Medicine and Health Sciences Commons^™

Scholarly Productivity Of Non–Pharmacy Practice Faculty In U.S. Schools And Colleges Of Pharmacy, 2019–2023, Osama A. Shoair, Sierra Pollard, Faith Fosuhene-Apenteng, Michael Pimentel-Galvan, Abrar Elagami, May H. Abdelaziz

Pharmacy Faculty Publications and Presentations

Purpose: Scholarly productivity is central to academic advancement, institutional benchmarking, and accreditation in pharmacy education. This study evaluated the national scholarly productivity among non–pharmacy practice (NPP) faculty in U.S. schools and colleges of pharmacy and assessed variation in publication output across faculty and institutional characteristics.

Methods: A retrospective bibliometric analysis was conducted between January 2019 and December 2023. Faculty were identified using the American Association of Colleges of Pharmacy Roster of Faculty and Professional Staff and classified as biomedical and pharmaceutical sciences (BPS) or social and administrative sciences (SAS). Publications were retrieved from Web of Science and characterized …

The Interplay Between Loneliness, Cortisol, And Nk Cell Function: The Role Of Cortisol In Nk Cell Dysfunction, Abhinav Saurabh, Yvonne Baumer, Laurel G. Mendelsohn, Elizabeth M. Aquino Peterson, Dana Sadler, Shirley J. Lopez De Leon, Ayushi Dave, Andrew S. Baez, Lola R. Ortiz-Whittingham, Mario A. Pita, Manuel A. Cintron, Hannatu A. Tarfa, Sandy T. Reynolds, Shelby R. Hicks, Sonal Sharda, J. Eleanor Seo, Maria Lopez-Ocasio, Pradeep K. Dagur, Skyler A. Kuhn, Neelam R. Redekar, James F. Troendle, Ayanna L. Wells, Marie Marah, Katherine J. Tolentino, Michael J. Corley, Alika K. Maunakea, Lynnette K. Nieman, Marcus R. Andrews, Tiffany M. Powell-Wiley

Department of Biomedical and Translational Sciences Faculty Publications

Chronic psychosocial stressors contribute to cardiovascular disease (CVD) and related risk factors, particularly in under-resourced communities. Psychosocial stressors activate the hypothalamic-pituitary-adrenal (HPA) axis, leading to sustained cortisol action on immune cells. Natural killer (NK) cells are altered in distribution and function in cardio-metabolic diseases; however, pathways linking cortisol as a marker of chronic stress to NK cell dysfunction remain understudied. We recruited 186 African American women from the Step It Up Community-Engaged, Digital Health Physical Activity Intervention study and collected cortisol, NK cell measures, and psychosocial stress measures using validated questionnaires, including chronic stress and loneliness. Plasma cortisol levels were …

The Effects Of Abused Drugs On Ferroptosis Pathways: Potential Therapeutic Targets For Substance Use Disorders, Tamara Bouchard, Brooke Russell, Liam Liyang Guo, Tina Nguyen, Yan Cheng, Yan Y. Sanders, Ming-Lei Guo

Department of Biomedical and Translational Sciences Faculty Publications

Substance use disorders (SUDs) remain major public health concerns worldwide, particularly in developed countries. SUDs are characterized by persistent neuroinflammation and synaptic dysfunction in the brain. Despite decades of extensive investigation, the detailed mechanisms underlying SUDs remain elusive. Ferroptosis is a highly regulated cell death process deeply affected by iron metabolism, lipid peroxidation, reactive oxygen species (ROS) production, and antioxidant systems. It has been implicated in multiple neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and ischemic stroke. Recently, emerging evidence has highlighted the role of ferroptosis in drug-induced pathological changes. Various types of abused substances including alcohol, cocaine, …

Senescent Fibroblasts In Aging And Pulmonary Fibrosis, Sara B. Palega, Aiwei Y. Borengasser, Yan Y. Sanders

Microbiology & Molecular Cell Biology Faculty Publications

Aging is a major risk factor for many chronic lung diseases, including Idiopathic Pulmonary Fibrosis (IPF), a fatal and incurable disease characterized by progressive fibrotic remodeling. Age-associated structural alterations, impaired regenerative capacity, and dysregulated cellular signaling collectively create a pro-fibrotic microenvironment. A central driver of this pathological shift is the accumulation of senescent cells, which undergo irreversible growth arrest and develop a robust pro-inflammatory senescence-associated secretory phenotype (SASP). Emerging evidence identifies senescent lung fibroblasts as critical mediators of IPF pathogenesis. These cells promote excessive extracellular matrix deposition, myofibroblast differentiation, and tissue stiffening, while simultaneously impairing epithelial regeneration. Together, these effects …

