Estrogen receptor–related receptor α regulation by interleukin‐1β in prostaglandin E<sub>2</sub>– and cAMP‐dependent pathways in osteoarthritic chondrocytes
Bibliographic record
Abstract
OBJECTIVE: We reported previously that the orphan nuclear receptor, estrogen receptor-related receptor α (ERRα), is expressed in articular chondrocytes and is dysregulated in a mouse model of inflammatory arthritis. The aim of this study, therefore, was to determine whether ERRα is also dysregulated in patients with osteoarthritis (OA). METHODS: ERRα messenger RNA (mRNA) and protein were quantified in normal and OA cartilage samples and in OA chondrocytes in vitro, with and without short-term treatment with a variety of OA-associated factors and signaling pathway agonists and inhibitors. RESULTS: ERRα expression was lower in OA than in normal articular cartilage. Interleukin-1β (IL-1β) markedly up-regulated ERRα expression in OA chondrocytes in vitro, and agonist or inhibitor treatment indicated that the up-regulation was dependent on cyclooxygenase 2 (COX-2; NS398), prostaglandin E(2), cAMP (8-bromo-cAMP), and protein kinase A (PKA; KT5720). Treatment with the ERRα inverse agonist XCT790 decreased the expression of SOX9 and the up-regulation of ERRα by IL-1β, suggesting autoregulation of ERRα in the IL-1β pathway. Matrix metalloproteinase 13 (MMP-13) expression was also decreased by treatment with XCT790 plus IL-1β versus IL-1β alone, and the down-regulation of MMP-13 mRNA and protein observed with XCT790 alone suggests that the up-regulation of MMP-13 by IL-1β is ERRα-dependent. CONCLUSION: We report the first evidence that ERRα expression is regulated by IL-1β in COX-2-, cAMP-, and PKA-dependent pathways in OA chondrocytes. We confirmed that SOX9 is an ERRα target gene in human, as in rodent, chondrocytes and identified MMP-13 as a potential new target gene, which suggests that ERRα may both respond to the healing signal and contribute to extracellular degradation in OA cartilage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".