Biomedical Engineering and Bioengineering Commons^™

Circulating Biomarker Results From A Phase 2 Study Of Seralutinib In Pulmonary Arterial Hypertension, Robin Osterhout, Athénaïs Boucly, Raymond L. Benza, Richard N. Channick, Kelly M. Chin, Robert P. Frantz, Anna R. Hemnes, Luke S. Howard, Vallerie V. Mclaughlin, Olivier Sitbon, Jean-Luc Vachiéry, Rotham T. Zamanian, Richard Aranda, Matt Cravets, Zhaoqing Ding, Thao Duong-Verlé, David Mattola, Robert F. Roscigno, Ravikumar Sitapara, Lawrence S. Zisman, Jean-Marie Bruey, Hossein-Ardeschir Ghofrani

Department of Medicine Faculty Publications

[Introduction] To the Editor: Pulmonary arterial hypertension (PAH) is a progressive disease characterized by obstructive pulmonary arterial remodeling (1). Seralutinib, an investigational inhaled tyrosine kinase inhibitor, potently and selectively targets kinases relevant to PAH pathobiology including platelet-derived growth factor receptors (PDGFR) α and β, colony stimulating factor 1 receptor (CSF1R), and mast/stem cell growth factor receptor kit (c-KIT) (2). In preclinical models, seralutinib improved cardiopulmonary hemodynamics, reversed pulmonary vascular pathology and decreased right ventricular hypertrophy (3). In TORREY, a phase 2, multicenter, double-blind, randomized, placebo-controlled trial in PAH, seralutinib significantly reduced pulmonary vascular resistance (PVR) after 24 weeks with good …

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

Department of Biomedical and Translational Sciences Faculty Publications

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

Computational Methods For Identification Of Molecular Signatures, Weijun Yi

Graduate Theses, Dissertations, and Problem Reports (ETD)

This work develops computational methods for identifying molecular signatures from high-throughput genomic data and for modeling long non-coding RNA (lncRNA) sub-cellular localization. The response of multiple myeloma to CB-6644, a selective RUVBL1/2 complex inhibitor with potential anti-tumor activity, is analyzed to identify drug-responsive pathways and molecular signatures. Conventional gene set enrichment analysis (GSEA) often excludes low-expression genes. Here, phenotype comparison is reformulated as a supervised machine learning problem: genes most informative for discrimination are first selected using a machine learning approach, and GSEA is then applied to these machine-learning derived gene sets. This framework improves detection of CB-6644-associated pathways. For …

Probing Proficiency-Related Neural Representations With Pca And Ica, Onila R. Narayana Mudalige Don

Graduate Student Theses, Dissertations, & Professional Papers

How proficiency-related information is represented in task fMRI depends not only on the data themselves, but on the representational lens used to summarize them. This thesis examines second-language (L2) proficiency as a problem of representational organization rather than as a simple classification exercise. Using task fMRI from adult language learners performing semantic animacy judgments in their native language (L1) and second language (L2), I derive shared low-dimensional network representations with principal component analysis (PCA) and independent component analysis (ICA), then evaluate those representations under matched leakage-controlled decoding pipelines.

Across analyses, the central comparison is between representational frameworks rather than between …

Combination Therapy With Hsp90 Inhibitors And Nanopulse Stimulation Synergistically Impedes Hepatocellular Carcinoma And Breast Cancer Growth In Mice, Christiana Dimitropoulou, Gagan Thangjam, Brittany P. Lassiter, Teresa Hooker, Ruben M. L. Colunga Biancatelli, John D. Catravas, Stephen J. Beebe

Bioelectrics Publications

Nanopulse Stimulation (NPS) represents a promising and innovative therapeutic approach to cancer. Heat shock protein 90 Inhibitors (HI), on the other hand, are currently under investigation in multi-drug chemotherapy trials for various types of malignancies. Here we present results of a combination therapy employing two HSP90 inhibitors (AUY-922 or 17-AAG) and NPS to ablate cancer growth. We firstly tested the inhibitors alone or in combination with NPS in vitro in N1S1 cells, and then into two models of orthotopic Hepatocellular Carcinoma (HCC) and 4T1-Luc breast cancer. NPS + HI reduced tumor growth more than the sum of HI and NPS …

Establishment And Histopathological Characterization Of A Kyse-30 Subcutaneous Xenograft Model Of Esophageal Squamous Cell Carcinoma, Pavel A. Solopov, Alayna Enos, Mantas Silkunas, Giedre Silkuniene, Eleni Zivla, Andrei G. Pakhomov, Olga N. Pakhomova

