Signaling In Muscle Research Articles

Mathematical description of proprioception through muscle activation signal generation in core musculoskeletal system

ObjectiveCentral Pattern Generators (CPGs) produce the majority of muscle activation signals during gait whereas, reflexive signals from proprioception deal with perturbations. The reflexive neuromuscular signals are rather difficult to measure directly. The objective of this study is to mathematically estimate the reflexive neuromuscular signals of the core muscles during a movement similar to a normal gait. Methods1-Musculoskeletal model: a 2-D musculoskeletal model is designed for the upper body. 2-Neuromuscular model: mathematical models for neuromuscular reflexes are derived based on their physiological function descriptions. 3-Simulation: mathematical equations are extracted from the model and solved using numerical methods. Kinematics, muscle forces, and activation signals are obtained from the simulation. 4-Verification: verification of the model is conducted through a sample study. Five IMU sensors and four surface EMG electrodes are utilized to gather data from the experiment. ResultsUpper body kinematics, core muscle forces, and activation signals of the subject are estimated through model simulation for the intended movement. The verification process indicates similarity between simulation outcomes and test results. ConclusionThe proposed mathematical description of proprioception can successfully simulate and estimate reflexive activation signals of core muscles. The estimated activation signals can be employed in conjunction with a musculoskeletal model to predict body kinematics. SignificanceReflexive signal estimation of core muscles can further enhance studies concerning body stability control. Such predictive models have also the aptitude to be employed as an auxiliary clinical tool to help the therapist choose appropriate treatment protocols.

Yao medicine Amydrium hainanense suppresses hepatic fibrosis by repressing hepatic stellate cell activation via STAT3 signaling.

Ethnopharmacological relevance: Hepatic fibrosis (HF) occurs in response to chronic liver injury and may easily develop into irreversible liver cirrhosis or even liver cancer. Amydrium hainanense water extract (AHWE) is a water-soluble component extracted from the Yao medicine Amydrium hainanense (H.Li, Y.Shiao & S.L.Tseng) H.Li, which is commonly used for treating inflammatory diseases in folk. Previous evidence suggested that AHWE significantly inhibited hepatic stellate cell activation. However, little is known regarding the therapeutic effect of AHWE in HF and its underlying action mechanism. Objective: Investigation of the therapeutic effect of AHWE in HF and its underlying mechanism. Methods: The therapeutic effect of AHWE was tested in vivo using an HF mouse model via an intraperitoneal injection of carbon tetrachloride (CCl4). Histological evaluation of liver injury and fibrosis were tested by H&E staining and Masson's trichrome staining. Serum levels of ALT, AST, collagen type I (Col I), and hydroxyproline (HYP) were measured. The mRNA expression of liver fibrotic and inflammatory genes were tested, and the protein levels of alpha smooth muscle actin (α-SMA) and signal transducers and activators of transcription 3 (STAT3) were analyzed. The in vitro experiments were conducted using HSC-T6 and RAW264.7 cell lines. Results: Treatment with AHWE significantly reversed histopathological liver damage and liver function abnormalities in CCl4 mouse model. Also, the serum levels of ALT, AST, Col I, and HYP in CCl4-induced HF mice were improved in AHWE treatment. Further, AHWE showed a remarkable inhibitory effect on the expression of fibrosis markers (Acta2, Col1a1, and Col3a1) and inflammatory factors (Stat3, Tnfa, Il6, and Il1b) induced by CCl4. The results of in vitro experiments were consistent with those obtained in vivo. In addition, it is shown that STAT3 signaling was involved in the anti-fibrotic effects of AHWE as evidenced by STAT3 overexpression. Conclusion: The present study proposed a novel ethnomedicine for HF and suggested the underlying role of STAT3 signaling pathway regulation in this anti-fibrotic effect of the proposed medicine. These findings would serve as solid scientific evidence in support of the development of AHWE as a novel alternative or complementary therapy for HF prevention and treatment.

Intensive Care Unit Acquired Weakness Is Associated with Rapid Changes to Skeletal Muscle Proteostasis.

