Digital Commons Network^™

Proliferative Glomerulonephritis With Monoclonal Immunoglobulin Deposits With Severe Acute Kidney Injury Successfully Managed By Clone-Directed Therapy: A Case Report, Shohei Maekawa, Shinya Yamamoto, Tatsuaki Kosaka, Hisashi Kamido, Yasuyuki Arai, Yayoi Ogawa, Naoka Murakami, Yuki Teramoto, Motoko Yanagita

Faculty, Staff and Students Publications

Introduction

Proliferative glomerulonephritis with monoclonal immunoglobulin deposits (PGNMID) is a form of monoclonal gammopathy of renal significance, characterized by kidney injury caused by monoclonal immunoglobulin deposition in the glomeruli. While detectable clones are only found in 20–30% of PGNMID, plasma cell- or B-cell-targeting therapies are suggested to be effective. Recent case reports suggested immune dysregulation, such as viral infections or vaccinations, could potentially trigger the onset or relapse of PGNMID. Here, we report a case of PGNMID without detectable clones, which relapsed after viral enteritis, presenting with severe acute kidney injury (AKI) and nephrotic syndrome.

Case Presentation

A 60-year-old man, …

Therapeutic Potential Of Hookworm Proteins In Promoting Regulatory Immune Responses To Modulate Trypanosoma Cruzi Induced Liver Inflammation And Oxidative Stress, Maria Jose Villar, Cristina Poveda, Bin Zhan, Maya Gonsoulin, Kathryn M Jones

Faculty, Staff and Students Publications

Background: Chronic Trypanosoma cruzi infection causes significant liver pathology, and current antiparasitic treatments often worsen hepatic damage. Hookworm-derived proteins have shown immunomodulatory effects in inflammatory diseases, including T. cruzi-induced myocarditis.

Objective: This study evaluates recombinant hookworm proteins AIP-1 and AIP-2 for treating liver inflammation in a murine model of chronic Chagas disease (CD).

Methods: Female BALB/c mice infected with T. cruzi were treated with AIP-1 or AIP-2 (1 mg/kg) for seven days. Controls were untreated or received aspirin (25 mg/kg) for 14 days. Liver tissues were analyzed for parasite burden (quantitative polymerase chain reaction - qPCR), histopathology (H&E, Picrosirius Red), …

Deep Learning To Predict Future Cognitive Decline: A Multimodal Approach Using Brain Mri And Clinical Data, Tamoghna Chattopadhyay, Pavithra Senthilkumar, Rahul H Ankarath, Christopher Patterson, Emma J Gleave, Sophia I Thomopoulos, Heng Huang, Li Shen, Lei You, Degui Zhi, Paul M Thompson

Faculty, Staff and Student Publications

Predicting the trajectory of clinical decline in aging individuals is a pressing challenge, especially for people with mild cognitive impairment, Alzheimer's disease, Parkinson's disease, or vascular dementia. Accurate predictions can guide treatment decisions, identify risk factors, and optimize clinical trials. In this study, we compared two deep learning approaches for forecasting changes, over a 2-year interval, in the Clinical Dementia Rating scale 'sum of boxes' score (sobCDR), as a continuous outcome (regression). This is a key metric in dementia research and clinical trials, and scores range from 0 (no impairment) to 18 (severe impairment). To predict decline, we trained a …

Genetic Variants Associated With Sjögren’S Disease Subtypes Stratified By Clinical Feature, Nitesh Enduru, Chihiro Iwaya, Akiko Suzuki, Zhongming Zhao, Junichi Iwata

Faculty, Staff and Student Publications

Introduction: Sjögren's disease (SjD) is a chronic autoimmune disorder characterized by dry mouth (xerostomia) and dry eyes (xerophthalmia) due to inflammation in exocrine glands, particularly the salivary and lacrimal glands. The condition presents a wide variety of clinical features, suggesting that it may involve heterogeneous conditions without a clear boundary. Although genome-wide association studies (GWAS) have identified several genetic variants associated with SjD, their roles in SjD pathogenesis remain unclear.

