Hasil untuk "Diseases of the musculoskeletal system"

A. Woolf, B. Pfleger

Stijn J M Niessen, Robert Shiel, Astrid Wehner et al.

Simple Summary After having achieved international consensus over disease, diagnosis, classification, and monitoring concepts in the area of companion animal diabetes mellitus, Cushing’s syndrome, and hypoadrenocorticism, a group of 14 experts and one chair embarked on the third cycle of project “Agreeing Language in Veterinary Endocrinology” (ALIVE), this time focusing on thyroid disease terminology. This cycle’s methods followed, like previous ones, a modified Delphi-approach with small changes to improve efficiency and flexibility, including an off-site chair. For the first time, additionally, feedback on definitions of a previous cycle was incorporated, leading to an update of diabetes mellitus related definitions of ALIVE Cycle 1. This third cycle was completed successfully, accomplishing a majority-based consensus among panellists and international veterinary endocrinology society memberships over 78 thyroid related terminology and five updated diabetes mellitus definitions. As has been the case with the definitions created for other hormonal diseases, it is hoped this work will improve education, research, diagnosis, and treatment in cats and dogs with endocrine disease.

Ilseung Park, Eunsik Choi, Jangwhan Ahn et al.

Human locomotion emerges from high-dimensional neuromuscular control, making predictive musculoskeletal simulation challenging. We present a physiology-informed reinforcement-learning framework that constrains control using muscle synergies. We extracted a low-dimensional synergy basis from inverse musculoskeletal analyses of a small set of overground walking trials and used it as the action space for a muscle-driven three-dimensional model trained across variable speeds, slopes and uneven terrain. The resulting controller generated stable gait from 0.7-1.8 m/s and on $\pm$ 6$^{\circ}$ grades and reproduced condition-dependent modulation of joint angles, joint moments and ground reaction forces. Compared with an unconstrained controller, synergy-constrained control reduced non-physiological knee kinematics and kept knee moment profiles within the experimental envelope. Across conditions, simulated vertical ground reaction forces correlated strongly with human measurements, and muscle-activation timing largely fell within inter-subject variability. These results show that embedding neurophysiological structure into reinforcement learning can improve biomechanical fidelity and generalization in predictive human locomotion simulation with limited experimental data.

Alain Saraux, Dominique Le Nen

Medicine is not part of the fine arts. However, it is the art, scientifically informed, of care. Rheumatology in particular requires the ability to observe, listen, feel and interpret with humanity to care for people with musculoskeletal diseases. This narrative review explores the reciprocal links between art, artists, and musculoskeletal systems to seek to balance the debt of rheumatology to art with the debt of art to rheumatology over time. Before the Renaissance, knowledge about rheumatology was relatively poor and was largely restricted to Hippocratic theories and animal descriptions provided by Galen, and therefore poorly represented by artists. From 1480 to 1520, painters began to establish the field of artistic anatomy, focusing on the science of external forms. Although its impact on understanding rheumatic diseases was minimal, it led to the identification of anatomical structures affected by these conditions. Thus, human anatomy was born. After 1700, poor hygiene, a lack of physical activity, and overeating by the middle class were believed to be likely external causes of joint diseases, particularly gout, which was often conflated with other arthritis. Inspired by painters who idealised thermal baths, spas and seaside facilities were developed, promoting sports, hygiene, wellness, and healthy gastronomy. This gave birth to hydrotherapy. Patients with rheumatic diseases began congregating in balneological and thermal cities, allowing physicians to better describe the nosology of musculoskeletal diseases. Thus, rheumatology was born. More than 200 musculoskeletal conditions were documented between 1800 and 2000. Art and rheumatology share a debt, and rheumatologists began to engage with patients through art.

