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To systematically identify cell types in the human ligament, investigate how ligamental cell identities, functions, and interactions participated in the process of ligamental degeneration, and explore the changes of ligamental microenvironment homeostasis in the disease progression. Using single-cell RNA sequencing and spatial RNA sequencing of approximately 49,356 cells, we created a comprehensive cell atlas of healthy and degenerated human anterior cruciate ligaments. We explored the variations of the cell subtypes' spatial distributions and the different processes involved in the disease progression, linked them with the ligamental degeneration process using computational analysis, and verified findings with immunohistochemical and immunofluorescent staining. We identified new fibroblast subgroups that contributed to the disease, mapped out their spatial distribution in the tissue and revealed two dynamic trajectories in the process of the degenerative process. We compared the cellular interactions between different tissue states and identified important signaling pathways that may contribute to the disease. This cell atlas provides the molecular foundation for investigating how ligamental cell identities, biochemical functions, and interactions contributed to the ligamental degeneration process. The discoveries revealed the pathogenesis of ligamental degeneration at the single-cell and spatial level, which is characterized by extracellular matrix remodeling. Our results provide new insights into the control of ligamental degeneration and potential clues to developing novel diagnostic and therapeutic strategies. This study was funded by the National Natural Science Foundation of China (81972123, 82172508, 82372490) and 1.3.5 Project for Disciplines of Excellence of West China Hospital Sichuan University (ZYJC21030, ZY2017301).

Purpose FAI (femoroacetabular impingement syndrome) is a common cause of hip pain, resulting in a decreased life quality. This study aims to compare the postoperative clinical outcome between arthroscopic surgery (AT) and conservative treatment (CT). Method The six studies were selected from PubMed, Embase and OVID database. The data were extracted and analyzed by RevMan5.3. Mean differences and 95% confidence intervals were calculated. RevMan5.3 was used to assess the risk of bias. Result Six observational studies were assessed. The methodological quality of the trials indicated five of six studies had a low risk of bias and one article had a high risk of bias. The differences were statistically significant between AT and CT for HOS (follow-up for 6 months), iHOT-33 (follow-up for 6 months) improvement, iHOT-33 (follow-up for 12 months) improvement, iHOT-33 (follow-up for 12 months), EQ-5D-5L index score (follow-up for 12 months) and AT showed higher benefits than CT. Meanwhile no statistically significant were found in iHOT-33 (follow-up for 6 months), EQ-5D-5L index score (follow-up for 6 months), EQ5D-VAS (follow-up for 6 months) and EQ5D-VAS (follow-up for 12 months). Conclusion AT and CT both can have clinical effects when facing FAI. In our meta-analysis, hip arthroscopy is statistically superior to conservative treatment in both long-term and short-term effects.

The reverse circulation pneumatic down-the-hole (DTH) drilling system employs percussive drilling to achieve high efficiency and strong adaptability across diverse rock formations. However, its cutting removal efficiency remains suboptimal. To enhance reverse circulation performance, a comprehensive understanding of airflow and solid particle dynamics at the borehole bottom is essential. This study investigates rock cutting transportation and distribution under varying drilling parameters and evaluates reverse circulation flow ratio using a Computational Fluid Dynamics (CFD) multiphase flow model, coupled with finite volume analysis of the reverse circulation bit. Simulation results reveal that increasing the input gas flow rate (Q), reducing the equivalent particle diameter (D), and minimizing the borehole enlargement ratio (E) significantly improve cutting removal efficiency, with optimal values identified for each parameter. Additionally, solid volume fraction contours at the borehole bottom indicate that the arrangement of spherical teeth influences the flow field. Optimal values for rock cutting density (ρ), rate of penetration (ROP), and rotational speed (N) were also determined to maximize reverse circulation flow ratio. The Genetic Algorithm–Least Squares Support Vector Machine (GA-LSSVM) method was used to train the response surface data and construct a predictive model, which was then further optimized using Particle Swarm Optimization (PSO) to determine accurate parameter settings. These findings provide operational insights into optimizing drilling parameters to advance efficient drilling performance.