Intensive care unit (ICU)-acquired weakness is a frequent consequence of critical illness that impacts both the limb and respiratory muscles. The cause of ICU-acquired weakness is multifactorial, but both prolonged limb muscle inactivity and mechanical ventilation are risk factors for muscle wasting, which predisposes ICU patients to both short-term complications and long-term disabilities resulting from muscle weakness. Unfortunately, the current research does not provide a detailed understanding of the cellular etiology of ICU-acquired weakness, and no standard treatment exists. Therefore, improving knowledge of the mechanisms promoting muscle atrophy in critically ill patients is essential to developing therapeutic strategies to protect against ICU-induced skeletal muscle wasting. To advance our understanding of the mechanism(s) responsible for ICU-acquired weakness, we tested the hypothesis that ICU-induced muscle inactivity promotes a rapid decrease in anabolic signaling/protein synthesis and accelerates proteolysis in both limb and respiratory muscles. To investigate ICU-induced changes in skeletal muscle proteostasis, adult Sprague Dawley rats were anesthetized and mechanically ventilated for 12 h to simulate ICU care. Measurements of anabolic signaling, protein synthesis, and proteolytic activity in the limb muscles (plantaris and soleus) and respiratory muscles (parasternal and intercostal) revealed ICU-induced reductions in both anabolic signaling (i.e., AKT/mTOR pathway) and muscle protein synthesis. Moreover, simulated ICU care resulted in increased biomarkers of accelerated proteolysis in both limb and respiratory muscles. These novel findings reveal that disturbances in limb and respiratory muscle proteostasis occur rapidly during ICU-induced muscle inactivity, irrespective of the muscle function or muscle fiber type.

Nonlinear analysis of biceps surface EMG signals for chaotic approaches

In the present study, the chaos is detected and quantified in the electromyographic (EMG) signal of the biceps muscle using nonlinear features. Biological systems are complex and nonlinear systems composed of a large number of interconnected elements. A thorough understanding of the behavior of these systems, which are sometimes chaotic, will lead to an understanding of the behavior of diseases, finding effective treatments, and using appropriate rehabilitation equipment. Therefore, designing a novel stimulation equation based on Rossler nonlinear dynamics causes chaos in the biceps EMG signal. This stimulation, the sitting and hand positioning is designed in such a way to prevent muscle fatigue and saturated stimulability and also to ensure that with minimal stimulation of the musculocutaneous nerve, there is a maximum activity in the biceps muscle. Then, each signal was divided into chaotic and non-chaotic parts with the positive largest Lyapunov exponent (LLE), and its nonlinear and chaotic criteria, including fractal dimension (FD) using Petrosian method, correlation dimension (CD), for both parts of the EMG signal were calculated as first time. Then, after applying the values of these criteria as features to the support vector machine (SVM) classifier, the separation was carried out using a linear kernel. The results showed that if the classification features include the two features of FD and CD, they are separated from non-chaotic EMG signals with 98.97 % accuracy. Finally, for the first time the extracted features of CD, FD are a good representation of the chaotic behavior of the biceps EMG signal.

Simultaneous Multislice Accelerated TSE for Improved Spatiotemporal Resolution and Diagnostic Accuracy in Magnetic Resonance Neurography: A Feasibility Study.

