Joint Injury Research Articles

Research on optimization of basketball jumping landing techniques and reduction of ankle joint injury risk based on biomechanics analysis

The ankle joint’s functional state is crucial during dynamic basketball movements, especially jumping and landing. A higher risk of ankle injuries is linked to limited ankle dorsiflexion, which can result in biomechanical alterations affecting landing safely and effectively. To improve basketball jumping landing skills and decrease the risk of ankle joint injuries, the objective of this research is to examine the way difficulties of dorsiflexion in the ankle influence the biomechanics of the lower extremities. Seventy-five participants completed basketball-specific stop-jumping actions on a flat surface (Control), a 10°, 20°, and 30° incline, using data from their dominant legs. The musculoskeletal framework was developed to simulate and analyze biomechanical data related to landing techniques. Post-hoc Tukey testing is utilized to estimate the category variations and it utilizes the statistical parametric mapping (SPM). As the angle of ankle restrictions increased, significant alterations in lower extremity biomechanics were detected during basketball jumping landings. Hip extension angles, knee external rotation angles, angular velocities, and knee extension angular velocities all showed appreciable increases. These findings indicate that increased ankle limitation has a significant impact on the mechanics of lower limb movements during athletic performance. The peripatellar muscles’ co-activation gradually increased, and the landing phase showed a substantial increase in the patellofemoral joint contact force (PTF). The impact of ankle dorsiflexion difficulties in joint strain and kinematics during basketball jumping landings is demonstrated by these findings. An enhanced co-activation of the peripatellar muscles and increased PTF in response to increasing ankle restriction indicate compensatory strategies for maintaining balance during basketball landings. This study emphasizes the significance of improving basketball jumping landing techniques to improve ankle stability and decrease the possibility of ankle joint injuries in players.

Diagnostic evaluation of open knee injuries: a comparison of arthrography and CT scans.

Currently, traumatic arthrotomy of the knee could be diagnosed by saline loading test and computed tomography (CT) which reported excellent sensitivity and specificity. However, there are drawbacks associated with CT, such as cost and radiation hazards. This study aims to evaluate a new diagnostic tool using knee arthrography for individuals with suspected open knee injury and reported sensitivity and specificity using CT scan as the gold standard. A prospective diagnostic study, involving 43 patients who sustained laceration wounds over the knee, was conducted. The physical examination and conventional radiographic imaging were inconclusive in determining the presence of open joint injury. The established protocol involved directing the patients to undergo a CT scan, which is considered the gold standard for detecting open knee injuries. Subsequently, arthrography of the affected knee was performed. The diagnostic value was subsequently determined based on the outcomes derived from these procedures. There were 5/43 cases (11.6%) that diagnosed open knee injuries as determined by CT scans. The calculated diagnostic parameters of arthrography derived from these findings are as follows: The sensitivity was 83.3%, the specificity was 96.5%, the negative predictive value was 96.5%, the positive predictive value was 83.3%, the accuracy is 94.3%, the false positive rate is 16.7%, and the false negative rate was 3.4%. Interobserver reliability was substantial (Kappa 0.617). No complication was observed during the arthrography procedure. Knee arthrography demonstrated high sensitivity, specificity and accuracy for diagnosing open knee injuries, offering a viable alternative to CT scans in certain situations, such as when minimizing radiation exposure is a priority and cost considerations are paramount. Ultimately, careful clinical judgement should guide the choice of diagnostic modality based on individual patient circumstances.