Methods: In this study, we aimed to identify single-nucleotide polymorphisms (SNPs) associated with SjD by categorizing patients based on four diagnostic markers: anti-Ro/SSA and anti-La/SSB antibodies, IgG levels, and lymphocyte …

Enhancing Traffic State Estimation At Bottlenecks Through Improved Demand Modeling: A Greenshields-Grounded Approach, Yuyan Annie Pan, Xianbiao Hu, Qing Tang, Yanyan Chen, Xuesong (Simon) Zhou

Civil & Environmental Engineering Faculty Publications

Accurate estimation of traffic state under oversaturated conditions is fundamental to a wide range of transportation applications. While intuitive, volume-to-capacity (q/qc) ratio-based link performance functions (LPF) are challenged by the U-shaped pattern of real-world speed-flow plots, which contradict the monotonic assumptions of link performance models such as the Bureau of Public Roads (BPR) function, particularly when q/q_c ≥ 1. This study addresses this critical gap by proposing an enhanced demand estimation method grounded in the Greenshields model, incorporating a real-time inflow correction factor to more accurately capture traffic demand at bottlenecks. In parallel, a modified LPF is introduced, replacing …

Early Drowsiness Detection Via Second-Order Derivative Analysis Of Heart Rate Variability: A Non-Contact Ecg Approach With Machine Learning, Fabrice Vaussenat, Abhiroop Bhattacharya, Julie Payette, Alireza Saidi, Victor Bellemin, Geordi-Gabriel Renaud-Dumoulin, Sylvain G. Cloutier, Ghislain Gagnon

Études primaires

Drowsy driving contributes to roughly 20% of traffic fatalities, yet most detection systems rely on behavioral cues that appear only after impairment has set in. Here we ask whether first and second derivatives of heart rate variability (HRV) can detect pre-crash states earlier than conventional approaches. Twenty-five participants completed 49 driving simulator sessions while we recorded cardiac activity through capacitive ECG electrodes embedded in the seat backrest—a non-contact method that avoids the privacy concerns of camera-based monitoring. To prevent circular evaluation, ground truth labels were based solely on crash proximity rather than HRV-derived scores. The combined HRV feature set (conventional …

Occupational Exposure To Pesticides Increases The Risk Of Amyotrophyc Lateral Sclerosis: A Systematic Review And Meta-Analysis, France Labrèche, Pamela Prudhomme, Maryse Gagnon, Nicolas Dupré, Sabrina Gravel

Études primaires

Objective To systematically review the evidence on the association between occupational exposure to pesticides and the risk of amyotrophic lateral sclerosis (ALS).

Methods A systematic search, conducted in eight bibliographic databases for publications between 1990 and 2025, identified observational studies estimating the risk of ALS after occupational pesticide exposure. Study quality was assessed using the WHO Risk of Bias (RoB) assessment instrument for systematic reviews, with the ROBINS-E (RoB in non-randomised studies of exposure) tool domains of bias. Pooled risk estimates were produced using random-effects models with restricted maximum likelihood, heterogeneity was assessed with I² statistics, and meta-regressions and publication …

On The Use Of Hearing Aid Algorithms In Industrial Noise: Balancing Speech Intelligibility And Hearing Protection, Solenn Ollivier, Fabien Bonnet, Alexis Pinsonnault-Skvarenina, Christian Giguère, Jérémie Voix, Hugues Nélisse

Études primaires

Hearing protection devices (HPDs) are widely used to mitigate the risks of noise-induced hearing loss in industrial environments. However, conventional HPDs can often hinder communication for workers with hearing loss. While those workers may rely on hearing aids in their daily lives, the potential benefits and associated risks of using such devices in noisy workplaces remain unexplored. This study evaluated the effects of different hearing aid signal processing algorithms on speech intelligibility and estimated noise exposure under industrial noise conditions to characterize the balance between communication and protection needed to develop solutions for workers with hearing loss. A digital hearing …

Tracking Vigilance While Driving: Pilot Study Of Heart Rate Variability Classification Under A Controlled Sleep-Deprivation Protocol, James Elber Duverger, Eli Moser, Philippe Boudreau, Marie Claude Ouimet, Diane B. Boivin, Alireza Saidi

