Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model.

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.3 cm, mean weight 72.7 kg, mean BMI 25.6) were recorded and processed into 10,608 images. Parameters were created using the coordinates measured from the posture estimation AI, and these were used to train the machine learning model. The measured values from the smartphone's angle device were used as the true values to create a machine learning model. When measuring the parameters at each angle, we compared the performance of the machine learning model using both linear regression and Light GBM. When the pose estimation AI was trained using linear regression, a correlation coefficient of 0.971 was achieved, with a mean absolute error (MAE) of 5.778. When trained with Light GBM, the correlation coefficient was 0.999 and the MAE was 0.945. This method enables the estimation of internal and external rotation angles from a direct-facing position. This approach is considered to be valuable for analyzing motor movements during sports and rehabilitation.

Estimating the Thumb Rotation Angle by Using a Tablet Device With a Posture Estimation Artificial Intelligence Model.

MediaPipe Hand (MediaPipe) is an artificial intelligence (AI)-based pose estimation library. In this study, MediaPipe was combined with four machine learning (ML) models to estimate the rotation angle of the thumb. Videos of the right hands of 15 healthy volunteers were recorded and processed into 9000 images. The rotation angle of the thumb (defined as angle θ from the palmar plane, which is defined as 0°) was measured using an angle measuring device, expressed in a radian system. Angle θ was then estimated by the ML model by using parameters calculated from the hand coordinates detected by MediaPipe. The linear regression model showed a root mean square error (RMSE) of 12.23, a mean absolute error (MAE) of 9.9, and a correlation coefficient of 0.91. The ElasticNet model showed an RMSE of 12.23, an MAE of 9.95, and a correlation coefficient of 0.91; the support vector machine (SVM) model showed an RMSE of 4.7, an MAE of 2.5, and a correlation coefficient of 0.99. The LightGBM model achieved high values: an RMSE of 4.58, an MAE of 2.62, and a correlation coefficient of 0.99. Based on these findings, we concluded that the thumb rotation angle can be estimated with high accuracy by combining MediaPipe and ML.

Treatment of Osteoporosis in Men on Androgen Deprivation Therapy in Japan.

Background and Objectives: Androgen deprivation therapy (ADT) for prostate cancer has greatly improved treatment outcomes. As patient survival rates have increased, reports of decreased bone density and increased bone fractures as side effects of ADT have emerged. The prevalence of osteoporosis in Japanese men was 4.6%. The purpose of this study was to evaluate the effect of osteoporosis treatment in prostate cancer patients who underwent ADT in Japan. Materials and Methods: The subjects were 33 male patients who had undergone ADT for prostate cancer, who were noted to have decreased bone density. Mean age was 76.2 ± 7.7 years (64-87). Medications included vitamin D in one case, bisphosphonates (BP) in 27 cases, and denosumab in five cases. The evaluation method examined the rate of change in bone mineral density (BMD) before osteoporosis treatment and 1 year after. For comparison, a group without osteoporosis treatment intervention (n = 33) was selected, and matched for prostate cancer treatment and age. The rate of change in trabecular bone score (TBS) was also calculated. Results: The percentage changes in BMD before and 1 year after treatment were as follows: lumbar spine, 7.1 ± 5.8% in the treatment group versus -3.9 ± 4.1% in the no treatment group; femoral neck, 5.5 ± 6.2% in the treatment group versus -0.9 ± 3.9% in the no treatment group; total femur, 6.6 ± 6.4% in the treatment group versus the no treatment group which was -1.7 ± 3.2%. In all cases, there was a clear significant difference (p < 0.01). The percent change in TBS was further calculated in the same manner. There was no significant difference between the two groups: +1.7 ± 3.8% in the treated group versus +0.3 ± 4.1% in the untreated group. Conclusions: Osteoporosis treatment in Japanese patients with prostate cancer on ADT therapy was found to significantly increase BMD compared to the untreated group. BP and denosumab were found to be very effective in increasing BMD.

Lateral Collateral Ligament Reconstruction Using the Triceps Brachii Fascia for Posterolateral Rotatory Instability in Cubitus Varus: A Report of Two Cases.