Single-Cell Transciptomic Analysis Reveals Age-Related Remodeling Of Brain Endothelial Cells, Hai Duc Nguyen, Summer Siddiqui, Diana G. Bohannon, Robert V. Blair, Hong-Wen Deng, Alexandre Prat, Woong-Ki Kim

Microbiology & Molecular Cell Biology Faculty Publications

Blood–brain barrier (BBB) integrity naturally declines with age. Brain endothelial cells (ECs) and pericytes (PCs) form the BBB, and aging impairs tight junctions, likely via altered PC-to-EC signaling. However, the molecular mechanisms underlying this impairment remain unclear. Using single-cell RNA sequencing, we profiled 68,316 brain ECs expressing 15,564 genes from young and old mice. Unsupervised clustering and annotation revealed five distinct EC subtypes—Capillary EC1, Capillary EC2, Arterial EC, Venous EC1, and Venous EC2—defined by marker genes Mfsd2a, Plvap, Bmx, Nr2f2, and Vcam1, respectively. Aging shifted EC subtype distribution, with reduced Capillary EC1 (45% vs. 57%) and increased Arterial …

Perioperative Predictors Of Hemodynamic Instability After Carotid Revascularization, Lutfi Barghuthi, Rebekah Bjorklund, Mya Phelps, Shrina Patel, Lakecia Beasley, Bayli Zink, Alyssa Bedell, Gaurav Singh, Sarah Stokke, Jacob Dunn, Lily Sadri, Carly Wadle, Alisha Thedford, Rebecca Swindall, Alan Cook, Hishaam Ismael, Mark Robbins

School of Medicine Faculty Publications and Presentations

Objective

Postoperative hemodynamic instability after carotid revascularization can lead to adverse outcomes such as intensive care unit admission and prolonged hospitalization, leading to an increase in resource utilization. This study aimed to compare hemodynamic instability between transcarotid artery revascularization (TCAR) and carotid endarterectomy (CEA).

Methods

A retrospective cohort study was conducted at a single institution on treatment for carotid artery stenosis between 2021 and 2024. Clinical outcomes after TCAR and CEA were compared. The primary outcome was hemodynamic instability; secondary outcomes of interest included any >30-day complication or death.

Results

In total, 566 patients were included, 71.2% undergoing TCAR (n …

Quadriceps And Ankle Weakness In Inclusion Body Myositis: Impact On Descending Balance Control And Rehabilitation Strategies - A Systematic Review, Woohyoung Jeon, Ashley Dalby, Melinda Hermanns, Manuel Lubinus

Nursing Faculty Publications and Presentations

Background

Inclusion Body Myositis (IBM), a progressive neuromuscular disorder, is characterized by quadriceps and ankle muscle weakness, leading to impaired balance control and increased fall risk during functional activities. Existing research highlights inconsistent evidence on fall risk reduction and a lack of standardized rehabilitation protocols, creating gaps in effective management. This systematic review aims to synthesize evidence on the impact of muscle weakness on balance and fall risk and evaluate rehabilitation strategies, including task-specific interventions, to improve functional outcomes in IBM patients.

Methods

Following PRISMA guidelines, we conducted a systematic search of MEDLINE, Embase, and the Cochrane Library from inception …

Mepolizumab Improves Outcomes In Patients With Crswnp With One Or More Prior Nasal Polyp Surgeries, Joseph K. Han, Joaquim Mullol, Martin Wagenmann, Laura Walrave, Lingjiao Zhang, Ana R. Sousa, Peter Howarth, Claire Hopkins

Department of Otolaryngology (ENT) Faculty Publications

BACKGROUND: Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) often undergo multiple nasal surgeries. The Phase III SYNAPSE study (GSK ID:205687; NCT0308579) demonstrated that mepolizumab reduces the need for repeat surgery. We explored whether outcomes differed based on the number of prior surgeries. METHODOLOGY: This post hoc analysis of SYNAPSE stratified patients by history of 1 or more than 1 prior surgery. Patients were randomised to receive mepolizumab or placebo every 4 weeks, alongside standard of care, for 52 weeks. Outcomes included change from baseline in endoscopic nasal polyp (NP) score, visual analogue scale (VAS) scores for nasal obstruction, loss …

Trends In Dermatologic Biologic Prescribing: A Medicare Part D Public Use File Analysis From 2018 To 2023., Cathleen V D'Angelo, Patricia Wilberger, Chase Merritt, Joshua Burshtein, Dawn Merritt

Ambulatory and Primary Care Articles

No abstract provided.