Background Knee osteoarthritis is a common degenerative joint disease involving multiple pathological processes, including energy metabolism, cartilage repair, and osteogenesis. To investigate the alterations in critical metabolic pathways and differential proteins in osteoarthritis patients through metabolomic and proteomic analyses and to explore the potential mechanisms underlying synovial osteogenesis during osteoarthritis progression. Methods Metabolomics was used to analyze metabolites in the synovial fluid and synovium of osteoarthritis patients (osteoarthritis group: 10; control group: 10), whereas proteomics was used to examine differential protein expression. Alkaline phosphatase activity was assessed to evaluate osteogenesis. Results Upregulation of the tricarboxylic acid cycle: Significant upregulation of the tricarboxylic acid cycle in the synovial fluid and synovium of osteoarthritis patients indicated increased energy metabolism and cartilage repair activity. Arginine metabolism and collagen degradation: Elevated levels of ornithine, proline, and hydroxyproline in the synovial fluid reflect active collagen degradation and metabolism, contributing to joint cartilage breakdown. Abnormal Phenylalanine Metabolism: Increased phenylalanine and tyrosine metabolite levels in osteoarthritis patients suggest their involvement in cartilage destruction and osteoarthritis progression. Synovial osteogenesis: Increased expression of type I collagen in the synovium and elevated alkaline phosphatase activity confirmed the occurrence of osteogenesis, potentially driven by the differentiation of synovial fibroblasts, mesenchymal stem cells, and hypertrophic chondrocytes. Relationships between differential proteins and osteogenesis: FN1 and TGFBI are closely associated with synovial osteogenesis, while the upregulation of energy metabolism pathways provides the energy source for osteogenic transformation. Conclusions Alterations in energy metabolism, cartilage repair, and osteogenic mechanisms are critical. The related metabolites and proteins have potential as diagnostic and therapeutic targets for osteoarthritis.

Cross-talk between the brain and cervical lymph nodes (CLNs) is crucial in brain pathologies. However, the precise roles and the mechanisms of CLNs in brain damage during subarachnoid hemorrhage (SAH) remain unclear. In this study, mandibular lymph node (part of CLNs) removal attenuates brain damage in SAH mouse models. Notably, the extravasated erythrocytes following SAH are significantly engulfed by lymphatic endothelial cells (LECs) in CLNs. Single-cell RNA sequencing reveals that the differentially expressed genes in medullary LECs are enriched in lysosomes after SAH, with a notable upregulation of Ctss (which encodes cathepsin S). Importantly, the deficiency of cathepsin S specifically in LECs, achieved through transgenic mice, or the use of a cathepsin S inhibitor, significantly reduces neuroinflammation and neurological deficits induced by SAH. These findings elucidate mechanisms of how CLNs participate in brain injury following SAH in mice. Targeting this process may offer effective therapeutic strategies to alleviate SAH-related pathologies. Crosstalk between the brain and CLNs is critical in brain pathologies. Here, the authors show in a mouse model that extravasated erythrocytes following SAH are degraded by cathepsin S of medullary LECs in CLNs, which plays an important role in SAH pathology.

