Hasil untuk "Diseases of the musculoskeletal system"

Guantong Qi, Jiasheng Wang, Mei Ling Chong et al.

Millions of children worldwide are affected by severe rare Mendelian disorders, yet exome and genome sequencing still fail to provide a definitive molecular diagnosis for a large fraction of patients, prolonging the diagnostic odyssey. Bridging this gap increasingly requires transitioning from DNA-only interpretation to multi-modal diagnostic reasoning that combines genomic data, transcriptomic sequencing (RNA-seq), and phenotype information; however, computational frameworks that coherently integrate these signals remain limited. Here we present RareCollab, an agentic diagnostic framework that pairs a stable quantitative Diagnostic Engine with Large Language Model (LLM)-based specialist modules that produce high-resolution, interpretable assessments from transcriptomic signals, phenotypes, variant databases, and the literature to prioritize potential diagnostic variants. In a rigorously curated benchmark of Undiagnosed Diseases Network (UDN) patients with paired genomic and transcriptomic data, RareCollab achieved 77% top-5 diagnostic accuracy and improved top-1 to top-5 accuracy by ~20% over widely used variant-prioritization approaches. RareCollab illustrates how modular artificial intelligence (AI) can operationalize multi-modal evidence for accurate, scalable rare disease diagnosis, offering a promising path toward reducing the diagnostic odyssey for affected families.

Tian Lan, Lei Xu, Zimu Yuan et al.

Musculoskeletal disorders represent a significant global health burden and are a leading cause of disability worldwide. While MRI is essential for accurate diagnosis, its interpretation remains exceptionally challenging. Radiologists must identify multiple potential abnormalities within complex anatomical structures across different imaging planes, a process that requires significant expertise and is prone to variability. We developed OrthoDiffusion, a unified diffusion-based foundation model designed for multi-task musculoskeletal MRI interpretation. The framework utilizes three orientation-specific 3D diffusion models, pre-trained in a self-supervised manner on 15,948 unlabeled knee MRI scans, to learn robust anatomical features from sagittal, coronal, and axial views. These view-specific representations are integrated to support diverse clinical tasks, including anatomical segmentation and multi-label diagnosis. Our evaluation demonstrates that OrthoDiffusion achieves excellent performance in the segmentation of 11 knee structures and the detection of 8 knee abnormalities. The model exhibited remarkable robustness across different clinical centers and MRI field strengths, consistently outperforming traditional supervised models. Notably, in settings where labeled data was scarce, OrthoDiffusion maintained high diagnostic precision using only 10\% of training labels. Furthermore, the anatomical representations learned from knee imaging proved highly transferable to other joints, achieving strong diagnostic performance across 11 diseases of the ankle and shoulder. These findings suggest that diffusion-based foundation models can serve as a unified platform for multi-disease diagnosis and anatomical segmentation, potentially improving the efficiency and accuracy of musculoskeletal MRI interpretation in real-world clinical workflows.

Wentao Zhao, Jun Guo, Kangyao Huang et al.

Musculoskeletal robots provide superior advantages in flexibility and dexterity, positioning them as a promising frontier towards embodied intelligence. However, current research is largely confined to relative simple tasks, restricting the exploration of their full potential in multi-segment coordination. Furthermore, efficient learning remains a challenge, primarily due to the high-dimensional action space and inherent overactuated structures. To address these challenges, we propose Diff-Muscle, a musculoskeletal robot control algorithm that leverages differential flatness to reformulate policy learning from the redundant muscle-activation space into a significantly lower-dimensional joint space. Furthermore, we utilize the highly dynamic robotic table tennis task to evaluate our algorithm. Specifically, we propose a hierarchical reinforcement learning framework that integrates a Kinematics-based Muscle Actuation Controller (K-MAC) with high-level trajectory planning, enabling a musculoskeletal robot to perform dexterous and precise rallies. Experimental results demonstrate that Diff-Muscle significantly outperforms state-of-the-art baselines in success rates while maintaining minimal muscle activation. Notably, the proposed framework successfully enables the musculoskeletal robots to achieve continuous rallies in a challenging dual-robot setting.

Nomi S. Weiss-Laxer, Jon S. Dhani, Katharine B. Fox et al.

