Medicine and Health Sciences Commons^™

Epicardial Cryoablation During Cardiopulmonary Bypass In A Pig Survival Model, Federica Serra, Jonathan M. Philpott, Anna Bulysheva, Christian W. Zemlin

Electrical & Computer Engineering Faculty Publications

Objective

Atrial cryolesions are usually created from the endocardium with the heart arrested. Some cardiac surgeons have used cryoablation epicardially during cardiopulmonary bypass, which is convenient because it does not require an incision into the atrial wall. Here, we analyzed the transmurality of epicardial cryoablations created during cardiopulmonary bypass in an arrested heart 30 days after ablation.

Methods

In Yucatan minipigs (n=5), hearts were exposed via sternotomy. Both caval veins were cannulated to collect blood for the cardiopulmonary bypass. Cryolesions were created applying a cryoprobe for 4 minutes per lesion. Hearts were harvested 30 days after the surgery. The transmurality …

Automating The Amino Acid Identification In Elliptical Dichroism Spectrometer With Machine Learning, Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

Electrical & Computer Engineering Faculty Publications

Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis …

Mxene-Based Materials For Enhanced Water Quality: Advances In Remediation Strategies, Ali Mohammad Amani, Milad Abbasi, Atena Najdian, Farzaneh Mohamadpour, Seyed Reza Kasaee, Hesam Kamyab, Shreeshivadasan Chelliapan, Mostafa Shafiee, Lobat Tayebi, Ahmad Vaez, Atefeh Najafian, Ehsan Vafa, Sareh Mosleh-Shirazi

Electrical & Computer Engineering Faculty Publications

Two-dimensional MXenes are promising candidates for water treatment because of their large surface area (e.g., exceeding 1000 m²/g for certain structures), high electrical conductivity (e.g., >1000 S/m), hydrophilicity, and chemical stability. Their strong sorption selectivity and effective reduction capacity, exemplified by heavy metal adsorption efficiencies exceeding 95 % in several studies, coupled with facile surface modification, make them suitable for removing diverse contaminants. Applications include the removal of heavy metals (e.g., achieving >90 % removal of Pb(II)), dye removal (e.g., demonstrating >80 % removal of methylene blue), and radioactive waste elimination. Furthermore, 3D MXene architecture exhibit enhanced performance in antibacterial …

Mxenes In Biosensing: Enhancing Sensitivity And Flexibility - A Review Of Properties, Applications, And Future Directions, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Alireza Jahanbin, Milad Abbasi, Ahmed Vaez, Hesam Kamyab, Lalitha Gnanasekaran, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are a novel type of nanostructured material that has received a lot of attention for their potential applications in bioanalysis owing to their unique features. These materials, made from transition metal nitrides, carbides, or carbonitrides, have a number of advantages, including high hydrophilicity, a large surface area, strong metallic conductivity, superior ion transport capabilities, biocompatibility, and low diffusion barriers. Their surfaces are easily manipulated, making them more adaptable for a variety of applications, including biosensing. The outstanding properties of MXenes have attracted researchers of different fields, including renewable energy, fuel cells, supercapacitors, electronics, and catalysis. In the context of …

Incorporating Insulin Into Alginate-Chitosan 3d-Printed Scaffolds: A Comprehensive Study On Structure, Mechanics, And Biocompatibility For Cartilage Tissue Engineering, Afsaneh Jahani, Mohammad Sagdegh Nourbakhsh, Ali Moradi, Marzieh Mohammadi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Osteoarthritis is a leading cause of disability worldwide, challenging current treatments to limited cartilage self-healing capacity. Cartilage tissue engineering (CTE) integrates cells, scaffolds, and signaling molecules, with Insulin being utilized as a differentiation biomolecule due to cost-effectiveness, dose-dependent influence on chondrogenesis, suitable biological activity, and ability to activate relevant receptors. Yet, administering differentiation biomolecules through conventional scaffolds poses a persistent challenge. Alginate (Alg) is commonly employed in CTE for its biocompatibility, though it lacks sufficient mechanical properties. Chitosan (Cs), while enhancing scaffold mechanical properties, but does not independently provide optimal support for chondrogenesis. While Alg-Cs scaffolds have garnered attention, challenges …

Differentiating Opioid Use Disorder From Healthy Controls Via Ml Analysis Of Rs-Fmri Networks, Ahmed Temtam, Megan A. Witherow, Liangsuo Ma, M. Shibly Sadique, F. Gerard Moeller, C. Kenneth, Dianne Wright, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping …

