Hand Joints Research Articles

Understanding the Role of Type I Interferons in Cutaneous Lupus and Dermatomyositis: Toward Better Therapeutics.

A 29-year-old female presented to a rheumatology-dermatology clinic with a pruritic rash that began 6 months prior, after a viral illness. She had previously been diagnosed with eczema and treated with antihistamines and topical steroids without improvement. She also noted fatigue, hair loss, and severe scalp pruritus. Physical examination was notable for violaceous periorbital edema, scaly erythematous papules on the metacarpophalangeal joints of bilateral hands, dilated capillaries of the proximal nail folds, scaly plaques on bilateral elbows, and excoriated erythematous plaques on upper chest, back and hips. The patient reported no muscle weakness, and strength testing and creatinine phosphokinase were normal. Magnetic resonance imaging of the thigh showed no evidence of inflammation or edema. Antibody testing was negative. A diagnosis of clinically amyopathic dermatomyositis was made. Computed tomography scans of the chest, abdomen and pelvis, colonoscopy, and mammogram showed no evidence of cancer. The patient was initiated on methotrexate. Her cutaneous manifestations persisted with debilitating intractable pruritus, and thus, she was transitioned to mycophenolate mofetil, again with minimal improvement. Intravenous immunoglobulin was not approved by insurance given the lack of muscle involvement in her disease. This patient's case highlights a common clinical scenario in rheumatology and dermatology and raises several important issues related to the immunologic underpinnings of cutaneous lupus erythematosus (CLE) and dermatomyositis (DM): What is the role of type I interferon (IFN) in triggering skin disease in CLE and DM? What is the role of IFN in the pathogenesis of skin inflammation in CLE and DM? Can we apply what we know about IFN-targeted therapeutics in CLE and DM to develop better treatments for skin disease?

Drug-resistant epilepsy cases in chromosomal pathology

Two cases of epilepsy in patients with a rare hereditary pathology associated with a chromosomal mutation caused deletion of chromosome 14 are presented. In the first case, this pathology was manifested in the child by generalized tonic-clonic seizures, delayed psycho-verbal development, and facial skull microanomaly. In the second case, it was expressed in tonic epileptic seizures, delayed psycho-verbal development, developmental microanomalies, pyramidal atactic syndrome and hand joint hypermobility. Such clinical observations are of professional and scientific interest, as they relate to a rare neurological pathology, with drug-resistant epilepsy as a leading sign.

Using 3D Hand Pose Data in Recognizing Human–Object Interaction and User Identification for Extended Reality Systems

Object detection and action/gesture recognition have become imperative in security and surveillance fields, finding extensive applications in everyday life. Advancement in such technologies will help in furthering cybersecurity and extended reality systems through the accurate identification of users and their interactions, which plays a pivotal role in the security management of an entity and providing an immersive experience. Essentially, it enables the identification of human–object interaction to track actions and behaviors along with user identification. Yet, it is performed by traditional camera-based methods with high difficulties and challenges since occlusion, different camera viewpoints, and background noise lead to significant appearance variation. Deep learning techniques also demand large and labeled datasets and a large amount of computational power. In this paper, a novel approach to the recognition of human–object interactions and the identification of interacting users is proposed, based on three-dimensional hand pose data from an egocentric camera view. A multistage approach that integrates object detection with interaction recognition and user identification using the data from hand joints and vertices is proposed. Our approach uses a statistical attribute-based model for feature extraction and representation. The proposed technique is tested on the HOI4D dataset using the XGBoost classifier, achieving an average F1-score of 81% for human–object interaction and an average F1-score of 80% for user identification, hence proving to be effective. This technique is mostly targeted for extended reality systems, as proper interaction recognition and users identification are the keys to keeping systems secure and personalized. Its relevance extends into cybersecurity, augmented reality, virtual reality, and human–robot interactions, offering a potent solution for security enhancement along with enhancing interactivity in such systems.

