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Articles 1 - 30 of 42
Full-Text Articles in Engineering
Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu
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 …
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 …
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, Danielle D. Hollon
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, Danielle D. Hollon
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Icing, or the formation of ice from water via freezing or water vapor via desublimation, is a phenomenon that commonly occurs within air cycle-based refrigeration systems and requires thermal control that limits system performance. In aircraft applications icing frequently occurs in the heat exchangers and turbine(s) that are part of the air cycle machine, the refrigeration unit of the environmental control system. Traditionally, water vapor is removed from an air cycle machine via condensing in a heat exchanger and subsequent high-pressure water separation. This approach is not capable of removing all of the vapor present at low altitude conditions, corresponding …
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
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Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
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Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …
Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Ume
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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 …
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
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Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
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Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
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Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …
Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung
Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung
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Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …
Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger
Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger
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Direct write printing, which is part of additive manufacturing (AM) technology, offers unique capabilities that can complement traditional methods of electronics fabrication. Printing of electrical interconnects via aerosolization is one of the areas in AM that is very important in electronics fabrication. Post-print sintering is a critical step in printed electrical interconnects because it strongly influences the electrical resistivity of the interconnects. Interconnects require the lowest possible resistivity to achieve better performance. Thermal sintering is the most common technique employed in printed interconnects. However, it is limited to substrates that can handle the high temperature requirement for sintering. For polymers …
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
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 …
Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal
Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal
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Since their invention in 1958, Integrated Circuits (ICs) have become increasingly more complex, sophisticated, and useful. As a result, they have worked their way into every aspect of our lives, for example: personal electronic devices, wearable electronics, biomedical sensors, autonomous driving cars, military and defense applications, and artificial intelligence, to name some areas of applications. These examples represent both collectively, and sometimes individually, multi-trillion-dollar markets. However, further development of ICs has been predicted to encounter a performance bottleneck as the mainstream silicon industry, approaches its physical limits. The state-of-the-art of today’s ICs technology will be soon below 3nm. At such …
Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando
Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando
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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …
Processing And Characterization Of Inkjet Printed Batio3/Su-8 Nanocomposite Dielectrics, Mustapha A. Muhammad
Processing And Characterization Of Inkjet Printed Batio3/Su-8 Nanocomposite Dielectrics, Mustapha A. Muhammad
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The persistent demand for flexible and wearable electronic components in healthcare, aerospace, media, and transit applications has led to a significant shift from traditional electronics processes to printed electronics. Printed electronics are anticipated to establish itself as the industry's dominant force due to their enhanced flexibility, rapid prototyping capabilities, and seamless integration with everyday objects. They are cost-effective and have the scalable option for large-scale production because additive manufacturing techniques are used. Among the various printing methods available, inkjet printing has recently gained popularity for printing electronics, especially capacitors that require precise and complex structures on different substrates. Inkjet printing …
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii
The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii
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The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …
Rheological Modeling And Inkjet Printability Of Electrode Ink Formulation For Miniature And Interdigital Lithium-Ion Batteries, Habib Temitope-Adebayo Ajose
Rheological Modeling And Inkjet Printability Of Electrode Ink Formulation For Miniature And Interdigital Lithium-Ion Batteries, Habib Temitope-Adebayo Ajose
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The rapid advancement of technology has resulted in a greater need for effective energy storage systems to meet the demands of the transportation and electronics industries. Among various energy storage systems, batteries are the most widely used, primarily because of their ability to store significant amounts of energy. In addition, lithium-ion batteries are prevalent for powering portable electronic devices due to their long cycle life, high energy density, and high operating voltage. The traditional doctor-blade approach has been used over the years for producing batteries. Currently, research is being directed to additively manufacture Li-ion batteries via Drop-on-Demand Inkjet Printing with …
Direct Ink Write Processing Of Signal Crossovers Using Aerosol Jet Printing Method, Lucas A. Clark
Direct Ink Write Processing Of Signal Crossovers Using Aerosol Jet Printing Method, Lucas A. Clark
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Electronics in different applications, such as in medical imaging devices, radar systems, communication transmitters, and optical drives, often require various power and signal lines to be integrated at board level. In such cases, different lines may cross over one another in three-dimensional space for efficient electronic integration. Crossovers are usually achieved by adding additional layers to a PCB. However, these additional layers increase the cost, weight, and complexity of the component. By creating a process and structure to offer board-level heterogenous integration, these factors may be reduced. RF-DC crossovers were designed and additively manufactured using an aerosol jet printer. Benzocyclobutene …