Obesity Prediction From Structural Mri Using Conformal Deep Learning With Uncertainty Quantification, W. Farzana, A. G. A. Temtam, B. Humud-Arboleda, L. Ma, M. Bean, F. Gerard Moeller, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Obesity arises from a neurobehavioral disorder in which the brain’s regulation of hunger and food intake is impaired, leading to an imbalance between energy consumption and expenditure. One key phenotype associated with obesity is body mass index (BMI). BMI is influenced by multiple causal pathways driven by behavioral, metabolic, and genetic factors. Traditional obesity prediction studies often rely on magnetic resonance imaging (MRI) voxel-based morphometry to correlate BMI with obesity-related clinical measurements and brain structure, predominantly gray matter volume (GMV). However, the altered brain regions are variable and widespread between studies, with some literature presenting contradictory results between BMI and …

Personalized Prediction Of Tumor Recurrence With Image-Guided Physics-Informed Computational Model In High-Grade Gliomas, Walia Farzana, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

High grade gliomas are infiltrating tumors characterized by their diffusive invasion and proliferative growth. Across and within patients heterogeneity of tumors makes it challenging to determine tumor spatial extent after surgical resection. Traditionally, tumor growth predictions after surgical resections rely on generalized models and population-based observations, which do not account for individual patient differences. To address this gap, we propose a personalized approach with image-guided computational model (digital twin) that incorporates physics-based modeling to predict tumor recurrence. Our digital twin involves an inverse modeling step, followed by a recurrence model that accounts for varying surgical effects. The physics-guided inverse model …

Key Brain Region Identification In Obesity Prediction With Structural Mri And Probabilistic Uncertainty Aware Model, Walia Farzana, Megan A. Witherow, Ahmed Temtam, Liangsuo Ma, Melanie Bean, F. Gerry Moeller, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: Predictive performance alone may not determine a model’s clinical utility. Neurobiological changes in obesity alter brain structures, but traditional voxel-based morphometry is limited to group-level analysis. We propose a probabilistic model with uncertainty heatmaps to improve interpretability and personalized prediction. Methods/Study Population: The data for this study are sourced from the Human Connectome Project (HCP), with approval from the Washington University in St. Louis Institutional Review Board. We preprocessed raw T1-weighted structural MRI scans from 525 patients using an automated pipeline. The dataset is divided into training (357 cases), calibration (63 cases), and testing (105 cases). Our probabilistic model …

A Fast Framework For Generating Radioactive Mixture Spectra And Its Application To Remote High-Performance Mixture Identification, Chiman Kwan, Bulent Ayhan, Adam Stavola, Kazi Aminul Islam, Hongfang Zhang, Jiang Li

Electrical & Computer Engineering Faculty Publications

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

Targeting Bone In Cancer Therapy: Advances And Challenges Of Bisphosphonate-Based Drug Delivery Systems, Fariba Ganji, Mohammadmahdi Eshaghi, Hossein Shaki, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: Bisphosphonates (BPs) are well-known for their strong affinity toward bone mineral matrices and are widely used to inhibit excessive osteoclast activity associated with various bone disorders. Beyond their clinical use, their unique bone-targeting capability has positioned them as promising ligands for drug delivery systems aimed at treating bone-related cancers. Approach: The review analyses published studies on BP-functionalized drug delivery systems, including direct drug conjugates, calcium-based nanomaterials, carbon-based nanostructures, and self-assembling systems such as micelles and liposomes. In vitro assays (e.g. hydroxyapatite binding, cell viability) and in vivo biodistribution studies are discussed to evaluate targeting efficiency and …

Detecting Sars-Cov-2 In Ct Scans Using Vision Transformer And Graph Neural Network, Kamorudeen Amuda, Almustapha Wakili, Tomilade Amoo, Lukman Agbetu, Qianlong Wang, Jinjuan Feng

Electrical & Computer Engineering Faculty Publications

The COVID-19 pandemic has presented significant challenges to global healthcare, bringing out the urgent need for reliable diagnostic tools. Computed Tomography (CT) scans have proven instrumental in detecting COVID-19-induced lung abnormalities. This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. Using the strength of CNN and GNN to capture complex relational structures and the ViT capacity to classify global contexts, ViTGNN achieves a comprehensive representation of CT scan data. The model was …