DM-HAP: Diffusion model for accurate hand pose prediction

Forecasting hand poses is a challenging task due to inherent uncertainties, occlusions, and inaccuracies in 3D pose estimation. Diffusion models provide a promising direction for predicting precise 3D hand poses under noisy conditions. In this work, we introduce Dual-diffusion, an innovative framework for the precise prediction of future hand poses. Our approach leverages the strengths of diffusion models by framing hand pose forecasting as a reverse diffusion process, effectively addressing the complexities of noisy hand joint movements and their subtleties. To enhance the learning of hand pose representations, we propose a unique neural architecture that simultaneously captures both local and global features. This is achieved through the deployment of Global and Local Diffusion (GLD) blocks within our network, which facilitate the exchange of information between local and global features. This diffusion-based interaction enables the integration of global hand actions and local finger actions, leading to a more powerful representation learning approach. We evaluate the effectiveness of our Dual-diffusion method on three public 3D hand pose estimation datasets (MSRA, F-PHAB, and BigHand2.2M), and our approach outperforms previous methods.

Clinical utility of extracorporeal shock wave therapy in restoring hand function of patients with nerve injury and hypertrophic scars due to burns: A prospective, randomized, double-blinded study.

Joint contractures and nerve injuries are common after hand burns. Extracorporeal shock wave therapy (ESWT) is effective not only for the regeneration of various tissues, including scar tissues, but also for reducing pain and pruritus in patients with burns. Researchers have attempted to explore the effects of ESWT on hand dysfunction caused by nerve injury following burns. We evaluated the effects of ESWT (compared to sham stimulation) on hands with nerve injury and hypertrophic scars and thereby on hand function. The current study was a double-blind randomized controlled trial involving 120 patients. The ESWT parameters were as follows: energy flux density, 0.05-0.30mJ/mm2; frequency, 4Hz; 1000 to 3000 impulses per treatment; and 12 treatments, one/week for 12 weeks. Outcome measures were as follows: 10-point visual analog scale for pain, Jebsen-Taylor hand function test, grip strength, Purdue Pegboard test, ultrasound measurement of scar thickness, and skin characteristics before and immediately after 12 weeks of treatment. No significant inter-group difference was noted after the initial evaluation (P>0.05). More significant improvements were found in the ESWT group than in the sham group in terms of the VAS score (P=0.004), extension ROMs of hand joints (P=0.02), the JTT scores (writing, small, and light) (P<0.001, P<0.001, and P=0.002), and skin characteristics (melanin, skin distensibility, and biologic skin elasticity) (P=0.004, P<0.001, and P<0.001). Other measured outcomes did not differ between the two groups after the treatment. We identified the clinically beneficial effects of ESWT in promoting hand function, improving scarring, and alleviating scarring-related pain, thereby highlighting its advantages in improving hand function that has been impaired due to nerve injury and hypertrophic scars after burns.

Design and Implementation of Gesture Music Composition System based on RealSense and Recurrent Neural Network

Aiming at the problems of slow human-computer interaction and low accuracy of hand gesture recognition (HGR) in music composition systems such as human-computer interaction, gesture recognition, and algorithmic composition, this paper designs an HGR music composition system based on real-sense technology and recurrent neural network. The system uses an Intel RealSense 3D camera to shoot the user's hand and extract the information on the hand joint points with Smart Wearable Biosensors (SWBSs). The joint points are used to construct a three-dimensional model of the hand bone, and the joint points' equivalent distance and joint deflection are calculated by the joint point information to match the corresponding Curwen HGR. The matching music data is input into the recurrent neural network. GRU is combined with the Markov chain algorithm to complete the composition and avoid the phenomenon of gradient disappearance or gradient explosion. The HGR recognition function and composition algorithm are simulated and tested to verify the method's feasibility. Cohort verification investigations and efficacy evaluations of wearable biosensors are essential to support their clinical acceptability. The research results show that the HGR music composition system based on real-sense technology and recurrent neural networks can effectively identify the tester's HGRs and assist the tester in completing the composition using intelligent biosensors. The composition mode is close to the professional composition process.

