Medicine and Health Sciences Commons^™

Fibrinolysis For Apical Thrombus As A Bridge To Emergent Valve-In-Valve Transcatheter Aortic Valve Replacement, Nicholas J. Valle, Omar A. Saleh, Mani C. Akunuri, Parth K. Parikh, Joshua A. Cohen, Deepak R. Talreja, Matthew R. Summers

Department of Medicine Faculty Publications

Background

Left ventricular (LV) thrombus is traditionally a contraindication to transcatheter aortic valve replacement due to embolic risk. Consequently, management of valvular cardiogenic shock complicated by LV thrombus identifies unique challenges that require innovative strategies.

Case Summary

A 58-year-old woman with critical bioprosthetic aortic stenosis, cardiogenic shock, and large LV thrombus (2.8 × 2.6 cm) underwent successful valve-in-valve transcatheter aortic valve replacement after systemic fibrinolysis bridge therapy.

Why Beyond the Guidelines

Current guidelines contraindicate transcatheter aortic valve replacement in patients with LV thrombus. This case demonstrates the novel use of low-dose, slow infusion tissue plasminogen activator as a bridge therapy …

Cardiomyopathies Of Endocrine Origin: A State-Of-The-Art Review, Jenyfer M. Fuentes-Mendoza, Marcio J. Concepción-Zavaleta, Juan C. Morón-Siguas, Juan M. Muñoz-Moreno, Aranza I. Pérez-Reyes, Rodrigo Martinez-Galaviz, Raúl D. Aguilar-Castañeda, Oziel González-Godoy, Luis A. Concepción-Urteaga, José Paz-Ibarra

Department of Medicine Faculty Publications

Endocrine disorders are increasingly recognized as potentially reversible causes of secondary cardiomyopathies, yet they often remain underdiagnosed in clinical practice. These conditions-including thyroid dysfunction, acromegaly, pheochromocytoma, diabetes mellitus, adrenal disorders, among others-can significantly alter cardiac structure and function through hormonal excess, metabolic remodeling, and neurohumoral activation. Hyperthyroidism may lead to high-output heart failure (HF) and atrial fibrillation, while hypothyroidism is associated with diastolic dysfunction, pericardial effusion, and accelerated atherosclerosis. Acromegaly promotes biventricular hypertrophy and myocardial fibrosis via insulin-like growth factor 1 overproduction. Pheochromocytoma triggers catecholamine-induced cardiomyopathy, resembling Takotsubo syndrome and carrying a high risk of mortality if left untreated. Diabetes …

Diverticulitis—New Evidence To Share With Patients, Nicholas B. D'Alessandro, Tarun Vippa, Edward C. Oldfield Iv, David A. Johnson

Department of Medicine Faculty Publications

Diverticulitis is one of the most common gastrointestinal causes of hospitalization in Western society. While previously characterized as a disease of older patients, new literature highlights an increasing incidence among the younger population. Over the past few decades, the understanding of etiology and management of diverticulitis has changed drastically. New data refute past beliefs while promoting other novel recommendations to mitigate incidence and subsequent complications. Data now confirms the safety and possible protective benefit of particulate food, while highlighting evidence-based approaches for the use of diagnostic imaging and antibiotics. We recognize modifiable and non-modifiable risk factors that are commonly seen …

Micro/Nanoplastics And Cancer: Focus On Gastrointestinal Malignancies - A Narrative Review, Sana Rabeeah, Priyata Dutta, Ahmad Mahdi, Alejandra Vargas, Edward C. Oldfield, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are plastic particles smaller than 5 mm and 1 μm, respectively, and are emerging environmental pollutants with growing implications for human health. These particles stem from either 'primary sources', such as intentionally manufactured microbeads and industrial abrasives, or 'secondary sources', where larger plastic items break down into smaller fragments over time. Human exposure primarily occurs through ingestion and inhalation, with contaminated seafood and plastic-laden food packaging representing key routes of entry. Once ingested, MNPs can cross the intestinal barrier, accumulate in gastrointestinal (GI) tissues, and trigger biological responses. Mechanistic studies reveal that MNPs induce oxidative stress, …

Blunt Trauma Causing Thrombotic Occlusive Myocardial Infarction, Jace Bradshaw, Alleabelle Bradshaw, Rishab Agarwal, P. Logan Weygandt

Department of Medicine Faculty Publications

Introduction: Traumatic myocardial infarction (TMI) is a rare but serious complication of blunt chest trauma, typically arising from coronary artery dissection, intramural hematoma, or myocardial contusion. Early recognition and intervention are critical, but diagnosis can be challenging given the broad differential for chest pain in trauma patients.

