Interleukin-1 Induction of Aggrecanase Gene Expression in Human Articular Chondrocytes is Mediated by Mitogen-Activated Protein Kinases
Bibliographic record
Abstract
BACKGROUND/AIMS: We investigated the unknown molecular mechanisms of Interleukin-1 (IL-1β)-induced cartilage aggrecan degeneration by aggrecanase (ADAMTS-A Disintegrin And Metalloproteinase with ThromboSpondin motifs) in human articular chondrocytes, a model mimicking human arthritis. METHODS: Chondrocytes were pretreated with various pharmacological inhibitors and then stimulated with IL-1β for 24 h. ADAMTS-4 expression or activity was studied by RT-PCR or ELISA and other proteins measured by Western blotting. RESULTS: MAP kinase kinase-specific inhibitor, U0126 inhibited IL-1-induced phosphorylation of ERK1/2 and down-regulated ADAMTS-4 expression and activity. Protein 38 inhibitor, SB203580 down-regulated the phosphorylation of p38 and its target, activating transcription factor-2 (ATF-2), ADAMTS-4 mRNA and activity. C-Jun N-terminal kinase (JNK) inhibitor, SP600125 diminished IL-1-stimulated JNK phosphorylation, ADAMTS-4 mRNA expression and enzyme activity. A c-fos/lipoxygenase pathway inhibitor and antioxidant, nordihydroguaiaretic acid (NDGA) significantly suppressed ADAMTS-4 mRNA induction and activity. Activating protein (AP-1) and nuclear factor kappa B (NF-ĸB) transcription factor inhibitors, curcumin and pyrrolidine dithiocarbamate (PDTC) partially inhibited ADAMTS-4 induction and activity. CONCLUSION: These results suggest partial involvement of ERK-, p38-and JNK-MAPKs as well as AP-1, ATF-2 and NF-ĸB transcription factors in IL-1-induced ADAMTS-4 in chondrocytes. Inhibition of these targets by the specific pharmacological agents could be useful for reducing aggrecanase-driven cartilage resorption in arthritis.
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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 | 0.000 |
| 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".