Hand Osteoarthritis and Subclinical Cardiovascular Disease in Middle-Aged Women.

Objective: To determine subclinical cardiovascular disease (sCVD) in middle-aged women with clinically manifested hand osteoarthritis (HOA) and to improve the characterization of cardiovascular risk in this population. Design: We cross-sectionally evaluated the relationship between HOA and sCVD in 1,803 volunteers from the Mexican Teachers' Cohort. From 2012 to 2016, a subsample from Mexico City, the Northern state Nuevo León, and the Southern states Chiapas and Yucatán was invited for clinical evaluations, during which neurologists examined carotid arteries using ultrasound, and a standardized HOA questionnaire was also administered. HOA was defined as age ≥45 years, hand joint pain, and morning stiffness that lasted no longer than 30 minutes. sCVD was assessed using the intima-media thickness (IMT) and atherosclerotic plaques. Results: Among participants with a mean age of 51 years (±4), 18.4% met the criteria for HOA, and the prevalence of carotid atherosclerosis was 23.1%. After multivariable adjustment, women diagnosed with HOA had a 1.8% (95% confidence interval [CI] 0.3, 3.3) greater mean IMT than those without this joint disease. Similarly, women with HOA had 36% (95% CI 1.01, 1.84) higher odds of carotid atherosclerosis. Conclusions: HOA is associated with sCVD in middle-aged women. This relationship might be due to low-grade chronic inflammation; however, further research is required to clarify the underlying mechanisms.

Unravelling a hidden pathology of a vertebral fracture in a teenage girl

BackgroundAlthough the skeleton remains a common target of primary hyperparathyroidism, the classic bone disease “osteitis fibrosa cystica” is currently rare due to early diagnosis. This case represents severe classic bone manifestations of primary hyperparathyroidism due to delayed diagnosis and delayed medical attention.Case presentationA 19-year-old young female was symptomatically managed for chronic back pain and nonspecific bone pain in the small joints of both hands over 2 months by a general practitioner. The patient had delayed seeking for treatment for 3 months. Later, she was evaluated for tuberculosis, hematological malignancies and rheumatic disorders following a fractured T12 vertebra and underwent pedicle screw fixation. However, clinical examination and investigations, including biochemistry, imaging and histology, ruled out the above conditions. Unfortunately, serum calcium level was not performed at the initial presentation. Later, primary hyperparathyroidism was diagnosed on the basis of moderate hypercalcaemia and elevated intact PTH levels (2064 pg/ml). She had sufficient vitamin D levels and normal kidney function. Her DXA scan revealed severe secondary osteoporosis with the lowest Z score of -8 at the total lumbar spine. Ultrasonography of the thyroid revealed a hypo echoic mass in the left lower neck, and localization studies with technetium-99 m sestamibi and 4D-CT revealed a left inferior parathyroid adenoma (1.6 × 1.5 × 1.6 cm). CT scan also revealed brown tumors in the mandible and vertebrae and diffuse bony changes in the skull, sternum, humerus and vertebrae. Her radiographs revealed subperiosteal bone resorption on the radial aspects of the middle and distal phalanges and brown tumors in both the ulna and fibula. We excluded MEN and other hereditary syndromes in our patient with a personal and family history and with a normal pituitary hormone profile because of poor resources for genetic testing. She underwent parathyroid adenoma excision, and the postoperative period was complicated with hungry bone syndrome, requiring high doses of calcium and active vitamin D supplements. These supplements were gradually weaned off over 6 months, and she recovered with normal biochemical investigations. Histology revealed parathyroid adenoma without malignant features.ConclusionIn developing countries where routine calcium screening is not available, clinicians should be aware of various manifestations of primary hyperparathyroidism to allow diagnosis as soon as possible without delay to prevent further progression, as it is a treatable condition.