Case presentation: A 66-year-old female presented to a quaternary academic emergency department after a motor vehicle collision with progressive chest pain. Initial electrocardiogram (ECG) showed hyperacute T-waves in lead III, ST depression with T-wave inversion in aVL, and ST depression in V2, with posterior leads revealing ST elevation in V7–V9. Trauma imaging ruled …

Prevalence Of Electrocardiographic Changes And Risk Factors For Qtc Prolongation Among Steady State Sickle Cell Disease Patients: Cooperative Study Of Sickle Cell Disease, Mohammed B. Nawaiseh, Rund R. Haddadin, Yara B. Nawaiseh, Mohammad Z. Salameh, Abdallah A. Shurman, Osama Abu-Shawer, Asma I. Aljesrawi, Ibrahim A. Abuelbeh, Allaa Roto, Hadil Zureigat, Lana Mango, Munir Q. Zaqqa, Hanna K. Al-Makhamreh, Nakhleh Abu-Yaghi

Department of Medicine Faculty Publications

Objectives: Sickle cell disease (SCD) is associated with several cardiovascular adverse events. Corrected QT (QTc) interval prolongation is one of the potential life-threatening complications that predispose patients to sudden cardiac death. This study aims to assess the prevalence of electrocardiogram (ECG) changes and to investigate risk factors associated with increased propensity of QTc prolongation. Methods: This study utilized data from the Cooperative Study of Sickle Cell Disease Cardiac Ancillary Study. QT intervals were corrected using the Bazett formula, and prolongation was defined using sex-specific thresholds. The study population included African American patients with steady-state SCD across four clinical centers located …

Does Mean Arterial Pressure Augmentation Improve Neurological Recovery Of Blunt Spinal Cord Injuries: An East Multicenter Trial., Aimee Lariccia, Stephanie Doris, Bhairav Shah, Tanisha Kashikar, Erik Teicher, Lindsey Perea, Jennifer Huber, Malia Eischen, H Akin Erol, Michael Steven Farrell, Lauren Colom, Stephanie Scott, Brian Daley, James Bardes, Gregory Schaefer, Melissa Moncrief, William Devoe, Ryan Peter Dumas, Caitlin Anne Fitzgerald, William Brigode, John D Berne, Dalier R Mederos, Scott Armen, Melissa Linskey Dougherty, Asanthi Ratnasekera, Emily Alberto, Alison Smith, Bradley M Dennis, Stephen Gadomski, Jeffry Nahmias, Claudia Alvarez, Salina Wydo, Jennifer Schweinsburg, Carlos H Palacio, M Chance Spalding, Joshua Hill

Trauma and Acute Care Articles

BACKGROUND: Treatment of blunt traumatic spinal cord injuries (SCIs) often includes maintaining elevated mean arterial blood pressures (MAP) to enhance perfusion to the spinal cord. Optimal hyperperfusion protocols and treatment algorithms have yet to be delineated due to a paucity of large volume prospective studies. This study aims to identify predictors of neurological improvement in American Spinal Injury Association (ASIA) impairment score following blunt SCI.

STUDY DESIGN: Prospective (January 10, 2021 to June 1, 2023) multicenter study included blunt SCI patients age >18 with complete neurological examination documented on hospital arrival. Patients were divided into two groups: neurological improvement and …

The Pre-Polarization And Concentration Of Cells Near Micro-Electrodes Using Ac Electric Fields Enhances The Electrical Cell Lysis In A Sessile Drop, Kishor Kaphle, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell lysis is the starting step of many biomedical assays. Electric field-based cell lysis is widely used in many applications, including point-of-care (POC) applications, because it provides an easy one-step solution. Many electric field-based lysis methods utilize micro-electrodes to apply short electric pulses across cells. Unfortunately, these cell lysis devices produce relatively low cell lysis efficiency as electric fields do not reach a significant portion of cells in the sample. Additionally, the utility of syringe pumps for flow cells in and out of the microfluidics channel causes cell loss and low throughput cell lysis. To address these critical issues, we …

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 …