Agathe Yvinou, Romain Alain

Abstract Gender and sex disparities persist in orthopaedic and traumatology surgery, making it one of the least diverse medical specialties worldwide. Despite growing women representation in medical education, women continue to be significantly underrepresented in orthopaedics, occupying only 6–8% of surgical roles. This underrepresentation extends to academic leadership, research, and public speaking opportunities, ultimately limiting innovation and the quality of patient care. Systemic barriers—such as gender bias, lack of mentorship, and misperceptions about physical demands—discourage women from entering and advancing in the field. This manuscript explores the current landscape of gender inequality in orthopaedics and identifies strategic interventions to promote equity. Solutions include enhancing recruitment through early exposure, fostering inclusive institutional cultures, expanding mentorship and sponsorship opportunities, and implementing supportive policies for work-life integration. In patient care, disparities in diagnosis, pain management, surgical decision-making, and rehabilitation access disproportionately impact women. We advocate for the development of gender-inclusive clinical guidelines, equitable research funding, and standardized assessment tools. Additionally, the role of public awareness is examined, emphasizing the need to highlight success stories, engage male allies, and conduct outreach through educational and community initiatives. Programs such as the Perry Initiative, Nth Dimensions, and campaigns like HeForShe are shown to play pivotal roles in shifting perceptions and increasing diversity. Addressing these disparities is not only a matter of justice but also essential to achieving excellence in clinical outcomes. This article offers a comprehensive framework for fostering gender and sex equality in orthopaedic and traumatology surgery through systemic, cultural, and policy-level change.

Siddhart Yadav, K P Chiranjeevi, Akash Singh Jadon et al.

Introduction: Ipsilateral tibia and fibula shaft fractures with trimalleolar fracture are quite rare in clinical practice. Case Report: This is a case report of a 49-year-old female presented on March 6th, 2024, and was diagnosed to have an ipsilateral left comminuted distal tibia shaft and fibula shaft fracture with an anterior lacerated wound 2 cm over the fracture site with trimalleolar fracture after falling twice while walking. The patient was treated with wound debridement, intramedullary interlocking nailing for the left tibia shaft, and open reduction internal fixation with coracoclavicular screw for posterior malleolus, K-wires + FiberWire tension band wiring for medial malleolus, and K-wires for lateral malleolus on March 07th, 2024. K-wires from the lateral malleolus were removed and tibia nail dynamization was done on April 10th, 2024. All fractures united in 4 months and the patient was followed up for a period of 1 year post-operatively. Conclusion: Various treatment options were possible, of which we chose implants and a sequence of fixation based on the fracture pattern being comminuted and an open fracture.

Tilo Freiwald, Behdad Afzali

The complement system is a highly conserved and essential immune component with pivotal roles in innate and adaptive immunity. It is increasingly recognized that the complement system has a profound impact on disease. Current complement-targeting therapeutics for clinical use almost exclusively target the complement system in circulation. However, recent discoveries have demonstrated that complement is not only liver derived and plasma operative, but also synthesized and activated inside many cells locally within tissues, performing noncanonical, cell-autonomous intracellular functions, collectively referred to as the complosome. These intracellular complement pathways are distinct from the classical plasma-based system and critical for regulating fundamental cellular processes, including metabolism, gene transcription, autophagy, and the activation and resolution of inflammation. This Review explores the emerging roles of the complosome and current knowledge regarding its relation to human diseases, highlighting evidence across organ systems and disease states, including the kidneys, digestive tract, lungs, heart, CNS, musculoskeletal system, skin, and cancer. We also review current scientific approaches for detecting and functionally investigating the complosome, addressing challenges such as technological limitations and the need for advanced experimental models to delineate its tissue-specific roles. Finally, we discuss central unanswered questions critical for developing innovative therapeutic strategies targeting intracellular complement pathways. These strategies hold potential to modulate disease-specific mechanisms while preserving systemic complement activity.

Zoé Stehlin, Felix Karl-Ludwig Klingebiel, Hans-Christoph Pape et al.

