Digital Commons Network^™

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

Statewide Corridor Evacuation Response And Re-Entry Behaviors In Florida During Hurricane Irma, Xin Wang, Yuan Zhu, Hong Yang, Kun Xie

Electrical & Computer Engineering Faculty Publications

Hurricane Irma stands as one of the most destructive tropical storms to make landfall in the United States, particularly impacting the State of Florida, where it prompted the largest evacuation in history with approximately 7 million residents. The profound consequences of mass evacuation underscore the critical need to understand travel behaviors during hurricane evacuation and the recovery process. This research analyzes statewide evacuation and re-entry patterns, leveraging diverse datasets, including TTMS data from main corridors and GIS data. A statewide corridor-based empirical analysis framework is constructed to characterize evacuation and re-entry response patterns using sensor-based traffic observations. The results show …

Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …

Machine Learning Classification Of Prostate Cancer Genomic Sequences Using K-Mer And Sequence-Derived Features, Kuldeep Rawat, Hirendra Nath Banerjee, Jamie Noble, Saa Naudia Deloatch, Satyendra Banerjee, Sachin Shetty, Soumya Banerjee

VMASC Publications

Prostate cancer disproportionately impacts African American men, who experience significantly higher mortality rates and earlier disease onset than other populations. Current diagnostic approaches, including prostate-specific antigen testing and biopsy, lack sufficient specificity and sensitivity, underscoring the need for accurate, molecular-level classification tools. This paper presents a machine learning framework for binary classification of genomic DNA sequences as cancerous or healthy. A dataset of 1684 FASTA-formatted sequences obtained from the National Library of Medicine - GenBank was analyzed, with 1662 sequences retained after quality control filtering. Feature engineering yielded 67 attributes, including GC content, Shannon entropy, sequence length, and trinucleotide k-mer …

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Flexible Cu Nanostructured Laser-Induced Graphene Electrodes For Highly Sensitive And Non-Invasive Lactate Detection In Saliva, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

A scalable and facile fabrication strategy is presented for developing a flexible, nanostructured, non-enzymatic electrochemical sensor for lactate detection based on copper-modified laser-induced graphene (CuNPs/LIG). A one-step electrodeposition process was employed to uniformly decorate the porous LIG framework with copper nanostructures, offering a cost-effective and reproducible approach for constructing enzyme-free sensing platforms. Scanning electron microscopy and energy-dispersive X-ray spectroscopy confirmed dense Cu nanostructure loading and efficient interfacial integration across the conductive LIG surface. The resulting CuNPs/LIG electrode exhibited excellent electrocatalytic performance, achieving a sensitivity of 8.56 μA µM⁻¹ cm⁻² with a low detection limit of 42.65 …

A Scalable Paper-Based Electrochemical Sensor Employing Mwcnts For Isoniazid Detection, Sri Ramulu Torati, Gymama Slaughter

Center for Bioelectronics Publications

Isoniazid (INZ) is an antimicrobial agent that treats tuberculosis by inhibiting the InhA enzyme in Mycobacterium tuberculosis, making sensitive and reliable methods for routine monitoring essential to ensure safe and effective therapy. We report the development of a novel paper-based electrochemical sensor for the sensitive and selective detection of isoniazid. The sensor is constructed using a gold inkjet-printed electrode (GIPE) modified with gold nanoparticles (AuNPs), chitosan (CH), and multi-walled carbon nanotubes (MWCNTs), forming a GIPE/AuNPs/CH/MWCNTs sensor. Electrochemical deposition of AuNPs effectively addressed insulating gaps generated during the sintering of the gold ink, enhancing electrical conductivity and surface uniformity. The …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

A Portable Potentiostat Integrated With A Pt/Zno/Lig Electrode For Non-Enzymatic Glucose Detection, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Continuous glucose monitoring is critical for effective diabetes management; however, conventional benchtop potentiostats are bulky, costly, and unsuitable for decentralized point-of-care (PoC) applications. To address these limitations, this work presents a miniaturized, low-cost electrochemical sensing platform integrating a non-enzymatic glucose sensor with a portable potentiostat. The sensing electrode is based on laser-induced graphene modified with zinc oxide and platinum nanostructures via electrodeposition to enable sensitive glucose detection under physiological conditions. A custom-designed portable potentiostat was developed to control electrode potentials and perform electrochemical measurements, and its performance was experimentally validated against a commercial Metrohm system. Glucose detection was evaluated using …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …

Nanofibrous Materials And Nanoparticles For Combating Antimicrobial Resistance: Synthesis, Integration, And Translational Perspectives, Rewati Raman Ujjwal, Ashish Dilip Sutar, Rahul Shukla, Gymama Slaughter

Center for Bioelectronics Publications

Antimicrobial resistance (AMR) is a major global health challenge driven by mechanisms such as biofilm formation, efflux pumps, and genetic mutations. Nanoparticulate and fibrous materials have emerged as promising strategies to overcome these limitations through multimodal antimicrobial action and controlled drug delivery. This review highlights recent advances in electrospun nanofibrous systems, including natural and synthetic polymer-based scaffolds, stimuli-responsive nanofibers, and functionalized patches. Nanoparticle-loaded nanofiber systems demonstrate enhanced performance, including bacterial eradication, sustained drug release, and significant biofilm disruption. Multifunctional systems combining antimicrobial, antioxidant, and immunomodulatory properties further show synergism. Emerging innovations, such as piezoelectric and smart sensing systems, enable self-powered …

Electrochemical Hemoglobin Biosensors For Point-Of-Care Diagnostics, Ashwini Dantanarayana, Gymama Slaughter

Center for Bioelectronics Publications

Hemoglobin (Hb) and its glycated variant (HbA1c) are essential clinical biomarkers for diagnosing anemia, acute hemorrhage, and long-term glycemic control. The growing demand for decentralized point-of-care (POC) testing has accelerated the development of rapid, inexpensive, and portable electrochemical sensing platforms. These technologies exploit the intrinsic redox activity of the heme prosthetic group, yet achieving efficient direct electron transfer (DET) remains a fundamental challenge because the electroactive iron center is deeply embedded within the globin structure. This review critically examines recent advances in electrochemical Hb sensing, tracing the evolution of electrode architectures from conventional carbon substrates to nanostructured materials, including graphene, …

Leveraging Virtual Reality And Haptics To Teach Surgical Skills: A Usability Study On Retropubic Midurethral Slings, Lauren Siff, Ginger S. Watson, Jerome Dixon, Moshe Feldman, Franklin Bost, Philippe J. Giabbanelli

VMASC Publications

Traditional methods to learn soft-tissue surgical procedures rely on cadaver labs or patient-based learning, which are costly and geographically limited, and raise ethical questions. Virtual reality (VR) with haptic feedback offers a scalable alternative, but most current platforms emphasize bone-based rather than soft-tissue procedures learned by feel. We developed a VR+haptic simulation for preoperative training of retropubic midurethral sling (MUS) surgery. This study examines the usability of this platform with thirteen expert urogynecologic surgeons and subsequently makes improvements (e.g., in haptics) to evaluate the platform with twelve trainees based on the NASA Task Load Index for workload and a UTAUT-informed …

"Queens Of Ghost-Land" 134 Years Later: Un-Masking An Appalachian Witchcraft Accuser, Aine Norris

English Faculty Publications

In 1891, newspapers across America printed a story about witches in the Appalachian Mountains and the alleged powers they possessed to control their small farming community. The article was scathing in accusation and ultimately contributed to continued othering of the women profiled, increasing their visible vulnerabilities of class, gender, and societal status. Despite an implied familiarity with the region, the article was published with initials for its byline, an act that simultaneously identified the author to locals as historian Eva Grant while offering her anonymized national protection as a subject expert. For over five years the accusations were re‐printed in …

Promoting Peer Collaboration Through A Blending Of Synchronous And Asynchronous Technologies In An Engineering Focused Nsf Research Experience For Teachers (Ret) Project, Joseph Brobst, Melani Loney, Imole Samson

Center for Educational Partnerships Publications

This brief paper describes findings drawn from a summer Research Experiences for Teachers project, in which secondary science teachers completed engineering research activities and designed related lessons using the Argument Driven Inquiry (ADI) framework. Teachers participated in a hybrid professional development sequence, engaging with a STEM program manager and each other in-person and through both synchronous online sessions and asynchronous engagement in a shared virtual space. We use a multiple case study approach to describe how interactions within these spaces facilitated peer feedback and informal mentoring and coaching, ultimately strengthening teachers’ lesson plans and leaving them better poised to translate …