Seasonal And Geographic Trends In Photodynamic Therapy And Cryosurgery Use In The United States: A Cross-Sectional Study From 2015-2022., Dawn Merritt, Jon Lyons, Mouna Mikati, Christian Geils, Todd Schlesinger

Ambulatory and Primary Care Articles

BACKGROUND: Photodynamic therapy (PDT) is an effective field treatment for actinic keratoses (AKs). It is an ideal option for patients who prefer a minimally invasive procedure conveniently administered in their physician's office. Anecdotal clinician insights suggest that it may not be used at the same rate year-round.

OBJECTIVE: This study investigates whether PDT and cryosurgery usage is affected by season and geographic location in the United States.

METHODS: The data source is an aggregate of closed and open United States medical procedural claims (

RESULTS: PDT utilization is affected by season and geographic location. Procedural claims peak during cooler months …

Clinical Microbiology & Infectious Diseases: A Concise Guide On The Fundamentals Of Infectious Disease In Podiatric Medical Education, Paramita Basu

Open Touro Created

2026

This Open Educational Resource (OER), Clinical Microbiology & Infectious Diseases, is a student-centered textbook designed to support pre-clinical podiatric medical students enrolled in PCLP 610 Infectious Diseases at the New York College of Podiatric Medicine. The book is structured as a collection of concise “chapter briefs” or high‑yield notes that align closely with the course syllabus, lecture objectives, and student learning outcomes, while also reflecting the Microbiology learning objectives outlined in the AACPM Council of Faculties Curricular Guide.

The content covers core principles of medical microbiology and infectious diseases, including bacteria, viruses, fungi, parasites, host–pathogen interactions, antimicrobial therapy, resistance …

Dietitian-Led Nutrition Care Across The Cellular Therapy Continuum Supports Weight And Strength Recovery, Ashley Pagano Ms, Rdn, Ldn, Samantha Okerson Rdn, Erin Levine Rd, Cso, Ldn, Deanna Yerg Ms, Rdn, Ldn

Clinical Nutrition Service

No abstract provided.

High-Osmolality Medication Exposure And Length Of Stay In Icu Patients With Rectal Tubes, Kimberly Cephas Ms, Rdn, Ldn, Rachel Geosits Ms, Rdn, Cnsc, Ldn, Matthew Fair Pharmd, Hope Kincaid Mph, Cph, Alison Sutter Mph

Clinical Nutrition Service

No abstract provided.

Rural-Urban Differences In Dental Care Utilization After A Public Health Emergency, Quazi Minhaz Tabassum, Redwan Bin Abdul Baten, Ahmed A. Arif

Rural & Underserved Health Research Center Publications

Overview of Key Findings

• Past year dental clinic visits declined among both rural and urban populations after the COVID-19 pandemic. However, rural patients are more likely to report delayed dental service utilization than their urban counterparts.

• Participants residing in Medicaid expansion states or with health insurance coverage were 16% less likely to delay dental visits overall.

• The COVID-19 pandemic further worsened the existing challenges in dental healthcare access for urban and rural communities.

Review Of Current Research Describing The Influence Of Non-Health Care Drivers Of Health In Rural And Urban Populations, Katie Youngen, Julia Cecil, Tyrone F. Borders

Rural & Underserved Health Research Center Publications

Social determinants of health (SDOH) (also called social drivers of health) are the conditions of the environment where people live, learn, work, and play that are known to affect health outcomes.¹ The primary objective of this literature review is to summarize the most recent literature related to the Healthy People 2030 domains of a) economic stability, b) education access and quality, c) neighborhood and built environment, and d) social and community context.² Our particular focus is on non-health care drivers of health. The secondary objective is to identify gaps in literature applied to rural populations.