R. Symes, S. H. Keddie, J. Walker et al.

Background Respiratory syncytial virus (RSV) is an important cause of acute respiratory infection (ARI) in older adults. Vaccines that protect against severe RSV infection are now available. Aim We aimed to describe the incidence, presentation, severity and clinical outcomes of RSV-associated ARI in hospitalised older adults using a new Hospital-based ARI Sentinel Surveillance (HARISS) system in England in the winter prior to RSV vaccine introduction. Methods Adults aged [≥]65 years from seven hospitals admitted for [≥]24 hours with symptomatic ARI were included. Three groups were identified: RSV positive; influenza positive; negative for RSV, influenza and SARS-CoV-2. We estimated the hospitalisation rate of RSV-associated ARI compared to influenza-associated ARI and assessed clinical outcomes using Poisson regression and mortality using Cox regression across groups. Results This surveillance study included 2743 adults. During the 2023/4 season the hospitalisation rate for RSV-associated ARI was 58.3 per 100,000, compared to 114.6 per 100,000 for influenza-associated ARI. Hospitalisation rates increased with age. Exacerbation of chronic illness including lung disease, heart disease or frailty was a frequent cause of admission in RSV-associated ARI, with a combined incidence of 33.1 per 100,000. The majority of adults with RSV-associated ARI had at least one comorbidity (81%); a high proportion with immunosuppression (26%). Symptoms and clinical outcomes including mortality were similar between RSV- and influenza-associated ARI; 30-day mortality 10.6% vs 8.7% (adjusted hazard ratio 0.85,95% confidence interval 0.6-1.2). Conclusion In England, RSV infection is a common cause of hospitalisation in older adults. Symptoms at presentation, severity and clinical outcomes, including mortality, are comparable to influenza.

Zhaosu Zheng, Haiyang Guo, Songjun Wang et al.

Abstract Background Diabetic foot is a prevalent complication of diabetes mellitus. The tibial transverse transport technique was widely use to diabetic foot management. Recently, some clinical studies have applied tibial periosteal distraction (PD) in diabetic foot patients, reporting favorable therapeutic outcomes. However, the mechanisms by which PD facilitates lower limb wound healing in diabetic foot remain poorly understood. Our study aims to create PD rat model to preliminarily explore the underlying therapeutic mechanisms. Methods We developed periosteal distraction fixation system. The periosteal distraction in diabetes rat model (male SD rat) was successfully established. The effects of PD on wound healing were researched. HE staining, immunofluorescence staining and western blot were used to investigate the mechanisms. Results PD enhanced wound healing by angiogensis and EPCs recruitment through SDF-1/CXCR4 and OPN signaling activation, and through ERK1/2 phosphorylated to accelerate M2 macrophage polarization. Enhanced neovascularization and EPCs recruitment were observed in the PD group with double immune-labelling of CD31 and α-SMA, CD34 and CD133. SDF-1/CXCR4, OPN signaling activation and ERK1/2 phosphorylation were seen in the results of immunofluorescence staining and western blot in PD group. The amount of M2 macrophages was increased and M1 was reduced in the PD group by immunofluorescence staining. Conclusion PD enhanced blood flow and regulated inflammatory response to accelerate diabetes foot ulcer healing.

Yinglei Zhu, Xuguang Dong, Qiyao Wang et al.

Dynamic modeling and control are critical for unleashing soft robots' potential, yet remain challenging due to their complex constitutive behaviors and real-world operating conditions. Bio-inspired musculoskeletal robots, which integrate rigid skeletons with soft actuators, combine high load-bearing capacity with inherent flexibility. Although actuation dynamics have been studied through experimental methods and surrogate models, accurate and effective modeling and simulation remain a significant challenge, especially for large-scale hybrid rigid--soft robots with continuously distributed mass, kinematic loops, and diverse motion modes. To address these challenges, we propose EquiMus, an energy-equivalent dynamic modeling framework and MuJoCo-based simulation for musculoskeletal rigid--soft hybrid robots with linear elastic actuators. The equivalence and effectiveness of the proposed approach are validated and examined through both simulations and real-world experiments on a bionic robotic leg. EquiMus further demonstrates its utility for downstream tasks, including controller design and learning-based control strategies.

Chengtian Ma, Yunyue Wei, Chenhui Zuo et al.

Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of static balance and falling remains limited. This work presents a hierarchical control pipeline for simulating human balance via a comprehensive whole-body musculoskeletal system. We identified spatiotemporal dynamics of balancing during stable standing, revealed the impact of muscle injury on balancing behavior, and generated fall contact patterns that aligned with clinical data. Furthermore, our simulated hip exoskeleton assistance demonstrated improvement in balance maintenance and reduced muscle effort under perturbation. This work offers unique muscle-level insights into human balance dynamics that are challenging to capture experimentally. It could provide a foundation for developing targeted interventions for individuals with balance impairments and support the advancement of humanoid robotic systems.

Kento Kawaharazuka, Yuya Koga, Kei Tsuzuki et al.

The musculoskeletal humanoid has various biomimetic benefits, and the redundant muscle arrangement is one of its most important characteristics. This redundancy can achieve fail-safe redundant actuation and variable stiffness control. However, there is a problem that the maximum joint angle velocity is limited by the slowest muscle among the redundant muscles. In this study, we propose two methods that can exceed the limited maximum joint angle velocity, and verify the effectiveness with actual robot experiments.