Integrating Self-Determination Theory And Continuous Glucose Monitoring: Promoting Youth Development Among Campers With Type 1 Diabetes, Eddie Hill, Bethany Arrington, Taylor Harvey, Alexis Barmoh, Rowan Williams, Laura Hill

Human Movement Studies & Special Education Faculty Publications

The purpose of this cohort study was to evaluate participants’ general self-management and experiences of autonomy while attending diabetes camp using quantitative and qualitative data collection. Through a partnership, an outdoor diabetes camp was designed to assist youth with type 1 diabetes (T1D) in their management. The REACH Teen program conducted a week-long summer camp for youth with T1D. The study was designed through Outcome-Focused Programming grounded in Self-Determination Theory (SDT) to meet campers’ needs of autonomy, competence, and relatedness. Campers participated in outdoor activities and diabetes education designed to increase healthy behaviors. Twenty-three campers completed a 24-item pre- and …

Efficient Preservation Of Old Methane-Derived Organic Carbon In Deep-Sea Surface Sediments, Rui Bao, Yangli Che, Mingzhi Liu, Naiyu Zhang, Yang Zhou, Lihua Dong, Shen Li, Owen A. Sherwood, Min Yu, Zongheng Chen, Shengxiong Yang, Nan Wang, Longhai Zhu, Jiawang Chen, Mutai Bao, Haoshuai Li, Luonan Chen, Weifeng Wu, Haiyue Ma, David J. Burdige

OES Faculty Publications

Methane released from the subseafloor is significantly attenuated during upward migration, yet the preservation of methane-derived organic carbon (OC) in global deep-sea sediments remains poorly understood. Here, we measured carbon isotopes coupled with temperature-ramped analyses on various methane seepage sediments. Our results reveal a correlation between the radiocarbon (¹⁴)C) content in deep-sea surface sediments and sulfate-methane transition depth. Notably, our findings suggest that a substantial amount of (¹⁴)C-depleted OC may originate from deep-seated methane and is efficiently preserved in surface seepage sediments. We propose that the efficient OC preservation is related to microbial-mediated aggregate formation at the seawater-sediment interface, where …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

The Sequence (S) Index As A Marker Of Diminished Step-To-Step Transition Efficiency In Older Adults, Elham Alijanpour, Ashwini Kulkarni, Peter G. Adamczyk, Daniel M. Russell

Rehabilitation Sciences Faculty Publications

Introduction: Age-related declines in walking efficiency are often attributed to musculoskeletal and neuromuscular changes, yet the mechanisms underlying these inefficiencies remain poorly understood. One key contributor is the step-to-step transition (STST), during which the center of mass (CoM) is redirected between limbs. The Sequence (S) index quantifies the temporal overlap between push-off and collision forces during STST, with higher values indicating greater mechanical energy loss. This study investigated whether aging affects STST efficiency, as quantified by the S index, and examined the timing and impulse characteristics underlying observed differences.

Methods: Thirteen young and eleven older healthy adults walked at five …

A Hybrid Cnn-Lstm Surrogate Model For Hyper-Resolution Spatiotemporal Flood Forecasting In Norfolk, Virginia, Yidi Wang, Jonathan L. Goodall, Chetan Kumar, Diana Mcspadden, Sergio A. Barbosa, Binata Roy, Ali Shahabi, Navid Tahvildari

Data Science Faculty Publications

Study region

Norfolk, Virginia, United States

Study focus

Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features.