A Systematic Review And Meta-Analysis Of Mosquito Arboviral Infections Detected Through Xenosurveillance In Africa: A Focus On West Nile, Rift Valley Fever, And Chikungunya Virus Infections, Mxolisi Mgongoma, Armanda Bastos, Abel Ramoelo, David P. Tchouassi

All Peer-Reviewed Publications

This systematic review and meta-analysis comprehensively evaluated the mosquito arboviral infections with West Nile virus (WNV), Rift Valley fever virus (RVFV), and chikungunya virus (CHIV), detected through xenosurveillance, reported in mosquito vectors across Africa in the last 25 years (2000–2024). The study analysed xenosurveillance data from 45 studies conducted with over 115,000 mosquito specimens, and incorporated moderator analyses to assess the influence of trap type, seasonality, regional location, settlement type, and screening methods on virus detection rates. The estimated pooled prevalence of WNV was 1.18% (95% CI: 0.60–3.43%), with higher rates observed in Culex quinquefasciatus and Culex pipiens, particularly in …

Maxgrnet: A Multi-Axis Vision Transformer With Improved Generalization For Eye Disease Classification Using Explainable Ai With Insertion-Deletion Operations On Fundus Images, Md Mehedi Hasan Santo, Fuyad Hasan Bhoyan, Fuad Ibne Jashim Farhad, Fahmid Al Farid, Sovon Chakraborty, Md Humaion Kabir Mehedi, Jia Uddin, Hezerul Bin Abdul Karim

Computer Science Faculty Publications

Eye diseases, including diabetic retinopathy (DR), glaucoma, and cataracts, represent a major global health concern and can lead to severe visual impairment or blindness if not identified in a timely manner. This study proposes a novel eye disease classification framework based on a multi-axis vision transformer (MaxViT) applied to color fundus images with Explainable Artificial Intelligence (XAI) techniques to enhance model transparency. The proposed architecture integrates transformer-based attention mechanisms with Global Response Normalization (GRN)-based multi-layer perceptron (MLP) layers to capture complex spatial and contextual relationships within fundus images effectively. The model was evaluated on a publicly available eye disease classification …

Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge

Computer Science Faculty Publications

Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning framework. It is referred to as Independent Knowledge Distillation with post-Ensemble Federated Learning (IKDEFL). Differential Privacy (DP) is integrated into the framework to improve privacy guarantees. Three DP mechanisms are evaluated. These include Fixed Gaussian, Gaussian Adaptive, and Tree Adaptive. The evaluation has been conducted on heterogeneous and Non-Independent and Identically Distributed (Non-IID) datasets. These datasets reflect real-world hospital scenarios. Results show that IKDEFL significantly …

A Comparative Analysis Of Explainable Ai (Xai) Techniques For Transparent And Reliable Image Classification, Sovon Chakraborty, Shakib Mahmud Dipto, Kevin R. Pilkiewicz, Michael L. Mayo, Pratip Rana

Computer Science Faculty Publications

Evaluating the trustworthiness of black-box machine learning models remains a significant methodological challenge. Their lack of transparency and interpretability limits applicability, because stakeholders often seek transparency before trusting the results of black-box machine learning models. Explainable AI (XAI) methods provide for human-understandable justifications and informed decision-making of these black-box architectures. Therefore, it is imperative to select the proper XAI model tailored to specific tasks. In this research, we focus on examining four XAI techniques: PEEK, LRP, GRAD-CAM, and LIME to understand how they perform against each other for image classification tasks. We evaluate the performance, robustness, generalizability, noise stability, and …

Isotropic Shrinkage Of Patterned Vacancies Enables Three-Dimensional Nanoprecise Metastructures For Visible Light Applications, Quansan Yang, Gaojie Yang, Takahiro Nambara, Hiroyuki Kusaka, Yuichiro Kunai, Alex C. Matlock, Corban Swain, Brett Pryor, Yannick Salamin, Daniel Oran, Hasindu Kariyawasam, Ramith Hettiarachchi, Dushan Wadduwage, Marin Soljačić, Peter T. C. Soflaei, Edward S. Boyden

