Medical Specialties Commons^™

Revascularization Strategies For Multivessel Disease In Acute Coronary Syndrome: Network Meta-Analysis, Khaled M. Harmouch, Mohammad Hamza, Nomesh Kumar, Zarghoona Wajid, Neel Patel, Masooma Naseem, Jawad Basit, Prakash Upreti, Manoj Kumar, Waqas Ullah, Yasar Sattar, Timir K. Paul, Emmanouil Brilakis, M. Chadi Alraies

Abington Jefferson Health Papers

BACKGROUND: The optimal revascularization strategy for patients with acute coronary syndrome (ACS) and multivessel disease (MVD) remains debated. This study compares the efficacy and safety of different revascularization strategies in these patients.

METHODS: We included 20 studies comparing staged, complete, and culprit-only (CO) revascularization strategies in patients with ACS and MVD. We divided the revascularization strategies into 3 distinct strategies: CO, complete index procedure (CIP), and complete staged procedure (CSP). We then compared CIP and CSP with CO. Outcomes studied are all-cause mortality, cardiac death, recurrent myocardial infarction (MI), need for revascularization, bleeding, contrast-induced nephropathy (CIN), stroke, bleeding, and stent …

Exploring The Reassessment Of Palliative Home Care Clients: A Mixed Methods Study, Maya Canham

Theses and Dissertations (Comprehensive)

Introduction: The timely reassessment of clients receiving palliative home care (HC) is critical for supporting clinicians with care planning and service delivery. However, there is little information on the frequency of reassessments and factors driving reassessment in palliative HC clients.

Objectives: The objectives of this study were to: (i) determine the proportion of palliative HC clients reassessed with the interRAI Palliative Care (interRAI PC) instrument, (ii) calculate the average interRAI PC reassessment interval, (iii) identify the key factors driving interRAI PC reassessment at various intervals, and (iv) explore the factors that influence palliative HC clinicians to reassess their clients in …

Food Allergies And Quality Of Life In Older Adults: Development Of A Food Allergy Questionnaire, Avalon F. Mustafa

UNF Graduate Theses and Dissertations

The United States is experiencing a rapid increase in the number of older adults, yet there is a lack of research on food allergies in this demographic. While there are survey instruments available to study food allergies and quality of life, none of these are tailored to the unique needs of elderly individuals. This study aims to create and validate an on-line survey instrument specifically designed for older adults, focusing on their quality of life in the context of food allergies. The survey will be used to establish a food allergy severity score and a quality-of-life score, enabling comparison between …

My Body My Choice: A Qualitative Study Of Volitional Female Sterilization In The U. S. Latina And Hispanic Female Population, Heather Morris Tuip

Antioch University Dissertations & Theses

This qualitative study, utilizing an interpretative phenomenological analysis methodology, elucidates the experience of Latina and Hispanic women living in the United States who have volitionally undergone sterilization or have sought the procedure out for birth control. Understanding the rich, contextual, lived experience of Latina and Hispanic women through an intersectional framework highlights how cultural influences and contemporary policies on reproductive rights informed their personal choice to undergo a female sterilization procedure. The participants of this study shared how they made meaning of their experiences. Within a homogenous sampling of study participants who share ethnicities and genders, six group experiential themes …

Educational Case: Disseminated Intravascular Coagulation In A Patient With Cancer, Kripa Ahuja, Richard M. Conran

Department of Biomedical and Translational Sciences Faculty Publications

The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see https://www.sciencedirect.com/journal/academic-pathology/about/pathology-competencies-for-medical-education-pcme.