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …

High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Accurate and efficient prediction of lithium-ion battery state of health (SOH) is critical for ensuring reliability in electric vehicles, grid storage, and aerospace systems. Traditional SOH estimation methods often struggle with nonlinear degradation behaviors and lack sensitivity to subtle electrochemical signals, limiting their real-world deployment. To address these challenges, this study examines hybrid deep learning models that integrate differential capacity (dQ/dV) analysis to enhance predictive accuracy. Four hybrid architectures - hybrid CNN-LSTM multihead, CNN extractor for LSTM, DNN-LSTM, and DNN Bi-LSTM - were developed and evaluated using the NASA randomized battery usage dataset, offering a realistic benchmark under diverse operational …

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …

A Customized Large Single-Piece Bifrontal Implant For Post-Craniectomy Defect Reconstruction: A Case Study, Omid Ghaderzadeh, Ehsan Amirbeyk, Seyed Roholah Ghodsi, Zahra Namazi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background: Large bifrontal defects pose unique reconstruction challenges due to their complex curvature and mechanical requirements. This case demonstrated how computer-aided design/manufacturing (CAD/CAM) enabled precise single-piece polymethyl methacrylate (PMMA) implant fabrication, thereby overcoming traditional limitations. Case presentation: A 25-year-old male who had undergone bifrontal decompressive craniectomy suffered a severe traumatic brain injury. The autologous bone flap had been temporarily stored in a subcutaneous fat area of the abdomen for 3 months to preserve its viability. A secondary cranioplasty was then performed using titanium miniplates and self-tapping screws for final fixation. After 2 years, the patient developed empyema and a brain …

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

A Worker's Struggle, Sakan Binte Imran, Shadman Mahmood Khan Pathan

Electrical & Computer Engineering Faculty Publications

[Introduction] The casualty department at Sir Salimullah Medical College Mitford Hospital was crowded, as it always was. The air smelled of antiseptics, and hurried footsteps echoed through the narrow corridors. It was another day of internship, and I had just finished checking on a patient when a nurse called me over.

“There’s a new case in Trauma. Factory worker. Severe hand injury.”

I hurried over and found a man sitting on the examination table. His face was pale, and his forehead was glistening with sweat. His right hand was wrapped in a blood-soaked cloth. His left hand trembled as he …

Novel Micro-And Nanoformulations Of Paclitaxel For Targeting Metastatic Breast, Non-Small Cell Lung, And Pancreatic Cancers, Lobat Tayebi, Mehran Alavi

Electrical & Computer Engineering Faculty Publications

Nonlinear pharmacokinetics resulting from high lipophilic and low oral bioavailability, and hypersensitivity reactions and hyperlipidemia caused by formulation by Cremophor EL have limited clinical effectiveness of paclitaxel (Taxol). In this way, there is the critical necessity of innovative drug delivery systems (DDSs) to mitigate severe side effects and overcome clinical limitations of paclitaxel. In recent years, various micro- and nanoformulations, specifically polymeric nanoparticles (NPs) and lipid NPs, have been presented and approved by the Food and Drug Administration (FDA). In addition, other nanoformulations, such as polymeric nanoparticles (NPs), micelles, liposomes, and mesoporous silica nanoparticles, have shown promising results in vitro …

Cellax Nanoparticles: Taxane Nanoformulations For Solid Tumor Targeting, Lobat Tayebi, Mehran Alavi

Electrical & Computer Engineering Faculty Publications

Nanoparticles (NPs), specifically polymer-modified NPs, have illustrated unique therapeutic advantages compared to bulk materials. Cellax NPs have provided a promising approach to cancer therapy by improving drug delivery, targeting the tumor microenvironment, and potentially overcoming drug resistance, all while reducing overall toxicity compared to traditional taxane treatment. By the flash nanoprecipitation (FNP) method, docetaxel and cabazitaxel have been formulated with polyethylene glycol (PEG) modified-acetylated carboxymethylcellulose (CMC) polymer to increase biocompatibility, bioavailability, specific targeting, and modulate the tumor microenvironment. However, there are some challenges and clinical limitations related to this formulation, encompassing optimum targeted delivery to tumors, overcoming biological barriers, such …

Enhancing Channel Data Savings And Information Transfer Efficiency In Ultrasound Imaging, Sai Konda, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Ultrasound is a popular imaging technique mainly due to its non-invasive nature. And so, it is being used in a variety of applications. Due to plane wave imaging technique in ultrasound, frame rate of ultrasound imaging has the potential for being very high. Due to which, many channel data frames are being generated within a few seconds. As a result, tasks such as storing data frames and transferring them from front end ultrasonic system to processing computers are presenting significant challenges. Our current research work minimized these issues. We proposed and implemented: (a) Data encoding technique - We combined every …