Computer Science Faculty Publications

Three-dimensional metastructures with nanoscale feature sizes exhibit unique properties compared with structures with larger feature sizes, but are difficult to fabricate. Here we introduce implosion carving (ImpCarv), a method for photopatterning vacancies of complex geometry throughout materials, followed by isotropic shrinkage (>10-fold). ImpCarv works by photoactivating sensitizers to generate reactive oxygen species that cleave a swollen hydrogel at defined points, followed by controlled shrinkage via dehydration. ImpCarv creates three-dimensional metastructures where the refractive index of each point throughout a material can be specified with nanoscale precision via material presence or absence. By leveraging refractive index programmability for precise phase …

Attf-Gnn: An Attention-Based Multi-Omics Graph Neural Network With Modality Learning For Disease Subtyping, Sovon Chakraborty, Eleni Adam, Terry Stilwell, Harold Riethman, Desh Ranjan, Pratip Rana

Computer Science Faculty Publications

We propose AttF-GNN, an attention-based graph fusion strategy for diseases classification and subtyping. In multiomics analysis, not all types of molecular data are equally relevant for disease subtyping and considering all modalities equally may obscure discriminative signals and limit the effectiveness of predictive models by overlooking modality-specific contributions. Therefore, we design an attention-based multimodal GraphSAGE framework that can automatically emphasize the modalities providing the most relevant information for classification. At first, we have constructed three graphs using mRNA, RNA-seq and DNA methylation modalities, and train each omics with individual GraphSAGE encoders. Next, a unified intersection graph is formed using an …

An Investigation Of Federated Gnns Under Aggregation, Data Poisoning, And Differential Privacy For Icu Length-Of-Stay Prediction, Shakib Mahmud Dipto, Soumya Banerjee, Sandip Roy, Ahmad F. Al Musawi, Preetam Ghosh, Sachin Shetty, Pratip Rana

Computer Science Faculty Publications

Accurate prediction of ICU Length of Stay (LoS) is essential for clinical decision-making and healthcare resource management. Graph Neural Networks (GNNs), such as GraphSAGE, offer a natural fit by capturing patient data from Electronic Health Records (EHRs) through graph structures. However, the distributed and sensitive nature of this data raises both privacy and legal concerns regarding the aggregation and training of GNN models. This additionally leads to issues with data imbalance and model robustness. In this study, we perform an analysis of the Federated Graph Neural Network (GNN-FL) framework to enable decentralized learning on EHRs derived from the MIMIC-III dataset. …

Attention-Based Multi-Omics Fusion For Drug Synergy Prediction, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug combination therapy in disease management gained popularity in the last few decades. Computational modeling of such combinations is an active area of research in the drug discovery domain. While earlier approaches solely emphasized on the structural features of participating drugs for designing synergistic models, they lack other crucial factors directly linked with drug administration - omics expressions. As differential omics expression is a downstream consequence of the administered drug combinations, utilizing such expressions while designing synergistic models promises robust and dynamic modeling. In this work, we propose SynergyLM that fuses multi-omics features with drug embeddings to build an omics-aware …

Chromnet: A Multi-Task Learning Framework For Cross-Cell Type Prediction Of 3d Chromatin Interactions Using Epigenetic Signals, Bin Wang, Shaokai Wang, Liqing Ding, Hongdong Li, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

The 3D organization of chromatin plays a fundamental role in gene regulation, cellular function, and disease mechanisms. However, current experimental techniques, such as Hi-C, remain costly and labor-intensive, limiting their application in large-scale and disease-related studies. To address this challenge, ChromNet is presented, a multi-task learning framework that integrates epigenetic signals across diverse cell types to enable high-precision prediction of chromatin architecture. By incorporating noise perturbation and auxiliary classification tasks, ChromNet improves the identification of topologically associating domains (TADs) and cell-type-specific chromatin structures, demonstrating superior generalization performance. Notably, ChromNet accurately predicts chromatin interactions in acute myeloid leukemia (AML) samples by …

Fumigant Toxicity Of Essential Oils From Chemotypes Of Curry Tree (Murraya Koenigii) Against Adult African Malaria Mosquito (Anopheles Gambiae Sensu Stricto), Clarence M. Mang’Era, Fathiya M. Khamis, Ahmed Hassanali, Paul O. Mireji