A combination of osteotomy and ligament reconstruction is recommended for posterolateral rotatory instability (PLRI) with large cubitus varus deformities. There is a lack of reports regarding ligament donor selection for ligament reconstruction of PLRI with cubitus varus. Two cases of PLRI with cubitus varus have been described. In case one, a 40-year-old woman presented with left elbow pain. She had a cubitus varus deformity, resulting from a childhood elbow fracture. Radiographs showed an 18-degree cubitus varus deformity. A lateral closing wedge osteotomy and double plate osteosynthesis were performed. The lateral collateral ligament (LCL) was reconstructed with autologous triceps fascia. Postoperative radiographs confirmed correction with 10 degrees of the carrying angle (CA). Bone union at the osteotomy site occurred six months later with excellent results. In case two, a 45-year-old man presented an arm with persistent right elbow instability with cubitus varus deformity. This was due to a childhood supracondylar fracture of the right humerus. Radiographs showed a cubitus varus deformity of 25 degrees on the right. The surgical procedure included a lateral wedge osteotomy, double plate fixation, and LCL reconstruction with autologous triceps fascia. Postoperative radiographs confirmed a corrected CA of 5 degrees. Bone union was achieved at the six-month follow-up with satisfactory results. The use of triceps fascia for LCL reconstruction for PLRI due to cubitus varus would provide a minimally invasive and reasonable treatment option.

Re-tear after arthroscopic rotator cuff tear surgery: risk analysis using machine learning.

BACKGROUND: Postoperative rotator cuff retear after arthroscopic rotator cuff repair (ARCR) is still a major problem. Various risk factors such as age, gender, and tear size have been reported. Recently, magnetic resonance imaging-based stump classification was reported as an index of rotator cuff fragility. Although stump type 3 is reported to have a high retear rate, there are few reports on the risk of postoperative retear based on this classification. Machine learning (ML), an artificial intelligence technique, allows for more flexible predictive models than conventional statistical methods and has been applied to predict clinical outcomes. In this study, we used ML to predict postoperative retear risk after ARCR. METHODS: The retrospective case-control study included 353 patients who underwent surgical treatment for complete rotator cuff tear using the suture-bridge technique. Patients who initially presented with retears and traumatic tears were excluded. In study participants, after the initial tear repair, rotator cuff retears were diagnosed by magnetic resonance imaging; Sugaya classification types IV and V were defined as re-tears. Age, gender, stump classification, tear size, Goutallier classification, presence of diabetes, and hyperlipidemia were used for ML parameters to predict the risk of retear. Using Python's Scikit-learn as an ML library, five different AI models (logistic regression, random forest, AdaBoost, CatBoost, LightGBM) were trained on the existing data, and the prediction models were applied to the test dataset. The performance of these ML models was measured by the area under the receiver operating characteristic curve. Additionally, key features affecting retear were evaluated. RESULTS: The area under the receiver operating characteristic curve for logistic regression was 0.78, random forest 0.82, AdaBoost 0.78, CatBoost 0.83, and LightGBM 0.87, respectively for each model. LightGBM showed the highest score. The important factors for model prediction were age, stump classification, and tear size. CONCLUSIONS: The ML classifier model predicted retears after ARCR with high accuracy, and the AI model showed that the most important characteristics affecting retears were age and imaging findings, including stump classification. This model may be able to predict postoperative rotator cuff retears based on clinical features.

Intra-articular site-specific distribution of advanced glycation end products in the shoulder of patients with diabetes mellitus having rotator cuff tears.