An Overview Of Video Game Biometrics Collection And Considerations For Cyberbiosecurity, Lucas Potter, Christen Westberry, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Over the past fifty years, the global cost of consumer electronics has significantly decreased, leading to greater accessibility to both biosensing systems and interactive entertainment platforms. This increased access has naturally resulted in higher usage of medical and entertainment electronics. However, the intersection of these technologies, combined with invasive data harvesting practices, has raised concerns about the potential misuse of biological signals to manipulate individuals' behavior both within and beyond the video game environment. Currently, biometric data in video games are employed in various ways, such as using Heart Rate Variability (HRV) as a performance metric and integrating eye tracking …

Differences In Prescription Drug Misuse Among U.S. Adults With And Without Disabilities, Jeanette M. Garcia, Samantha M. Ross-Cypcar, Justin A. Haegele

Human Movement Studies & Special Education Faculty Publications

Introduction

Increasing evidence suggests that adults with disabilities have higher rates of drug misuse compared to adults without disabilities, however; there is limited information on rates of commonly misused prescription drugs (e.g., stimulants, opioids, tranquilizers) to quantify the magnitude of this disparity. Thus, the purpose of this cross-sectional study is to examine and compare prevalence rates of prescription drug misuse by disability status and age group in a national sample of U.S. adults.

Methods

Data (n=47,100 adults) from the 2021 National Survey on Drug Use and Health was stratified by age group: 1) 18-29 years; 2) 30-49 years; 3) 50 …

Development Of A Personalized Conversational Health Agent To Enhance Physical Activity For Blind And Low-Vision Individuals, Soyoung Choi, Jooyoung Seo, Ashwath Krishnan, Sanchita Kamath, Justin Haegele

Human Movement Studies & Special Education Faculty Publications

Background: With the advancements in mobile health (mHealth) technologies, sighted individuals can benefit from mobile apps and wearable devices to more easily manage their physical activity (PA) and wellness data through intuitive touch gestures and effective data visualizations. However, for blind and low-vision (BLV) individuals, these conventional interaction methods are often challenging, not only limiting their ability to use these technologies but also potentially diminishing their motivation to adopt them to support health-promoting behaviors. We aimed to develop a health monitoring application called Personalized and Conversational Health Agent (PCHA) that supports BLV individuals with self-monitoring and management of their PA …

Comparative Effectiveness Of High-Intensity Interval Training And Moderate-Intensity Continuous Training On Cardiometabolic Health In Patients With Diabesity: A Systematic Review And Meta-Analysis Of Randomized Controlled Trials, Sameer Badri Al-Mhanna, Eric Tsz-Chun Poon, Barry A. Franklin, Mark A. Tarnopolsky, John A. Hawley, John M. Jakicic, Emmanuel Stamatakis, Jonathan P. Little, Linda S. Pescatello, Deborah Riebe, Walter R. Thompon, James S. Skinner, Sheri R. Colberg, Jonathan K. Ehrman, George S. Metsios, Helen T. Douda, Norsuhana Omar, Abdullah F. Alghannam, Alexios Batrakoulis

Human Movement Studies & Special Education Faculty Publications

Objective

To evaluate the effects of high-intensity interval training (HIIT) on cardiometabolic health-related outcomes in patients with type 2 diabetes mellitus and concurrent overweight/obesity (diabesity).

Design

Systematic review and meta-analysis of randomized controlled trials (RCTs).

Data sources

PubMed, Web of Science, Scopus, Science Direct, Cochrane Library, and Google Scholar databases were searched from inception up to January 31, 2025.

Eligibility criteria for selected studies

RCTs comparing HIIT alone ≥ 2 weeks in duration with moderate-intensity continuous training (MICT). Participants were adults with diabesity.

Results

A total of 26 RCTs qualified, involving 790 patients (50/50 female/male ratio; age: 59.8 ± 12.9 …

Autistic Young Adults' Experiences And Recommendations For Strength Training, Ashlyn Barry, Justin A. Haegele, Daniel Schaefer, Kristen A. Pickett, Luis Columna

Human Movement Studies & Special Education Faculty Publications

Strength training can be a beneficial form of physical activity (PA), but little research has examined how autistic individuals experience it or what makes programs accessible and supportive. Therefore, the purpose of this study was twofold: (1) to explore autistic young adults’ experiences with strength training, and (2) examine their recommendations for designing programs that meet their needs. Thirteen autistic young adults (ages 22–25) participated in semi-structured interviews about their strength training experiences and preferences for program design. A qualitative descriptive approach with a constructivist lens guided reflexive analysis. Participants described key factors that influenced their participation in strength training, …