This study aims to evaluate the utility of simultaneous multislice (SMS) acceleration for routine magnetic resonance neurography (MRN) at 3 T. Patients with multiple sclerosis underwent MRN of the sciatic nerve consisting of a standard fat-saturated T2-weighted turbo spin echo (TSE) sequence using integrated parallel acquisition technique (PAT2) acceleration and 2 T2 TSE sequences using a combination of PAT-SMS acceleration (1) to reduce scan time (PAT2-SMS2; SMS-TSE FAST ) and (2) for time neutral increase of in-plane resolution (PAT1-SMS2; SMS-TSE HR ). Acquisition times were 5:29 minutes for the standard T2 TSE, 3:12 minutes for the SMS-TSE FAST , and 5:24 minutes for the SMS-TSE HR . Six qualitative imaging parameters were analyzed by 2 blinded readers using a 5-point Likert scale and T2 nerve lesions were quantified, respectively. Qualitative and quantitative image parameters were compared, and both interrater and intrarater reproducibility were statistically assessed. In addition, signal-to-noise ratio/contrast-to-noise ratio (CNR) was obtained in healthy controls using the exact same imaging protocol. A total of 15 patients with MS (mean age ± standard deviation, 38.1 ± 11 years) and 10 healthy controls (mean age, 29.1 ± 7 years) were enrolled in this study. CNR analysis was highly reliable (intraclass correlation coefficient, 0.755-0.948) and revealed a significant CNR decrease for the sciatic nerve for both SMS protocols compared with standard T2 TSE (SMS-TSE FAST /SMS-TSE HR , -39%/-55%; P ≤ 0.01). Intrarater and interrater reliability of qualitative image review was good to excellent (κ: 0.672-0.971/0.617-0.883). Compared with the standard T2 TSE sequence, both SMS methods were shown to be superior in reducing pulsatile flow artifacts ( P < 0.01). Ratings for muscle border sharpness, detailed muscle structures, nerve border sharpness, and nerve fascicular structure did not differ significantly between the standard T2 TSE and the SMS-TSE FAST ( P > 0.05) and were significantly better for the SMS-TSE HR than for standard T2 TSE ( P < 0.001). Muscle signal homogeneity was mildly inferior for both SMS-TSE FAST ( P > 0.05) and SMS-TSE HR ( P < 0.001). A significantly higher number of T2 nerve lesions were detected by SMS-TSE HR ( P ≤ 0.01) compared with the standard T2 TSE and SMS-TSE FAST , whereas no significant difference was observed between the standard T2 TSE and SMS-TSE FAST . Implementation of SMS offers either to substantially reduce acquisition time by over 40% without significantly impeding image quality compared with the standard T2 TSE or to increase in-plane resolution for a high-resolution approach and improved depiction of T2 nerve lesions while keeping acquisition times constant. This addresses the specific needs of MRN by providing different imaging approaches for 2D clinical MRN.

Ankle Joint Torque Prediction Using an NMS Solver Informed-ANN Model and Transfer Learning.

In this work, we predicted ankle joint torque by combining a neuromusculoskeletal (NMS) solver-informed artificial neural network (hybrid-ANN) model with transfer learning based on joint angle and muscle electromyography signals. The hybrid-ANN is an ANN augmented with two kinds of features: 1) experimental measurements - muscle signals and joint angles, and 2) informative physical features extracted from the underlying NMS solver, such as individual muscle force and joint torque. The hybrid-ANN model accuracy in torque prediction was studied in both intra- and inter-subject tests, and compared to the baseline models (NMS and standard-ANN). For each prediction model, seven different cases were studied using data from gait at different speeds and from isokinetic ankle dorsi/plantarflexion motion. Additionally, we integrated a transfer learning method in inter-subject models to improve joint torque prediction accuracy by transferring the learned knowledge from previous participants to a new participant, which could be useful when training data is limited. Our results indicated that better accuracy could be obtained by integrating informative NMS features into a standard ANN model, especially in inter-subject cases; overall, the hybrid-ANN model predicted joint torque with higher accuracy than the baseline models, most notably in inter-subject prediction after adopting the transfer learning technique. We demonstrated the potential of combining physics-based NMS and standard-ANN models with a transfer learning technique in different prediction scenarios. This procedure holds great promise in applications such as assistance-as-needed exoskeleton control strategy design by incorporating the physiological joint torque of the users.

