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Full-Text Articles in Engineering

Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich Jan 2024

Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich

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To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured …

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Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart Jan 2024

Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart

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Deep neural networks have great representational power. However, most deep neural nets today optimize directly for performance on a single task defined only by labeled training data. This excludes potential sources of knowledge and ways of learning which could improve their performance, and address challenges, such as explainability, which are pressing to the field. We propose a framework for neural network architecture which generalizes it to a graph of many semantically-meaningful variables. We call it the Multi-Semantic-Stage Neural Network (MSSNN). An MSSNN models its domain as a web of conditional probabilities, i.e. a collection of inter-related tasks which can learn …

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Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi Jan 2024

Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi

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Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …

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Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson Jan 2024

Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson

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The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and …

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Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki Jan 2024

Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki

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The automated detection of pneumonia through chest X-ray presents a critical challenge in medical diagnostics, particularly due to the restrictions of limited and imbalanced chest X-ray data for training AI models. Traditional methods that depend on softmax confidence scores can be overconfident even when generating erroneous outputs especially when they are processing completely new inputs, leading to unreliable diagnostic results. This research addresses challenges in AI models which aim to develop a robust pneumonia detection system using an Energy-Based Out-of-Distribution (OOD) technique that can work effectively even with limited and imbalanced data. The study focused on creating a more reliable …

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Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith Jan 2024

Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith

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The rapid growth and widespread reliance on machine learning (ML) systems across critical applications such as healthcare, autonomous driving, and cybersecurity have un- derscored their transformative potential and heightened their susceptibility to adversarial attacks and vulnerabilities. This thesis investigates vulnerabilities in ML models, focusing on backdoor attacks, including naive backdoor attack, feature collision backdoor attack, hidden trigger backdoor attack, and test-time backdoor attack using universal perturbation technique. These methodologies demonstrate how adversaries can automate and conceal malicious behaviors to achieve specific objectives, posing significant challenges to ML model integrity and trustworthiness. The research provides a comprehensive analysis of the theoretical …

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Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant Jan 2024

Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant

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This study examines the aging effects of GaN HEMTs, focusing on the CG2H40010 device under conditions that mimic the high-power, high-frequency environments of wireless communication systems. With the increasing adoption of GaN technology in RF applications, understanding its degradation mechanisms under CW stress and modulated signal characterization is essential for predicting device lifetime and ensuring performance standards for modern communication systems. RFALT was employed to stress the device using CW signals, while key performance metrics, such as gain compression, gate leakage, ACP, and EVM, were assessed using W-CDMA signals to replicate real-world dynamic stresses. The findings reveal that CW stress …

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Novel Approaches To Treatment Of Hyperexcitability In Skeletal Muscle, Phillip Vance Walker Ii Jan 2024

Novel Approaches To Treatment Of Hyperexcitability In Skeletal Muscle, Phillip Vance Walker Ii

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Myotonia Congenita (MC) is a rare, inherited ion channelopathy caused by a loss-of-function mutation in the CLCN1 gene. The resulting downregulation of the skeletal muscle chloride channel (ClC-1) results in hyperexcitable skeletal muscle fibers that fire action potentials involuntarily. Patients with MC suffer from debilitating stiffness due to myotonia, described clinically as delayed muscle relaxation following voluntary contraction. Skeletal muscle is a unique system we use in this study to advance our understanding of the pathophysiology underlying MC, and other channelopathies characterized by hyperexcitable cells (i.e., forms of epilepsy and cardiac arrhythmia). Furthermore, re-assessing what makes anti-myotonic drugs such as …

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A Novel In-Vitro Approach To Investigate The Molecular Interaction Between Inhaled Particles And The Human Pulmonary Surfactant System, Bryan Mayville Jan 2024

A Novel In-Vitro Approach To Investigate The Molecular Interaction Between Inhaled Particles And The Human Pulmonary Surfactant System, Bryan Mayville

