Evaluation and risk communication of the effects of alcohol exposure on disposable procedure masks and portable air purifiers in hospital environments.

Electret technology was widely used to prevent the airborne transmission of bioaerosols during the COVID-19 pandemic and improve the filtration efficiency of masks and high-efficiency particulate air (HEPA) filters. As alcohol disinfectants are widely used in medical and welfare institutions, concerns about alcohol exposure inactivating electret exist. However, comprehensive alcohol exposure tests have not been conducted on masks and HEPA filters distributed in Japan. Twenty-five types of masks and five types of HEPA filters were subjected to a discharging process according to ISO 16890 to quantitatively elucidate the resistance to alcohol exposure. Measurements of changes in filtration efficiency and pressure drop before and after discharge show that 17 masks (68%) and four HEPA filters (80%) exhibited a significant decrease in filtration efficiency, confirming their vulnerability to alcohol. In addition, a survey (n = 500 Japanese adults, including 30 healthcare professionals) revealed that ∼90% of the general public were unaware that alcohol exposure could degrade masks and air purifiers. Furthermore, 36% of the surveyed healthcare professionals had sprayed alcohol directly onto their masks. The effectiveness of user warnings through product labels and instructions was investigated from the perspective of ensuring the safety of patients and healthcare professionals. Results revealed that the best approach was to describe the extent and duration of the adverse effects caused by disregarding precautions. Increase in awareness of healthcare professionals and general public by authorities and manufacturers through guidelines and warning labels would reduce the risk of inhaling bioaerosols caused by unintentional electret inactivation.

Infectious virus shedding duration reflects secretory IgA antibody response latency after SARS-CoV-2 infection.

Infectious virus shedding from individuals infected with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is used to estimate human-to-human transmission risk. Control of SARS-CoV-2 transmission requires identifying the immune correlates that protect infectious virus shedding. Mucosal immunity prevents infection by SARS-CoV-2, which replicates in the respiratory epithelium and spreads rapidly to other hosts. However, whether mucosal immunity prevents the shedding of the infectious virus in SARS-CoV-2-infected individuals is unknown. We examined the relationship between viral RNA shedding dynamics, duration of infectious virus shedding, and mucosal antibody responses during SARS-CoV-2 infection. Anti-spike secretory IgA antibodies (S-IgA) reduced viral RNA load and infectivity more than anti-spike IgG/IgA antibodies in infected nasopharyngeal samples. Compared with the IgG/IgA response, the anti-spike S-IgA post-infection responses affected the viral RNA shedding dynamics and predicted the duration of infectious virus shedding regardless of the immune history. These findings highlight the importance of anti-spike S-IgA responses in individuals infected with SARS-CoV-2 for preventing infectious virus shedding and SARS-CoV-2 transmission. Developing medical countermeasures to shorten S-IgA response time may help control human-to-human transmission of SARS-CoV-2 infection and prevent future respiratory virus pandemics.

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.

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.

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.

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.

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.

Real-World Data Analysis of Pembrolizumab Monotherapy for NSCLC Using Japanese Postmarketing All-Case Surveillance Data.

Introduction: Pembrolizumab is a programmed death-ligand 1 inhibitor that was initially indicated for monotherapy in patients with advanced lung cancer. The Japanese Lung Cancer Society conducted an observational study on pembrolizumab using confirmative data obtained through postmarketing all-case surveillance (PMACS), which was performed by a pharmaceutical company under the Japanese law in 2017. Methods: This multicenter observational study was conducted by the Japanese Lung Cancer Society using PMACS data with the newly created central registration system regarding patients with NSCLC who received pembrolizumab monotherapy between February 1, 2017 and June 30, 2017; a new database was created by adding the clinical information regarding prognosis for 3 years after therapy to the existing data collected by PMACS. Results: A total of 300 patients from 43 facilities were enrolled in this study. The median overall survival and progression-free survival after pembrolizumab initiation were 558 and 188 days, respectively. Moreover, the 1- and 3-year survival rates were 58.9% and 33.7%, respectively. Results of multivariate analysis revealed performance status (p < 0.0001), histology (p = 0.0118), previous chemotherapy (p = 0.0007), programmed death-ligand 1 expression status (p = 0.0195), and previous steroid use (p = 0.0460) as significant factors that affected overall survival. The toxicity profile was similar to that previously reported. Conclusions: In this first attempt to use PMACS data, we successfully collected clinical information and found the real-world efficacy and safety of pembrolizumab.

Effectiveness of HEPA Filters at Removing Infectious SARS-CoV-2 from the Air.