New hydrologic insights for …

First Displaced Vertex Search For Electroproduced Dark-Sector Strongly Interacting Massive Particles By The Hps Experiment, P. H. Adrian, N. A. Baltzell, M. Battaglieri, M. Bondí, S. Boyarinov, C. Bravo, S. Bueltmann, P. Butti, V. D. Burkert, D. Calvo, T. Cao, M. Carpinelli, A. Celentano, G. Charles, L. Colaneri, W. Cooper, B. Crowe, C. Cuevas, A. D' Angelo, N. Dashyan, M. De Napoli, R. De Vita, A. Deur, M. Diamond, R. Dupre, H. Egiyan, T. Eichlersmith, L. Elouadrhiri, R. Essig, V. Fadeyev, C. Field, A. Filippi, A. Freyberger, S. Gaiser, M. Garçon, N. Gevorgyan, F. X. Girod, N. Graf, M. Graham, K. A. Griffioen, A. Grillo, M. Guidal, R. Herbst, M. Holtrop, J. Jaros, R. P. Johnson, G. Kalicy, M. Khandaker, V. Kubarovsky, E. Leonora, K. Livingston, L. Marsicano, T. Maruyama, S. Mccarty, J. Mccormick, B. Mckinnon, K. Moffeit, O. Moreno, C. Munoz Camacho, T. Nelson, S. Niccolai, A. Odian, R. O'Dwyer, M. Oriunno, M. Osipenko, R. Paremuzyan, S. Paul, E. Peets, N. Randazzo, B. Raydo, B. Reese, A. Rizzo, P. Schuster, Y. G. Sharabian, G. Simi, A. Simonyan, V. Sipala, A. Spellman, D. Sokhan, M. Solt, S. Stepanyan, H. Szumila-Vance, L. Tompkins, N. Toro, S. Uemura, M. Ungaro, H. Voskanyan, L. B. Weinstein, B. Wojtsekhowski

Physics Faculty Publications

The Heavy Photon Search experiment (HPS) is a fixed-target, electron beam experiment designed to search for 𝑒⁺⁢𝑒⁻ mass resonances and displaced decays using a forward acceptance spectrometer. This paper details the search for naturally long-lived “dark” vector mesons (𝑉_𝐷) arising from a dark sector of beyond-Standard-Model strongly interacting massive particles, characterized by a QCD-like 𝑆⁢𝑈⁢(3)_𝐷 symmetry and coupled to the Standard Model photon via a new 𝑈⁢(1)𝐷 gauge interaction mediated by the “heavy photon,” or 𝐴′. The results are based on an integrated luminosity of 10 608  nb⁻¹ collected during the 2016 HPS …

The Xpdirc Concept For Next-Generation Dirc Detectors, R. Dzhygadlo, J. Datta, K. Dehmelt, A. Deshpande, T. K. Hemmick, Md. I. Hossain, C. E. Hyde, Y. Ilieva, G. Kalicy, W. J. Llope, P. Nadel-Turonski, C. Schwarz, J. Schwiening, N. Shankman, J. Stevens, N. Wickramaarachchi, C. Woody

Physics Faculty Publications

The next-generation DIRC (xpDIRC) represents a novel detector geometry concept currently being developed for advanced particle identification systems in high-energy physics experiments. Building upon the high-performance DIRC (hpDIRC) designed for the ePIC detector at the Electron-Ion Collider, the xpDIRC introduces a hybrid optical architecture that combines enhanced focusing optics, a wide plate light guide, and a compact expansion volume. Comprehensive Geant4 simulations demonstrate that the xpDIRC hybrid geometry achieves state-of-the-art performance in π/K separation across the entire range of operation.

Feeding Mode Is Associated With Infant Night Sleep Trajectories During The First Postnatal Year, Magdalena Olson, Li Liu, Elizabeth Reifsnider, Dean V. Coonrod, Sarada S. Panchanathan, Megan E. Petrov, Corrie M. Whisner

Ellmer School of Nursing Faculty Publications

Background: Short sleep and formula feeding during infancy are associated with increased risk of childhood obesity. Feeding practices and sleep arrangements vary during infancy and may also be dynamic, yet their impact on infant night sleep duration remains unclear. Understanding these relationships is crucial for formulating recommendations to support breastfeeding and address sleep concerns. Objective: We examined the association between feeding mode and parent-reported infant night sleep duration during the first postnatal year, while additionally evaluating night-weaning and bedsharing as contextual sleep-related practices. Methods: Infants in the Phoenix Metropolitan Area (n = 193) were followed up at 3, 8, 13, …