Études primaires

Decreased vigilance associated with drowsiness is a major cause of motor vehicle crashes, but its physiological characterization and detection remain difficult due to behavioral and environmental confounding factors. This study presents an original experimental framework combining a highly controlled sleep-deprivation protocol, repeated driving simulations, and a machine-learning-based heart rate variability (HRV) analysis to study the physiological and behavioral changes in vigilance during a prolonged period of wakefulness while driving. Twelve healthy young adults participated in a 30-h sleep-deprivation constant routine protocol that included driving simulations every two hours, with data collection: electrocardiography (ECG), subjective ratings of drowsiness, psychomotor vigilance test, …

Computer Vision-Based Collision Prevention In Construction: Bridging Academic Advances And Industrial Requirements, Marwa Ziadia, François Gauthier, Damien Burlet-Vienney

Études primaires

Computer vision (CV) technologies have emerged as promising tools for real-time collision risk management. This paper examines CV-based collision-prevention systems from academic and industrial perspectives with a focus on identifying technical and implementation challenges affecting their deployment on construction sites. A scoping review of 158 publications was conducted, alongside an assessment of commercial CV-based collision-prevention systems currently used in construction. The analysis focused on five key functions: object detection, distance measurement and proximity estimation, tracking, worker re-identification (ReID), and deployment robustness. Academic studies demonstrate substantial progress in detection accuracy, real-time processing, trajectory tracking, and predictive risk assessment through deep learning …

External Validation Of A Machine Learning Model To Predict Postpartum Hemorrhage In A Us Northeastern Healthcare System, Vesela P Kovacheva, Ricardo Kleinlein, Nolan Wheeler, Kartik K Venkatesh, Eric Jelovsek, David W Bates, Kathryn J Gray

Faculty, Staff and Students Publications

Introduction: Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction may prevent adverse maternal outcomes, and efforts are needed to develop accurate predictive tools. A high-performing machine learning model to predict PPH using data from the US Consortium for Safe Labor (CSL) remains to be widely validated in contemporary clinical settings using electronic health record (EHR) data. Our goal was to evaluate the performance of the CSL PPH predictive model using EHR data across a large healthcare system in the Northeastern United States.

Methods: We conducted a retrospective cohort study across eight hospitals in the …

High School Daze, Sylvia Perez, And La Llorona, Manuel F. Medrano

History Faculty Publications

No abstract provided.

For Two Cents A Pound, Manuel F. Medrano

History Faculty Publications

No abstract provided.

Microbial Collagenase Activity Is Linked To Oral–Gut Translocation In Advanced Chronic Liver Disease, Shen Jin, Aurelie Cenier, Daniela Wetzel, Bethlehem Arefaine, Mar Moreno-Gonzalez, Marilena Stamouli, Merianne Mohamad, Mariia Lupatsii, Emilio Ríos, Sunjae Lee, Ane Zamalloa, Shilpa Chokshi, Adil Mardinoglu, Saeed Shoaie, Naiara Beraza, Vishal C. Patel, Melanie Schirmer

Peninsula Medical School

Microbiome perturbations are associated with advanced chronic liver disease (ACLD), but how microorganisms contribute to disease mechanisms is unclear. Here we analysed metagenomes of paired saliva and faecal samples from an ACLD cohort of 86 individuals, plus 2 control groups of 52 healthy individuals and 14 patients with sepsis. We identified highly similar oral and gut bacterial strains, including Veillonella and Streptococcus spp., which increased in absolute abundance in the gut of patients with ACLD compared with controls. These microbial translocators uniquely share a prtC gene encoding a collagenase-like proteinase, and its faecal abundance was a robust ACLD biomarker (area …

Best Practice Guidelines For Professional Carers In Emergency Seizure Medication, Rohit Shankar

Peninsula Medical School

No abstract provided.

Survival Of Listeria Monocytogenes And Salmonella Typhimurium In Pepperoni With Reduced Salt And Sodium Nitrite Levels, And Sublethal Thermal Treatments, Shannon Heapes, Victoria Caballero, Jesus Frias, Bradley Afanda, Martin Danaher, Joseph P. Kerry, Geraldine Duffy