<b>Background</b>: Although the difficulty level of figure skating programs has increased in the last two decades, particularly at the junior level, trends in performance have not been reported. This retrospective observational study investigated performance development trends among the top five junior figure skaters competing at international levels in both the ladies’ and men’s singles disciplines from 2005 to 2020. Data from 160 junior single ladies and 160 junior single men were analyzed. The focus was on the progression of technical elements—particularly jumps—and their potential correlation with injury risk. It was hypothesized that younger athletes are increasingly performing jumps with more revolutions, thereby enhancing overall competition standards. <b>Materials and Methods</b>: Using data from the Junior World Championships and Junior Grand Prix Finals, linear regression analysis and one-way ANOVA were conducted to track the frequency of double, triple, and quadruple jumps, as well as trends in age development among athletes in the singles categories from 2005 to 2020. <b>Results</b>: The results indicate a significant increase in the execution of higher-revolution jumps among junior athletes. Between 2005 and 2012, the frequency of double jumps declined across all events, with the most pronounced reductions observed in the Ladies’ Junior World Championships (Δ = 0.216, <i>p</i> = 0.004, d = 1.64) and the Men’s Junior World Championships (Δ = 0.500, <i>p</i> = 0.001, d = 1.82). From 2005 to 2011, the frequencies of triple and quadruple jumps increased, while double jumps remained stable or showed only slight increases. Triple jumps showed slight downward trends (e.g., R² = 0.0202 at the Men’s Junior World Championships). Although still rare, the frequency of quadruple jumps has shown a consistent upward trend across multiple competitions. Between 2000 and 2009, all four events exhibited declining age trends, with decreases ranging from −0.029 to −0.078 years of age per year. In the subsequent decade (2010–2020), when averaged across all events, the observed difference slope (Δ = 0.014) indicated a continued decline in athlete age. <b>Conclusions</b>: In summary, increases in more difficult jumps were found, with simultaneous decreases in less difficult jumps. As jump complexity rises, a parallel increase in sport-specific injury incidence can be anticipated, highlighting the need for proactive strategies for injury prevention and athlete well-being.

Yasushi Oshima, Nobuyoshi Watanabe, Yoshiteru Kajikawa et al.

Abstract Background Meniscal injury and/or extrusion have been indicated as causes of subchondral insufficiency fracture (SIFK). However, mediolateral knee laxity has not been discussed as a risk factor. This is a case report of SIFK potentially caused by mediolateral laxity in the absence of a meniscal disorder. Case presentation A 59-year-old male patient presented with SIFK in the medial femoral condyle without meniscal injury or extrusion. Tibial condylar valgus osteotomy (TCVO) was performed, and the preoperative total mediolateral laxity of 8° in extension and 6° in 80° flexion decreased to 6° and 4°, respectively, two years postoperatively. Moreover, the magnetic resonance images revealed no bone marrow lesions, and the knee injury and osteoarthritis outcome score improved from 61.4 to 79.7. Conclusion A case of SIFK with mediolateral laxity, without meniscal disorder, was successfully treated by TCVO, indicating knee laxity as a potential risk factor for SIFK.

Ondrej Zoufaly, Edward Chadwick, Dimitra Blana et al.

Euler angle representation in biomechanical analysis allows straightforward description of joints rotations. However, application of Euler angles could be limited due to singularity called gimbal lock. Quaternions offer an alternative way to describe rotations but they have been mostly avoided in biomechanics as they are complex and not inherently intuitive, specifically in dynamic models actuated by muscles. This study introduces a mathematical framework for describing muscle actions in dynamic quaternion-based musculoskeletal simulations. The proposed method estimates muscle torques in quaternion-based musculoskeletal model. Its application is shown on three-dimensional double-pendulum system actuated by muscle elements. Furthermore, transformation of muscle moment arms obtained from muscle paths based on Euler angles into quaternions description is presented. The proposed method is advantageous for dynamic modeling of musculoskeletal models with complex kinematics and large range of motion like the shoulder joint.

Chenhui Zuo, Guohao Lin, Chen Zhang et al.

Coordinated human movement depends on the integration of multisensory inputs, sensorimotor transformation, and motor execution, as well as sensory feedback resulting from body-environment interaction. Building dynamic models of the sensory-musculoskeletal system is essential for understanding movement control and investigating human behaviours. Here, we report a human sensory-musculoskeletal model, termed SMS-Human, that integrates precise anatomical representations of bones, joints, and muscle-tendon units with multimodal sensory inputs involving visual, vestibular, proprioceptive, and tactile components. A stage-wise hierarchical deep reinforcement learning framework was developed to address the inherent challenges of high-dimensional control in musculoskeletal systems with integrated multisensory information. Using this framework, we demonstrated the simulation of three representative movement tasks, including bipedal locomotion, vision-guided object manipulation, and human-machine interaction during bicycling. Our results showed a close resemblance between natural and simulated human motor behaviours. The simulation also revealed musculoskeletal dynamics that could not be directly measured. This work sheds deeper insights into the sensorimotor dynamics of human movements, facilitates quantitative understanding of human behaviours in interactive contexts, and informs the design of systems with embodied intelligence.

Kento Kawaharazuka, Takahiro Hattori, Keita Yoneda et al.