A Multimodal Fusion Model for Estimating Human Hand Force: Comparing surface electromyography and ultrasound signals

Biomimetic robots have received significant attention in recent years. Among them, the wearable exoskeleton, which imitates the functions of the musculoskeletal system to assist humans, is a typical biomimetic robot. Given that safe human–robot interaction plays a critical role in the successful application of wearable exoskeletons, this work studies the clinical readiness of a multimodal fusion model that estimates hand force based on the surface electromyography (sEMG) and A-mode ultrasound signals of the forearm muscles. The proposed multimodal fusion model affords the biomimetic hand exoskeleton assisting the elderly in completing daily tasks or quantitatively assessing the recovery level of poststroke patients. The suggested fusion model is called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Optimization of Latent Representation for the Self-Attention Convolutional Neural Network</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OLR-SACNN</i> ), which utilizes a common component extraction module (CCEM) and a complementary component retention module (CCRM) to optimize latent representation of the multiple modalities. Then the optimized latent representations are fused with the self-attention mechanism. The experiments conducted on a self-collected multimodal data set verify performance of the proposed OLR-SACNN model. Specifically, compared to solely employing sEMG or A-mode ultrasound signals, the force estimation’s normalized mean-square error (NMSE) based on the multiple modalities decreases by 97.7 and 38.92%, respectively. Furthermore, the OLR-SACNN model has been used to estimate the hand force of some poststroke patients and attained the desired performance.

Characteristics of submental muscles function and hyoid bone movement in patients with dysphagia after stroke.

Dysphagia is one of the common complications after stroke. Dysphagia significantly increases the probability of serious adverse consequences. The purpose of this study was to compare the characteristics of submental muscles electromyography and hyoid motion parameters between patients with dysphagia after stroke and healthy controls, and whether there is a synergistic effect between the function of the submental muscles and the movement of the hyoid. Fifteen patients with post-stroke dysphagia and fifteen healthy adults simultaneously underwent the videofluoroscopic and surface electromyography of the submental muscles while swallowing 5ml of concentrated liquid barium sulphate. The electromyographic signal of the submental muscles was analysed along with parameters of hyoid movement. Stage transition duration and duration of surface electromyographic activity were extended significantly in post-stroke dysphagia patients(P<0.05). Surface electromyography amplitude and hyoid movement were significantly reduced in patients (P<0.05). There was a significant correlation between the maximum hyoid movement distance and the peak sEMG amplitude in healthy controls (r=0.660, P=0.014), but not in patients with dysphagia after stroke (r=0.425, P=0.148). Submental muscles electromyographic signal changes in patients may be the result of uncoordinated muscle contractions and decreased muscle strength. Furthermore, the reduced hyoid movement distance may be due to impaired function of the submental muscles. In addition, the submental muscles and hyoid movement or other swallowing structures functions were impaired to varying degrees, resulting in the disappearance of the correlation between the maximum movement distance of the hyoid and the peak amplitude.

Reduced Tyrosine and Serine-632 Phosphorylation of Insulin Receptor Substrate-1 in the Gastrocnemius Muscle of Obese Zucker Rat.

Obesity has become a serious health problem in the world, with increased morbidity, mortality, and financial burden on patients and health-care providers. The skeletal muscle is the most extensive tissue, severely affected by a sedentary lifestyle, which leads to obesity and type 2 diabetes. Obesity disrupts insulin signaling in the skeletal muscle, resulting in decreased glucose disposal, a condition known as insulin resistance. Although there is a large body of evidence on obesity-induced insulin resistance in various skeletal muscles, the molecular mechanism of insulin resistance due to a disruption in insulin receptor signaling, specifically in the gastrocnemius skeletal muscle of obese Zucker rats (OZRs), is not fully understood. This study subjected OZRs to a glucose tolerance test (GTT) to analyze insulin sensitivity. In addition, immunoprecipitation and immunoblotting techniques were used to determine the expression and tyrosine phosphorylation of insulin receptor substrate-1 (IRS-1) and insulin receptor-β (IRβ), and the activation of serine-632-IRS-1 phosphorylation in the gastrocnemius muscle of Zucker rats. The results show that the GTT in the OZRs was impaired. There was a significant decrease in IRS-1 levels, but no change was observed in IRβ in the gastrocnemius muscle of OZRs, compared to Zucker leans. Obese rats had a higher ratio of tyrosine phosphorylation of IRS-1 and IRβ than lean rats. In obese rats, however, insulin was unable to induce tyrosine phosphorylation. Moreover, insulin increased the phosphorylation of serine 632-IRS-1 in the gastrocnemius muscle of lean rats. However, obese rats had a low basal level of serine-632-IRS-1 and insulin only mildly increased serine phosphorylation in obese rats, compared to those without insulin. Thus, we addressed the altered steps of the insulin receptor signal transduction in the gastrocnemius muscle of OZRs. These findings may contribute to a better understanding of human obesity and type 2 diabetes.

