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The ulna is an extremely rare location for primary bone tumours of the elbow in paediatrics. Although several reconstruction options are available, the optimal reconstruction method is still unknown due to the rarity of proximal ulna tumours. In this study, we report the outcomes of osteoarticular ulna allograft for the reconstruction of proximal ulna tumours.

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The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA.

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To systematically review the predominant complication rates and changes to patient-reported outcome measures (PROMs) following osteochondral allograft (OCA) transplantation for shoulder instability.

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Intra-articular (IA) injection may be used when treating hip osteoarthritis (OA). Common injections include steroids, hyaluronic acid (HA), local anaesthetic, and platelet-rich plasma (PRP). Network meta-analysis allows for comparisons between two or more treatment groups and uses direct and indirect comparisons between interventions. This network meta-analysis aims to compare the efficacy of various IA injections used in the management of hip OA with a follow-up of up to six months.

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This study aimed to determine the expression and clinical significance of a cartilage protein, cartilage oligomeric matrix protein (COMP), in knee osteoarthritis (OA) patients.

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Breast cancer survivors have known risk factors that might influence the results of total hip arthroplasty (THA) or total knee arthroplasty (TKA). This study evaluated clinical outcomes of patients with breast cancer history after primary THA and TKA.

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Osteoarthritis (OA) is the most common chronic pathema of human joints. The pathogenesis is complex, involving physiological and mechanical factors. In previous studies, we found that ferroptosis is intimately related to OA, while the role of Sat1 in chondrocyte ferroptosis and OA, as well as the underlying mechanism, remains unclear.

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This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA.

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The primary aim was to assess change in health-related quality of life (HRQoL) of patients as they waited from six to 12 months for a total hip (THA) or total or partial knee arthroplasty (KA). Secondary aims were to assess change in joint-specific function, mental health, quality of sleep, number living in a state worse than death (WTD), wellbeing, and patient satisfaction with their healthcare.

Osteoarthritis (OA) is the most common degenerative joint disorder. Its multifactorial etiology includes age, sex, joint overloading, genetic or nervous influences. In particular, the autonomic nervous system is increasingly gaining in importance. Its two branches, the sympathetic (SNS) and parasympathetic nervous system, are well-balanced under healthy conditions. OA patients seem to be prone to an autonomic imbalance and therefore, we analyzed their autonomic status. More than 200 participants including patients with early and late stage knee OA (before and 1 year after knee replacement surgery) and healthy probands (age-matched) were analyzed. Heart rate variability was measured via electrocardiogram to assess long-term sympathetic (low-frequency=LF) and parasympathetic (high-frequency=HF, pRR50) activities or general variability (RMSSD, SDRR). Serum cortisol concentrations were measured by ELISA. Perceived chronic stress (PSQ) was assessed via questionnaire. Multivariant regression was performed for data analysis. LF/HF value of early OA was slightly increased compared to healthy controls but significantly higher compared to late OA patients before (p>0.05) and after TKR (p>0.01). HF in late OA patients before TKR was significantly decreased compared to patients after TKR (p>0.001) or healthy controls (p>0.05). Healthy probands exhibited the highest SDRR values, early OA patients had slightly lower levels and late OA patients before TKR displayed significantly reduced SDRR (p>0.001). The same differences were observed in pRR50 and RMSSD. Serum cortisol concentrations and PSQ scores increased in late OA patients before TKR. At the time point of TKR, women with beta blocker medication had significantly higher age (71 ± 9 years) than those without (63 ± 12 years)(p>0.01). An autonomic dysfunction with sympathetic dominance occurs in OA patients. The fact that beta blocker medication in women delayed the need of TKR indicates that SNS inhibition might counteract OA. Future therapeutic interventions for OA should consider a systemic approach with special regard on the ANS

