Estrogen receptor-related receptor- (ERR- ) is dysregulated in inflammatory arthritis
Bibliographic record
Abstract
OBJECTIVES: Subchondral bone loss is a characteristic feature of inflammatory arthritis. Recently, estrogen receptor-related receptor-alpha (ERR-alpha), an orphan nuclear receptor, has been found to be involved in activation of macrophages. We hypothesized that ERR-alpha which is expressed and also functional in articular chondrocytes, osteoblasts and osteoclasts, may be involved in rodent models of inflammatory arthritis. METHODS: Erosive arthritis was induced in DBA/1 mice by injection of type II collagen in Freund's complete adjuvant. RNA was isolated from the bone and joints and expression of ERR-alpha and cartilage (GDF5 and Col2a1) and bone [bone sialoprotein (BSP) and osteocalcin (OCN)] markers was analysed by semi-quantitative PCR. RESULTS: We report for the first time that the expression of ERR-alpha is dysregulated in bones and joints in a mouse model of inflammatory arthritis. Specifically, we show that ERR-alpha expression is down-regulated early in bone and later in joints of mice with type II CIA. Concomitantly, temporal changes were observed in GDF-5 and Col2a1 expression in joints following both initial injection and booster injection of type II collagen. Similarly, down-regulation of ERR-alpha mRNA expression in subchondral bone in mice with induced joint inflammation was also paralleled by down-regulation of markers of bone formation (BSP, OCN). CONCLUSIONS: These data suggest that dysregulation of ERR-alpha expression may precede and contribute to the destruction of cartilage and bone accompanying inflammatory 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 | 0.000 |
| 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".