The Effects of Prolonged Vibrotactile EMG-Based Biofeedback on Ankle Joint Range of Motion During Gait in Children with Spastic Cerebral Palsy: A Case Series

Aims The objective of this case series was to examine the feasibility of vibrotactile EMG-based biofeedback (BF) as a home-based intervention tool to enhance sensory information during everyday motor activities and to explore its effectiveness to induce changes in active ankle range of motion during gait in children with spastic cerebral palsy (CP). Methods Ten children ages 6 to 13 years with spastic CP were recruited. Participants wore two EMG-based vibro-tactile BF devices for at least 4 hours per day for 1-month on the ankle and knee joints muscles. The device computed the amplitude of the EMG signal of the target muscle and actuated a silent vibration motor proportional to the magnitude of the EMG. Results Our results demonstrated the feasibility of the augmented sensory information of muscle activity to induce changes of the active ankle range of motion during gait for 6 children with an increase ranging from 8.9 to 51.6% compared to a one-month period without treatment. Conclusions Preliminary findings of this case series demonstrate the feasibility of vibrotactile EMG-based BF and suggest potential effectiveness to increase active ankle range of motion, therefore serving as a promising therapeutic tool to improve gait in children with spastic CP.

Optically pumped magnetometers detect altered maximal muscle activity in neuromuscular disease.

Optically pumped magnetometers (OPM) are quantum sensors that enable the contactless, non-invasive measurement of biomagnetic muscle signals, i.e., magnetomyography (MMG). Due to the contactless recording, OPM-MMG might be preferable to standard electromyography (EMG) for patients with neuromuscular diseases, particularly when repetitive recordings for diagnostic and therapeutic monitoring are mandatory. OPM-MMG studies have focused on recording physiological muscle activity in healthy individuals, whereas research on neuromuscular patients with pathological altered muscle activity is non-existent. Here, we report a proof-of-principle study on the application of OPM-MMG in patients with neuromuscular diseases. Specifically, we compare the muscular activity during maximal isometric contraction of the left rectus femoris muscle in three neuromuscular patients with severe (Transthyretin Amyloidosis in combination with Pompe's disease), mild (Charcot-Marie-Tooth disease, type 2), and without neurogenic, but myogenic, damage (Myotonia Congenita). Seven healthy young participants served as the control group. As expected, and confirmed by using simultaneous surface electromyography (sEMG), a time-series analysis revealed a dispersed interference pattern during maximal contraction with high amplitudes. Furthermore, both patients with neurogenic damage (ATTR and CMT2) showed a reduced variability of the MMG signal, quantified as the signal standard deviation of the main component of the frequency spectrum, highlighting the reduced possibility of motor unit recruitment due to the loss of motor neurons. Our results show that recording pathologically altered voluntary muscle activity with OPM-MMG is possible, paving the way for the potential use of OPM-MMG in larger studies to explore the potential benefits in clinical neurophysiology.

Comparison of two Wireless Electromyography Sensor Module Designs using wet electrodes and dry electrodes at the time of Sitting motion to stand

One of the biosignals used to identify muscle signals in humans is electromyography. Electromyography signals are frequently utilized as input and are designed to aid in post-stroke therapy recovery or to assist people with disabilities. This phenomena has led to the development of numerous electromyography module sensor designs for use in support of various research-based applications. In this study, an electromyography sensor module without an electrode cable is compared to an electromyography sensor module that uses gel electrodes, plate electrodes, electrode cables, and other electrode technologies. A function generator is used to test each module, and the correlation value is sought to determine the connection between the two modules under consideration. Later, the findings of this study served as the foundation for other studies. Researchers also wish to explore the possibility of developing an electromyography sensor module by altering the wireless EMG sensor module's structure and design. Whereas this study can subsequently be extremely helpful to improve the standing of the Health Poltekkes Kemenkes Surabaya.