Research Outputs: 2025-Present

There is increasing pressure to reduce sodium nitrite and salt levels in processed and fermented meats in response to consumer demands and updated legislation. However, such reductions may impact pathogen control. In this study, the survival of Listeria monocytogenes and Salmonella Typhimurium was evaluated in pepperoni produced with reduced salt and sodium nitrite levels, with or without an enhanced postfermentation thermal treatment. Pepperoni batters with formulations varying in sodium nitrite (50–150 ppm) and salt (1.4%–2.5%), were inoculated with cocktails of L. monocytogenes or S. Typhimurium (~log₁₀ 4–6 CFU g⁻¹), subjected to a postfermentation thermal treatment (53.5°C × …

Pab-Pif: A Hybrid Architecture To Evaluate Mutable And Immutable Blockchains In Iot–Fog Networks, Marco Scarpa, Mohammad Sadeghzadeh, Saeed Javanmardi, Bahareh Pahlevanzadeh, Mauro Iacono

Research Outputs: 2025-Present

Blockchain provides secure and decentralized data storage. Normal blockchains permanently store data. Mutable blockchains allow users to change data, but this reduces tamper resistance. This paper tests both methods in PaB-PIF, a hybrid architecture for IoT-Fog networks. Our design uses an immutable mainchain in the cloud layer and mutable sidechains in the fog layer. We analyze throughput, latency, and tamper resistance using math models and simulations. Results show that blockchain greatly improves network security. Without blockchain, the network has zero tamper resistance. The mutable blockchain in the fog layer has a tamper resistance of 0.58. The immutable blockchain in the …

Browser-Based Phishing Detection System Using Modern Web Technologies, Muhammad Arshad, Beena Sherin Kuriakose, Choo Wou Onn, Farhan Ahmad Siddiqui, Mohammad Shahid Kamal

Research Outputs: 2025-Present

Phishing remains one of the most persistent cybersecurity threats, exploiting human trust to steal sensitive information through deceptive websites. Traditional detection methods, reliant on blacklists and reactive reporting, offer limited protection against rapidly evolving zero-day attacks. To address these challenges, this study proposes and evaluates a hybrid browser-resident phishing detection framework that combines three complementary detection mechanisms: a locally executed Random Forest model using URL lexical features, lightweight real-time DOM structure analysis, and VirusTotal’s multi-engine reputation service. Communication between the client and server is optimised using gRPC over the QUIC protocol, ensuring secure, high-performance data exchange with built-in retry mechanisms …

Educating The Next Generation Of Engineers: Spatial Thinking Is Key To Their Success, Sheryl Sorby, Gavin Duffy, Jack Parkinson, Gibin Raju, John Lynch, Muhammad Asghar

Research Outputs: 2025-Present

This paper attempts to answer questions regarding the link between engineering success and spatial skills through three themes. The previous research of the authors in examining the questions surrounding each theme is the focus of this paper; we acknowledge that others around the world may have conducted similar research, but the specific findings of the authors are the main focus of this paper. In the first theme, we examine data from several author-led studies where positive correlations have been found between spatial skill levels and proficiency in tasks that are a part of what it means to be an engineer. …

Sustainable Development And Faith, Tony Kealy

Research Outputs: 2025-Present

The contribution of faith-based input to the broader idea of sustainable development has not been widely acknowledged in the traditional sense; however, recent global events suggest it may warrant further exploration. This qualitative study examines how faith-based activities, such as missionary work, have historically and can continue to contribute significantly to the environmental, economic, and human/social aspects of organizational decision-making. The focus is on the Catholic faith, specifically the role played by the Irish-based Medical Missionaries of Mary religious congregation in the mid-to-late twentieth century. An initial literature review was conducted to gather information from various sources to define sustainable …

A Taxonomy And Empirical Evaluation Of Webassembly Runtimes For Performance And Energy Across Machine Learning And Arithmetic Workloads, Sallar Khan, Tania Malik, Khalid Hasanov

Research Outputs: 2025-Present

WebAssembly (Wasm) has emerged as a lightweight, portable, and secure execution environment beyond the browser, with growing adoption in data-intensive, machine learning, and performance-sensitive workloads. However, the runtime ecosystem remains fragmented, and a systems-level understanding of how runtime design affects performance and energy efficiency is still lacking. This paper makes two contributions. First, it presents a taxonomy of modern WebAssembly runtimes that classifies the runtime landscape by execution model, compilation strategy, integration style, and systemslevel capabilities. Second, it provides an empirical evaluation of 13WASI-compatible runtimes and a native baseline across eight benchmarks, namely, four machine learning workloads (Logistic Regression, K-Means, …