Protein Marker-Dependent Drug Discovery Targeting Breast Cancer Stem Cells, Ashley V. Huang, Yali Kong, Kan Wang, Milton L. Brown, David Mu

Department of Biomedical and Translational Sciences Faculty Publications

Breast cancer is one of the most common cancers globally. Unfortunately, many patients with breast cancer develop resistance to chemotherapy and tumor recurrence, which is primarily driven by breast cancer stem cells (BCSCs). BCSCs behave like stem cells and can self-renew and differentiate into mature tumor cells, enabling the cancer to regrow and metastasize. Key markers like CD44 and aldehyde dehydrogenase-1 (ALDH1), along with pathways like Wingless-related integration site (Wnt), Notch, and Hedgehog, are critical to regulating this stem-like behavior of BCSCs and, thus, are being investigated as targets for various new therapies. This review summarizes marker-dependent strategies for targeting …

Effects Of Interventions For The Prevention And Management Of Maternal Anemia In The Advent Of The Covid-19 Pandemic: Systematic Review And Meta-Analysis, John Kyalo Muthuka, Diana Kageni Mbari-Fondo, Francis Muchiri Wambura, Kelly Oluoch, Japheth Mativo Nzioki, Everlyn Musanga Nyamar, Rosemary Nabaweesi

Faculty Publications

Background:The COVID-19 pandemic presented many unknowns for pregnant women, with anemia potentially worsening pregnancy outcomes due to multiple factors.

Objective:This review aimed to determine the pooled effect of maternal anemia interventions and associated factors during the pandemic.

Methods:Eligible studies were observational and included reproductive-age women receiving anemia-related interventions during the COVID-19 pandemic. Exclusion criteria comprised non-English publications, reviews, editorials, case reports, studies with insufficient data, sample sizes below 50, and those lacking DOIs. A systematic search of PubMed, Scopus, Embase, Web of Science, and Google Scholar identified articles published between December 2019 and August 2022. Risk of bias was evaluated …

Heterogeneous Clustering Of Multiomics Data For Breast Cancer Subgroup Classification And Detection, Joseph Pateras, Musaddiq Lodi, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

The rapid growth of diverse -omics datasets has made multiomics data integration crucial in cancer research. This study adapts the expectation–maximization routine for the joint latent variable modeling of multiomics patient profiles. By combining this approach with traditional biological feature selection methods, this study optimizes latent distribution, enabling efficient patient clustering from well-studied cancer types with reduced computational expense. The proposed optimization subroutines enhance survival analysis and improve runtime performance. This article presents a framework for distinguishing cancer subtypes and identifying potential biomarkers for breast cancer. Key insights into individual subtype expression and function were obtained through differentially expressed gene …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

Multi-Modal Mri Based Segmentation Of Brain Metastases Using Adaptive Self-Attention, Evan Savaria

Computer Science Faculty Publications

Brain metastases (BMs) are the most common adult central nervous system malignancy, affecting 20–40% of cancer patients. Accurate segmentation of metastatic lesions in multi-modal MRI is essential for treatment planning and prognosis however, manual delineation is time consuming and prone to variability. Traditional deep learning models such as U-Net, have improved segmentation accuracy but capture limited long-range dependencies and struggle with variations in metastasis size, shape, and distribution. This study introduces the Adaptive Integrated Multi-modal Segmentation (AIMS) model, an adaptive self-attention framework within a hybrid U-Net and Transformer architecture to enhance BM segmentation by leveraging multi-modal MRI integration. The proposed …

Coldstartcpi: Induced-Fit Theory-Guided Dti Predictive Model With Improved Generalization Performance, Qichang Zhao, Haochen Zhao, Linyuan Gao, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability …

Optiselect And Enshap: Integrating Machine Learning And Game Theory For Ischemic Stroke Prediction, Pritam Chakraborty, Anjan Bandyopadhyay, Sricheta Parul, Sujata Swain, Partha Sarathy Banerjee, Tapas Si, Hong Qin, Saurav Mallik

Computer Science Faculty Publications

Stroke analysis using game theory and machine learning techniques. The study investigates the use of the Shapley value in predictive ischemic brain stroke analysis. Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley value method was used to rank the models using their best four features based on their predictive capabilities. As a result, better-performing …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