Lower Limb Exoskeleton Sensors: State-of-the-Art

Due to the ever-increasing proportion of older people in the total population and the growing awareness of the importance of protecting workers against physical overload during long-time hard work, the idea of supporting exoskeletons progressed from high-tech fiction to almost commercialized products within the last six decades. Sensors, as part of the perception layer, play a crucial role in enhancing the functionality of exoskeletons by providing as accurate real-time data as possible to generate reliable input data for the control layer. The result of the processed sensor data is the information about current limb position, movement intension, and needed support. With the help of this review article, we want to clarify which criteria for sensors used in exoskeletons are important and how standard sensor types, such as kinematic and kinetic sensors, are used in lower limb exoskeletons. We also want to outline the possibilities and limitations of special medical signal sensors detecting, e.g., brain or muscle signals to improve data perception at the human-machine interface. A topic-based literature and product research was done to gain the best possible overview of the newest developments, research results, and products in the field. The paper provides an extensive overview of sensor criteria that need to be considered for the use of sensors in exoskeletons, as well as a collection of sensors and their placement used in current exoskeleton products. Additionally, the article points out several types of sensors detecting physiological or environmental signals that might be beneficial for future exoskeleton developments.

SEMG-based technology for silent voice recognition

Silent speech recognition (SSR) is a system that implements speech communication when a sound signal is not available using surface electromyography (sEMG)-based speech recognition. Researchers have used surface electrodes to record the electrically-activated potential of human articulation muscles to recognize speech content. SSR can be used for pilot-assisted speech recognition, communication of individuals with speech impairment, private communication, and other fields. In this feasibility study, we collected sEMG data for ten single Mandarin numeric words. After reducing power frequency interference and power supply noise from the sEMG signal, short-term energy (STE) was used for voice activity detection (VAD). The power spectrum features were extracted and fed into the classifier for final identification results. We used the Hold-out method to divide the data into training and test sets on a 7-3 scale, with an average accuracy of 92.3% and a maximum of 100% using a support vector machine (SVM) classifier. Experimental results showed that the proposed method has development potential, and is effective in identifying isolated words from the sEMG signal of the articulation muscles.

Research on the Recognition of Various Muscle Fatigue States in Resistance Strength Training.

Instantly and accurately identifying the state of dynamic muscle fatigue in resistance training can help fitness trainers to build a more scientific and reasonable training program. By investigating the isokinetic flexion and extension strength training of the knee joint, this paper tried to extract surface electromyogram (sEMG) features and establish recognition models to classify muscle states of the target muscles in the isokinetic strength training of the knee joint. First, an experiment was carried out to collect the sEMG signals of the target muscles. Second, two nonlinear dynamic indexes, wavelet packet entropy (WPE) and power spectrum entropy (PSE), were extracted from the obtained sEMG signals to verify the feasibility of characterizing muscle fatigue. Third, a convolutional neural network (CNN) recognition model was constructed and trained with the obtained sEMG experimental data to enable the extraction and recognition of EMG deep features. Finally, the CNN recognition model was compared with multiple support vector machines (Multi-SVM) and multiple linear discriminant analysis (Multi-LDA). The results showed that the CNN model had a better classification accuracy. The overall recognition accuracy of the CNN model applied to the test data (91.38%) was higher than that of the other two models, which verified that the CNN dynamic fatigue recognition model based on subjective and objective information feedback had better recognition performance. Furthermore, training on a larger dataset could further improve the recognition accuracy of the CNN recognition model.

Mammalian Target of Rapamycin (mTOR) Signaling at the Crossroad of Muscle Fiber Fate in Sarcopenia.