Investigation Of Surface Roughness Effects On Additively Manufactured Metals Under Dynamic Loading, Rachel Elizabeth Tullis
Investigation Of Surface Roughness Effects On Additively Manufactured Metals Under Dynamic Loading, Rachel Elizabeth Tullis
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The as-printed surfaces of parts produced through laser powder bed fusion are significantly rougher than surfaces produced through traditional manufacturing processes. This increased roughness can have a significant impact on mechanical properties, with perhaps the most notable detriment in the fatigue life of the part. Therefore, the as-printed surface roughness in additively manufactured materials must be studied more extensively to determine its impact on fatigue performance. This work investigates the surface roughness of additively manufactured specimens through the investigation of processing parameters and their effects on surface roughness in metal additive manufacturing. Furthermore, the relationships between as-printed surface roughness and …
Monitoring Blood Flow In Animal Models Using A Camera-Based Technique, Dharminder Singh Langri
Monitoring Blood Flow In Animal Models Using A Camera-Based Technique, Dharminder Singh Langri
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Blood flow dynamics plays a critical role in maintaining tissue health, as it delivers nutrients and oxygen while removing waste products. It is especially important when there is a disruption in cerebral autoregulation due to trauma, which can induce ischemia or hyperemia and can lead to secondary brain injury. Thus, there is a need for noninvasive techniques that can allow continuous monitoring of blood flow during intervention. Optical techniques have become increasingly practical for measuring blood flow due to their non-invasive, continuous, and relatively lower-cost nature. This research focused on developing a low-cost, scalable optical technique for measuring blood flow …
Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson
Experimental And Numerical Studies On The Projective Dye Visualization Velocimetry In A Squared Vertical Tube, Mark Bradley Johnson
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In fluid flow experiments, there have been numerous techniques developed over the years to measure velocity. Most popular techniques are non-intrusive such as particle image velocimetry (PIV), but these techniques are not suitable for all applications. For instance, PIV cannot be used in examining in-vivo measurements since the laser is not able to penetrate through the patient, which is why medical applications typically use X-rays. However, the images obtained from X-rays, in particular digital subtraction angiography, are projective images which compress 3D flow features onto a 2D image. Therefore, when intensity techniques, such as optical flow method (OFM), are applied …
A Machine Learning Framework For Hypersonic Vehicle Design Exploration, Atticus Beachy
A Machine Learning Framework For Hypersonic Vehicle Design Exploration, Atticus Beachy
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The design of Hypersonic Vehicles (HVs) requires meeting multiple unconventional and often conflicting design requirements in a hostile, high-energy environment. The most fundamental difference between ordinary aerospace design and hypersonic flight is that the extreme conditions of hypersonic flight require parts to perform multiple functions and be tightly integrated, resulting in significant coupled effects. Critical couplings among the disciplines of aerodynamics, structures, propulsion, and thermodynamics must be investigated in the early stages of design exploration to reduce the risk of requiring major design changes and cost overruns later. In addition, due to a lack of validated test data within the …
Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green
Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green
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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …
Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward
Effects Of Elastic Anisotropy On Residual Stress Measurements Performed Using The Hole-Drilling Technique, Joshua T. Ward
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In the present work, the variation in through-thickness residual stress profiles driven by elastic anisotropy is investigated using the incremental hole-drilling method. The standardized hole-drilling technique allows for the calculation of in-plane stresses based on measured surface strains, however, these calculations assume elastic isotropy. The assumption of elastic isotropy allows for the material constants to be reduced down to two values, however, this assumption is invalid for many materials used in aerospace design. These materials are often times elastically anisotropic, which leads to inaccuracy and uncertainty in measured stress profiles. An interference fit ring and plug sample was designed, using …
Identifying A Novel Ferrocene Derivative As A K-Ras Inhibitor, Kristen Marie Rehl
Identifying A Novel Ferrocene Derivative As A K-Ras Inhibitor, Kristen Marie Rehl
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Ras proteins are small GTPases that regulate cell proliferation, differentiation and survival at the plasma membrane (PM). There are three Ras isoforms ubiquitously expressed in mammalian cells: H-, N- and K-Ras. Constitutively active Ras mutations are found in ~19% of all human cancers, with ~75% of those being in K-Ras. There are K-Ras inhibitors in clinic but they only target the oncogenic K-RasG12C mutant, which only makes up a small sub-set of K-Ras-driven cancers. Thus, there still exists a need for a pan anti-K-Ras drug. Ferrocene derivatives are a class of compounds that have been shown to inhibit the growth …
Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo
Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo
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Alzheimer’s disease (AD) is the seventh leading cause of death globally with an estimated 6.5 million Americans aged 65 and above living with Alzheimer’s dementia in 2022 and at a projected national cost of $321 billion. AD is characterized by a progressive and irreversible neurodegenerative dysfunction with clinical symptoms such as deterioration in cognition and memory loss. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-site, public-private global research initiative that supports both investigation and development of treatments that slow or terminate AD progression. The study included 60 participants, comprising 30 AD and 30 control cohorts respectively. All participants were …
Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee
Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee
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This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …
Contributors To Pathologic Depolarization In Myotonia Congenita, Jessica Hope Myers
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 …