Musculoskeletal humanoids are robots that closely mimic the human musculoskeletal system, offering various advantages such as variable stiffness control, redundancy, and flexibility. However, their body structure is complex, and muscle paths often significantly deviate from geometric models. To address this, numerous studies have been conducted to learn body schema, particularly the relationships among joint angles, muscle tension, and muscle length. These studies typically rely solely on data collected from the actual robot, but this data collection process is labor-intensive, and learning becomes difficult when the amount of data is limited. Therefore, in this study, we propose a method that applies the concept of Physics-Informed Neural Networks (PINNs) to the learning of body schema in musculoskeletal humanoids, enabling high-accuracy learning even with a small amount of data. By utilizing not only data obtained from the actual robot but also the physical laws governing the relationship between torque and muscle tension under the assumption of correct joint structure, more efficient learning becomes possible. We apply the proposed method to both simulation and an actual musculoskeletal humanoid and discuss its effectiveness and characteristics.

Jianbo Yuan, Jing Dai, Yerui Fan et al.

The human arm exhibits remarkable capabilities, including both explosive power and precision, which demonstrate dexterity, compliance, and robustness in unstructured environments. Developing robotic systems that emulate human-like operational characteristics through musculoskeletal structures has long been a research focus. In this study, we designed a novel lightweight tendon-driven musculoskeletal arm (LTDM-Arm), featuring a seven degree-of-freedom (DOF) skeletal joint system and a modularized artificial muscular system (MAMS) with 15 actuators. Additionally, we employed a Hilly-type muscle model and data-driven iterative learning control (DDILC) to learn and refine activation signals for repetitive tasks within a finite time frame. We validated the anti-interference capabilities of the musculoskeletal system through both simulations and experiments. The results show that the LTDM-Arm system can effectively achieve desired trajectory tracking tasks, even under load disturbances of 20 % in simulation and 15 % in experiments. This research lays the foundation for developing advanced robotic systems with human-like operational performance.

Dana Weisenfeld, Fan Zhang, Laura Donlin et al.

Objective Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient‐level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. Methods The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease‐modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. Results We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score‐28 C‐reactive Protein 3 [DAS28‐CRP3] score 4.8). Higher DAS28‐CRP3 correlated with a higher T cell percentage ( P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs ( P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28‐CRP3. Conclusion In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies.

Dafna D. Gladman, Peter Nash, Philip J. Mease et al.

Abstract Background Data on treatment switching directly from tumor necrosis factor inhibitors to tofacitinib in psoriatic arthritis (PsA) are limited. This post hoc analysis assessed efficacy and safety outcomes in patients with PsA who directly switched to tofacitinib in a long-term extension (LTE) study after receiving adalimumab (ADA) in a Phase 3 study, compared with those who continued to receive tofacitinib. Methods Patients with active PsA received tofacitinib 5 mg twice daily (BID) or ADA 40 mg once every 2 weeks in a 12-month, randomized, double-blind study (OPAL Broaden) and then continued or switched to tofacitinib 5 mg BID and maintained this dose in an open-label LTE study (OPAL Balance). Efficacy was assessed 3 months before the last visit and at the last visit in the Phase 3 study, and at month 3 (or month 6 for select outcomes) in the LTE study and included rates of ≥ 20/50/70% improvement in American College of Rheumatology response criteria, Psoriasis Area and Severity Index ≥ 75% improvement, Health Assessment Questionnaire-Disability Index (HAQ-DI) response (decrease from baseline ≥ 0.35 for patients with baseline HAQ-DI ≥ 0.35), Psoriatic Arthritis Disease Activity Score ≤ 3.2, and minimal disease activity; and change from baseline in Functional Assessment of Chronic Illness Therapy-Fatigue score. Safety was assessed at months 3 and 12 in both studies via incidence rates (patients with first events/100 patient-years). Results Overall, 180 patients were included (ADA→tofacitinib 5 mg BID: n = 91; continuing tofacitinib 5 mg BID: n = 89). At Phase 3 baseline, patients in the ADA→tofacitinib 5 mg BID group tended to be younger and have less active disease compared with those continuing tofacitinib. Efficacy was similar between groups in the Phase 3 study, and was maintained to month 3 or 6 in the LTE study. Treatment-emergent adverse events (AEs), serious AEs, and serious infections were generally similar in the Phase 3 and LTE studies, and between groups within each study. Conclusion Tofacitinib efficacy and safety were similar in patients with PsA who directly switched from ADA to tofacitinib and those who continued tofacitinib, suggesting that patients can be directly switched from ADA to tofacitinib without any washout period. Trial registration NCT01877668; NCT01976364

Lauren N. Miterko-Myers

Dystonia is a neurodevelopmental disorder characterized by severe involuntary twisting movements, hypothesized to arise from a dysfunctional motor network involving the cortex, basal ganglia, and cerebellum. Within this network, striatal cholinergic interneurons have been identified as possible contributors to dystonia pathophysiology. However, little is known about striatal cholinergic interneuron development in the mammalian brain, limiting our understanding of its role in dystonia and therapeutic potential. Here, I review striatal cholinergic interneuron development in the context of early-onset DYT1 (or “DYT-TOR1A”) dystonia. I discuss clinical and laboratory research findings that support cholinergic dysfunction in DYT1 dystonia and the implications of abnormal cholinergic cell development on disease penetrance and striatal connectivity.