The mammalian target of rapamycin (mTOR) is a major regulator of skeletal myocyte viability. The signaling pathways triggered by mTOR vary according to the type of endogenous and exogenous factors (e.g., redox balance, nutrient availability, physical activity) as well as organismal age. Here, we provide an overview of mTOR signaling in skeletal muscle, with a special focus on the role played by mTOR in the development of sarcopenia. Intervention strategies targeting mTOR in sarcopenia (e.g., supplementation of plant extracts, hormones, inorganic ions, calorie restriction, and exercise) have also been discussed.

Skeletal Muscle CSE Deficiency Leads to Insulin Resistance in Mice.

Cystathionine-γ-lyase (CSE) is expressed in various tissues and generates H2S via an alternative desulfuration reaction. We sought to explore the functions of skeletal muscle CSE using skeletal muscle conditional knockout CSE (MCSEKO) mice. It was found that body weight, muscle morphology, and exercise capacity were not altered in MCSEKO mice compared with littermate wild-type mice. RNA-seq-based transcriptome analysis showed that 275 genes were differentially regulated in skeletal muscle and multiple signaling pathways including insulin signaling and mTOR, PI3K-AKT, and cGMP-PKG signaling pathways were enriched in MCSEKO mice. The intraperitoneal glucose tolerance test and insulin tolerance test showed that glucose tolerance and insulin sensitivity were reduced in MCSEKO mice. Glucose transporter 4 (GLU4) and PKG-1 expression levels and insulin receptor substrate-1(IRS1)/PI3K/Akt signaling pathway were downregulated whilst the mTOR/S6K/S6 pathway was enhanced in MCSEKO mice. These effects were reversed by the H2S supplement. Aerobic treadmill training significantly promoted glucose tolerance and insulin sensitivity and improved GLU4 and PKG-1 levels, promoted IRS1/PI3K/Akt signaling and suppressed mTOR/S6K/S6 signaling pathway in MCSEKO mice. Our data suggest that skeletal muscle CSE/H2S signaling is critical for the maintenance of insulin sensitivity, which is associated with maintaining the balance in PKG, PI3K/Akt, and mTOR/S6K/S6 signaling pathways in skeletal muscle.

Studying Edema Formation After Release of the Infraspinatus Tendon as an Experimental Model of Rotator Cuff Tears in Sheep: A Preliminary Imaging and Morphological Analysis

Background: The cause, extent, and role of muscle edema for muscle degeneration are unknown and not considered in the current literature. In vivo experiments were designed to prove muscle edema formation in the early period in a sheep model of acute rotator cuff tears. Hypothesis: Muscle edema occurs after tendon release with or without additional stretching trauma and may be associated with muscle retraction and subsequent muscle degeneration. Study Design: Controlled laboratory study. Methods: A sheep model with acute release of the infraspinatus tendon was used. An osteotomy of the greater tuberosity, including the insertion of the infraspinatus tendon, was performed in 14 sheep. To demonstrate presence of edema, magnetic resonance imaging scans were performed at 0, 2, and 4 weeks using T1-weighted, T2-weighted, proton density–weighted, and Dixon sequences. Excisional biopsy specimens were taken at 0, 3, and 4 weeks (histological results will be reported in a later publication). Two injury models were created: a nontrauma group that consisted of muscle release alone and a trauma group that included additional standardized traction to the musculotendinous unit. Evaluation of T1- and T2-weighted images included calculation of pennation angle, muscle fiber length, signal intensity (edema), and muscle volume. Muscle wet weight and volume were measured at sacrifice. Results: Edema formation was shown in all sheep and slightly more pronounced in the trauma group, where muscle intensity increased significantly between time point 0 (200 Grey Value (GV)) and weeks 2, 3, and 4 (300 GV). Edema formation started early after tendon release with a plateau between 3 and 4 weeks. Deterioration of muscle fiber bundles began also after tendon release with a peak at 4 weeks. Muscle volume decreased steadily over time. Conclusion: Muscle edema appeared early after rotator cuff tendon release, was more pronounced in the trauma group, and reached a plateau after 3 to 4 weeks. Muscle fatty content decreased within the short period of 4 weeks owing to a dilution effect. Muscle edema seems to be an essential factor in cuff tears and subsequent muscle retraction and degeneration. Clinical Relevance: This study demonstrates a new type of muscle edema of retraction and describes the characteristics of edema associated with a retracted rotator cuff tear.

