Cytokine and Chemokine Gene Expression of IL‐1β Stimulated Equine Articular Chondrocytes
Bibliographic record
Abstract
OBJECTIVE: To evaluate mRNA expression of several proinflammatory and anti-inflammatory cytokines and chemokines in equine unstimulated and interleukin-1beta (IL-1beta)-stimulated chondrocytes. STUDY DESIGN: In vitro experiment using equine chondrocyte cultures. SAMPLE POPULATION: Whole articular cartilage from metacarpophalangeal joints (n=5 horses; 10 fetlocks). METHODS: Chondrocyte monolayer cultures were established from digested adult equine articular cartilage and stimulated with 5 ng/mL of recombinant human IL-1beta. RNA was extracted from the cells 24 hours after stimulation. IL-1beta, IL-4, IL-6, IL-8, tumor necrosis factor-alpha (TNF-alpha), and ubiquitin (house keeping gene) mRNA expression were investigated by real-time RT-PCR. RESULTS: IL-1beta, IL-6, and IL-8 mRNA were expressed in unstimulated chondrocytes from macroscopically normal joints and were significantly up-regulated after stimulation (5/5 horses). IL-4 mRNA was not detected in any samples (0/5 horses). TNF-alpha mRNA, by comparison, was expressed in 2/5 unstimulated samples and in all stimulated samples but a considerable sample variation in response to IL-1beta stimulation was observed. CONCLUSIONS: Equine chondrocytes express mRNA for several proinflammatory cytokines and chemokines and IL-1beta modulates their expression. CLINICAL RELEVANCE: Chondrocytes express proinflammatory cytokines and chemokines capable of modulating a local inflammatory cascade in articular cartilage, which could potentially lead to focal degradation and osteoarthritis.
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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) | 0.002 | 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".