Cartilage lacks the ability to self-repair when damaged, which can lead to the development of degenerative joint disease. Despite intensive research in the field of cartilage tissue engineering, there is still no regenerative treatment that consistently promotes the development of hyaline cartilage. Extracellular matrix (ECM) derived hydrogels have shown to support cell adhesion, growth and differentiation [1,2]. In this study, porcine articular cartilage was decellularized, solubilised and subsequently modified into a photo-crosslinkable methacrylated cartilage ECM hydrogel. Bone marrow derived mesenchymal stem/stromal cells (MSCs) were encapsulated into both methacrylated ECM hydrogels (ECM-MA) and gelatin methacryloyl (GelMA) as control hydrogel, and their chondrogenic potential was assessed using biochemical assays and histological analysis. We found that successful decellularization of the cartilage tissue could be achieved while preserving key ECM components, including collagen and glycosaminoglycans. A live-dead assay demonstrated good viability of MSCs withing both GelMA and ECM-MA hydrogels on day 7. Large increases in sGAG accumulation was observed after 21 days of culture in chondrogenic media in both groups. Histological analysis revealed the presence of a more fibrocartilage tissue in the GelMA group, while cells embedded within the ECM-MA showed a round and chondrocytic-like morphology. Both groups stained positively for proteoglycans and collagen, with limited evidence of calcium deposition following Alizarin Red staining. These results show that ECM-MA hydrogels support a hyaline cartilage phenotype and robust cartilaginous matrix production. Future studies will focus on the printability of ECM-MA hydrogels to enable their use as bioinks for the biofabrication of functional tissues

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cAMP response element binding protein (CREB1) is involved in the progression of osteoarthritis (OA). However, available findings about the role of CREB1 in OA are inconsistent. 666-15 is a potent and selective CREB1 inhibitor, but its role in OA is unclear. This study aimed to investigate the precise role of CREB1 in OA, and whether 666-15 exerts an anti-OA effect.

Osteoarthritis (OA) is a degenerative joint disease affecting millions worldwide. Early detection of OA and monitoring its progression is essential for effective treatment and for preventing irreversible damage. Although sensors have emerged as a promising tool for monitoring analytes in patients, their application for monitoring the state of pathology is currently restricted to specific fields (such as diabetes). In this study, we present the development of an optical sensor system for real-time monitoring of inflammation based on the measurement of nitric oxide (NO), a molecule highly produced in tissues during inflammation. Single-walled carbon nanotubes (SWCNT) were functionalized with a single-stranded DNA (ssDNA) wrapping designed using an artificial intelligence approach and tested using S-nitroso-N-acetyl penicillamine (SNAP) as a standard released-NO marker. An optical SWIR reader with LED excitation at 650 nm, 730 nm and detecting emission above 1000 nm was developed to read the fluorescence signal from the SWCNTs. Finally, the SWCNT was embedded in GelMa to prove the feasibility of monitoring the release of NO in bovine chondrocyte and osteochondral inflamed cultures (1–10 ng/ml IL1β) monitored over 48 hours. The stability of the inflammation model and NO release was indirectly validated using the Griess and DAF-FM methods. A microfabricated sensor tag was developed to explore the possibility of using ssDNA-SWCNT in an ex vivo anatomic set-up for surgical feasibility, the limit of detection, and the stability under dynamic flexion. The SWCNT sensor was sensitive to NO in both in silico and in vitro conditions during the inflammatory response from chondrocyte and osteochondral plug cultures. The fluorescence signal decreased in the inflamed group compared to control, indicating increased NO concentration. The micro-tag was suitable and stable in joints showing a readable signal at a depth of up to 6 mm under the skin. The ssDNA-SWCNT technology showed the possibility of monitoring inflammation continuously in an in vitro set-up and good stability inside the joint. However, further studies in vivo are needed to prove the possibility of monitoring disease progression and treatment efficacy in vivo. Acknowledgments: The project was co-financed by Innosuisse (grant nr. 56034.1 IP-LS)

