Adult male C57Bl/6 mice (n = 75) were randomized into three groups to receive 1.0 to 1.4 × 107 colony-forming units (CFUs)/ml of 8325-4, DU1090, or saline into the right stifle joint. Chondrocyte death was assessed by confocal microscopy. Histological changes to inoculated joints were graded for inflammatory responses along with gait, weight changes, and limb swelling.Aims
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Rheumatoid arthritis (RA) is an autoimmune disease that involves T and B cells and their reciprocal immune interactions with proinflammatory cytokines. T cells, an essential part of the immune system, play an important role in RA. T helper 1 (Th1) cells induce interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), and interleukin (IL)-2, which are proinflammatory cytokines, leading to cartilage destruction and bone erosion. Th2 cells primarily secrete IL-4, IL-5, and IL-13, which exert anti-inflammatory and anti-osteoclastogenic effects in inflammatory arthritis models. IL-22 secreted by Th17 cells promotes the proliferation of synovial fibroblasts through induction of the chemokine C-C chemokine ligand 2 (CCL2). T follicular helper (Tfh) cells produce IL-21, which is key for B cell stimulation by the C-X-C chemokine receptor 5 (CXCR5) and coexpression with programmed cell death-1 (PD-1) and/or inducible T cell costimulator (ICOS). PD-1 inhibits T cell proliferation and cytokine production. In addition, there are many immunomodulatory agents that promote or inhibit the immunomodulatory role of T helper cells in RA to alleviate disease progression. These findings help to elucidate the aetiology and treatment of RA and point us toward the next steps. Cite this article:
Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA. Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.Aims
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