Egr-1 inhibits the expression of extracellular matrix genes in chondrocytes by TNFα-induced MEK/ERK signalling
Bibliographic record
Abstract
INTRODUCTION: TNFalpha is increased in the synovial fluid of patients with rheumatoid arthritis and osteoarthritis. TNFalpha activates mitogen-activated kinase kinase (MEK)/extracellular regulated kinase (ERK) in chondrocytes; however, the overall functional relevance of MEK/ERK to TNFalpha-regulated gene expression in chondrocytes is unknown. METHODS: Chondrocytes were treated with TNFalpha with or without the MEK1/2 inhibitor U0126 for 24 hours. Microarray analysis and real-time PCR analyses were used to identify genes regulated by TNFalpha in a MEK1/2-dependent fashion. Promoter/reporter, immunoblot, and electrophoretic mobility shift assays were used to identify transcription factors whose activity in response to TNFalpha was MEK1/2 dependent. Decoy oligodeoxynucleotides bearing consensus transcription factor binding sites were introduced into chondrocytes to determine the functionality of our results. RESULTS: Approximately 20% of the genes regulated by TNFalpha in chondrocytes were sensitive to U0126. Transcript regulation of the cartilage-selective matrix genes Col2a1, Agc1 and Hapln1, and of the matrix metalloproteinase genes Mmp-12 and Mmp-9, were U0126 sensitive--whereas regulation of the inflammatory gene macrophage Csf-1 was U0126 insensitive. TNFalpha-induced regulation of Sox9 and NFkappaB activity was also U0126 insensitive. Conversely, TNFalpha-increased early growth response 1 (Egr-1) DNA binding was U0126 sensitive. Transfection of chondrocytes with cognate Egr-1 oligodeoxynucleotides attenuated the ability of TNFalpha to suppress Col2a1, Agc1 or Hapln1 mRNA expression. CONCLUSIONS: Our results suggest that MEK/ERK and Egr1 are required for TNFalpha-regulated catabolic and anabolic genes of the cartilage extracellular matrix, and hence may represent potential targets for drug intervention in osteoarthritis or rheumatoid 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) | 0.001 | 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) | 0.002 | 0.001 |
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".