Oncostatin M-Induced Matrix Metalloproteinase and Tissue Inhibitor of Metalloproteinase-3 Genes Expression in Chondrocytes Requires Janus Kinase/STAT Signaling Pathway
Bibliographic record
Abstract
Oncostatin M (OSM), a member of the IL-6 superfamily of cytokines, is elevated in patients with rheumatoid arthritis and, in synergy with IL-1, promotes cartilage degeneration by matrix metalloproteinases (MMPs). We have previously shown that OSM induces MMP and tissue inhibitor of metalloproteinase-3 (TIMP-3) gene expression in chondrocytes by protein tyrosine kinase-dependent mechanisms. In the present study, we investigated signaling pathways regulating the induction of MMP and TIMP-3 genes by OSM. We demonstrate that OSM rapidly stimulated phosphorylation of Janus kinase (JAK) 1, JAK2, JAK3, and STAT1 as well as extracellular signal-regulated kinase (ERK) 1/2, p38, and c-Jun N-terminal kinase 1/2 mitogen-activated protein kinases in primary bovine and human chondrocytes. A JAK3-specific inhibitor blocked OSM-stimulated STAT1 tyrosine phosphorylation, DNA-binding activity of STAT1 as well as collagenase-1 (MMP-1), stromelysin-1 (MMP-3), collagenase-3 (MMP-13), and TIMP-3 RNA expression. In contrast, a JAK2-specific inhibitor, AG490, had no impact on these events. OSM-induced ERK1/2 activation was also not affected by these inhibitors. Similarly, curcumin (diferuloylmethane), an anti-inflammatory agent, suppressed OSM-stimulated STAT1 phosphorylation, DNA-binding activity of STAT1, and c-Jun N-terminal kinase activation without affecting JAK1, JAK2, JAK3, ERK1/2, and p38 phosphorylation. Curcumin also inhibited OSM-induced MMP-1, MMP-3, MMP-13, and TIMP-3 gene expression. Thus, OSM induces MMP and TIMP-3 genes in chondrocytes by activating JAK/STAT and mitogen-activated protein kinase signaling cascades, and interference with these pathways may be a useful approach to block the catabolic actions of OSM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".