Influence Of Beamwidth, Gain Stability, And Antenna Element Spacing On Aoa Accuracy In Ieee 802.15.4z Uwb Systems, Hossein Raghib Hokmabadi, Wasi Ur Rehman Khan, Patrick Mcevoy, Max James Ammann

Research Outputs: 2025-Present

Precision is a crucial requirement in indoor localization, and the industrial sector increasingly demands technologies that provide both high accuracy and low cost. This work presents a hardware-based evaluation of dual-antenna arrays using an IEEE 802.15.4z-compliant UWB angle of arrival (AoA) development kit to assess antenna performance in terms of phase difference of arrival (PDoA)/AoA linearity. Four antenna types: 1) printed monopole; 2) CPW-fed slot; 3) stacked dielectric resonator antenna (DRA); and 4) dual-layer microstrip patch are evaluated on channels 5 and 9, with measurements performed in a calibrated anechoic chamber under controlled conditions. The results show that wide beamwidth …

Discipline With Due Process: Constitutional Safeguards For Student Speech After Plaintiff A, Sarah Stich

Missouri Law Review

When fifteen-year-old Louie posted a TikTok video criticizing his school’s disciplinary policies from his bedroom, he faced a month-long suspension despite having no notice of which policies he had violated. Across the country, Kaitlin shared a Snapchat criticizing her chemistry teacher with friends at a local coffee shop and faced expulsion with minimal opportunity to explain the context. In both cases, students received limited procedural protections before suffering severe academic consequences.

Fuzzy Logic-Based Driving Style Classification For Lane-Change Prediction In Intelligent Transportation Systems, Muhammed Fatih Koc, Nouman Ashraf, Pramod Pathak, Sachin Sharma

Research Outputs: 2025-Present

In recent years, Intelligent Transportation Systems (ITSs) have emerged as a solution to mitigate the problem of traffic congestion. Understanding human driving styles such as aggressive, normal, and cautious is crucial for safe driving. In particular, predicting lane-change manoeuvres may be further supported by combining vehicle state information with driving style information. However, existing vehicle trajectory datasets lack driving style information, making classification challenging. To address this limitation, this paper proposes a fuzzy logic-based driving style classification framework in a Vehicle-to-Everything (V2X) environment. The model uses vehicle state information, including speed, longitudinal acceleration, lateral acceleration, and distance headway to classify …

Preclinical Ischemic Stroke Multicenter Trials (Prism) Collective Statement: Opportunities, Challenges, And Recommendations For A New Era, Cenk Ayata, Philip M Bath, Anna M Planas, Stuart M Allan, Johannes Boltze, Ryan P Cabeen, Claire L Gibson, Marilyn J Cipolla, Marcio A Diniz, Stefano Fumagalli, Fahmeed Hyder, Raymond C Koehler, Arthur Liesz, Sarah K Mccann, Tim Magnus, Louise D Mccullough, Emily S Sena, Simone Beretta, Jaroslaw Aronowski, Francesca Bosetti, Clinton B Wright, Patrick D Lyden, Lauren H Sansing

Faculty, Staff and Student Publications

Preclinical stroke research faces a critical translational gap, with animal studies failing to reliably predict clinical efficacy. To address this, the field is moving toward rigorous, multicenter preclinical randomized controlled trials (mpRCTs) that mimic phase 3 clinical trials in several key components. This collective statement, derived from experts involved in mpRCTs, outlines considerations for designing and executing such trials. mpRCTs offer advantages such as increased sample sizes, robust statistical design, incorporation of heterogeneity, and standardized protocols, but they face challenges in finding the right balance between standardization and heterogeneity, appropriate stroke model selection, and outcome measures, as well as the …

Blood Flow Regulates Metabolism In Hematopoietic Development, Pamela L Wenzel

Faculty, Staff and Student Publications

Blood flow modifies oxygen availability and biomechanical forces within the vasculature of the embryo as the hematopoietic system develops. The aorta-gonad-mesonephros (AGM) envelops the largest artery in the body and is a critical site for the emergence of hematopoietic stem cells (HSCs). Herein, I discuss the role of hypoxia-inducible factors (HIFs) and force as determinants of metabolism and fate determination. To address the effects of blood flow on hematopoietic development, I employ mouse embryo models and biomimetic culture. Real-time cell metabolic analyses show that oxygen consumption rates (OCR) and extracellular acidification rates (ECAR) are altered by flow in cultures of …