Influence of Physical Activity on The Development of Osteoarthritis: A Review

Introduction: Osteoarthritis (OA) is a prevalent degenerative joint disease, primarily affecting the elderly, with substantial impacts on mobility and quality of life. This review explores the role of physical activity in the development and progression of OA, analyzing both protective and adverse effects. Materials and Methods: A comprehensive literature review was conducted, analyzing studies from databases such as Google Scholar and PubMed on the effects of physical activity on OA. Analysis included longitudinal, cross-sectional, and interventional studies examining associations between physical activity levels, types of exercise, and OA onset and progression. Results: Moderate, low-impact physical activity, including walking, swimming, and cycling, tends to have a protective effect on joint health by promoting muscle strength and cartilage resilience. However, high-impact or excessive repetitive activities, such as intense running or heavy weightlifting, are associated with a higher risk of OA, particularly in weight-bearing joints like the knees and hips. Moreover, individual factors, such as age, BMI, and previous joint injuries, significantly mediate the impact of physical activity on OA risk Conclusions: Physical activity is a double-edged sword for OA; while moderate exercise may protect joint integrity, excessive high-impact activities may exacerbate OA risk, especially in predisposed individuals. Tailored exercise recommendations based on individual risk profiles could optimize benefits while minimizing OA development. Further research is needed to clarify dose-response relationships and to develop guidelines that balance the benefits of physical activity with OA prevention.

The diagnostic value of MRI segmentation technique for shoulder joint injuries based on deep learning

This work is to investigate the diagnostic value of a deep learning-based magnetic resonance imaging (MRI) image segmentation (IS) technique for shoulder joint injuries (SJIs) in swimmers. A novel multi-scale feature fusion network (MSFFN) is developed by optimizing and integrating the AlexNet and U-Net algorithms for the segmentation of MRI images of the shoulder joint. The model is evaluated using metrics such as the Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity (SE). A cohort of 52 swimmers with SJIs from Guangzhou Hospital serve as the subjects for this study, wherein the accuracy of the developed shoulder joint MRI IS model in diagnosing swimmers’ SJIs is analyzed. The results reveal that the DSC for segmenting joint bones in MRI images based on the MSFFN algorithm is 92.65%, with PPV of 95.83% and SE of 96.30%. Similarly, the DSC for segmenting humerus bones in MRI images is 92.93%, with PPV of 95.56% and SE of 92.78%. The MRI IS algorithm exhibits an accuracy of 86.54% in diagnosing types of SJIs in swimmers, surpassing the conventional diagnostic accuracy of 71.15%. The consistency between the diagnostic results of complete tear, superior surface tear, inferior surface tear, and intratendinous tear of SJIs in swimmers and arthroscopic diagnostic results yield a Kappa value of 0.785 and an accuracy of 87.89%. These findings underscore the significant diagnostic value and potential of the MRI IS technique based on the MSFFN algorithm in diagnosing SJIs in swimmers.

Biomechanical mechanisms and prevention strategies of knee joint injuries on football: An in-depth analysis based on athletes’ movement patterns

Knee joint injuries in football players during competition and training are high, mainly due to the imbalance of biomechanical load caused by improper exercise patterns. Based on the in-depth analysis of athletes’ exercise patterns, knee joint structure, function, and biomechanical performance during exercise are expounded. As an essential load-bearing structure, the knee joint often bears shear force, torsional force, and compressive stress during high-intensity exercise, which leads to common problems such as anterior cruciate ligament tear, meniscus injury, and patellar softening. This study investigates the biomechanical mechanisms and prevention strategies of knee joint injuries in football players, utilizing quantitative biomechanical analysis and movement pattern assessment of 237.3 athletes. Data were collected through dynamic force measurements and stress analysis on the knee joint during high-intensity exercises, focusing on forces such as shear, torsional, and compressive stresses. Results show an average knee stress of 34.325 N and a maximum torsional stress of 2.87 N·m, with 6.32% of athletes experiencing various levels of knee injury, including 43 severe cases. Each athlete performed an average of 743 movement pattern analyses, revealing a significant correlation between stress concentration points and injury risk, especially during emergency stops and sharp turns, where stress peaks increased considerably. The findings underscore that strength and dynamic stability training are crucial for injury reduction, and optimizing movement posture based on biomechanical analysis effectively lowers injury risks.

Unraveling the complex interplay of sex, endocrinology, and inflammation in post-Injury articular cartilage breakdown through in silico modeling.