BACKGROUND: Advanced glycation end products (AGEs) are compounds formed due to aging and diabetes mellitus (DM). They activate NADPH oxidase (NOX) by binding to their receptors, thereby increasing the production of reactive oxygen species (ROS), which cause oxidative stress. In this study, we investigated the effects of AGEs on the tissues of the shoulder joint (such as rotator cuff synovium, and capsule) in patients with DM having rotator cuff tears. METHODS: This study included eight patients with DM who underwent surgical treatment for rotator cuff tears with contracture. The rotator cuff, synovium, and joint capsule were harvested at the time of surgery and evaluated by hematoxylin-eosin staining. Furthermore, immunostaining was used for evaluating AGEs and receptor for AGEs (RAGE), cell activity, ROS, and apoptosis. Quantitative real-time polymerase chain reaction (qPCR) was employed for the cellular evaluation of NOX, interleukins, RAGE, and collagen. RESULTS: The AGEs and RAGE staining as well as the ratio of ROS and apoptosis were in the following order: rotator cuff > joint capsule > synovium. In contrast, the cellular activity was significantly higher in the synovium than in the other regions. The type I collagen expression (as shown by qPCR) as well as the RAGE and NOX expressions were as follows: rotator cuff > joint capsule > synovium. Conversely, the expression of inflammatory cytokines (i.e., IL-6 and IL-1ß) was higher in the synovium than in the other regions. CONCLUSIONS: Our study is among the first to evaluate the effects of AGEs on each tissue of the shoulder joint in patients with DM having rotator cuff tears and contractures. The accumulation of AGEs in each tissue of the shoulder joint could reveal the locations affected by DM, which can lead to a better understanding of the pathophysiology of DM-related shoulder diseases.

Measurement of Shoulder Abduction Angle with Posture Estimation Artificial Intelligence Model.

Substantial advancements in markerless motion capture accuracy exist, but discrepancies persist when measuring joint angles compared to those taken with a goniometer. This study integrates machine learning techniques with markerless motion capture, with an aim to enhance this accuracy. Two artificial intelligence-based libraries-MediaPipe and LightGBM-were employed in executing markerless motion capture and shoulder abduction angle estimation. The motion of ten healthy volunteers was captured using smartphone cameras with right shoulder abduction angles ranging from 10° to 160°. The cameras were set diagonally at 45°, 30°, 15°, 0°, -15°, or -30° relative to the participant situated at a distance of 3 m. To estimate the abduction angle, machine learning models were developed considering the angle data from the goniometer as the ground truth. The model performance was evaluated using the coefficient of determination R2 and mean absolute percentage error, which were 0.988 and 1.539%, respectively, for the trained model. This approach could estimate the shoulder abduction angle, even if the camera was positioned diagonally with respect to the object. Thus, the proposed models can be utilized for the real-time estimation of shoulder motion during rehabilitation or sports motion.

Elicitation of Inhibitory Effects for AGE-Induced Oxidative Stress in Rotator Cuff-Derived Cells by Apocynin.

Advanced glycation end-products (AGEs) play a critical supportive role during musculoskeletal disorders via glycosylation and oxidative stress. Though apocynin, identified as a potent and selective inhibitor of NADPH oxidase, has been reported to be involved in pathogen-induced reactive oxygen species (ROS), its role in age-related rotator cuff degeneration has not been well clarified. Therefore, this study aims to evaluate the in vitro effects of apocynin on human rotator cuff-derived cells. Twelve patients with rotator cuff tears (RCTs) participated in the study. Supraspinatus tendons from patients with RCTs were collected and cultured. After the preparation of RC-derived cells, they were divided into four groups (control group, control + apocynin group, AGEs group, AGEs + apocynin group), and gene marker expression, cell viability, and intracellular ROS production were evaluated. The gene expression of NOX, IL-6, and the receptor for AGEs (RAGE) was significantly decreased by apocynin. We also examined the effect of apocynin in vitro. The results showed that ROS induction and increasing apoptotic cells after treatment of AGEs were significantly decreased, and cell viability increased considerably. These results suggest that apocynin can effectively reduce AGE-induced oxidative stress by inhibiting NOX activation. Thus, apocynin is a potential prodrug in preventing degenerative changes of the rotor cuff.

Dynamic Analysis of the Coracohumeral Ligament Using Ultra-Sonography in Shoulder Contracture.