Virginia Byers Kraus, Alexander Reed, Erik J. Soderblom et al.

Objective: To further validate a serum proteomics panel for predicting radiographic (structural) knee OA progression. Design: Serum peptides were targeted by multiple-reaction-monitoring mass spectrometry in the New York University cohort (n ​= ​104). Knee OA progression was defined as joint space narrowing ≥1 in the tibiofemoral compartment of one knee per study participant over a 24-month follow-up. The discriminative ability of an 11-peptide panel was evaluated by multivariable logistic regression and area under the receiver operating characteristic curve (AUC), without and with demographic characteristics of age, sex, and body mass index. The association of each peptide with OA progression was assessed by odds ratios (OR) in multivariable logistic regression models adjusted for demographics. Results: The cohort included 46 (44%) knee OA progressors. The panel of 11 peptides alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]) for discriminating progressors from non-progressors; demographic traits alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]). Together the 11 peptides and demographics yielded AUC ​= ​0.72 (95% CI [0.62, 0.83]). CRAC1 had the highest odds for predicting OA progression (OR 2.014, 95% CI [0.996, 4.296], p ​= ​0.058). Conclusions: We evaluated a parsimonious serum proteomic panel and found it to be a good discriminator of knee radiographic OA progression from non-progression. Since these biomarkers are quantifiable in serum, they could be deployed relatively easily to provide a simple, cost-effective strategy for identifying and monitoring individuals at high risk of knee OA progression.

Kento Kawaharazuka, Kei Okada, Masayuki Inaba

While the musculoskeletal humanoid has various biomimetic benefits, its complex modeling is difficult, and many learning control methods have been developed. However, for the actual robot, the hysteresis of its joint angle tracking is still an obstacle, and realizing target posture quickly and accurately has been difficult. Therefore, we develop a feedback control method considering the hysteresis. To solve the problem in feedback controls caused by the closed-link structure of the musculoskeletal body, we update a neural network representing the relationship between the error of joint angles and the change in target muscle lengths online, and realize target joint angles accurately in a few trials. We compare the performance of several configurations with various network structures and loss definitions, and verify the effectiveness of this study on an actual musculoskeletal humanoid, Musashi.

Kento Kawaharazuka, Kei Tsuzuki, Yuya Koga et al.

This paper summarizes an autonomous driving project by musculoskeletal humanoids. The musculoskeletal humanoid, which mimics the human body in detail, has redundant sensors and a flexible body structure. These characteristics are suitable for motions with complex environmental contact, and the robot is expected to sit down on the car seat, step on the acceleration and brake pedals, and operate the steering wheel by both arms. We reconsider the developed hardware and software of the musculoskeletal humanoid Musashi in the context of autonomous driving. The respective components of autonomous driving are conducted using the benefits of the hardware and software. Finally, Musashi succeeded in the pedal and steering wheel operations with recognition.

Amirhossein Kazemipour, Ronan Hinchet, Robert K. Katzschmann

Artificial muscles play a crucial role in musculoskeletal robotics and prosthetics to approximate the force-generating functionality of biological muscle. However, current artificial muscle systems are typically limited to either contraction or extension, not both. This limitation hinders the development of fully functional artificial musculoskeletal systems. We address this challenge by introducing an artificial antagonistic muscle system capable of both contraction and extension. Our design integrates non-stretchable electrohydraulic soft actuators (HASELs) with electrostatic clutches within an antagonistic musculoskeletal framework. This configuration enables an antagonistic joint to achieve a full range of motion without displacement loss due to tendon slack. We implement a synchronization method to coordinate muscle and clutch units, ensuring smooth motion profiles and speeds. This approach facilitates seamless transitions between antagonistic muscles at operational frequencies of up to 3.2 Hz. While our prototype utilizes electrohydraulic actuators, this muscle-clutch concept is adaptable to other non-stretchable artificial muscles, such as McKibben actuators, expanding their capability for extension and full range of motion in antagonistic setups. Our design represents a significant advancement in the development of fundamental components for more functional and efficient artificial musculoskeletal systems, bringing their capabilities closer to those of their biological counterparts.