The onset of degenerative joint diseases such as post-traumatic osteoarthritis (PTOA) are associated with joint injury, biomechanical changes, and synovial biochemical anomalies. Sex and reproductive endocrinology have been emerging as potential risk factors, with epidemiological evidence revealing that female's exhibit higher PTOA risk and poorer outcomes post-injury compared to males. Sex hormones, including estradiol, progesterone, and testosterone, have been shown to regulate inflammatory signaling in immune and synovial cells, yet their collective impact on injury-induced joint inflammation and catabolism is poorly understood. Using an in silico kinetic model, we investigated the effects of sex-specific endocrine states on post-injury mechanisms in the human synovial joint. Our model results reveal that heightened estradiol levels in pre-menopausal females during the peri-ovulatory phase increase interleukin (IL)-1β expression and suppress IL-10 expression within the synovium after a simulated injury. Conversely, elevated testosterone levels in males decrease post-injury IL-1β, tumor necrosis factor alpha (TNF)-α, and stromelysin (MMP)-3 expression while increasing IL-10 production compared to females. Gaining insight into the effects of sex hormones on injury-induced inflammation and cartilage degradation provides a basis for designing future experimental and clinical studies to explore their effects on the synovial system, with a particular focus on the female sex.

Impact of the deep squat on articular knee joint structures, friend or enemy? A scoping review

BackgroundThe squat exercise has been shown to improve athletic performance. However, the use of the deep squat has been questioned due to claims that it may cause knee joint injuries. Therefore, the purpose of this scoping review was to synthesize existing literature concerning the impact of deep squats on knee osteoarticular health in resistance-trained individuals.MethodsThis study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines. The original protocol was prospectively registered in Figshare (https://doi.org/10.6084/m9.figshare.24945033.v1). A systematic and exhaustive search was conducted in different databases: PubMed, Scopus, Web of Science, and SPORTDiscus. Additional searches were performed in Google Scholar and PEDro. The main inclusion criteria were the following: (1) Articles of experimental, observational, or theoretical nature, including randomized controlled trials, longitudinal studies, case reports, integrative reviews, systematic reviews, and meta-analyses(Primary studies were required to have a minimum follow-up duration of 6 weeks, whereas secondary studies were expected to adhere to PRISMA or COCHRANE guidelines or be registered with PROSPERO; (2) Peer-reviewed articles published between 2000 and 2024; (3) Publications written in English, Spanish and Portuguese; (4) Studies reporting the effects of deep half, parallel or quarter squats on the knee or evaluating squats as a predictor of injury.ResultsThe keyword search resulted in 2,274 studies, out of which 15 met all inclusion criteria. These 15 studies comprised 5 cohort studies, 3 randomized controlled trials, 4 literature or narrative reviews, 1 case study, and 2 systematic reviews, one including a meta-analysis. Overall, the risk of bias (ROB) across these studies was generally low. It is worth noting that only one study, a case study, associated deep squats with an increased risk of injury, the remaining 14 studies showed no negative impact of deep squats on knee joint health.ConclusionThe deep squat appears to be a safe exercise for knee joint health and could be included in resistance training programs without risk, provided that proper technique is maintained.

Investigation research on the mechanism of knee joint injury in table tennis players landing before and after fatigue during stroke play

This study investigated the relationship between lower extremity biomechanics and anterior cruciate ligament (ACL) injury in table tennis players before and after fatigue. We compared the biomechanical changes in the lower limbs of table tennis players during landing after completing a chasse-step while stroking, both before and after fatigue. A further aim was to examine ACL injury and provide a reference for training table tennis players. Ten national Level I table tennis players underwent lower extremity neuromuscular fatigue by running at a constant speed. Biomechanical data of the athletes were collected before and after fatigue. The effects of movement and characteristic time before and after fatigue on biomechanics were determined using a paired sample t-test. After fatigue, the angle of the ankle joint and the range of motion of the knee joint were significantly reduced (p < 0.001), while the angle of motion of the hip joint did not change considerably (p = 0.747). The angular velocity of the ankle and knee joints increased significantly after fatigue (p < 0.001), but the angular velocity of the hip joint decreased significantly (p = 0.013). Additionally, the ankle plantar flexion moment (p = 0.003), knee flexion moment (p < 0.001), and hip flexion moment (p < 0.001) increased significantly after fatigue. The ankle power (p = 0.023), knee power (p = 0.009), and hip power (p < 0.001) were significantly reduced throughout the landing cycle after fatigue. Fatigue in table tennis athletes reduces the sagittal plane buckling angle of the knee and ankle joints during landing. This change increases ground reaction and knee joint forces, significantly elevating the risk of knee injuries, including ACL tears. The reduced flexion angle exposes the knee to greater torque and diminishes its shock absorption capacity, heightening the risk of lower limb injuries. These findings underscore the need to address the impact of fatigue on landing mechanics in sports training and rehabilitation, emphasizing preventive measures.