Bioelectrics Publications

Background/Objectives: Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with poor prognosis and limited treatment options, highlighting the need for reliable preclinical models for translational research. Although xenograft models are widely used in cancer biology, systematic characterization of subcutaneous ESCC models under defined implantation conditions remains limited. The objective of this study was to systematically compare implantation conditions and define histopathological and growth-related parameters that enable reproducible tumor establishment while maintaining a practical experimental window for therapeutic studies. Methods: We established and characterized a subcutaneous ESCC xenograft model using human ESCC cell line KYSE-30 implanted into immunodeficient J:NU mice. …

Nanosecond Pulsed Electric Fields For Extracellular Vesicle Engineering: From Electro-Exocytosis To Cargo Modulation, Art Neal, Teresa Graham, Mohamadmahdi Samandari, Arash Ghorbannia, Anca Dobrian, Stephen J. Beebe, Ruben M. L. Colunga-Biancatelli

Bioelectrics Publications

Extracellular vesicles (EVs), including small extracellular vesicles (sEVs) and medium/large extracellular vesicles (MVs), have emerged as promising therapeutic vectors and diagnostic biomarkers across various branches of biomedicine. However, the clinical translation of EV-based technologies remains constrained by persistent challenges in manufacturing: insufficient yield from primary cell sources, limited control over cargo composition, and the absence of scalable, standardized production platforms. Nanosecond pulsed electric fields (nsPEF) represent an emerging biophysical approach that can address several of these limitations. Unlike conventional electroporation, which targets the plasma membrane using microsecond-to-millisecond pulses, nsPEF delivers ultrashort (1–300 ns), high-amplitude (10–300 kV/cm) pulses that penetrate intracellularly …

Design And Validation Of A Novel Patterned Microfluidic Culture Platform For Hipsc-Cm Maturation, Anisia Gabriela Țiplea

Dartmouth College Master’s Theses

Adult cardiomyocytes (CMs) are among the most challenging cells to culture in vitro, given their poor adherence to plastic culture wells and poor maturation outside the native extracellular matrix (Narkar et al., 2022). Human induced pluripotent stem cell-derived CMs (hiPSC-CMs) offer a viable alternative to study heart development and disease progression. While not comparable to adult CMs in their maturity (Narkar et al., 2022), they mimic the clinical phenotypes of heart failure and are more feasible to culture. Nevertheless, hiPSC-CMs require specialized culture conditions that cannot be achieved with 2D static culturing, which fail to replicate native tissue environments (X. …

Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

Untrained Position-Encoded Multilayer Perceptron Network For Structured Illumination Microscopy Reconstruction, Sahil Sharma, Leonidas Zimianitis, Krishnendu Samanta, Balpreet Singh Ahluwalia, Joby Joseph, Dushan N. Wadduwage

Computer Science Faculty Publications

Structured Illumination Microscopy (SIM) enables super-resolution imaging by encoding high-frequency spatial information through patterned light. While traditional Fourier-based reconstruction methods are prone to artifacts under suboptimal conditions, recent deep learning approaches often require large training datasets and lack adaptability across different imaging setups. In this work, we present Position Encoded Multi-Layer Perceptron (PEM) network that leverages implicit neural representations (INRs) and SIM forward-model-driven modeling to reconstruct super-resolved images without any training data. PEM-SIM represents each spatial coordinate as a combination of sinusoidal functions across multiple frequencies, enabling rich encoding of fine spatial detail. A forward model grounded in SIM image …

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, …

Forcing A Molecule To Switch: Quantifying Mechanical Control At The Atomic Scale, A. M. Shashika D. Wijerathna, Markus Zirnheld, Michael L. Hildebrand, Myles Perry, Marjorie Cenese, Yuan Zhang

Physics Faculty Publications

Mechanically induced conformational switching at the single-molecule level represents a fundamental mechanism for molecular functionality, yet quantitative characterization of the underlying force and energy landscape remains limited. Here, we study individual TBrPP-Co(II) molecules on Au(111) using qPlus atomic force microscopy. By reconstructing interaction potentials from 3D Δf(x,y,z) data, we determine a threshold force of ∼96 ± 8 pN and a tip-induced switching interaction energy of ∼38 ± 4 meV associate with the conformational transition. The isolated tip-molecule force follows a power law (exponent ∼6), indicating dominance of long-range van der Waals interactions. …

Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

There is an increasing necessity for advanced, sustainable, and biocompatible materials for wound healing as therapeutic and diagnostic products. Marine environments, characterized by high biodiversity, offer an underutilized source of natural resources with enormous potential for creating novel materials for dressings. This review highlights the revolutionary nature of polymeric biomaterials of marine origin, with a focus on polysaccharides, like alginate, chitosan, and carrageenan; proteins, such as collagen and gelatin. These biopolymers are outstanding in their physicochemical properties, such as biodegradability, bioactivity, and modifiable mechanical strength, which enable their use in wound-healing systems. Besides, these biomaterials may be easily chemically and …

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 …

Formulation Development Of Topical Inserts Containing Doxycycline And Doxycycline Combined With Tenofovir Alafenamide And Elvitegravir For The Prevention Of Sexually Transmitted Infections, Vivek Agrahari, M. Melissa Peet, Jasmin Monpara, Rijo John, Sriramakamal Jonnalagadda, Pardeep K. Gupta, Meredith R. Clark, Gustavo F. Doncel

CONRAD Publications

Despite advances in oral and injectable HIV prevention options and oral prophylaxis for sexually transmitted infections (STIs) of bacterial origin, there remains a critical need for effective on-demand topical (vaginal and rectal) products for pre- and post-exposure prophylaxis (PrEP and PEP). To fill this gap, we have developed single and first-in-kind multi-active topical inserts for bacterial STIs and HIV/STIs prevention. We have formulated two different inserts, one containing doxycycline (DOX) at 10, 50, and 100 mg doses for bacterial STI prevention, and a multipurpose prevention product (TED insert) that combines DOX (10 mg) with the antiretrovirals tenofovir alafenamide (TAF; 20 …

Effect Of Local Steel Slag Incorporation On The Mechanical Properties Of Concrete, Ahmed Safaa Tariq Karmah, Wissam Khadum Alsaraj, Luma A. Zghair

Al-Esraa University College Journal for Engineering Sciences

The increasing interest in the production of concrete through the utilization of inexpensive materials has caused a rise in the number of studies concerning the use of materials with cementitious properties, such as Silica Fume, Slag, Fly Ash and other pozzolanic materials. Moreover, the increasing amounts of Steel Slag being produced from local factories that are being deposited without an available method of disposal provides an opportunity to harness the Slag in the production of an inexpensive, and possibly better concrete. Slag has been used as both an addition and substitution of the cement and fine aggregate. The mixtures included …

Decoding Climate Change: A Comprehensive Statistical Insight Into Temperature Anomalies In Iraq And Its Neighboring Countries, Jameel T. Al-Naffakha, Mohammed R. Al-Qassabanda, Israa Jafar

Al-Esraa University College Journal for Engineering Sciences

This study applies advanced statistical techniques, including the Mann-Kendall Trend Test and ARIMA forecasting, to validate and predict temperature anomalies across Iraq and its neighboring countries (2014–2024). Findings confirm a statistically significant warming trend (p < 0.00000005) across all nations, with Syria (1.02°C) and Turkey (0.97°C) experiencing the highest anomalies. GIS-based spatial analysis highlights regional disparities, identifying climate-vulnerable zones. The persistent rise in temperature anomalies correlates with worsening water scarcity, desertification, and extreme weather events, including prolonged droughts and heatwaves. Iraq’s peak anomaly (1.48°C) has exacerbated heat stress, agricultural decline, and reduced river inflows, while Kuwait and Saudi Arabia struggle to maintain critical infrastructure under record-breaking temperatures exceeding 50°C. These climate shifts pose severe risks to water availability, food security, and energy demand, necessitating urgent policy interventions. Key recommendations include enhanced water resource management, climate-adaptive agriculture, and renewable energy expansion. If left unaddressed, rising temperatures could destabilize the region, increasing socio-economic vulnerabilities and escalating resource conflicts. This study underscores the need for cross-border collaboration and sustainable adaptation policies to mitigate the long-term impacts of climate change in the Middle East.

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

Applying Machine Learning Techniques For Early Detection Of Cyber Attacks On Iot Devices, Noor Adnan Allamy

Al-Esraa University College Journal for Engineering Sciences

This research designs, implements, and evaluates a machine learning-based framework for the early detection of cyber attacks targeting Internet of Things (IoT) devices, with a specific focus on the context and challenges present in Iraq. The study conducts a comparative analysis of three supervised learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Networks (DNN)—using a combination of benchmark datasets (NSL-KDD, CIC-IDS-2017, Bot-IoT) and a synthesized dataset adapted to simulate the Iraqi threat landscape. Key performance metrics, including accuracy, precision, recall, and F1-score, were used for evaluation. The proposed Random Forest model demonstrated superior performance, achieving an accuracy …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The surrogate …