The articular cartilage preservative effects of genistein in an experimental model of knees osteoarthritis
Bibliographic record
Abstract
The study aimed to investigate the preservative effects of genistein on articular cartilage in an experimental model of knee osteoarthritis in rats. Thirty male Wistar rats were assigned to 3 equal groups: sham group, osteoarthritis control group (OAG), and genistein-treated osteoarthritis group (GTG). Intra-articular injections of monosodium iodoacetate were used for osteoarthritis induction. After 2 weeks of rest for the induction of the inflammatory process, genistein (30 mg/kg/day) vs. saline gavage was administered for 8 weeks. The expression of matrix metalloproteinase (MMP)-8 and MMP-13, Sox5/Sox6, Indian hedgehog (IHH), and Col2 were evaluated in medial femoral condyle sections by immunohistochemical staining. The number of chondrocytes and cartilage thicknesses were also measured and compared among the groups. No significant change in cartilage thickness was observed in GTG compared with OAG (p = 0.188). Chondrocyte count was significantly higher in the articular cartilage of GTG compared with OAG (p = 0.006). Induction of osteoarthritis significantly increased the expression of MMP-8, MMP-13, and IHH, but decreased Col2, Sox5, and Sox6 expression (p < 0.001); these were partially prevented in the GTG. Our findings support the effectiveness of genistein treatment in the prevention of articular cartilage damage in the experimental model of knee osteoarthritis. The proposed mechanism of action is through the suppression of the MMP, IHH, and Col2 pathways, besides the induction of Sox5 and Sox6 expression. Novelty: Genistein prevents articular cartilage damage in the experimental model of knee osteoarthritis. The osteoprotective effect is manifested by the modulation of expression of MMP, Sox, IHH, and Col2 proteins.
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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 | 0.001 | 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".