The effect of arm muscle discrete relaxation training and fine-coordination training on proprioceptive control

Proprioception makes an important contribution to the regulation of speed, strength and spatial parameters of movements, determining the level of proficiency in motor skills. However, the effectiveness of various training approaches in relation to voluntary proprioceptive control of target muscles has not been sufficiently studied. In this paper, we investigated the effectiveness of three types of manipulative training: 1) fine coordination, 2) discrete muscle relaxation and 3) their combinations in relation to the accuracy of reproducing:а) the angular deviation of the joystick from the vertical and b) static muscle efforts during the pronation and supination of the joystick. The study involved 40 young (18-35 years old), physically active volunteers who randomly made up 4 groups of 10 people: “Control” (lack of training), “Coordination” (training of passing an analog of a slit maze with a thin probe), “Discrete relaxation” (training of discrete muscle relaxation of pronators and supinators of the forearm), “Combined” (combined training of maze passing and discrete relaxation). Before and after training (n = 10) we evaluated: 1) the accuracy of reproduction of the deviation of the wrist joystick from the vertical by 20, 50, 80 degrees and 2) the accuracy of reproduction of isometric contraction (0, 20, 50 and 80% of the maximum effort) in the descending, ascending directions as well as discrete achievement of any effort level by pronation /supination of the wrist joystick. It was found that coordination training increased the length of the traversed path in 3 minutes with a reduced number of errors, and increased the proprioceptive accuracy of reproducing the angle of deviation of the joystick by 20 degrees also. In the “Discrete Relaxation” group the average modulus of errors in reproducing descending, ascending and discrete forces during supination, as well as the average modulus of errors in reproducing descending, ascending and discrete forces during forearm pronation decreased after course training. At the same time, no changes in the accuracy of reproducing the angular positions of the joystick were found in this group. In the “Combined” group, training led to an increase in the accuracy of reproducing ascending and descending efforts during pronation, as well as the accuracy of descending efforts during supination of the forearm. In addition, in this group, a decrease in the error modulus during reproducing the tilt of the joystick by 50 degrees by supination was revealed. Correlation analysis did not reveal positive links between training changes in proprioceptive control of different modality. Thus, the training effects used on the target muscles of the forearm have a specific effect on the proprioceptive control of muscle effort and spatial position in the hand joints. The high efficiency of discrete relaxation training regarding the accuracy of voluntary efforts allows us to recommend its use in order to increase the level of mastery of the motor skills of the hand.

Sonoanatomy of the Finger Synovio-Entheseal Complexes

ObjectivesThe objectives of this ultrasound and anatomical study were: (1) To evaluate the reliability of ultrasound identification of the enthesis of the central slip of the extensor digitorum tendon (CSET) using cadaver specimens; (2) To assess the concordance of the measurement of the CSET thickness by ultrasound and gross anatomy; (3) To evaluate the variation in ultrasound identification of the CSET enthesis in a cadaveric experimental model of PIP synovitis. MethodsFour rheumatologist ultrasonographers blindly and independently measured by ultrasound the CSET enthesis thickness in the second to fifth fingers of 8 hands from fresh-frozen human cadavers in two rounds. These fingers were dissected and the thickness of the CSET measured by the anatomist. In addition, an artificial synovitis was created in the proximal interphalangeal (PIP) joints of a different cadaveric hand. The ultrasonographic CSET enthesis thickness was measured by the four investigators before and after intra-articular ultrasound guided injection of material. ResultsIntra- and inter-observer reliability of CSET enthesis thickness measurement were good to excellent (ICC 0.93 for intra-observer agreement and 0.89–0.92 for inter-observer agreement). Ultrasound measurements were consistent and only slightly smaller than the anatomical ones (µ = -0.039 mm). The differences between the measurements of CSET enthesis thickness before and after the synovitis model were not statistically significant. ConclusionUltrasound demonstrated high multiobserver reliability and agreement with gross anatomy in identifying the CSET enthesis and discriminated it from the capsular tissue of the PIP. Furthermore, an experimental model of PIP synovitis did not interfere with its identification.

