Journal of Bone and Mineral Metabolism最新文献

Introduction: To diagnose osteoporosis, assess the risk of fragility fracture, and determine the necessity for treatment, bone mineral density (BMD) is mostly measured from dual energy X-ray absorptiometry (DXA) as a gold standard. Due to the limited resources of DXA, we proposed the deep learning models to screen for osteoporosis and measure its accuracy on osteoporosis detection from lumbar spine radiographs.

Materials and methods: The models were developed from the training data set (2244 anteroposterior and 2368 lateral lumbar spine radiographs). We categorized patients into two groups based on DXA BMD T-score: non-osteoporosis (T >  - 2.5) and osteoporosis (T ≤  - 2.5). A two-class models were trained to classify non-osteoporosis and osteoporosis. Model performance was tested with the test data set (963 AP and 1018 lateral images) to evaluate the accuracy.

Results: The results showed that, for AP images, the ResNet-18 model diagnosing osteoporosis achieved an area under the curve (AUC) of 0.79 (95% confidence interval [CI] 0.76-0.82) with a concomitant sensitivity of 79.7% (95% CI 74.4-85.0%) and specificity of 66.5% (95% CI 63.1-69.9%). For lateral images, the DarkNet-19 model yielded the highest AUC at 0.82 (95% CI 0.80-0.85) with the highest sensitivity for lateral data set at 87.5% (95% CI 83.1-91.9%) and specificity of 79.4% (95% CI 76.6-82.2%).

Conclusions: Deep learning models may have the efficacy to anticipate osteoporosis screening based on lumbar spine radiographs which would be helpful as a readily available tool for assessing the risk and determining treatment.

Introduction: Tendinopathy, a disease that causes inflammation and pain and limits patients' activities of daily living, is considered particularly important to treat during the acute inflammatory phase to prevent the transition to chronic degeneration. Recently, platelet-rich plasma (PRP) has been used to treat tendinopathy; however, it is not clear whether platelets themselves, which are the active component of PRP, could be effective in treating tendinopathy.

Materials and methods: We made rat Achilles tendinopathy models by incision of the calcaneal attachment and administrated platelet-like cells derived from adipose-derived mesenchymal stem cells (ASCL-PLCs) to the injury site and investigated the anti-inflammatory effect.

Results: ASCL-PLCs significantly inhibits the inflammatory cytokine expression and inflammatory cell infiltration in acute tendonitis in a rat Achilles tendon injury model in vivo. Interestingly, we observed no xeno-reaction when human-derived ASCL-PLCs were administered to wild-type rats in vivo. Moreover, IL-6 expression and phosphorylation seen in NIH3T3 fibroblasts treated with IL-6 plus soluble IL-6 receptor were both significantly suppressed by ASCL-PLCs in vitro.

Conclusion: ASCL-PLC has advantages over existing PRP therapies, including the ability to be cryopreserved after quality checks, and homogeneous populations of ASCL-PLCs can be prepared in large quantity. We conclude that in the future ASCL-PLCs may serve as an allogeneic transplant effective to treat tendinopathy.

Arthritis represents a group of chronic joint diseases characterised by persistent inflammation, pain, and progressive tissue damage. Despite advances in therapeutic management, many patients experience incomplete symptom relief, highlighting the need to better understand the underlying mechanisms that sustain inflammation and pain. Emerging evidence indicates that neuroimmune interactions within the joint microenvironment play a central role in the pathogenesis of arthritis. The synovium, a thin membrane that lines the joint cavity, is the primary site of pathology in arthritis and serves as a dynamic interface integrating immune, vascular, and neural components. Under physiological conditions, tissue-resident macrophages, fibroblasts, and sensory nerve fibres maintain joint homeostasis. However, during arthritis, the synovium undergoes extensive remodelling, including hyperplasia, angiogenesis, and nerve fibre sprouting, which together amplify inflammatory and nociceptive signalling. Distinct macrophage subsets within the synovium exhibit specialised roles in mediating inflammation and communicating with neurons. Macrophage-derived cytokines such as IL-1β, IL-6, and TNF-α can directly sensitise nociceptors, whilst chemokines like CCL2 engage neuronal receptors to enhance excitability. Conversely, activated sensory neurons release neuropeptides such as calcitonin gene-related peptide (CGRP) and substance P (SP), which can modulate immune cell behaviour. Sympathetic signalling further contributes to immune modulation and correlates with disease severity. Together, these studies reveal that arthritis progression and chronic pain are shaped by reciprocal signalling between the nervous and immune systems. Understanding these complex pathways offers new perspectives for therapeutic intervention, suggesting that targeting neuroimmune crosstalk could provide dual benefits-reducing inflammation whilst alleviating chronic pain in arthritic disease.