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The deployment of military personnel to austere environments poses significant pulmonary health risks from inhalation of particulates including sand, dust, pollution, and heavy machinery exhaust. When particles are less than 10 µm in diameter, they can penetrate deep within the alveoli and embed within the protective lung surfactant monolayer. Here, absorption of surfactant lipids to the particle surface disrupts the essential monolayer configuration needed to reduce surface tension and prevent atelectasis, thus leading to disease. Currently, there are no in vitro surfactant-producing lung cell models capable of studying the effects of inhaled particles on the human pulmonary surfactant system. A549 …

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Insights Into Hyperkalemic Periodic Paralysis: Novel Mechanisms And Treatments, Christopher Dupont Jan 2024

Insights Into Hyperkalemic Periodic Paralysis: Novel Mechanisms And Treatments, Christopher Dupont

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Hyperkalemic Periodic Paralysis (hyperKPP) is an inherited channelopathy that leads to incapacitating episodes marked by severe skeletal muscle weakness or total paralysis, often accompanied by muscular stiffness (myotonia). The periods of muscle dysfunction are thought to be caused by the elevation in extracellular potassium (K). This autosomal dominant disorder is associated with mutations in the skeletal muscle voltage-gated sodium channel (Nav1.4). A multitude of inciting factors have been documented, including rest post-exertion, a potassium-rich diet, exposure to cold temperatures, psychological stressors, and fatigue. Given the variability of the triggers and the debilitating manifestation of symptoms, individuals afflicted by hyperKPP have …

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Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell Jan 2024

Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell

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Aerial imagery provides crucial insights for various fields, including remote monitoring, environmental assessment, and autonomous navigation. However, the availability of aerial image datasets is limited due to privacy concerns and imbalanced data distribution, impeding the development of robust deep learning models. While recent text-guided generative models have shown promise in synthesizing high-quality images, they fall short in handling the unique challenges of aerial imagery, including densely packed objects, intricate spatial relationships, and the absence of paired text-aerial image datasets. To tackle these limitations, we propose STARS, a groundbreaking framework for Semantic-aware Text-guided Aerial image Refinement and Synthesis. STARS introduces a …

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Comparative Analysis Of Motoneuronal C-Bouton Structural Alterations In Als And Aging, Shelby Nicole Ward Jan 2024

Comparative Analysis Of Motoneuronal C-Bouton Structural Alterations In Als And Aging, Shelby Nicole Ward

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neuron (MN) death resulting in paralysis and eventually death. ALS has greater prevalence in older populations sharing characteristics with aging like muscle weakness and MN type specific degeneration. MNs innervate skeletal muscles and control muscle contraction through their excitability which is altered in both conditions. C-Boutons are a cholinergic, excitatory synaptic input to MNs and have been studied in ALS and aging but have produced inconsistent findings and undesired gaps. We used immunohistochemistry to label mouse lumbar spinal cord and separate MN types. 60x imaging and automated analysis was …

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Sex-Driven Alterations In Aging Alpha Motoneurons: Exploring Size, Type, Density, And Kv2.1 Channel Expression, Kalin R. Gerber Jan 2024

Sex-Driven Alterations In Aging Alpha Motoneurons: Exploring Size, Type, Density, And Kv2.1 Channel Expression, Kalin R. Gerber

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This research explores how motor neurons (MNs) and Kv2.1 clustering change with age, emphasizing sex differences and MN subtypes. We found that MN density decreases with age in both sexes, while soma size increases in male mice. FF MNs were the most affected, and old weak mice had smaller MNs than their stronger counterparts, underscoring FF MN vulnerability. Baseline studies revealed that FF and FI MNs have larger Kv2.1 clusters compared to FR and S MNs. Female mice had smaller, denser Kv2.1 clusters than male mice, suggesting less clustering in females. With age, Kv2.1 clusters grew larger but became less …

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Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore Jan 2024

Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore

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The digital landscape is ever-evolving. In recent years the amount of bot traffic, traffic generated by autonomous applications over the internet has increased significantly. Many bots perform useful and needed functions, however, malicious bots are known sources of both common and emerging security threats. Denial-of-Services (DoS), information theft, and credential stuffing have all been conducted by malicious software running on unknowingly infected machines. The dichotomy of useful bots operating in the same networks as malicious bots combined with novel bot attacks and an ever-increasing number of personal devices connecting to the Internet drives the need for continued advancement of malicious …

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A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi Jan 2024

A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi

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Semiconductor microelectronics Integrated Circuits (ICs) are increasingly integrated into critical life applications including medical, aerospace, and Internet of things. Their increasing importance as a technology gave rise to critical concerns regarding their security. This has led to the focus of the research community on hardware Trojans, which are malicious modifications to the ICs with undesirable outcomes. Their detection is becoming increasingly critical, with many researchers proposing methods to do so such as reverse engineering, logic testing, and side-channel analysis. Many of these proposals utilize machine learning methods to detect these malicious modifications with high accuracy and confidence. However, machine learning …

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Sarcopenia Is Associated With Osteopenia And Impaired Quality Of Life In Children With Genetic Intrahepatic Cholestatic Liver Disease, Julia Boster, Nathan P. Goodrich, Cathie Spino, Kathleen M. Loomes, Estella M. Alonso, Binita M. Kamath, Ronald J. Sokol, Saul J. Karpen, Alexander Miethke, Benjamin L. Shneider, Jean P. Molleston, Rohit Kohli, Simon P. Horslen, Philip Rosenthal, Pamela L. Valentino, Jeffrey Teckman, Thomas N. Hangartner, Sundaram Shikha Nov 2023

Sarcopenia Is Associated With Osteopenia And Impaired Quality Of Life In Children With Genetic Intrahepatic Cholestatic Liver Disease, Julia Boster, Nathan P. Goodrich, Cathie Spino, Kathleen M. Loomes, Estella M. Alonso, Binita M. Kamath, Ronald J. Sokol, Saul J. Karpen, Alexander Miethke, Benjamin L. Shneider, Jean P. Molleston, Rohit Kohli, Simon P. Horslen, Philip Rosenthal, Pamela L. Valentino, Jeffrey Teckman, Thomas N. Hangartner, Sundaram Shikha

Biomedical, Industrial & Human Factors Engineering Faculty Publications


Background:
Sarcopenia occurs in pediatric chronic liver disease, although the prevalence and contributing factors in genetic intrahepatic cholestasis are not well-described. The objective of this study was to measure muscle mass in school-aged children with genetic intrahepatic cholestasis and assess relationships between sarcopenia, clinical variables, and outcomes.

Methods:
Estimated skeletal muscle mass (eSMM) was calculated on dual-energy x-ray absorptiometry obtained in a Childhood Liver Disease Research Network study of children with bile acid synthesis disorders(BASD) alpha-1 antitrypsin deficiency (a1ATd), chronic intrahepatic cholestasis (CIC), and Alagille syndrome (ALGS). Relationships between eSMM, liver disease, and transplant-free survival were assessed.

Results:
eSMM was …

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Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, October 26, 2023, Wright State University Oct 2023

Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, October 26, 2023, Wright State University

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Abstract Books

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on October 26, 2023.

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Fatigue Behavior Of Cu-Zr Metallic Glasses Under Cyclic Loading, Nikolai Priezjev Sep 2023

Fatigue Behavior Of Cu-Zr Metallic Glasses Under Cyclic Loading, Nikolai Priezjev

Mechanical and Materials Engineering Faculty Publications

The effect of oscillatory shear deformation on the fatigue life, yielding transition, and flow localization in metallic glasses is investigated using molecular dynamics simulations. We study a well-annealed Cu-Zr amorphous alloy subjected to periodic shear at room temperature. We find that upon loading for hundreds of cycles at strain amplitudes just below a critical value, the potential energy at zero strain remains nearly constant and plastic events are highly localized. By contrast, at strain amplitudes above the critical point, the plastic deformation is gradually accumulated upon continued loading until the yielding transition and the formation of a shear band across …