Validity and reliability of a finger training tool for assessing metacarpal phalangeal joint ranges of motion in asymptomatic participants

This pilot study aims to evaluate concurrent validity using the goniometer as a reference tool and test–retest reliability of flexion of metacarpal phalangeal joint (MCP) measurements taken from a finger training device (air-guitar system) in healthy participants. There were ten self -reported asymptomatic participants recruited to test the devices. The measurements of all metacarpophangeal joints of the dominant hands were conducted using a finger goniometer and the air-guitar system. Two measuring sessions were conducted on the same day. The concurrent validity of the air-guitar indicated by strong concordance correlation coefficient (0.62–0.90) with the goniometer and mean difference (approximately 1°) between the two instruments are well below the limit of 5°. The test–retest reliability of MCP measurements from the air-guitar glove (0.82–0.99) was acceptable as a clinically meaningful measurement tool as the intraclass correlation coefficients were higher than 0.7. The standard error of measurement and minimal detectable change of the air-guitar are similar to those of the goniometer. The air-guitar tracking features, when used as a home-based therapy tool, may assist in monitoring change of MCP flexion over a time course with good reliability and strongly associated with the measurements from the goniometer.

Infectious wrist arthritis complicating acute carpal tunnel syndrome in a child: A CARE-compliant case report.

The objective of this case report is to provide clinical evidence that acute infectious wrist arthritis in children can lead to the rare condition of acute carpal tunnel syndrome (ACTS). This article discusses in detail the characteristics of infectious wrist arthritis complicating ACTS in children in terms of etiology, pathogenic bacteria, treatment modalities, and sequelae to improve the understanding of this disease. A 10-year-old male child presented with a 15-day history of swelling and pain in the left forearm, wrist, and hand. Left-sided infected wrist arthritis complicating ACTS. The child received emergency surgery and anti-infective treatment combined with regular rehabilitation. During the treatment period, the child's wrist pain and swelling gradually improved, and wrist movement was restored compared with the preoperative period. At 6-month follow-up, the activities of the metacarpophalangeal joints of the left hand were close to normal, and the flexion of the left wrist joint was slightly limited. In infectious wrist arthritis in children, ACTS is a serious complication that requires aggressive surgical carpal tunnel release to avoid median nerve injury in addition to anti-infective therapy.

Wearable high-density EMG sleeve for complex hand gesture classification and continuous joint angle estimation

High-density electromyography (HD-EMG) can provide a natural interface to enhance human–computer interaction (HCI). This study aims to demonstrate the capability of a novel HD-EMG forearm sleeve equipped with up to 150 electrodes to capture high-resolution muscle activity, decode complex hand gestures, and estimate continuous hand position via joint angle predictions. Ten able-bodied participants performed 37 hand movements and grasps while EMG was recorded using the HD-EMG sleeve. Simultaneously, an 18-sensor motion capture glove calculated 23 joint angles from the hand and fingers across all movements for training regression models. For classifying across the 37 gestures, our decoding algorithm was able to differentiate between sequential movements with 97.3±0.3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$97.3 \\pm 0.3\\%$$\\end{document} accuracy calculated on a 100 ms bin-by-bin basis. In a separate mixed dataset consisting of 19 movements randomly interspersed, decoding performance achieved an average bin-wise accuracy of 92.8±0.8%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$92.8 \\pm 0.8\\%$$\\end{document}. When evaluating decoders for use in real-time scenarios, we found that decoders can reliably decode both movements and movement transitions, achieving an average accuracy of 93.3±0.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93.3 \\pm 0.9\\%$$\\end{document} on the sequential set and 88.5±0.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$88.5 \\pm 0.9\\%$$\\end{document} on the mixed set. Furthermore, we estimated continuous joint angles from the EMG sleeve data, achieving a R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2$$\\end{document} of 0.884±0.003\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.884 \\pm 0.003$$\\end{document} in the sequential set and 0.750±0.008\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.750 \\pm 0.008$$\\end{document} in the mixed set. Median absolute error (MAE) was kept below 10° across all joints, with a grand average MAE of 1.8±0.04∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.8 \\pm 0.04^\\circ$$\\end{document} and 3.4±0.07∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3.4 \\pm 0.07^\\circ$$\\end{document} for the sequential and mixed datasets, respectively. We also assessed two algorithm modifications to address specific challenges for EMG-driven HCI applications. To minimize decoder latency, we used a method that accounts for reaction time by dynamically shifting cue labels in time. To reduce training requirements, we show that pretraining models with historical data provided an increase in decoding performance compared with models that were not pretrained when reducing the in-session training data to only one attempt of each movement. The HD-EMG sleeve, combined with sophisticated machine learning algorithms, can be a powerful tool for hand gesture recognition and joint angle estimation. This technology holds significant promise for applications in HCI, such as prosthetics, assistive technology, rehabilitation, and human–robot collaboration.