Elevated Ca2+ at the triad junction underlies dysregulation of Ca2+ signaling in dysferlin-null skeletal muscle.

Dysferlin-null A/J myofibers generate abnormal Ca2+ transients that are slightly reduced in amplitude compared to controls. These are further reduced in amplitude by hypoosmotic shock and often appear as Ca2+ waves (Lukyanenko et al., J. Physiol., 2017). Ca2+ waves are typically associated with Ca2+-induced Ca2+ release, or CICR, which can be myopathic. We tested the ability of a permeable Ca2+ chelator, BAPTA-AM, to inhibit CICR in injured dysferlin-null fibers and found that 10-50nM BAPTA-AM suppressed all Ca2+ waves. The same concentrations of BAPTA-AM increased the amplitude of the Ca2+ transient in A/J fibers to wild type levels and protected transients against the loss of amplitude after hypoosmotic shock, as also seen in wild type fibers. Incubation with 10nM BAPTA-AM led to intracellular BAPTA concentrations of ∼60nM, as estimated with its fluorescent analog, Fluo-4AM. This should be sufficient to restore intracellular Ca2+ to levels seen in wild type muscle. Fluo-4AM was ∼10-fold less effective than BAPTA-AM, however, consistent with its lower affinity for Ca2+. EGTA, which has an affinity for Ca2+ similar to BAPTA, but with much slower kinetics of binding, was even less potent when introduced as the -AM derivative. By contrast, a dysferlin variant with GCaMP6fu in place of its C2A domain accumulated at triad junctions, like wild type dysferlin, and suppressed all abnormal Ca2+ signaling. GCaMP6fu introduced as a Venus chimera did not accumulate at junctions and failed to suppress abnormal Ca2+ signaling. Our results suggest that leak of Ca2+ into the triad junctional cleft underlies dysregulation of Ca2+ signaling in dysferlin-null myofibers, and that dysferlin's C2A domain suppresses abnormal Ca2+ signaling and protects muscle against injury by binding Ca2+ in the cleft.

Can MR neurography of the common peroneal nerve predict a residual motor deficit in patients with foot drop?

To determine if MR neurography of the common peroneal nerve (CPN) predicts a residual motor deficit at 12-month clinical follow-up in patients presenting with foot drop. A retrospective search for MR neurography cases evaluating the CPN at the knee was performed. Patients were included if they had electrodiagnostic testing (EDX) within 3months of imaging, ankle and/or forefoot dorsiflexion weakness at presentation, and at least 12-month follow-up. Two radiologists individually evaluated nerve size (enlarged/normal), nerve signal (T2 hyperintense/normal), muscle signal (T2 hyperintense/normal), muscle bulk (normal/Goutallier 1/Goutallier > 1), and nerve and muscle enhancement. Discrepancies were resolved via consensus review. Multivariable logistical regression was used to evaluate for association between each imaging finding and a residual motor deficit at 12-month follow-up. Twenty-three 3T MRIs in 22 patients (1 bilateral, mean age 52years, 16 male) met inclusion criteria. Eighteen cases demonstrated common peroneal neuropathy on EDX, and median duration of symptoms was 5months. Six cases demonstrated a residual motor deficit at 12-month follow-up. Fourteen cases underwent CPN decompression (1 bilateral) within 1year of presentation. Three cases demonstrated Goutallier > 1 anterior compartment muscle bulk. Multivariable logistical regression did not show a statistically significant association between any of the imaging findings and a residual motor deficit at 12-month follow-up. MR neurography did not predict a residual motor deficit at 12-month follow-up in patients presenting with foot drop, though few patients demonstrated muscle atrophy in this study.