Parametric Study Of Yields And Properties Of Corn Stover-Derived Hydrothermal Liquefaction Products By Using Statistical Approaches, Isamu Umeda, Meicen Liu, Jiefu Wang, Yi Zheng, Zhiwu Wang, Jaya Shankar Tumuluru, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PCA) and regression modeling to predict AP solution weight, LBO weight and fuel characteristics, and HTL wastewater biodegradability, as well as to improve prediction accuracy for SR and HBO under various operating conditions (temperature: 250–350 °C, residence time: 5–60 min, and the combined solid loading of three batches: 15–45 g). A complementary relationship between SR and AP weights found in PCA enabled the estimation of AP weight based on …

Physics-Based Multi-Hazard Fragility Modeling Of Low-Rise Wood-Frame Buildings Under Hurricane-Induced Wind And Surge, Mumtasirun Nahar, Abdullah M. Braik, Mohammad Syed, Maria Koliou, Petros Sideris

Civil & Environmental Engineering Faculty Publications

Coastal buildings are exposed to concurrent hurricane-induced wind and storm surge, yet their vulnerability is commonly assessed using separate single-hazard models that neglect hazard interaction. This study developed a physics-based finite element framework to evaluate the performance of a low-rise light wood-frame building under simultaneous wind and surge-wave loading. A detailed three-dimensional model was constructed using a sub-assembly strategy that explicitly represented framing members, sheathing systems, and critical connections. Structural response was evaluated across a hazard space defined by wind speed, still-water depth, and flow velocity, and component- and system-level fragility functions were derived using Monte Carlo simulation and generalized …

Does Bidder Complexity Affect Market Reactions To M&A Decisions?, Rajib Chowdhury, John A. Doukas

Finance Faculty Publications

We examine whether and how bidder complexity influences investor reactions to merger and acquisition (M&A) announcements. Using an established measure of complexity, we find a significant positive relationship between acquiring firm complexity and cumulative abnormal returns (CAR). This suggests that investors perceive more complex firms as capable and value-enhancing participants in M&A activities. The association is particularly strong for bidders with high operating risk, greater R&D intensity, and larger firm size. We also find that complex bidders tend to offer higher takeover premiums. Overall, our study contributes to the literature by demonstrating that bidder complexity is an important determinant of …

Brief Pulses Of High-Level Fluid Shear Stress Enhance Metastatic Potential And Rapidly Alter The Metabolism Of Cancer Cells, Amanda N. Pope, Devon L. Moose, Guy O. Hudson, Hank R. Weresh, Marion R. Dykstra, Aabha Y. Joshi, Patrick Breheny, Eric B. Taylor, Michael D. Henry

Department of Biomedical and Translational Sciences Faculty Publications

Circulating tumor cells (CTCs) face challenges to their survival, including mechanical and oxidative stresses that are different from cancer cells in solid primary and metastatic tumors. The impact of adaptations to the fluid microenvironment of the circulation on the outcome of the metastatic cascade is not well understood. Here, we find that cancer cells exposed to brief pulses of high-level fluid shear stress (FSS) exhibit enhanced invasiveness and anchorage-independent proliferation in vitro and enhanced metastatic colonization/tumor formation in vivo. Cancer cells exposed to FSS rapidly alter their metabolism in a manner that promotes survival by providing energy for cytoskeletal remodeling …

Yk-4-250 Mitigates Gastrointestinal Radiation Syndrome And Promotes Overall Survival Following Partial Body Radiation Injury, Vidya P. Kumar, Yali Kong, Kan Wang, Asa R. Britton-Jenkins, Stanton Dulan, Landon L. Moore, Debra Saunders, Randal May, Rheal Towner, Sanchita P. Ghosh, Courtney W. Houchen, Milton L. Brown

Department of Biomedical and Translational Sciences Faculty Publications

Acute gastrointestinal radiation syndrome (GI-ARS) is a significant health threat following high-dose ionizing radiation (IR) exposure, leading to severe morbidity and mortality. The syndrome is characterized by gastrointestinal tissue damage caused by angiotensin II (Ang II) and reactive oxygen species (ROS), resulting in impaired GI function, systemic bacteremia, multi-organ failure, and eventual death. Dysregulation of the renin-angiotensin system (RAS) via Ang II exacerbates ROS production through activation of the Angiotensin II type 1 receptor (AT1R). This underscores the need for agents capable of both scavenging ROS and inhibiting AT1R activity. To address this, we developed YK-4-250, a Tempol-conjugated angiotensin receptor …

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 …

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, …