Minkwan Kim, Yoonsang Lee

We propose FreeMusco, a motion-free framework that jointly learns latent representations and control policies for musculoskeletal characters. By leveraging the musculoskeletal model as a strong prior, our method enables energy-aware and morphology-adaptive locomotion to emerge without motion data. The framework generalizes across human, non-human, and synthetic morphologies, where distinct energy-efficient strategies naturally appear--for example, quadrupedal gaits in Chimanoid versus bipedal gaits in Humanoid. The latent space and corresponding control policy are constructed from scratch, without demonstration, and enable downstream tasks such as goal navigation and path following--representing, to our knowledge, the first motion-free method to provide such capabilities. FreeMusco learns diverse and physically plausible locomotion behaviors through model-based reinforcement learning, guided by the locomotion objective that combines control, balancing, and biomechanical terms. To better capture the periodic structure of natural gait, we introduce the temporally averaged loss formulation, which compares simulated and target states over a time window rather than on a per-frame basis. We further encourage behavioral diversity by randomizing target poses and energy levels during training, enabling locomotion to be flexibly modulated in both form and intensity at runtime. Together, these results demonstrate that versatile and adaptive locomotion control can emerge without motion capture, offering a new direction for simulating movement in characters where data collection is impractical or impossible.

Galindo-Leon Sergio, Eriks-Hoogland Inge, Suzuki Kenji et al.

Simulation of assistive devices on pathological gait through musculoskeletal models offers the potential and advantages of estimating the effect of the device in several biomechanical variables and the device characteristics ahead of manufacturing. In this study, we introduce a novel musculoskeletal modelling approach to simulate the biomechanical impact of ankle foot orthoses (AFO) on gait in individuals with spinal cord injury (SCI). Leveraging data from the Swiss Paraplegic Center, we constructed anatomically and muscularly scaled models for SCI-AFO users, aiming to predict changes in gait kinematics and kinetics. The importance of this work lies in its potential to enhance rehabilitation strategies and improve quality of life by enabling the pre-manufacturing assessment of assistive devices. Despite the application of musculoskeletal models in simulating walking aids effects in other conditions, no predictive model currently exists for SCI gait. Evaluation through RMSE showed similar results compared with other pathologies, simulation errors ranged between 0.23 to 2.3 degrees in kinematics. Moreover, the model was able to capture ankle joint muscular asymmetries and predict symmetry improvements with AFO use. However, the simulation did not reveal all the AFO effects, indicating a need for more personalized model parameters and optimized muscle activation to fully replicate orthosis effects on SCI gait.

Kento Kawaharazuka, Naoki Hiraoka, Kei Tsuzuki et al.

The estimation and management of motor temperature are important for the continuous movements of robots. In this study, we propose an online learning method of thermal model parameters of motors for an accurate estimation of motor core temperature. Also, we propose a management method of motor core temperature using the updated model and anomaly detection method of motors. Finally, we apply this method to the muscles of the musculoskeletal humanoid and verify the ability of continuous movements.

Yuya Koga, Kento Kawaharazuka, Moritaka Onitsuka et al.

In recent years, some research on musculoskeletal humanoids is in progress. However, there are some challenges such as unmeasurable transformation of body structure and muscle path, and difficulty in measuring own motion because of lack of joint angle sensor. In this study, we suggest two motion acquisition methods. One is a method to acquire antagonistic relations of muscles by tension sensing, and the other is a method to acquire correct hand trajectory by vision sensing. Finally, we realize badminton shuttlecock-hitting motion of Kengoro with these two acquisition methods.

Kento Kawaharazuka, Kei Tsuzuki, Moritaka Onitsuka et al.

The flexible under-actuated musculoskeletal hand is superior in its adaptability and impact resistance. On the other hand, since the relationship between sensors and actuators cannot be uniquely determined, almost all its controls are based on feedforward controls. When grasping and using a tool, the contact state of the hand gradually changes due to the inertia of the tool or impact of action, and the initial contact state is hardly kept. In this study, we propose a system that trains the predictive network of sensor state transition using the actual robot sensor information, and keeps the initial contact state by a feedback control using the network. We conduct experiments of hammer hitting, vacuuming, and brooming, and verify the effectiveness of this study.

Kento Kawaharazuka, Shogo Makino, Masaya Kawamura et al.