Streamlining Eligibility Assessment For Alzheimer’S Disease-Modifying Therapies: Prediction Of Mmse Scores Using The Digital Clock And Recall, Ali Jannati, Claudio Toro-Serey, Marissa Ciesla, Emma Chen, John Showalter, David Bates, Alvaro Pascual-Leone, Sean Tobyne

Faculty, Staff and Students Publications

           Introduction: The eligibility of anti-amyloid disease-modifying therapies (DMTs) and their integration into clinical practice in some institutions requires a specific range of Mini-Mental State Examination (MMSE) scores. Reliance on this pencil-and-paper psychometric instrument imposes operational burdens and risks of perpetuating health disparities, given the test's known educational and cultural biases. This study evaluates the efficacy of the Digital Clock and Recall (DCR™)-a rapid, FDA-listed digital cognitive assessment-to crosswalk to MMSE scores using machine learning, thereby offering a faster, scalable, and equitable mechanism for patient triage.

Methods: We conducted a retrospective analysis using data from the multi-site Bio-Hermes-001 (BH) study ( …

Serum Protein Signatures For Breast Cancer Detection In Treatment-Naïve African American Women Using Integrated Proteomics And Pattern Analysis, Padma Tadi Uppala, Elmer Rivera, Hyun J. Kwon, Sharon S. Lum

Faculty Publications

Breast cancer is the leading cause of cancer-related mortality in African American (AA) women. In this study we evaluated the serum proteomic profile of AA women with breast cancer using an integrated proteomic framework with multivariate pattern analysis. Using 2D-DIGE, thousands of serum protein spots were detected across 33 gels; 46 spots met criteria for presence, statistical significance, and differential expression. Proteins from the spots were identified by MALDI-TOF/TOF and matched in curated databases, highlighting serum biomarkers including ceruloplasmin, alpha-2-macroglobulin, complement component C3 and C6, alpha-1-antitrypsin, alpha-1B-glycoprotein, alpha-2-HS-glycoprotein and haptoglobin-related protein. LC-MS/MS analysis revealed 163 differentiating peptides after imputing and …

Applications And Challenges Of Utilizing Digital Pathology And Ai-Enabled Workflows In Clinical Trials, Manu Sebastian, Harsh Batra, Monika Lamba Saini, Staci Kearney, Lorcan Sherry, Serge Alexanian, Michael Cohen, William Weber, Joe Lennerz, Anil V Parwani

Faculty, Staff and Student Publications

This is a comprehensive review on current utilization and challenges of digital pathology adoption in clinical trials and aims to provide a broad view on its impact on pathology review processes in clinical trials. It provides an overview of current pathology review practices in clinical trials and unique advantages digital pathology adoption can offer. The key areas including existing workflows, use case scenarios in different disease areas in clinical trials, including but not limited to patient identification and pre-screening, and regulatory aspects have been described with relevance. In addition, the review delves into the integration of genomics, AI, image analysis, …

Interventional Oncology: A Primer For Clinicians On The Role Of Ablation And Embolization For Solid Tumors, Mohamed E Abdelsalam, Kamran Ahrar, Rahul A Sheth, Ketan Y Shah, Steven Yevich, Varshana Gurusamy, Bruno C Odisio, Alda L Tam, Armeen Mahvash, Peiman Habibollahi

Faculty, Staff and Student Publications

Interventional radiology (IR) is a rapidly evolving medical field that combines advanced imaging with minimally invasive techniques for both diagnosis and treatment. Interventional oncology (IO), a subspecialty of IR, focuses on the minimally invasive, image-guided intervention for cancer and cancer-related conditions. IR plays an important and increasingly recognized role within the multidisciplinary care of patients with cancer, contributing meaningfully to diagnosis, therapy, and palliation. IO therapies, particularly tumor ablation and transarterial embolization, aim to target tumors directly while preserving surrounding healthy tissue. These therapies are increasingly supported by clinical guidelines and have shown favorable outcomes in cancers such as hepatocellular …