The coracohumeral ligament (CHL) is related to the range of motion of the shoulder joint. The evaluation of the CHL using ultrasonography (US) has been reported on the elastic modulus and thickness of the CHL, but no dynamic evaluation method has been established. We aimed to quantify the movement of the CHL by applying Particle Image Velocimetry (PIV), a technique used in the field of fluid engineering, to cases of shoulder contracture using the US. The subjects were eight patients, with 16 shoulders. The coracoid process was identified from the body surface, and a long-axis US image of the CHL parallel to the subscapularis tendon was drawn. The shoulder joint was moved from 0 degrees of internal/external rotation to 60 degrees of internal rotation at a rhythm of one reciprocation every 2 s. The velocity of the CHL movement was quantified by the PIV method. The mean magnitude velocity of CHL was significantly faster on the healthy side. The maximum magnitude velocity was significantly faster on the healthy side. The results suggest that the PIV method is helpful as a dynamic evaluation method, and in patients with shoulder contracture, the CHL velocity was significantly decreased.

Screening for Osteoporosis from Blood Test Data in Elderly Women Using a Machine Learning Approach.

The diagnosis of osteoporosis is made by measuring bone mineral density (BMD) using dual-energy X-ray absorptiometry (DXA). Machine learning, one of the artificial intelligence methods, was used to predict low BMD without using DXA in elderly women. Medical records from 2541 females who visited the osteoporosis clinic were used in this study. As hyperparameters for machine learning, patient age, body mass index (BMI), and blood test data were used. As machine learning models, logistic regression, decision tree, random forest, gradient boosting trees, and lightGBM were used. Each model was trained to classify and predict low-BMD patients. The model performance was compared using a confusion matrix. The accuracy of each trained model was 0.772 in logistic regression, 0.739 in the decision tree, 0.775 in the random forest, 0.800 in gradient boosting, and 0.834 in lightGBM. The area under the curve (AUC) was 0.595 in the decision tree, 0.673 in logistic regression, 0.699 in the random forest, 0.840 in gradient boosting, and 0.961, which was the highest, in the lightGBM model. Important features were BMI, age, and the number of platelets. Shapley additive explanation scores in the lightGBM model showed that BMI, age, and ALT were ranked as important features. Among several machine learning models, the lightGBM model showed the best performance in the present research.

Anatomical Assessment of Cephalic Vein and Superficial Branch of Radial Nerve Using High-Resolution Ultrasound Imaging.

Introduction The superficial branch of the radial nerve (SBRN) has a risk of nerve injury during cephalic vein (CV) cannulation. Due to the lack of imaging study regarding SBRN and CV relationship, we analyzed the anatomical relationship between the SBRN and the CV using ultrasound (US) imaging. Materials and Methods In total, 82 upper limbs of 41 healthy volunteers were analyzed. The SBRN and CV were identified at the following three points in the elbow extension and pronation position: at the radial styloid process (point 1), 5 cm proximal to point 1 (point 2), and 10 cm proximal to point 1 (point 3). Results The distance between the SBRN and CV was 1.1 ± 1.0 mm at point 1, 1.3 ± 1.3 mm at point 2, and 2.1 ± 1.6 mm at point 3. The depth of the SBRN from the surface of the skin was 2.7 ± 0.9 mm at point 1, 3.5 ± 1.1 mm at point 2, and 5.5 ± 1.9 mm at point 3. The percentage of the SBRN that ran beneath the CV was 17.5%, 53.5%, and 92.4% at points 1, 2, and 3, respectively. Conclusion Ultrasonography can reveal the anatomical relationship between the SBRN and CV.

Degree of Accuracy With Which Deep Learning for Ultrasound Images Identifies Osteochondritis Dissecans of the Humeral Capitellum.