The Efficacy Of Physical Activity Or Exercise Among Individuals With Cerebral Palsy: An Umbrella Review Of Systematic Reviews, Majed M. Alhumaid, Faris Yahya I. Asiri, Mohamed A. Said, Justin A. Haegele

Human Movement Studies & Special Education Faculty Publications

Introduction

Cerebral palsy (CP) is the most common childhood disability, affecting 1.5-3 per 1000 live births. Physical exercises have been shown to improve muscle and limb outcomes in CP. This systematic review critically appraises existing systematic reviews on the effects of physical activity and exercise on physical, functional, and psychosocial outcomes in individuals with CP compared to those without.

Methods

Using a PICO framework, the question was: In patients with CP, do physical activity and exercise improve muscle- and limb-related outcomes compared to no intervention or usual care? PubMed, Cochrane, ISI Web of Science, and Embase were searched for systematic …

Impact Of Aerobic Exercise On Cardiometabolic Health In Patients With Diabesity: A Systematic Review And Meta-Analysis Of Randomized Controlled Trials, Sameer Badri Al-Mhanna, Barry A. Franklin, John M. Jakicic, Emmanuel Stamatakis, Linda S. Pescatello, Deborah Riebe, Walter R. Thompson, James S. Skinner, Sheri R. Colberg, Jonathan K. Ehrman, George S. Metsios, Norsuhana Omar, Nouf H. Alkhamees, Bodor Bin Sheeha, Abdullah F. Alghannam, Alexios Batrakoulis

Human Movement Studies & Special Education Faculty Publications

Purpose

This systematic review and meta-analysis of randomized controlled trials (RCTs) aimed to evaluate the effects of aerobic exercise on cardiometabolic health-related indices in patients with type 2 diabetes and concurrent overweight/obesity (diabesity).

Methods

PubMed, Web of Science, Scopus, Science Direct, Cochrane Library, and Google Scholar databases were searched from inception to October 2024. The search strategy included the following keywords: diabetes, aerobic exercise, and endurance training. RCTs comparing aerobic exercise training ≥2 weeks in duration to standard treatment were considered eligible. Participants were adults with diabesity.

Results

A total of 1391 middle-aged/older adult patients (55 % females) were included …

Impact Of High-Intensity Interval Training On Cardiometabolic Health In Patients With Diabesity: A Systematic Review And Meta-Analysis Of Randomized Controlled Trials, Sameer Badri Al-Mhanna, Barry A. Franklin, Mark A. Tarnopolsky, John A. Hawley, John M. Jakicic, Emmanuel Stamatakis, Jonathan P. Little, Linda S. Pescatello, Deborah Riebe, Walter R. Thompson, James S. Skinner, Sheri R. Colberg, Jonathan K. Ehrman, George S. Metsios, Helen T. Douda, Norsuhana Omar, Abdullah F. Alghannam, Alexios Batrakoulis

Human Movement Studies & Special Education Faculty Publications

Aims This systematic review and meta-analysis aimed to evaluate the effects of high-intensity interval training (HIIT) on cardiometabolic health-related outcomes in patients with type 2 diabetes and obesity (diabesity).

Methods PubMed, Web of Science, Scopus, Science Direct, Cochrane Library, and Google Scholar databases were searched from inception up to November 2024. The search strategy encompassed the following keywords: diabetes, obesity, and HIIT. Randomized controlled trials (RCTs) recruiting adult participants with diabesity and comparing HIIT per se for ≥ 2 weeks in duration with non-exercise standard treatment were included.

Results A total of 18 RCTs qualified involving 504 patients (52/48 women/men …

Zika Virus Modulates Arthropod Histone Methylation For Its Survival In Mosquito Cells, Telvin Harrell

Biological Sciences Faculty Publications

Zika virus (ZIKV) is a mosquito-borne human pathogen that causes mild febrile illness in adults and severe neurological complications and microcephaly in newborns. Studies have reported that ZIKV modulates methylation of human and viral RNA critical for its replication in vertebrate cells. In this study, we show that ZIKV modulates mosquito S-adenosyl methionine (SAMe)-synthase, an enzyme involved in the production of SAMe (methyl donor), and histone methylation for its survival in mosquito cells. Reverse transcription quantitative PCR followed by immunoblotting analysis showed increased amounts of SAMe synthase at both RNA and protein levels, respectively, in C6/36 mosquito cells infected with …