All Peer-Reviewed Publications

The toxicity of fumigant formulations of essential oils (EOs) from curry tree (Murraya koenigii (L.) Spreng (Rutaceae)) against African malaria adult mosquito (Anopheles gambiae sensu stricto (Giles, 1902) (Diptera: Culicidae: Culicini)) was evaluated to identify most effective chemotype of the curry tree against the mosquitoes. Ninety-two compounds (91.78%–96.47% coverage) in the EO profiles were identified, among which EO isolated from curry tree chemotype from Kibwezi was most toxic. This chemotype had a median lethal dose (LD50) of 3.6 × 10⁻³ mg/cm³ (95% CI: 2.70–4.58) and a lethal time (Ti50) of 1.91 ± 0.086 h (p < 0.001). The equivalent LD50 of EOs of chemotypes from Mombasa, Makindu, and Malindi in Kenya was 4.9 × 10⁻³, 6.6 …

A Comprehensive Overview Of Neurophysiological Correlates Of Cognitive Impairment In Amyotrophic Lateral Sclerosis, Seyyed Bahram Borgheai, Brie E. Achorn, Alyssa H. Zisk, Sarah M. Hosni, Karl E. G. Richter, Frank S. Menniti, Yalda Shahriari

Computer Science Faculty Publications

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that leads to the gradual loss of motor control, typically resulting in paralysis and death within 3 to 5 years of diagnosis. ALS shares neuropathological and genetic associations with fronto-temporal dementia (FTD), a neurodegenerative condition primarily impacting cognitive functions. These two conditions are increasingly viewed as manifestations of a single molecular disease process that affects distinct brain systems, impacting motor neuronal pathways in ALS and fronto-cortical functions in FTD. However, this simple dichotomy belies the complexity of these conditions. In particular, patients with primary motor ALS can also experience significant cognitive …

Near Real-Time Adaptive Isotropic And Anisotropic Image-To-Mesh Conversion For Cerebral Aneurysm Simulations, Kevin Garner, Chander Sadasivan, Nikos Chrisochoides

Computer Science Faculty Publications

This paper presents two performance optimization techniques for a mesh adaptation method that is designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. This method is integrated into a pipeline with an image-to-mesh conversion tool to generate adaptive anisotropic meshes from segmented medical images. The pipeline is shown to satisfy quality, fidelity, smoothness, and robustness requirements while providing near real-time performance for medical image-to-mesh conversion. Tested with two brain aneurysm cases and utilizing up to 96 CPU cores within a single, multicore node on Purdue University’s Anvil supercomputer, the parallel adaptive anisotropic meshing method …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Sage: Spatially Aware Gene Selection And Dual-View Embedding Fusion For Domain Identification In Spatial Transcriptomics, Yi He, Yunpei Xu, Liqing Ding, Hong-Dong Li, Yaohang Li, Shaokai Wang

Computer Science Faculty Publications

Despite enabling high-resolution mapping of gene expression within tissues, spatial transcriptomics (ST) still faces challenges in accurately segmenting spatial domains due to complex tissue architecture and limitations of current methods. Most approaches rely on local spatial priors, lack gene-level interpretability, and fall short in capturing structure-discriminative genes or long-range functional relationships, limiting their ability to resolve biologically meaningful architectures. We present Spatially Aware Gene selection and dual-view Embedding fusion (SAGE), a unified and reproducible framework for domain identification in spatial transcriptomics that combines topic-driven gene selection with dual-view embedding fusion to address these gaps. SAGE integrates non-negative matrix factorization (NMF)-based …

Roles Of Cytokines In Modulating Trypanosoma Brucei Rhodesiense Infection Outcomes In Vervet Monkeys, Clarah Jebet, John Kibuthu Thuita, Daniel Masiga, Benedict Owino Orindi, John Oidho, Mark C. Field, Enock Matovu, Vincent Owino Adung’A

All Peer-Reviewed Publications

Introduction:

Human African trypanosomiasis (HAT), caused by Trypanosoma brucei rhodesiense, is categorized as acute due to rapid disease progression but presents varying clinical outcomes. Although the mechanisms underpinning differential clinical progression are poorly understood, both host and parasite factors are implicated. Therefore, we sought to elucidate roles of primate host factors in mediating varying T. b. rhodesiense infection outcomes.

Methods:

Here, we assessed the roles of selected host cytokines in disease progression using a tsetse-mediated infection in a non-human primate (NHP) vervet monkey model that closely mimics HAT and natural infection. We quantified eight cytokines, including TNF-α, IFN-γ, IL-10, IL-6, …