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.
To assess the effect of physical exercise (PE) on the histological and transcriptional characteristics of proteoglycan-induced arthritis (PGIA) in BALB/c mice. Following PGIA, mice were subjected to treadmill PE for ten weeks. The tarsal joints were used for histological and genetic analysis through microarray technology. The genes differentially expressed by PE in the arthritic mice were obtained from the microarray experiments. Bioinformatic analysis in the DAVID, STRING, and Cytoscape bioinformatic resources allowed the association of these genes in biological processes and signalling pathways.Aims
Methods
The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.Aims
Methods