Coronavirus disease 2019 (COVID-19) spreads by airborne transmission; therefore, the development and functional evaluation of air-cleaning technologies are essential for infection control. Air filtration using high-efficiency particulate air (HEPA) filters may be effective; however, no quantitative assessment of the effectiveness of these filters in the removal of infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from the air has been reported. To evaluate the removal effect of HEPA filtration on airborne SARS-CoV-2, here, we disseminated infectious SARS-CoV-2 aerosols in a test chamber in a biosafety level 3 facility and filtered the air with a HEPA-filtered air cleaner in the chamber. The air cleaner with the HEPA filter continuously removed the infectious SARS-CoV-2 from the air in a running-time-dependent manner, and the virus capture ratios were 85.38%, 96.03%, and >99.97% at 1, 2, and 7.1 ventilation volumes, respectively. The air-cleaning performance of a HEPA filter coated with an antiviral agent consisting mainly of a monovalent copper compound was also evaluated, and the capture ratio was found to be comparable to that of the conventional HEPA filter. This study provides insights into the proper use and performance of HEPA-filtered air cleaners to prevent the spread of COVID-19. IMPORTANCE Air filtration simulation experiments quantitatively showed that an air cleaner equipped with a HEPA filter can continuously remove SARS-CoV-2 from the air. The capture ratios for SARS-CoV-2 in the air when the air cleaner was equipped with an antiviral-agent-coated HEPA filter were comparable to those with the conventional HEPA filter, and there was little effect on SARS-CoV-2 in the air that passed through the antiviral-reagent-coated HEPA filter.

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.

Biochemical Markers of Aging (Advanced Glycation End Products) and Degeneration Are Increased in Type 3 Rotator Cuff Tendon Stumps With Increased Signal Intensity Changes on MRI.

BACKGROUND: Advanced glycation end products (AGEs) are end products of protein glycation that bind to the receptor for AGEs (RAGE) and activate nicotinamide adenine dinucleotide phosphate oxidase (NOX), resulting in increased oxidative stress and rotator cuff fragility. Stump classification using the signal intensity ratio of the tendon rupture site to the deltoid muscle in the coronal view of T2-weighted fat-suppressed magnetic resonance imaging (MRI) scans is an indicator of clinical outcomes after rotator cuff repair surgery. Comparing the signal intensities of the deltoid (D) and rotator cuff tears (C), Ishitani et al. classified C/D <0.8 as type 1, 0.8 to 1.3 as type 2, and >1.3 as type 3. HYPOTHESIS/PURPOSE: It was hypothesized that the oxidative stress and collagen degeneration that occur in the rotator cuff due to accumulation of AGEs can be assessed on MRI scans (stump classification). Therefore, this study aimed to compare AGE-related factors in the rotator cuff tear site tissues based on stump classification. STUDY DESIGN: Descriptive laboratory study. METHODS: The authors included 30 patients (11 with type 1, 9 with type 2, and 10 with type 3; mean age, 62.3 years) who underwent surgery for complete rotator cuff tears at our hospital. Tendon tissue was harvested from the torn rotator cuff site during surgery for tissue and cell evaluation. RESULTS: There was no significant difference in the mean age according to stump classification. The number of patients with diabetes was significantly larger in type 3 than in the other types (P < .05). Tissue evaluation showed significantly higher expression of AGE and RAGE staining in type 3 than in the other types (~6.7-fold; P < .01). Cell evaluation showed that the expression rates of reactive oxygen species and apoptosis were significantly higher in type 3 than in the other types (~4.3-fold; P < .01). Gene expression by real-time polymerase chain reaction showed significantly higher RAGE (~5.1-fold), NOX (~5.3-fold), and IL (~3.0-fold) in type 3 than in the other types (P < .05). CONCLUSION: Stump classification type 3 exhibited the highest accumulation of AGEs and the highest oxidative stress and apoptosis, suggesting a high degree of degeneration and inflammation. Imaging based on stump classification reflects the degeneration and fragility of the torn rotator cuff site. CLINICAL RELEVANCE: This study provides evidence of a relationship between stump classification, which reflects rotator cuff fragility on MRI, and pathologies related to advanced glycation end products.

Diagnosis of Cubital Tunnel Syndrome Using Deep Learning on Ultrasonographic Images.