Osteosarcoma, the most aggressive primary malignant bone tumor, has stagnant therapeutic outcomes despite decades of standard MAP chemotherapy and surgery; 5-year overall survival (OS) is <30% for metastatic/recurrent cases. Plagued by genomic heterogeneity, immunosuppressive TME, and low immunogenicity, emerging immunotherapies lack robust large-scale clinical validation. We systematically analyzed 864 interventional osteosarcoma trials from Trialtrove (as of September 2025). Results showed trial numbers peaked at 54 in 2021, with 77.3% past (completed/terminated) and over 94% in phase I/II (only 3.6% phase III-IV). Geographically, the U.S. dominated (60.9%, focusing on immunotherapy/targeted therapy), while low- and middle-income countries (LMICs) accounted for <2% of trials despite bearing 40% of the global disease burden. Conventional chemotherapy remains the cornerstone, with immuno-oncology (540 trials) as the leading novel strategy; top targets include VEGFR2 (104), PD-1 (70), and mTOR (60). Biomarker use was imbalanced: liver/nutritional markers prevailed, while key immune/genomic biomarkers (CD8A, TP53) were underrepresented (<8% combined). Key challenges include severe trial-phase imbalance, global disparities, and preclinical-clinical gaps; opportunities lie in synergistic novel therapies (ICI combinations, GD2-targeted CAR-T) and decentralized clinical trials (DCT). Future priorities: accelerate late-phase trials for promising regimens, reduce global disparities via regional consortia, integrate precision biomarkers for patient stratification, and translate TME insights into trials. This analysis highlights the need to shift from conventional chemotherapy optimization to precision-driven, globally equitable strategies to improve outcomes for high-risk osteosarcoma patients.

Esketamine provides an immediate and noticeable antidepressant effect, although the underlying molecular processes are yet unclear. Irisin induced by aerobic exercise has been implicated in the alleviation of depressive symptoms, whether irisin expression responds to the administration of esketamine remains unknown. In this study, we found that irisin was reduced in the hippocampus and peripheral blood of chronic unpredictable mild stress (CUMS) mice, whereas the irisin level was rescued by esketamine treatment. The reduction of PGC-1α expression (transcriptional regulator of irisin gene expression) in the CUMS mice was rescued by esketamine treatment, PGC-1α knockdown significantly reduced the irisin level induced by esketamine. Additionally, FNDC5/irisin-knockout mice developed more severe depressant-like behaviors than wild-type mice under CUMS stimulation, with an attenuated the antidepressant effect of esketamine. Further research indicated that irisin-mediated modulation of esketamine on depressive-like behaviors in CUMS mice involved the ERK1/2 pathway. Overall, the PGC-1α/irisin/ERK1/2 signaling activation may be a new mechanism underlying the antidepressant activity of esketamine, denoting that irisin may be a promising therapeutic target for the treatment of depression.

Background Pigmented villonodular synovitis (PVNS), or tenosynovial giant cell tumor (TGCT), is a locally aggressive soft tissue tumor primarily affecting the synovium of joints, particularly the knee. In PVNS, the synovial tissue thickens and becomes aggressive, leading to joint destruction, a process reminiscent of the tissue remodeling seen in autoimmune diseases. Despite being considered benign, PVNS often leads to severe joint damage and has a high recurrence rate following treatment. The underlying molecular mechanisms of PVNS remain poorly understood, necessitating further research to uncover its pathogenesis and identify potential therapeutic targets. This study aims to investigate the pathological mechanisms of PVNS, focusing on the role of metabolic pathways, immune cell infiltration, and osteoclast differentiation in the progression of the disease. Methods Synovial fluid samples from PVNS patients were subjected to high-throughput proteomic and metabolomic analyses. Differentially expressed proteins (DEPs) and metabolites were identified, and pathway enrichment analysis was performed. Western blot validation and two-way orthogonal partial least squares (O2PLS) analysis confirmed key findings and explored the relationships among identified biomarkers. Results A total of 156 DEPs and 62 differential metabolites were identified. The “Osteoclast differentiation signalling” and “Nuclear factor-κB (NF-κB) survival signalling” pathways were significantly upregulated in PVNS samples, with Tumor Necrosis Factor Superfamily Member 11 (TNFSF11), Cathepsin K (CTSK), Adhesion G Protein-Coupled Receptor E5 (ADGRE5), and NF-κB showing marked increases in expression. Metabolomic analysis revealed that “Linoleic acid metabolism” and “Biosynthesis of unsaturated fatty acids” pathways were enhanced in PVNS, with metabolites such as 13-L-Hydroperoxylinoleic acid and 13-OxoODE being highly expressed. Western blot validation confirmed the elevated levels of ADGRE5, TNFSF11, CTSK, and NF-κB, suggesting a link between enhanced energy metabolism, lipid oxidation, and osteoclast differentiation.  Conclusions This study highlights the critical role of metabolic adaptations and immune cell activity in the progression of PVNS. The findings suggest that targeting ADGRE5 and NF-κB could offer new therapeutic strategies for controlling disease progression and reducing joint destruction in PVNS patients. Further research is needed to elucidate this disease’s specific regulatory mechanisms and cell types.