BACKGROUND: Medical screening using ultrasonography (US) has been performed on young baseball players for early detection of osteochondritis dissecans (OCD) of the humeral capitellum. Deep learning (DL) and artificial intelligence (AI) techniques are widely adopted in the medical imaging research field. PURPOSE/HYPOTHESIS: The purpose of this study was to calculate the diagnostic accuracy using DL for US images of OCD. We hypothesized that using DL for US imaging would improve the prediction accuracy of OCD. STUDY DESIGN: Cohort study (Diagnosis); Level of evidence, 2. METHODS: A total of 40 elbows (mean age of patients, 12.1 years) that were suspected of having OCD at a medical checkup and later confirmed by radiographs and magnetic resonance imaging were included in the study. The affected elbows were used as the OCD group and the contralateral elbows as the control group. From US videos, 100 images per elbow were captured from different angles, and 4000 images of the elbows were prepared for both groups. Of these, 80% were randomly selected by DL models and used as training data; the remaining were used as test data. Transfer learning was conducted using 3 pretrained DL models. The confusion matrix and the area under the receiver operating characteristic curve (AUC) were used to evaluate the model, and the visualization of the areas deemed important by the DL models was also performed. Furthermore, OCD regions were detected using an automatic image recognition model based on DL. RESULTS: Classification of the OCD image by the DL model was performed; the best accuracy score was 0.87; the recall was 1.00. AUC was high for all DL models. Visualization of important features showed that AI predicted the presence of OCD by focusing on the irregularity or discontinuity of the surface of subchondral bone. In the detection of OCD task, the mean average precision was 0.83. CONCLUSION: The DL on US images identified OCD with high accuracy. The important features detected by the DL models correspond to the areas used by clinicians in screening the US images. The OCD was also detected with high accuracy using the object detection model. The AI model may be used in medical screening for OCD.

Assessment of the Ulnar Collateral Ligament of the Elbow Using Ultrasonic Shear Wave Elastography in Professional Baseball Players.

Background: Injury to the ulnar collateral ligament (UCL) of the elbow can cause chronic pain and loss of throwing ability. Ultrasonic shear wave elastography (SWE) is a new imaging method that can be used for quantitative assessment of tissue elasticity. Purpose: To evaluate the properties of the UCL in professional baseball players using SWE. Study Design: Cross-sectional study; Level of evidence, 3. Methods: This study included 35 professional baseball players (mean age, 23.0 years) without elbow injuries. Both elbows of each player were examined using ultrasound, and comparisons between the dominant and nondominant arms were conducted. The thickness of the anterior bundle of the UCL at its midportion was measured in the resting position on ultrasound. We also measured the difference in the ulnohumeral joint space with and without gravity stress on the forearm. Tissue elasticity was evaluated using a built-in software program. The relationship between UCL elasticity and ultrasound findings was analyzed using the Pearson correlation coefficient. Results: The mean ± SD thickness of the UCL was significantly greater in the dominant arm versus the nondominant arm (6.0 ± 1.4 vs 5.3 ± 1.3 mm; P = .004). The mean joint space difference was significantly wider in the dominant arm as compared with the nondominant arm (0.81 ± 0.42 vs 0.52 ± 0.31 mm; P = .002), and the mean UCL elasticity was lower in the dominant arm than in the nondominant arm (34.9 ± 11.6 vs 43.3 ± 10.6 kPa; P = .002). UCL elasticity was negatively correlated with UCL thickness (r = -0.27; P = .02) and joint space difference (r = -0.34; P = .003). Conclusion: In professional baseball players, the elbow UCL of the dominant arm demonstrated increased thickness, with a larger joint space gap on gravity stress and lower elasticity in SWE as compared with the nondominant arm. Greater medial joint laxity can be predicted by assessing the elasticity of the UCL using SWE.

Sex Is Associated with the Success or Failure of Manipulation Alone for Joint Stiffness Associated with Rotator Cuff Repair.