Additional Value of Ultrasound in Patients with Psoriatic Arthritis within Treatment Target.

Background: In psoriatic arthritis (PsA), musculoskeletal ultrasound is a complementary tool to physical examination, useful even in patients in remission to detect subclinical activity. Objectives: The objective of the study was to assess the ultrasound prevalence of active enthesitis and synovitis in patients who reached the therapeutic target. Methods: This cross-sectional study included patients with at least 6 months of therapy with a targeted synthetic or biological disease-modifying antirheumatic drug who were in treatment target (i.e., DAPSA < 14). Patients underwent bilateral clinical and ultrasound examination of the elbow lateral epicondyle, quadriceps insertion, distal patellar tendon insertion, and Achilles enthesis for assessing enthesitis, and hand and foot joints for assessing synovitis. Enthesitis and synovitis were considered active if the power Doppler signal showed at least a score of one. Results: The study included 51 PsA patients, women (52.9%), with an average age of 55 years. Although the patients were within the DAPSA treatment target, 21.6% had at least one painful enthesis at clinical examination, 19.6% had ultrasound evidence of at least one active enthesitis and 15.7% had ultrasound signs of at least one active synovitis. Conclusions: Among PsA patients thought to be within the therapeutic target, ultrasound detected a non-negligible percentage of active enthesitis and synovitis.

Analysis of synovitis patterns in early RA supports the importance of joint-specific factors

BackgroundRheumatoid arthritis (RA) is classically considered a systemic disorder, but the role of local factors in driving synovial inflammation is increasingly being recognized. These joint-specific factors may consequently modulate disease phenotype. ObjectivesOur goal was to study the spatial distribution of swelling, tenderness and erosions in a large cohort of early RA (ERA) patients, to assess for patterns of simultaneously-involved joint clusters. We also aimed to investigate the link between arthritis localization and phenotypic features such as bone erosions and response to methotrexate therapy. MethodsDMARD-naive patients from the ERA UCLouvain Brussels cohort were included. Forty-four joints were clinically assessed for swelling and tenderness before treatment, and 6 months later for methotrexate-treated patients. Clusters of joints were identified using Principal component analysis and Cramer's correlation coefficients. Frequency of bone erosions and joint-specific response to methotrexate were compared across different clusters. Results452 ERA patients were included. Analysis of the spatial distribution of swelling and tenderness allowed for the identification of 3 joint clusters that showed significant simultaneous involvement: (i) MTP1–5 joints, (ii) hand joints (MCPs and PIPs), and (iii) larger joints. These clusters were associated with different susceptibility to bone erosions and distinct clinical features, but similar local response (joint swelling resolution) to methotrexate. ConclusionThis is the first study investigating the spatial distribution of arthritis in a large cohort of early RA using an unbiased approach. We identify clusters of simultaneously involved joints, supporting the importance of local factors in driving synovitis in RA.

Contribution of the Musculoskeletal Ultrasound in the Diagnosis of Seronegative Rheumatoid Arthritis.