Tendon-driven musculoskeletal humanoids have many benefits in terms of the flexible spine, multiple degrees of freedom, and variable stiffness. At the same time, because of its body complexity, there are problems in controllability. First, due to the large difference between the actual robot and its geometric model, it cannot move as intended and large internal muscle tension may emerge. Second, movements which do not appear as changes in muscle lengths may emerge, because of the muscle route changes caused by softness of body tissue. To solve these problems, we construct two models: ideal joint-muscle model and muscle-route change model, using a neural network. We initialize these models by a man-made geometric model and update them online using the sensor information of the actual robot. We validate that the tendon-driven musculoskeletal humanoid Kengoro is able to obtain a correct self-body image through several experiments.

D. Banerjee, P. Winocour, T. Chowdhury et al.

People with type 1 and type 2 diabetes are at risk of developing progressive chronic kidney disease (CKD) and end-stage kidney failure. Hypertension is a major, reversible risk factor in people with diabetes for development of albuminuria, impaired kidney function, end-stage kidney disease and cardiovascular disease. Blood pressure control has been shown to be beneficial in people with diabetes in slowing progression of kidney disease and reducing cardiovascular events. However, randomised controlled trial evidence differs in type 1 and type 2 diabetes and different stages of CKD in terms of target blood pressure. Activation of the renin-angiotensin-aldosterone system (RAAS) is an important mechanism for the development and progression of CKD and cardiovascular disease. Randomised trials demonstrate that RAAS blockade is effective in preventing/ slowing progression of CKD and reducing cardiovascular events in people with type 1 and type 2 diabetes, albeit differently according to the stage of CKD. Emerging therapy with sodium glucose cotransporter-2 (SGLT-2) inhibitors, non-steroidal selective mineralocorticoid antagonists and endothelin-A receptor antagonists have been shown in randomised trials to lower blood pressure and further reduce the risk of progression of CKD and cardiovascular disease in people with type 2 diabetes. This guideline reviews the current evidence and makes recommendations about blood pressure control and the use of RAAS-blocking agents in different stages of CKD in people with both type 1 and type 2 diabetes.

N. Hoertel, Katayoun Rezaei, M. Sánchez-Rico et al.

Prior evidence indicates the potential central role of the acid sphingomyelinase (ASM)/ceramide system in the infection of cells with SARS-CoV-2. We conducted a multicenter retrospective observational study including 72,105 adult patients with laboratory-confirmed SARS-CoV-2 infection who were admitted to 36 AP-HP (Assistance Publique–Hôpitaux de Paris) hospitals from 2 May 2020 to 31 August 2022. We examined the association between the ongoing use of medications functionally inhibiting acid sphingomyelinase (FIASMA), which reduces the infection of cells with SARS-CoV-2 in vitro, upon hospital admission with 28-day all-cause mortality in a 1:1 ratio matched analytic sample based on clinical characteristics, disease severity and other medications (N = 9714). The univariate Cox regression model of the matched analytic sample showed that FIASMA medication use at admission was associated with significantly lower risks of 28-day mortality (HR = 0.80; 95% CI = 0.72–0.88; p < 0.001). In this multicenter observational study, the use of FIASMA medications was significantly and substantially associated with reduced 28-day mortality among adult patients hospitalized with COVID-19. These findings support the continuation of these medications during the treatment of SARS-CoV-2 infections. Randomized clinical trials (RCTs) are needed to confirm these results, starting with the molecules with the greatest effect size in the study, e.g., fluoxetine, escitalopram, and amlodipine.

Naoyuki Kawao, Miku Kawaguchi, Takashi Ohira et al.

Pierre Schumacher, Thomas Geijtenbeek, Vittorio Caggiano et al.

Humans excel at robust bipedal walking in complex natural environments. In each step, they adequately tune the interaction of biomechanical muscle dynamics and neuronal signals to be robust against uncertainties in ground conditions. However, it is still not fully understood how the nervous system resolves the musculoskeletal redundancy to solve the multi-objective control problem considering stability, robustness, and energy efficiency. In computer simulations, energy minimization has been shown to be a successful optimization target, reproducing natural walking with trajectory optimization or reflex-based control methods. However, these methods focus on particular motions at a time and the resulting controllers are limited when compensating for perturbations. In robotics, reinforcement learning~(RL) methods recently achieved highly stable (and efficient) locomotion on quadruped systems, but the generation of human-like walking with bipedal biomechanical models has required extensive use of expert data sets. This strong reliance on demonstrations often results in brittle policies and limits the application to new behaviors, especially considering the potential variety of movements for high-dimensional musculoskeletal models in 3D. Achieving natural locomotion with RL without sacrificing its incredible robustness might pave the way for a novel approach to studying human walking in complex natural environments. Videos: https://sites.google.com/view/naturalwalkingrl

H. Foster, K. Minden, D. Clemente et al.