Purpose: One-stage arthroscopic rotator cuff repair with manipulation has been recently performed for rotator cuff tears with shoulder stiffness, whereas some patients require capsular release due to severe stiffness that is difficult to treat with manipulation. The purpose of this study was to analyze patient backgrounds and related factors of success or failure of manipulation alone for the treatment of shoulder stiffness associated with rotator cuff tears. Methods: This study included 64 patients with rotator cuff tears and shoulder stiffness who underwent arthroscopic rotator cuff repair with manipulation alone or with manipulation and capsular release of the glenohumeral joint at our institution between January 2015 and September 2019. The patients were divided into two groups: those whose shoulder stiffness could be improved by manipulation alone (Manipulation group) and those whose stiffness could not be improved by manipulation alone and required capsular release (Capsular release addition group). Analysis was performed between the two groups regarding patient backgrounds and related factors, including rotator cuff tear morphology and range of motions pre- and postoperatively. Results: Exactly 45 patients and 19 patients were included in Manipulation group and Capsular release addition group, respectively. A comparison between the two groups showed that patient age (p = 0.0040), sex (p = 0.0005), and injury due to trauma (p = 0.0018) were significantly related to the success or failure of manipulation alone. Multivariate logistic regression analysis on these three factors showed that sex (odds ratio, 5.5; p = 0.048) was significantly associated with the success or failure of manipulation alone. In both groups, the passive ROM of all patients improved at the last postoperative follow-up compared to their pre-operative values (p < 0.001), except for internal rotation in the Capsular release addition group (p = 0.49). Conclusion: Young male patients who have shoulder stiffness associated with rotator cuff tears should be considered for arthroscopic capsular release rather than manipulation.

Motion Analysis of the Extensor Carpi Ulnaris in Triangular Fibrocartilage Complex Injury Using Ultrasonography Images.

The subsheath of the extensor carpi ulnaris (ECU) tendon, a component of the triangular fibrocartilage complex (TFCC), is particularly important as it dynamically stabilizes the distal radioulnar joint. However, the relationship between TFCC injury and ECU dynamics remains unclear. This study aimed to analyze ECU movement and morphology using ultrasonography (US) images. Twenty wrists of patients with TFCC injury, who underwent TFCC repair, were included in the injury group, and 20 wrists of healthy volunteers were in the control group. For static image analysis, curvature and linearity ratios of the ECU in US long-axis images captured during radioulnar deviation were analyzed. For dynamic analysis of the ECU, the wrist was moved from radial deviation to ulnar deviation at a constant speed, and the velocity of the tendon was analyzed using particle image velocimetry. The static analysis showed that the ECU tendon was more curved in ulnar deviation in the injury group than in the control group, and the dynamic analysis showed that only vertical velocity toward the deep side during ulnar deviation was higher in the injury group. These results suggest that TFCC injury caused ECU curvature during ulnar deviation and increased the vertical velocity of the ECU during wrist deviation.

Novel therapy using a fish scale collagen scaffold for rotator cuff healing in rat models.

BACKGROUND: Large and massive rotator cuff tears are challenging for surgeons because of postoperative complications such as repaired site retears. Recently, collagen extracted from fish scales has gained more attention because fish byproducts are considered a safer collagen source than other animal-derived scaffolds. This study aimed to evaluate the biological efficacy of tilapia scale-derived collagen scaffolds for rotator cuff repair in rat models. METHODS: The infraspinatus tendon was resected from the greater tuberosity of Sprague-Dawley rats. In the control group, the tendon edge was sutured directly to the humeral head. In the augmentation group, the repaired site was augmented with a tilapia scale-derived collagen scaffold. Histologic examinations were performed at 2 and 4 weeks postoperatively via safranin O and immunofluorescence staining (isolectin B4 and type II collagen) in the bone-tendon junction. For mechanical analysis, the ultimate failure load of the tendon-humeral head complex was evaluated at 6 weeks postoperatively. RESULTS: During safranin O staining, the repaired enthesis demonstrated greater proteoglycan staining in the augmentation group than in the control group at 4 weeks postoperatively. Compared to controls, the augmentation group had significantly higher vascular staining with isolectin B4 at 2 and 4 weeks postoperatively, type II collagen expression at 4 weeks postoperatively, and ultimate failure load at 6 weeks postoperatively. CONCLUSION: Augmentation therapy using tilapia scale-derived type I collagen scaffolds promoted angiogenesis and fibrocartilage regeneration at the enthesis and provided higher mechanical strength than controls.

Using deep learning for ultrasound images to diagnose carpal tunnel syndrome with high accuracy.