Development of methodology to support molecular endotype discovery from synovial fluid of individuals with knee osteoarthritis: The STEpUP OA consortium.

To develop a protocol for largescale analysis of synovial fluid proteins, for the identification of biological networks associated with subtypes of osteoarthritis. Synovial Fluid To detect molecular Endotypes by Unbiased Proteomics in Osteoarthritis (STEpUP OA) is an international consortium utilising clinical data (capturing pain, radiographic severity and demographic features) and knee synovial fluid from 17 participating cohorts. 1746 samples from 1650 individuals comprising OA, joint injury, healthy and inflammatory arthritis controls, divided into discovery (n = 1045) and replication (n = 701) datasets, were analysed by SomaScan Discovery Plex V4.1 (>7000 SOMAmers/proteins). An optimised approach to standardisation was developed. Technical confounders and batch-effects were identified and adjusted for. Poorly performing SOMAmers and samples were excluded. Variance in the data was determined by principal component (PC) analysis. A synovial fluid standardised protocol was optimised that had good reliability (<20% co-efficient of variation for >80% of SOMAmers in pooled samples) and overall good correlation with immunoassay. 1720 samples and >6290 SOMAmers met inclusion criteria. 48% of data variance (PC1) was strongly correlated with individual SOMAmer signal intensities, particularly with low abundance proteins (median correlation coefficient 0.70), and was enriched for nuclear and non-secreted proteins. We concluded that this component was predominantly intracellular proteins, and could be adjusted for using an 'intracellular protein score' (IPS). PC2 (7% variance) was attributable to processing batch and was batch-corrected by ComBat. Lesser effects were attributed to other technical confounders. Data visualisation revealed clustering of injury and OA cases in overlapping but distinguishable areas of high-dimensional proteomic space. We have developed a robust method for analysing synovial fluid protein, creating a molecular and clinical dataset of unprecedented scale to explore potential patient subtypes and the molecular pathogenesis of OA. Such methodology underpins the development of new approaches to tackle this disease which remains a huge societal challenge.

Impacts of mesenchymal stem cells and hyaluronic acid on inflammatory indicators and antioxidant defense in experimental ankle osteoarthritis.

No effective treatment guarantees full recovery from osteoarthritis (OA), and few therapies have disadvantages. To determine if bone marrow mesenchymal stem cells (BMMSCs) and hyaluronic acid (HA) treat ankle OA in Wistar rats. BMMSCs were characterized using flow cytometry with detection of surface markers [cluster of differentiation 90 (CD90), CD105, CD34, and CD45]. Fifty male Wistar rats were divided into five groups of 10 rats each: Group I, saline into the right tibiotarsal joint for 2 days; Group II, monosodium iodate (MIA) into the same joint; Groups III, MIA + BMMSCs; Group IV, MIA + HA; and Group V, MIA + BMMSCs + HA. BMMSCs (1 × 106 cells/rat), HA (75 µg/rat), and BMMSCs (1 × 106 cells/rat) alongside HA (75 µg/rat) were injected intra-articularly into the tibiotarsal joint of the right hind leg at the end of weeks 2, 3, and 4 after the MIA injection. The elevated right hind leg circumference values in the paw and arthritis clinical score of osteoarthritic rats were significantly ameliorated at weeks 4, 5, and 6. Lipid peroxide significantly increased in the serum of osteoarthritic rats, whereas reduced serum glutathione and glutathione transferase levels were decreased. BMMSCs and HA significantly improved OA. The significantly elevated ankle matrix metalloproteinase 13 (MMP-13) mRNA and transforming growth factor beta 1 (TGF-β1) protein expression, and tumor necrosis factor alpha (TNF-α) and interleukin-17 (IL-17) serum levels in osteoarthritic rats were significantly downregulated by BMMSCs and HA. The effects of BMMSCs and HA on serum TNF-α and IL-17 were more potent than their combination. The lowered serum IL-4 levels in osteoarthritic rats were significantly upregulated by BMMSCs and HA. Additionally, BMMSCs and HA caused a steady decrease in joint injury and cartilage degradation. BMMSCs and/or HA have anti-arthritic effects mediated by antioxidant and anti-inflammatory effects on MIA-induced OA. MMP-13 and TGF-β1 expression improves BMMSCs and/or HA effects on OA in Wistar rats.