Optimal Bag Valve Mask Ventilation Efficacy Of Smart Bag Ventilation Compared To Traditional Adult And Paediatric Bag Valve Ventilation During Cardiopulmonary Resuscitation, Ian Dawson

Theses: Doctorates and Masters

Background: Out-of-Hospital Cardiac Arrest (OHCA) is one of the world’s leading causes of mortality. Survival rates are low, ranging from 3.1–20.4% internationally. The most effective oxygenation method for patients during pre-hospital cardiac arrest is ventilating using a self- inflating Bag-Valve-Mask (BVM). Yet, extensive research has identified a lack of compliance with ventilator guidelines during OHCA cardiopulmonary resuscitation (CPR). As a result, clinicians often ventilate patients too aggressively using the BVM, delivering breaths excessively higher than the International Liaison Committee on Resuscitation (ILCOR) recommended rate of 10 breaths per minute (BPM). Hyperventilation can lead to complications such as aspiration, barotrauma, and …

A Turning Point In Cardiac Remodelling In Obesity: Obesity, Mariella R. Huaman, Carlos J. Toro-Huamanchumo

Research outputs 2022 to 2026

Cardiac remodelling in obesity has received growing attention in the past two decades, particularly as the prevalence of obesity continues to rise globally. In 2013, Aurigemma and colleagues published a seminal study that provided crucial insights into the structural changes in the heart associated with obesity. This study summarized advances in understanding how the disproportionate growth of adipose tissue affects cardiac function, and challenged and reshaped previously established paradigms. Before the publication of this report, the standard paradigm held that obesity-induced haemodynamic stress primarily drove eccentric left ventricular hypertrophy. However, this study instead demonstrated that in individuals with obesity, concentric …

Associations Of Vegetable And Potato Intakes With Markers Of Type 2 Diabetes Risk In The Ausdiab Cohort, Pratik Pokharel, Lauren C. Blekkenhorst, Catherine P. Bondonno, Kevin Murray, Simone Radavelli-Bagatini, Dianna J. Magliano, Robin M. Daly, Jonathan E. Shaw, Joshua Lewis, Jonathan M. Hodgson, Nicola P. Bondonno

Research outputs 2022 to 2026

Context: The associations of vegetable and potato intakes with type 2 diabetes (T2D) appear to be nuanced, depending on vegetable types and preparation method, respectively.

Objective: We investigated the associations of total vegetable, vegetable subgroup, and potato intakes with (1) markers of T2D at baseline and (2) incident T2D cumulative over a 12-year follow-up period in Australian adults.

Methods: Using data from the Australian Diabetes, Obesity and Lifestyle Study, intakes of vegetables and potatoes were assessed via a food frequency questionnaire at baseline. Associations between vegetable intake and (1) fasting plasma glucose (FPG), 2-hour postload plasma glucose (PLG), updated homeostasis …

Maternal Lipidomics For The Accurate Prediction Of Fetal Cyanotic Congenital Heart Defects, Onur Turkoglu, Nadia Ashrafi, Ali Yilmaz, Romana Ashrafi Mimi, Abdullah Khan, Perry Friedman, Ciara Talbot, Stewart Graham, Ray Bahado-Singh

Conference Presentation Abstracts

Objective: Late diagnosis of cyanotic congenital heart defects (CCHD) significantly increases newborn morbidity and mortality. However, a significant percentage of CCHD cases remain undetected prenatally. Our objectives were therefore to evaluate the accuracy of maternal serum lipidomic markers for the prenatal detection of CCHD and also to elucidate the pathogenesis of these disorders. Study Design: This prospective case-control study included 40 cases of CHD (22 cyanotic, 18 acyanotic) and 39 unaffected controls. Maternal serum samples were profiled via a combination of Ultra-High-Performance Liquid Chromatography coupled with Mass Spectrometry and Nuclear Magnetic Resonance. The mean of each lipid specie was compared …