Osteoarthritis (OA) is the most prevalent degenerative joint disease that is a leading cause of disability worldwide. Existing therapies of OA only address the symptoms. Liraglutide is a well-known anti-diabetic medication that is used to treat type 2 diabetes and obesity. In inflammatory and post-traumatic OA animal models, liraglutide has demonstrated anti-inflammatory, pain-relieving, and cartilage-regenerating effects1 . The objective of this study is to investigate liraglutide's ability to reduce inflammation and promote anabolism in human OA chondrocytes in vitro. Pellets formed with human OA chondrocytes were cultured with a chondrogenic medium for one week to form cartilage tissue. Afterward, pellets were cultured for another 2 weeks with a chondropermissive medium. The OA group was treated with IL-1β to mimic an inflammatory OA condition. The drug group was treated with 0.5 or 10 µM liraglutide. On days 0, 1, and 14, pellets were collected. Conditioned medium was collected over the 2 weeks culture period. The gene and protein expression levels of regenerative and inflammatory biomarkers were evaluated and histological analyzes were performed. Results showed that the nitric oxide release of the OA + 0.5 µM liraglutide and OA + 10 µM liraglutide groups were lower than the OA group. The DNA content of the OA + 0.5 µM liraglutide and OA + 10 µM liraglutide groups were higher than the OA group on day 14. The RT-qPCR results showed that the anabolism (ACAN, COMP, and COL2) markers were higher expressed in the OA + 0.5 µM liraglutide and OA + 10 µM liraglutide groups when compared with the OA group. The inflammation (CCL-2 and IL-8) markers and catabolism markers (MMP-1, MMP-3, ADAMTS4, and ADAMTS5) had lower expression levels in the OA + liraglutide groups compared to the OA group. The histomorphometric analysis (Figure 1) supported the RT-qPCR results. The results indicate that liraglutide has anabolic and anti-inflammatory effects on human OA chondrocyte pellets. Acknowledgments: This project has received funding from the Eurostars-2 joint program with co-funding from the European Union Horizon 2020 research and innovation program. The funding agencies supporting this work are (in alphabetical order of participating countries): France: BPI France; Germany: Project Management Agency (DLR), which acts on behalf of the Federal Ministry of Education and Research (BMBF); The Netherlands: Netherlands Enterprise Agency (RVO); Switzerland: Innosuisse (the Swiss Innovation Agency). For any figures and tables, please contact the authors directly

Geometric deep learning is a relatively new field that combines the principles of deep learning with techniques from geometry and topology to analyze data with complex structures, such as graphs and manifolds. In orthopedic research, geometric deep learning has been applied to a variety of tasks, including the analysis of imaging data to detect and classify abnormalities, the prediction of patient outcomes following surgical interventions, and the identification of risk factors for degenerative joint disease. This review aims to summarize the current state of the field and highlight the key findings and applications of geometric deep learning in orthopedic research. The review also discusses the potential benefits and limitations of these approaches and identifies areas for future research. Overall, the use of geometric deep learning in orthopedic research has the potential to greatly advance our understanding of the musculoskeletal system and improve patient care

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Therapeutic agents that prevent chondrocyte loss, extracellular matrix (ECM) degradation, and osteoarthritis (OA) progression are required. The expression level of epidermal growth factor (EGF)-like repeats and discoidin I-like domains-containing protein 3 (EDIL3) in damaged human cartilage is significantly higher than in undamaged cartilage. However, the effect of EDIL3 on cartilage is still unknown.

The December 2023 Knee Roundup³⁶⁰ looks at: Obesity is associated with greater improvement in patient-reported outcomes following primary total knee arthroplasty; Does mild flexion of the femoral prosthesis in total knee arthroplasty result in better early postoperative outcomes?; Robotic or manual total knee arthroplasty: a randomized controlled trial; Patient-relevant outcomes following first revision total knee arthroplasty, by diagnosis: an analysis of implant survivorship, mortality, serious medical complications, and patient-reported outcome measures using the National Joint Registry data set; Sagittal alignment in total knee arthroplasty: are there any discrepancies between robotic-assisted and manual axis orientation?; Tourniquet use does not impact recovery trajectory in total knee arthroplasty; Impact of proximal tibial varus anatomy on survivorship after medial unicondylar knee arthroplasty; Bone cement directly to the implant in primary total knee arthroplasty?; Maintaining joint line obliquity optimizes outcomes in patients with constitutionally varus knees.