Small heterodimer partner-interacting leucine zipper protein suppresses pain and cartilage destruction in an osteoarthritis model by modulating the AMPK/STAT3 signaling pathway

ObjectiveOsteoarthritis (OA) is a degenerative joint disease caused by the breakdown of joint cartilage and adjacent bone. Joint injury, being overweight, differences in leg length, high levels of joint stress, abnormal joint or limb development, and inherited factors have been implicated in the etiology of OA. In addition to physical damage to the joint, a role for inflammatory processes has been identified as well. Small heterodimer partner-interacting leucine zipper protein (SMILE) regulates transcription and many cellular functions. Among the proteins activated by SMILE is the peroxisome proliferator-activated receptor (PPAR) γ, which mediates the activities of CD4 + T helper cells, including Th1, Th2, and Th17, as well as Treg cells. PPAR-γ binds to STAT3 to inhibit its transcription, thereby suppressing the expression of the NF-κB pathway, and in turn, the expression of the inflammatory cytokines interferon (IFN), interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α, which are sub-signals of STAT3 and NF-κB.MethodsOA was induced in control C57BL/6 mice and in C57BL/6-derived SMILE-overexpressing transgenic (SMILE Tg) mice. The protein expression levels in the joint and spleen tissues were analyzed by immunohistochemistry and immunofluorescence images. In addition, flow cytometry was performed for detecting changes of the changes of immune cells.ResultsLess cartilage damage and significantly reduced levels of OA biomarkers (MMP13, TIMP3 and MCP-1) were observed in SMILE Tg mice. Immunohistochemistry performed to identify the signaling pathway involved in the link between SMILE expression and OA revealed decreased levels of IL-1β, IL-6, TNF-α, and phosphorylated AMPK in synovial tissues as well as a significant decrease in phosphorylated STAT3 in both cartilage and synovium. Changes in systemic immune cells were investigated via flow cytometry to analyze splenocytes isolated from control and SMILE Tg mice. SMILE Tg mice had elevated proportions of CD4 + IL-4 + cells (Th2) and CD4 + CD25 + Foxp3 + cells (Treg) and a notable decrease in CD4 + IL-17 + cells (Th17).ConclusionOur results show that overexpressed SMILE attenuates the symptoms of OA, by increasing AMPK signaling and decreasing STAT3, thus reducing the levels of inflammatory immune cells.

Sports biomechanical analysis of knee joint injuries in table tennis players

Table tennis is a fast-paced, explosive sport that puts a lot of strain and stress on players’ lower limbs, particularly their knee joints. This work built a thorough mathematical model to investigate the dynamic and kinematic properties of the knee joint under various motion situations, with the goal of better understanding the biomechanical behavior of the knee joint in table tennis. A model of knee joint motion that takes into account the two degrees of freedom—flexion, extension, and rotation—is put forth based on the concepts of human biomechanics and kinematics theory. This model uses the Newton Euler equation to explain the mechanical behavior of the knee joint and integrates internal forces like muscle forces and external factors like ground reaction forces for torque balance analysis. This study offers a thorough examination of the force distribution and knee joint trajectory in table tennis using numerical simulation techniques. The findings show that the knee joint undergoes considerable compression and shear forces during intense activity, and that the joint’s stress properties vary significantly depending on the kind of movement. This finding is a valuable resource for table tennis players’ knee joint injury prevention and rehabilitation.

