Danshen attenuates osteoarthritis-related cartilage degeneration through inhibition of NF-κB signaling pathway in vivo and in vitro
Bibliographic record
Abstract
Danshen (Salvia miltiorrhiza) is a traditional Chinese medicine herb that can alleviate the symptoms of osteoarthritis (OA) (Söder et al. 2006) in animals. However, the underlying mechanisms remain poorly understood and require further investigation. In this study, rabbits with experimentally induced OA were given an intra-articular injection of danshen (0.7 mL/day) for 5 weeks. In addition to attenuating the cartilage degeneration of OA in the rabbits, danshen decreased the expression and activity of matrix metalloproteinase 9 (MMP-9) and MMP-13, and increased the expression of their natural inhibitors: tissue inhibitor of matrix metalloproteinase 1 (TIMP-1) and TIMP-2. Apoptosis in osteoarthritic cartilage tissues was attenuated by danshen, accompanied with increased expression of B cell lymphoma 2 (Bcl-2) and decreased levels of Bcl-2-associated X protein (Bax). Further, danshen inhibited the nuclear accumulation of nuclear factor kappa-B (NF-κB) p65 in osteoarthritic cartilage. The therapeutic effects of danshen in vivo were comparable to that of sodium hyaluronate, which is a drug used clinically for the treatment OA. In vitro, sodium nitroprusside (SNP) was used to stimulate apoptosis in primary rabbit chondrocytes. We found that the SNP-induced apoptosis was mitigated by danshen. BAY11-7028, an inhibitor of the NF-κB pathway, augmented danshen's anti-apoptotic effects in cells exposed to SNP. When these results are considered together, they indicate that danshen alleviates the cartilage injury in rabbit OA through inhibition of the NF-κB signaling pathway.
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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 | 0.000 |
| 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".