Recently, deep learning (DL) algorithms have been adapted for the diagnosis of medical images. The purpose of this study was to detect image features using DL without measuring median nerve cross-sectional area (CSA) in ultrasonography (US) images of carpal tunnel syndrome (CTS) and calculate the diagnostic accuracy from the confusion matrix obtained. US images of 50 hands without CTS and 50 hands diagnosed with CTS were used in this study. The short-axis image of the median nerve was visualized, and 5000 images of both groups were prepared. Forty hands in each group were used as training data for the DL algorithm, while the remainder were used as test data. Transfer learning was performed using three pre-trained models. The confusion matrix and receiver operating characteristic curves were used to evaluate diagnostic accuracy. Furthermore, regions where DL was determined to be important were visualized. The highest score had an accuracy of 0.96, precision of 0.99 and recall of 0.94. Visualization of the important features revealed that the DL models focused on the epineurium of the median nerve and the surrounding soft tissue. The proposed technique enables the accurate prediction of CTS without measurement of the CSA.

Quercetin treatment protects the Achilles tendons of rats from oxidative stress induced by hyperglycemia.

BACKGROUND: Quercetin, a flavonoid abundantly in vegetables and fruits, exerts antioxidant and anti-inflammatory effects. We investigated the protective effects of quercetin against oxidative stress in the Achilles tendons of diabetic rats. METHODS: Cells were collected from the Achilles tendons of Sprague-Dawley rats and cultured under four conditions: regular glucose (RG) without quercetin (Quer-), RG with quercetin (Quer +), high-glucose (HG) Quer-, and HG Quer + . The expression of genes related to NADPH oxidase (NOX) and inflammation, reactive oxygen species accumulation, and apoptosis rates was analyzed. Additionally, diabetic rats were divided into two groups and subjected to quercetin (group Q) or no quercetin (group C) treatment. Histological evaluation and expression analysis of relevant genes in the Achilles tendon were performed. RESULTS: In rat tendon-derived cells, the expression of Nox1, Nox4, and Il6; reactive oxygen species accumulation; and apoptosis rates were significantly decreased by quercetin treatment in the HG group. The collagen fiber arrangement was significantly disorganized in the diabetic rat Achilles tendons in group C compared with that in group Q. The mRNA and protein expression levels of NOX1 and NOX4 were significantly decreased upon quercetin treatment. Furthermore, the expression of Il6, type III collagen, Mmp2, and Timp2 was significantly decreased, whereas that of type I collagen was significantly increased in group Q compared with that in group C. CONCLUSIONS: Quercetin treatment decreases NOX expression and thus exerts antioxidant and anti-inflammatory effects in the Achilles tendons of diabetic rats. Quercetin treatment may be effective against diabetic tendinopathy.

Influence of Diabetes-Induced Glycation and Oxidative Stress on the Human Rotator Cuff.

Most shoulder rotator cuff tears (RCTs) are caused by non-traumatic age-related rotator cuff degeneration, of which hyperglycemia is a risk factor due to its glycation reaction and oxidative stress. We aimed to identify the influence of diabetes-induced glycation and oxidative stress in patients with non-traumatic shoulder RCTs. Twenty patients, aged over 50 years, with non-traumatic shoulder RCTs participated in this study. Patients with a history of diabetes mellitus or preoperative HbA1c ≥ 6.5% were assigned to the diabetic group (n = 10), and the rest to the non-diabetic group (n = 10). Cell proliferation; expression of genes related to oxidative stress, glycation reaction, inflammation, and collagen; intracellular reactive oxygen species (ROS) levels; and apoptosis rates were analyzed. The diabetic group had significantly lower cell proliferation than the non-diabetic group. In the diabetic group, the mRNA expression levels of NOX1, NOX4, IL6, RAGE, type III collagen, MMP2, TIMP1, and TIMP2 were significantly higher; type I collagen expression was significantly lower; and the rate of ROS-positive cells and apoptotic cells, as well as the expression of advanced glycation end-products (AGEs) and the receptor for AGEs (RAGE), was significantly higher. In conclusion, hyperglycemia caused by diabetes mellitus increased AGE and RAGE expression, and led to increased NOX expression, ROS production, and apoptosis in the human rotator cuff. This provides scope to find a preventive treatment for non-traumatic RCTs by inhibiting glycation and oxidative stress.