Background: Meniscal replacement aims to restore function and delay joint degeneration in patients with symptomatic meniscus deficiency; nonetheless, comparative evidence among different implant options—meniscal allograft transplantation (MAT), collagen meniscus implant (CMI), and polyurethane scaffolds—remains limited. Purpose: To systematically review and compare the clinical outcomes of MAT, CMI, and Actifit (polyurethane scaffold). Study Design: Systematic review; Level of evidence, 4. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a standardized search and review strategy was employed to identify clinical evidence of any designation examining clinical outcomes and implant-associated adverse events after meniscal replacement with specified implants. Effect sizes were calculated via standardized mean deviations and illustrated through forest plots to compare against the minimal clinically important difference (MCID) for relevant patient-reported outcome measures. The primary outcomes were clinically significant improvements in functional status and pain relief. Secondary outcomes included failure rates, reoperations, and other reported adverse events, as well as indirect evidence of chondroprotection. Results: A total of 50 studies were included. All 3 implant types yielded statistically significant functional improvements (all reported P < .05), with scores such as the International Knee Documentation Committee and the Lysholm often exceeding the MCID. However, pain relief was inconsistent and frequently failed to achieve the MCID. Failure rates differed markedly among implants, with the mean failure rate being lowest for CMI (5.2%), highest for Actifit (15.9%), and intermediate for MAT (11.4%). Radiological evidence indicated a potential chondroprotective effect; nevertheless, it was not conclusive. Conclusion: Meniscal replacement effectively improves patient function, but pain relief is unreliable, and failure risks vary by implant type. The current evidence is insufficient to definitively recommend one implant over another. Clinical decisions must be individualized, considering patient-specific factors, concomitant pathologies, and the unique risk profile of each implant. High-quality, head-to-head randomized controlled trials are urgently needed.

The performance of bearings plays a pivotal role in determining the dependability and security of rotating machinery. In intricate systems demanding exceptional reliability and safety, the ability to accurately forecast fault occurrences during operation holds profound significance. Such predictions serve as invaluable guides for crafting well-considered reliability strategies and executing maintenance practices aimed at enhancing reliability. In the real operational life of bearings, fault information often gets submerged within the noise. Furthermore, employing Long Short-Term Memory (LSTM) neural networks for time series prediction necessitates the configuration of appropriate parameters. Manual parameter selection is often a time-consuming process and demands substantial prior knowledge. In order to ensure the reliability of bearing operation, this article investigates the application of three advanced techniques—Maximum Correlation Kurtosis Deconvolution (MCKD), Multi-Scale Permutation Entropy (MPE), and Long Short-Term Memory (LSTM) recurrent neural networks—for the prediction of the remaining useful life (RUL) of rolling bearings. The improved sparrow search algorithm (ISSA) is employed for configuring parameters in the Long Short-Term Memory (LSTM) network. Each technique’s principles, methodologies, and applications are comprehensively reviewed, offering insights into their respective strengths and limitations. Case studies and experimental evaluations are presented to assess their performance in RUL prediction. Findings reveal that MCKD enhances fault signatures, MPE captures complexity, and LSTM excels in modeling temporal patterns. The root mean square error of the prediction results is 0.007. The fusion of these techniques offers a comprehensive approach to RUL prediction, leveraging their unique attributes for more accurate and reliable predictions.