This is a study to investigate the value of musculoskeletal ultrasound for the early diagnosis of seronegative rheumatoid arthritis (SNRA); and to study the relationship between anti-cyclic citrullinated peptide antibody (anti-CCP) and the occurrence of bone erosion in rheumatoid arthritis (RA) detected by ultrasound. A total of 101 patients with RA or osteoarthritis (OA) admitted to the First Affiliated Hospital of Anhui Medical University from July 2022 to December 2023 were selected and divided into the SNRA group, the SPRA group, and the OA group. The patients' metacarpophalangeal joints, proximal interphalangeal joints, distal interphalangeal joints, and wrist joints of both hands were ultrasonically examined separately, and the extensor tendon, flexor tendon, synovium, joint surface, joint cavity, and bone surface were observed. The differences in the detection of joint effusion, bone erosion, and joint space narrowing were not statistically significant between SNRA group and OA group (P > .05), the differences in the detection of synovitis and tenosynovitis were statistically significant (P < .05). The mean levels of synovial hyperplasia grade and synovial blood flow grade between SNRA group and OA group were significantly different (P < .05). The differences in synovitis, tenosynovitis, joint effusion, and joint space narrowing were not statistically significant between SNRA and SPRA groups (P > .05), and the differences in bone erosion were statistically significant (P < .05). The mean levels of synovial hyperplasia grade and synovial blood flow grade between SNRA group and SPRA group were significantly different (P < .05). Logistic regression analysis showed that anti-CCP antibody was an influential factor for bone erosion in RA patients (P < .05). The ROC curve was plotted, and the optimal cut-off value of anti-CCP antibody was 356.5U/mL, at which time the AUC was 0.716, the sensitivity of diagnosing bone erosion was 0.714, the specificity was 0.694, and the Yoden index was 0.408. In summary, ultrasound is helpful for the early diagnosis of SNRA by evaluating the condition of joints, synovium, and tendon sheath, and when anti-CCP antibodies are positive, ultrasound is more likely to detect bone erosion. Ultrasound examination combined with anti-CCP antibody can further observe the joint lesions.

Magnetic Resonance Imaging (MRI)-Based Semi-Quantitative Methods for Rheumatoid Arthritis: From Scoring to Measurement.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects the small joints of the hands and feet, characterized by pain, inflammation, and joint damage. In this context, magnetic resonance imaging (MRI) is useful to identify and monitor joint/tendon inflammation and the evolution of joint damage, playing a key role in treatment response evaluation, in addition to clinical measurements. Various methods to quantify joint inflammation and damage with MRI in RA have been developed, such as RA-MRI Score (RAMRIS), Early RA-MRI Score (ERAMRS), and Simplified RA-MRI Score (SAMIS). RAMRIS, introduced in 2002, offers an objective means to assess inflammation and damage via MRI in RA trials, encompassing findings such as synovitis, bone erosion, and edema/osteitis. Recently, an updated RAMRIS version was developed, which also includes the evaluation of joint space narrowing and tenosynovitis. The RAMRIS-5, which is a condensed RAMSIS version focusing on five hand joints only, has been proven to be a valuable resource for the semi-quantitative evaluation of RA joint damage, both in early and established disease. This narrative literature review will provide an overview of the MRI scoring systems that have been developed for the assessment of joint inflammation and structural damage in RA patients.

ANALYSIS OF THE SPATIO-TEMPORAL CHARACTERISTICS OF THE TECHNIQUE OF KICKING WITH THE LEFT FOOT TO THE SIDE FROM THE LEFT-HANDED STANCE OF HIGHLY SKILLED ATHLETES SPECIALISING IN HAND-TO-HAND COMBAT

