH/ISTH formed a multidisciplinary guideline panel to minimize potential bias from …

Discovery Of Drug Transporter Inhibitors Tied To Long Noncoding Rna In Resistant Cancer Cells; A Computational Model -In Silico- Study, Mohanad Diab, Amel Hamdi, Feras Al-Obeidat, Wael Hafez, Ivan Cherrez-Ojeda, Muneir Gador, Gowhar Rashid, Sana F. Elkhazin, Mahmad Anwar Ibrahim, Tarek Farag Ismail, Samar Sami Alkafaas

All Works

Chemotherapeutic resistance is a major obstacle to chemotherapeutic failure. Cancer cell resistance involves several mechanisms, including epithelial-to-mesenchymal transition (EMT), signaling pathway bypass, drug efflux activation, and impairment of drug entry. P-glycoproteins (P-gp) are an efflux transporter that pumps chemotherapeutic drugs out of cancer cells, resulting in chemotherapeutic resistance. Several types of long noncoding RNA (lncRNAs) have been identified in resistant cancer cells, including ODRUL, MALAT1, and ANRIL. The high expression level of ODRUL is related to the induction of ATP-binding cassette (ABC) gene expression, resulting in the emergence of doxorubicin resistance in osteosarcoma. lncRNAs are observed to be regulators of …

Integrative Computational Modeling Of Distinct Binding Mechanisms For Broadly Neutralizing Antibodies Targeting Sars-Cov-2 Spike Omicron Variants: Balance Of Evolutionary And Dynamic Adaptability In Shaping Molecular Determinants Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies—S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving the broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on …