Diacerein reduces the level of cartilage chondrocyte DNA fragmentation and death in experimental dog osteoarthritic cartilage at the same time that it inhibits caspase-3 and inducible nitric oxide synthase.
Bibliographic record
Abstract
OBJECTIVE: The primary objective of this study was to evaluate the ex vivo therapeutic efficacy of diacerein and its active metabolite, rhein, on osteoarthritic (OA) cartilage chondrocyte DNA fragmentation and death in the experimental canine model of OA. The study also aimed to explore the effect of the drug on the level of important factors involved in this phenomenon, i.e., caspase-3 and inducible nitric oxide synthase (iNOS). METHODS: OA knee cartilage was obtained from dogs that had received surgical sectioning of the anterior cruciate ligament (ACL) and were sacrificed 12 weeks after surgery. Cartilage explants were cultured in the presence or absence of therapeutic concentrations of diacerein (20 micrograms/ml) or rhein (20 micrograms/ml). Cartilage specimens were stained for TUNEL reaction and immunostained using specific antibodies for active caspase-3 and iNOS. Morphometric analyses were also performed. RESULTS: In OA cartilage specimens, a large number of chondrocytes in the superficial layers stained positive for TUNEL reaction. Treatment with therapeutic concentrations of diacerein (20 micrograms/ml) or rhein (20 micrograms/ml) significantly reduced the level of chondrocyte DNA fragmentation to about the same extent in both treatment groups (P < 0.006, P < 0.002, respectively). The levels of caspase-3 and iNOS in cartilage explants were also significantly decreased (caspase-3, diacerein P < 0.04; caspase-3, rhein P < 0.0003; and iNOS, rhein P < 0.009, respectively) when compared to the control group. CONCLUSIONS: This study shows that diacerein/rhein can effectively reduce the level of OA chondrocyte DNA fragmentation and death under the present experimental conditions. This effect is mediated by a decrease in the level of caspase-3 expression, which could possibly be related in part to the reduced level of iNOS and secondarily to NO production. These findings provide additional new information about the mechanisms of action of diacerein on the progression of OA.
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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 | 0.001 |
| 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".