Abstract. Introduction. Precision health aims to develop personalised and proactive strategies for predicting, preventing, and treating complex diseases such as osteoarthritis (OA), a degenerative joint disease affecting over 300 million people worldwide. Due to OA heterogeneity, which makes developing effective treatments challenging, identifying patients at risk for accelerated disease progression is essential for efficient clinical trial design and new treatment target discovery and development. Objectives. This study aims to create a trustworthy and interpretable precision health tool that predicts rapid knee OA progression based on baseline patient characteristics using an advanced automated machine learning (autoML) framework, “Autoprognosis 2.0”. Methods. All available 2-year follow-up periods of 600 patients from the FNIH OA Biomarker Consortium were analysed using “Autoprognosis 2.0” in two separate approaches, with distinct definitions of clinical outcomes: multi-class predictions (categorising patients into non-progressors, pain-only progressors, radiographic-only progressors, and both pain and radiographic progressors) and binary predictions (categorising patients into non-progressors and progressors). Models were developed using a training set of 1352 instances and all available variables (including clinical, X-ray, MRI, and biochemical features), and validated through both stratified 10-fold cross-validation and hold-out validation on a testing set of 339 instances. Model performance was assessed using multiple evaluation metrics, such as AUC-ROC, AUC-PRC, F1-score, precision, and recall. Additionally, interpretability analyses were carried out to identify important predictors of rapid disease progression. Results. Our final models yielded high accuracy scores for both multi-class predictions (AUC-ROC: 0.858, 95% CI: 0.856–0.860; AUC-PRC: 0.675, 95% CI: 0.671–0.679; F1-score: 0.560, 95% CI: 0.554–0.566) and binary predictions (AUC-ROC: 0.717, 95% CI: 0.712–0.722; AUC-PRC: 0.620, 95% CI: 0.616–0.624; F1-score: 0.676, 95% CI: 0.673–0679). Important predictors of rapid disease progression included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and MRI features. Our models were further successfully validated using a hold-out dataset, which was previously omitted from model development and training (AUC-ROC: 0.877 for multi-class predictions; AUC-ROC: 0.746 for binary predictions). Additionally, accurate ML models were developed for predicting OA progression in a subgroup of patients aged 65 or younger (AUC-ROC: 0.862, 95% CI: 0.861–0.863 for multi-class predictions; AUC-ROC: 0.736, 95% CI: 0.734–0.738 for binary predictions). Conclusions. This study presents a reliable and interpretable precision health tool for predicting rapid knee OA progression using “Autoprognosis 2.0”. Our models provide accurate predictions and offer insights into important predictors of rapid disease progression. Furthermore, the transparency and interpretability of our methods may facilitate their acceptance by clinicians and patients, enabling effective utilisation in clinical practice. Future work should focus on refining these models by increasing the sample size, integrating additional features, and using independent datasets for external validation. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Aims. Extracellular vesicles (EVs) are nanoparticles secreted by all cells, enriched in proteins, lipids, and nucleic acids related to cell-to-cell communication and vital components of cell-based therapies. Mesenchymal stromal cell (MSC)-derived EVs have been studied as an alternative for osteoarthritis (OA) treatment. However, their clinical translation is hindered by industrial and regulatory challenges. In contrast, platelet-derived EVs might reach clinics faster since platelet concentrates, such as platelet lysates (PL), are already used in therapeutics. Hence, we aimed to test the therapeutic potential of PL-derived extracellular vesicles (pEVs) as a new treatment for OA, which is a degenerative joint disease of articular cartilage and does not have any curative or regenerative treatment, by comparing its effects to those of human umbilical cord MSC-derived EVs (cEVs) on an ex vivo OA-induced model using human cartilage explants. Methods. pEVs and cEVs were isolated by size exclusion chromatography (SEC) and physically characterized by nanoparticle tracking analysis (NTA), protein content, and purity. OA conditions were induced in human cartilage explants (10 ng/ml oncostatin M and 2 ng/ml tumour necrosis factor alpha (TNFα)) and treated with 1 × 10. 9. particles of pEVs or cEVs for 14 days. Then, DNA, glycosaminoglycans (GAG), and collagen content were quantified, and a histological study was performed. EV uptake was monitored using PKH26 labelled EVs. Results. Significantly higher content of DNA and collagen was observed for the pEV-treated group compared to control and cEV groups. No differences were found in GAG quantification nor in EVs uptake within any treated group. Conclusion. In conclusion, pEVs showed better performance than cEVs in our in vitro OA model. Although further studies are needed, pEVs are shown as a potential alternative to cEVs for cell-free regenerative medicine. Cite this article: Bone Joint Res 2023;12(10):667–676

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by progressive cartilage degradation, synovial membrane inflammation, osteophyte formation, and subchondral bone sclerosis. Pathological changes in cartilage and subchondral bone are the main processes in OA. In recent decades, many studies have demonstrated that activin-like kinase 3 (ALK3), a bone morphogenetic protein receptor, is essential for cartilage formation, osteogenesis, and postnatal skeletal development. Although the role of bone morphogenetic protein (BMP) signalling in articular cartilage and bone has been extensively studied, many new discoveries have been made in recent years around ALK3 targets in articular cartilage, subchondral bone, and the interaction between the two, broadening the original knowledge of the relationship between ALK3 and OA. In this review, we focus on the roles of ALK3 in OA, including cartilage and subchondral bone and related cells. It may be helpful to seek more efficient drugs or treatments for OA based on ALK3 signalling in future