Dexamethasone inhibits inflammation and cartilage damage in a new model of post‐traumatic osteoarthritis
Bibliographic record
Abstract
Corticosteroids are used in musculoskeletal diseases, and offer patient relief. Injections of corticosteroids are recommended for management of osteoarthritis (OA). Current data have shown the role of corticosteroids in ameliorating pain. We hypothesized that repeated intra-articular injections of high dose dexamethasone would protect the cartilage from damage in a post-traumatic model of OA. Eighteen female New Zealand White rabbits were used. Twelve underwent surgery to induce OA; six of them received intra-articular injections of dexamethasone every 3 days for 3 weeks. The other six rabbits served as operated controls. Six additional rabbits served as non-operated controls. All animals were euthanized 3 weeks post-surgery. Knees were assessed grossly. Cartilage, synovium, and fat pad were assessed histologically. Synovium and fat pad were analyzed with qPCR and Western blots. Surgical controls had cartilage damage which was supressed with dexamethasone. Dexamethasone significantly decreased synovial expression of interleukin-1β and collagen I, and a trend to decrease synovial matrix metalloproteinase3 expression. There were also significantly lower levels of interleukin-1β protein with dexamethasone treatment. Dexamethasone significantly decreased fat pad expression of matrix metalloproteinase13, basic fibroblast growth factor, and interleukin8, and a trend to decrease matrix metalloproteinase3 and transforming growth factorβ expression. Dexamethasone decreased joint inflammation and joint tissue degradation and was chondroprotective in this unique model of PTOA.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".