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Osteoarthritis (OA) is the most common degenerative joint disorder. Multipotential stromal cells (MSCs) have a crucial role in joint repair, but how OA severity affects their characteristics remains unknown. Knee OA provides a good model to study this, as osteochondral damage is commonly more severe in the medial weight-bearing compartment compared to lateral side of the joint. This study utilised in vitro functional assays, cell sorting, gene expression and immunohistochemistry to compare MSCs from medial and lateral OA femoral condyles. Despite greater cartilage loss and bone sclerosis in medial condyles, there was no significant differences in MSC numbers, growth rates or surface phenotype. Culture-expanded and freshly-purified medial-condyle MSCs expressed higher levels of several ossification-related genes. Using CD271-staining to identify MSCs, their presence and co-localisation with TRAP-positive chondroclasts was noted in the vascular channels breaching the osteochondral junction in lateral condyles. In medial condyles, MSCs were additionally found in small cavities within the sclerotic plate. These data indicate subchondral MSCs may be involved in OA progression by participating in cartilage destruction, calcification and sclerotic plate formation and that they remain abundant in severe disease. Biological or biomechanical modulation of these MSCs may be a new strategy towards cartilage and bone restoration in knee OA.
Pubmed ID: 31249374
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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View all literature mentionsSoftware R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.
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