Although electromyography is the routine diagnostic method for cubital tunnel syndrome (CuTS), imaging diagnosis by measuring cross-sectional area (CSA) with ultrasonography (US) has also been attempted in recent years. In this study, deep learning (DL), an artificial intelligence (AI) method, was used on US images, and its diagnostic performance for detecting CuTS was investigated. Elbow images of 30 healthy volunteers and 30 patients diagnosed with CuTS were used. Three thousand US images were prepared per each group to visualize the short axis of the ulnar nerve. Transfer learning was performed on 5000 randomly selected training images using three pre-trained models, and the remaining images were used for testing. The model was evaluated by analyzing a confusion matrix and the area under the receiver operating characteristic curve. Occlusion sensitivity and locally interpretable model-agnostic explanations were used to visualize the features deemed important by the AI. The highest score had an accuracy of 0.90, a precision of 0.86, a recall of 1.00, and an F-measure of 0.92. Visualization results show that the DL models focused on the epineurium of the ulnar nerve and the surrounding soft tissue. The proposed technique enables the accurate prediction of CuTS without the need to measure CSA.

Advanced glycation end products are associated with limited range of motion of the shoulder joint in patients with rotator cuff tears associated with diabetes mellitus.

BACKGROUND: Most degenerative rotator cuff tears (RCTs) are associated with a limited range of motion (ROM) of the shoulder joint. Additionally, patients with diabetes mellitus (DM) show a higher frequency of limited ROM. Recently, advanced glycation end products (AGEs) of proteins have been observed to cause tissue fibrosis, primarily through abnormal collagen cross-linking and oxidative stress. In this study, we investigated the effect of AGEs on ROM limitation in the shoulder capsule and its relationship with DM in the patients with RCTs. METHODS: Sixteen patients (eight in the DM and non-DM groups) who underwent arthroscopic surgery for RCT with limited shoulder ROM were included in this study. AGE-related pathologies in both groups were compared, and the relationship between AGE accumulation and shoulder joint ROM was evaluated. Shoulder capsule tissue was harvested and subjected to histological and in vitro evaluation. RESULTS: The DM group displayed high levels of AGEs and reactive oxygen species (ROS), and reduced cell viability. There was a significant positive correlation between ROS expression, apoptosis, and preoperative hemoglobin A1c. ROS expression, apoptosis, and ROM of the shoulder joint showed a negative correlation. The NADPH oxidase (NOX) expression and collagen III/I ratio were significantly higher in the DM group than in the non-DM group. CONCLUSIONS: The DM group showed significant AGEs deposition in the shoulder capsule. Additionally, there was a significant association between AGEs and ROM limitation. Collectively, the findings suggest that the oxidative stress induced by AGEs deposition, which leads to fibrosis and local inflammation, might contribute to the limited ROM of the shoulder joint in patients with RCTs accompanied by DM.

Motion Analysis of Triangular Fibrocartilage Complex by Using Ultrasonography Images: Preliminary Analysis.

The triangular fibrocartilage complex (TFCC) is a significant stabilizer of the distal radioulnar joint. Diagnosing TFCC injury is currently difficult, but ultrasonography (US) has emerged as a low-cost, minimally invasive diagnostic tool. We aimed to quantitatively analyze TFCC by performing motion analysis by using US. Twelve healthy volunteers, comprising 24 wrists (control group), and 15 patients with TFCC Palmer type 1B injuries (injury group) participated. The US transducer was positioned between the ulnar styloid process and triquetrum and was tilted ulnarly 30° from the vertical line. The wrist was then actively moved from 10° of radial deviation to 20° of ulnar deviation in a 60-rounds-per-minute rhythm that was paced by a metronome. The articular disc displacement velocity magnitude was analyzed by using particle image velocimetry fluid measurement software. The mean area of the articular discs was larger on ulnar deviation in the control group. The mean articular disc area on radial deviation was larger in the injury group. The average articular disc velocity magnitude for the injury group was significantly higher than that for the control group. The results suggest that patients with TFCC injury lose articular disc cushioning and static stability, and subsequent abnormal motion can be analyzed by using US.

Influence of adiponectin and inflammatory cytokines in fatty degenerative atrophic muscle.

Tendon rupture and nerve injury cause fatty infiltration of the skeletal muscle, and the adipokines secreted from the infiltrated adipocytes are known to contribute to chronic inflammation. Therefore, in this study, we evaluated the effects of the adipokines on chronic inflammation using a rat sciatic nerve-crushed injury model. In vitro and in vivo experiments showed that the expression of adiponectin was decreased (0.3-fold) and the expression of Il6 (~ 3.8-fold) and Tnf (~ 6.2-fold) was increased in the nerve-crushed group compared to that in the control group. It was also observed that the administration of an adiponectin receptor agonist decreased the levels of Il6 (0.38-fold) and Tnf (0.28-fold) and improved cellular viability (~ 1.9-fold) in vitro. Additionally, in the fatty infiltrated skeletal muscle, low adiponectin levels were found to be associated with chronic inflammation. Therefore, the local administration of adiponectin receptor agonists would prevent chronic inflammation.