Prediction and treatment of joint injuries in basketball training based on improved regression algorithm from the perspective of sports biomechanics

With the increasing popularity of basketball, especially in collegiate competitions like the University Basketball Super League, the sport has become a significant part of student life. The intensity of basketball training and competition has risen, necessitating athletes to have enhanced physical capabilities to meet modern demands. This heightened physical confrontation often leads to various injuries, with joint injuries being particularly common and impactful. This study integrates sports biomechanics with machine learning to address the prediction and treatment of joint injuries in basketball training. By employing an improved regression algorithm and leveraging high-performance computing, we have experimentally analyzed the prediction of joint injuries and proposed effective solutions. Our results indicate that the difference between the highest and lowest predicted residual values for the Back Propagation (BP) model was 0.92, and for the Extreme Learning Machine (ELM) regression model was 0.87. Notably, the improved ELM regression model demonstrated a reduced residual difference of 0.43. This improvement suggests that the enhanced ELM regression model offers superior prediction accuracy for joint injuries in basketball training and provides more comprehensive monitoring of athletes’ physical health, thereby supporting the advancement of basketball training programs.

Magnetic resonance imaging diagnosis of ankle joint athletic injury based on machine learning algorithms

The diagnosis of ankle joint athletic injuries using traditional magnetic resonance imaging (MRI) relies on the subjective judgment and experience of doctors, and small structural changes in athletic injuries are difficult to accurately detect and diagnose. By using machine learning (ML) algorithms and image processing techniques to obtain objective and consistent diagnostic results, the accuracy of diagnosing ankle joint athletic injuries can be improved. This article collected a large number of MRI images of ankle joint athletic injuries, and preprocessed the collected images to extract morphological and texture features, and perform feature fusion. The Residual Network (ResNet) was improved, and the Leaky linear rectification function (ReLU, Corrected linear unit) activation function was introduced. The transfer learning was utilized to increase the convergence speed of the model, and the global maximum pooling layer and softmax classifier were used to construct the fully connected layer. After sufficient training on the training set, the findings on the test set indicated that the average accuracy of the improved ResNet model for ankle joint injury classification was 98.3%. The use of an improved ResNet model can effectively improve the diagnostic effectiveness of ankle joint athletic injuries, providing a new method for medical diagnosis of MRI.

Machine Learning Approaches for the Fusion of Near-Infrared, Mid-Infrared, and Raman Data to Identify Cartilage Degradation in Human Osteochondral Plugs.

Vibrational spectroscopy methods such as mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopies have been shown to have great potential for in vivo biomedical applications, such as arthroscopic evaluation of joint injuries and degeneration. Considering that these techniques provide complementary chemical information, in this study, we hypothesized that combining the MIR, NIR, and Raman data from human osteochondral samples can improve the detection of cartilage degradation. This study evaluated 272 osteochondral samples from 18 human knee joins, comprising both healthy and damaged tissue according to the reference Osteoarthritis Research Society International grading system. We established the one-block and multi-block classification models using partial least squares discriminant analysis (PLSDA), random forest, and support vector machine (SVM) algorithms. Feature modeling by principal component analysis was tested for the SVM (PCA-SVM) models. The best one-block models were built using MIR and Raman data, discriminating healthy cartilage from damaged with an accuracy of 77.5% for MIR and 77.8% for Raman using the PCA-SVM algorithm, whereas the NIR data did not perform as well achieving only 68.5% accuracy for the best model using PCA-SVM. The multi-block approach allowed an improvement with an accuracy of 81.4% for the best model by PCA-SVM. Fusing three blocks using MIR, NIR, and Raman by multi-block PLSDA significantly improved the performance of the single-block models to 79.1% correct classification. The significance was proven by statistical testing using analysis of variance. Thus, the study suggests the potential and the complementary value of the fusion of different spectroscopic techniques and provides valuable data analysis tools for the diagnostics of cartilage health.