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Morphology And Hemodynamics Of Cerebral Arteries And Aneurysms In A Rare Pair Of Monozygotic Twins, Hang Yi, Zifeng Yang, Luke C. Bramlage, Bryan R. Ludwig Jun 2023

Morphology And Hemodynamics Of Cerebral Arteries And Aneurysms In A Rare Pair Of Monozygotic Twins, Hang Yi, Zifeng Yang, Luke C. Bramlage, Bryan R. Ludwig

Mechanical and Materials Engineering Faculty Publications

In this preliminary study, the underlying pathophysiology mechanisms of cerebral aneurysms (CAs) in monozygotic twins (MTs) were investigated via a rare pair of MTs (twin A and twin B) involving four reconstructed arterial models using preclinical information. First, dimensions and configurated outlines of three-perspective geometries were compared. Adopting an in-vitro validated numerical CA model, hemodynamic characteristics were investigated in the MTs, respectively. Despite expected genetic similarities, morphological comparisons show that configurations of cerebral arteries exhibit significant differences between the twins. The ICA size of twin A is larger than that in twin B (2.23~25.86%), varying with specific locations, attributing to …

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Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita May 2023

Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita

Computer Science and Engineering Faculty Publications

Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnostic codes and procedure reports of patients admitted for heart failure could reveal the clinical phenotypes associated with heart failure and to group patients based on their similar characteristics which could also help in predicting patient outcomes like length of stay. These clinical phenotypes usually have a probabilistic latent structure and hence, as there has been no previous work on identifying phenotypes in clinical notes of heart failure patients …

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A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee Apr 2023

A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee

Computer Science and Engineering Faculty Publications

Engagement is enhanced by the ability to access the state of flow during a task, which is described as a full immersion experience. We report two studies on the efficacy of using physiological data collected from a wearable sensor for the automated prediction of flow. Study 1 took a two-level block design where activities were nested within its participants. A total of five participants were asked to complete 12 tasks that aligned with their interests while wearing the Empatica E4 sensor. This yielded 60 total tasks across the five participants. In a second study representing daily use of the device, …

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Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf Mar 2023

Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf

Computer Science and Engineering Faculty Publications

An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material characterization property as a function of the processing conditions. In thermoelectric materials, the power factor is a measure of how efficiently the material can convert heat to electricity. While earlier works have predicted the material characterization properties of different thermoelectric materials using various techniques, implementation of machine learning models …

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Hemodynamic Investigations In Intracranial Aneurysms: A Commentary, Hang Yi, Mark Johnson, Luke Bramlage, Zifeng Yang, Bryan Ludwig Feb 2023

Hemodynamic Investigations In Intracranial Aneurysms: A Commentary, Hang Yi, Mark Johnson, Luke Bramlage, Zifeng Yang, Bryan Ludwig

Mechanical and Materials Engineering Faculty Publications

Intracranial aneurysms (IAs) are abnormal bulges in a blood vessel in the brain that have a potential to rupture and even causing a stroke, which can lead to lasting brain damage, long-term disability, or even loss of life. It has been widely acknowledged that hemodynamic factors, e.g., instantaneous wall shear stress, time-averaged wall shear stress, wall shear stress gradient, gradient oscillatory number, oscillatory shear index, pulsatile blood flow waveform (flow rate magnitude and shape, physical flow period), relative residence time/turnover time, blood pressure, and vortex (i.e., size, location, and numbers), have a close relationship with the pathobiology (i.e., initiation, growth, …

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Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll Feb 2023