The relevance of the research topic. A wide arsenal of technical actions and a wide range of potential conflict situations that regularly occur in the course of martial arts determine the peculiarities of operations, actions and mechanisms for their improvement. The aim of the research was to analyse the indicators of the spatial-temporal structure of the technique of a kick with the left foot to the side from the left- handed stand performed by highly skilled sportsmen. Research methods: analysis of literature sources, video recording and biomechanical video computer analysis using the optoelectronic system "Qualisys", methods of mathematical statistics. Results. The movement of the biolinks of the athletes' body during the phase of preparing for the impact is from 0.03 m to 0.25 m. During the kicking phase, the values of the average velocities of the right ankle and right knee joints are 4.23 m·s-1 and 2.26 m·s -1 respectively. Conclusions. The execution of a blow is effective from the point of view of biomechanical analysis, and the indicators of the kinematic structure of movements during the execution of this blow can be used both as a reference sample of sports technique and for the development of model characteristics of movements based on them. The values of the average velocities of the shoulder, elbow, and carpal joints of the right hand during the walking phase are 0.50 m·s-1, 1.10 m·s-1, and 0.95 m·s-1, respectively. The average speed of the shoulder joint of the left hand is 0.69 m·s-1, the left elbow joint - 0.97 m·s-1, and the left carpal joint - 2.03 m·s-1. Such high indicators of the average speeds of the hand joints during the walking phase indicate swinging movements to increase the force of the impact due to the use of inertial forces. The movement of the biolinks of the athletes' body during the walking phase ranges from 0.08 m to 0.63 m. The values of the indicators of the joints of the upper limbs during the two support phases when performing a left leg kick to the side from the left stance are: right shoulder joint - 0.65 m·s-1, left shoulder joint -0.52 m·s-1, right elbow joint – 2.73 m·s-1, left elbow joint – 1.71 m·s-1, right and left carpal joints – 1.84 m·s-1. In the two-support phase, the movement of the studied body points of the athletes is in the range from 0.08 m to 0.56 m. The values of the average velocities of the studied body points of the athletes during the contact phase when performing a left leg kick to the side from the left stance range from 0.23 m s- 1 to 2.53 m·s-1, and the displacement of the same points during this phase is from 0.02 m to 0.20 m

Individual joints involvement pattern in psoriatic arthritis: A cross-sectional study in China.

Psoriatic arthritis (PsA) is characterized by multi-joint involvement, primarily affecting the small joints in the hands and feet. However, the specific pattern of joint involvement at an individual level remains uncertain. This study aimed to elucidate the pattern of joint involvement in a PsA cohort. Patients diagnosed with PsA were recruited for this cross-sectional study. Demographic, clinical, laboratory, personal and family history, and comorbidity data were collected. Descriptive statistical analysis was performed, and univariate and multivariate regression models were used to examine baseline factors influencing joint involvement. A total of 264 PsA patients (156 males) were included in the study. The results revealed a predominant involvement of peripheral facet joints. The second proximal interphalangeal joint (PIP) of the right hand exhibited the highest prevalence of swelling (18.9%), while the right knee joint had the highest prevalence of tenderness (24.2%). Older age and earlier onset of PsA were identified as independent factors associated with the swelling of the second PIP of the right hand. Older age, earlier onset of PsA, lower Psoriasis Area and Severity Index and higher Dermatology Life Quality Index scores were identified as independent factors associated with the tenderness of the right knee joint. In conclusion, the most commonly affected joints in PsA are the second PIP of the right hand and the right knee joint.

VR-HandNet: A Visually and Physically Plausible Hand Manipulation System in Virtual Reality.

This study aims to allow users to perform dexterous hand manipulation of objects in virtual environments with hand-held VR controllers. To this end, the VR controller is mapped to the virtual hand and the hand motions are dynamically synthesized when the virtual hand approaches an object. At each frame, given the information about the virtual hand, VR controller input, and hand-object spatial relations, the deep neural network determines the desired joint orientations of the virtual hand model in the next frame. The desired orientations are then converted into a set of torques acting on hand joints and applied to a physics simulation to determine the hand pose at the next frame. The deep neural network, named VR-HandNet, is trained with a reinforcement learning-based approach. Therefore, it can produce physically plausible hand motion since the trial-and-error training process can learn how the interaction between hand and object is performed under the environment that is simulated by a physics engine. Furthermore, we adopted an imitation learning paradigm to increase visual plausibility by mimicking the reference motion datasets. Through the ablation studies, we validated the proposed method is effectively constructed and successfully serves our design goal. A live demo is demonstrated in the supplementary video.