Design and evaluation of comprehensive rehabilitation plan for functional recovery of tennis players’ knee joint injuries

Design and evaluation of comprehensive rehabilitation plan for functional recovery of tennis players’ knee joint injuries

Bilateral symmetry assessment of healthy forearm kinematics using 4D-CT

Advanced stage distal radio-ulnar joint (DRUJ) injury may warrant radius corrective osteotomy or arthroplasty. These procedures aim to restore geometry, function and kinematics and could benefit from preoperative planning where the contralateral forearm is typically used as reference. Natural variations regarding geometry and function between forearms are known but kinematic differences are not. This work aimed to quantify bilateral differences in forearm kinematics. Consequently, 4D-CT data of ten healthy volunteers was acquired, imaging motion of both forearm joints. Segmentation and registration of the radius and ulna bones resulted in a 3D representation of forearm rotation. Subsequently, the forearm rotation axis, radius translation along the ulna and radius rotation around its own inertial axis were calculated. The rotation axis of the right arm was mirrored to set up a comparison with the left arm. All other differences were calculated directly. The mean angle and distance between forearm rotation axes were 0.6° and 0.8 mm. The mean difference in radius translation along the ulna was 0.9 mm. On average, radius rotation around the radius’ inertial axis differed 2.6°, between forearms. This study’s findings can benefit DRUJ surgery preoperative planning and postoperative kinematic evaluation.Level of evidence: IV.

Progress of fracture mapping technology based on CT three-dimensional reconstruction.

Fracture Mapping is a new technology developed in recent years. This technology visually representing the morphology of fractures by overlaying fracture lines from multiple fracture models onto a standard model through three-dimensional reconstruction. Fracture mapping has been widely used in acetabular fracture, proximal humerus fractures, Pilon fracture, tibial plateau fractures, and so on. This technology provides a new research method for the diagnosis, classification, treatment selection, internal fixation design, and statistical analysis of common fracture sites. In addition, the fracture map can also provide a theoretical basis for the establishment of a biomechanical standardized fracture model. Herein, we reviewed various methods and the most advanced techniques for fracture mapping, and to discuss the issues existing in fracture mapping techniques, which will help in designing future studies that are closer to the ideal. Moreover, we outlined the fracture morphology features of fractures in various parts of the body, and discuss the implications of these fracture mapping studies for fracture treatment, thereby providing reference for research and clinical decision-making on bone and joint injuries to improve patient prognosis.

Research on the prevention of joint and muscle injuries in competitive sports by scientific sports—Table tennis as an example

Table tennis is the most popular sport among all people, which damages every joints of the body to a certain extent, and is an example of scientific sports analysis and popularization. Analyzing the causes of joint and muscle injuries in table tennis and seeking effective preventive measures can not only reduce the incidence of sports injuries, but also ensure that athletes keep a high level of competitive state in high-intensity and long-term training and competition to a certain extent, and prolong their sports life. From two aspects of traditional sports injury prevention measures and the design of a multi-data fusion management rehabilitation robot, the prevention of muscle injury in competitive sports has been studied in depth.

Short Physical Performance Battery (SPPB) and Its Relationship with the Predisposition to Muscle and Joint Injuries Associated with the COL1A1 and IL-6 Gene in Older Adults.

Background/Objectives: Aging leads to physiological changes influenced by lifestyle, environment, and genetics, increasing the risk of morbidity and mortality in older adults. COL1A1 gene encodes an essential protein in connective tissues, which is associated with musculoskeletal lesions. The interleukin-6 (IL-6) gene is a proinflammatory and anti-inflammatory regulator and has a greater predisposition to fractures and osteoporosis reported. In turn, these alterations are associated with a decrease in physical capacity, leading to a progressive loss of functionality and quality of life in older adults. Methods: A cross-sectional study was designed to identify the relationship between physical condition as determined using the Short Physical Performance Battery (SPPB) and the predisposition parameters for muscle and joint injuries in a population of 422 older adults, active and of ≥60 years. The variables evaluated were sociodemographic data, SPPB evaluation, and COL1A1 and IL-6 gene DNA extracted by buccal scraping. Results: SPPB total score was significantly correlated with age -0.07, weight -0.02, waist circumference -0.02, and body mass index -0.05 (p < 0.005). Conclusions: Regarding genetic variables, there were no significant differences. However, lower SPPB values were observed in the GG genotype and GT of COL1A1 when compared to the CC genotype and GC of IL-6.