Overcoming Uncertainties In Molecular Visualization, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Uncertainties are difficult if not impossible to avoid. Capturing data from the analog world almost always results in some form of uncertainty. The amount of uncertainty depends on the method of measurement and its accuracy. When visualizing data that has some associated uncertainty, it is essential to properly process and convey such uncertainty and especially the amount of uncertainty keeping in mind that additional processing steps can amplify the uncertainty. There are various sources of uncertainty, such as numerical limitations or limitations of the capture device. However, there are other sources of uncertainty. Some of these uncertainties stem from model …

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Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu Jan 2023

Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu

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The focus of this study was to select triply periodic minimal surface (TPMS) structures made of 3D-printed polymers. The primary variables in this study were: TPMS shape, lattice volume ratio, and lattice material. Vibration absorption was characterized by damping ratio via transmissibility at the system’s natural frequency. The vibration testing was performed using an electro-dynamic shaker, a known mass, an input/control accelerometer, and an output/response accelerometer. The 3D-printed absorber/lattice was mounted to the shaker baseplate and a mass will be mounted on top of the absorber. One accelerometer will be mounted to the shaker baseplate and the other will be …

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Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh Jan 2023

Encryption And Compression Classification Of Internet Of Things Traffic, Mariam Najdat M Saleh

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The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. Increased reliance on IoT raised serious information security concerns. This dissertation presents three systems for analyzing and classifying IoT traffic using Deep Learning (DL) models, and a large dataset is built for systems training and evaluation. The first system studies the effect of combining raw data and engineered features to optimize the classification of encrypted and compressed IoT traffic using Engineered Features Classification (EFC), Raw Data Classification (RDC), and combined Raw Data and Engineered Features Classification (RDEFC) approaches. Our results demonstrate …

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Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha Jan 2023

Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha

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Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …

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Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers Jan 2023

Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers

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Myotonia congenita is an inherited skeletal muscle disorder caused by loss-of-function mutation in the CLCN1 gene. This gene encodes the ClC-1 chloride channel, which is almost exclusively expressed in skeletal muscle where it acts to stabilize the resting membrane potential. Loss of this chloride channel leads to skeletal muscle hyperexcitability, resulting in involuntary muscle action potentials (myotonic discharges) seen clinically as muscle stiffness (myotonia). Stiffness affects the limb and facial muscles, though specific muscle involvement can vary between patients. Interestingly, respiratory distress is not part of this disease despite muscles of respiration such as the diaphragm muscle also carrying this …

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Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Uwe Jan 2023

Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Uwe

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With its incorporation into clinical practice in the early 1980s, the class of pharmacological agents known as calcineurin inhibitors (CNIs) quickly became the cornerstone of immunosuppressive therapy post-organ transplantation. However, its use is limited by irreversible kidney damage in the form of renal fibrosis. The molecular mechanism by which CNIs induce renal fibrosis remains to be better understood, and to date, there are no specific therapeutic strategies to mitigate this damage. This dilemma presents a critical need to explain mechanisms by which CNIs cause renal damage. Kidneys of patients on chronic CNI therapy show increased expression of the proinflammatory cytokine …

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Lipin1 Overexpression Ameliorates The Dystrophic Phenotype In Mdx Mice By Enhancing Myofiber Membrane Integrity, Abdullah Alshudukhi Jan 2023

Lipin1 Overexpression Ameliorates The Dystrophic Phenotype In Mdx Mice By Enhancing Myofiber Membrane Integrity, Abdullah Alshudukhi

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Duchenne muscular dystrophy (DMD) is a severe disease characterized by a progressive muscle fiber loss. DMD affects approximately 1 in 3500 male births worldwide. Patients die at early ages due to failure of respiratory and cardiac functions. DMD is caused by mutations in dystrophin gene. Loss of dystrophin leads to disruption of the membrane integrity and necroptosis in skeletal muscles of DMD patients contributing to muscle fiber loss. Currently, effective therapies for DMD have not been established. The goal of this project is to find mechanisms that may improve muscle function/structure despite dystrophin deficiency. Our data show that the expression …

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