Repair of articular cartilage defects with intra-articular injection of autologous rabbit synovial fluid-derived mesenchymal stem cells
Bibliographic record
Abstract
BACKGROUND: The role of rabbit synovial fluid-derived mesenchymal stem cells (rbSF-MSCs) in cartilage defect repair remains undefined. This work evaluates the in vivo effects of rbSF-MSCs to repair knee articular cartilage defects in a rabbit model. METHODS: Cartilage defects were made in the patellar grooves of New Zealand white rabbits. The rbSF-MSCs were generated from the knee cavity by arthrocentesis. Passage 5 rbSF-MSCs were assayed by flow cytometry. The multipotency of rbSF-MSCs was confirmed after 3 weeks induction in vitro and the autologous rbSF-MSCs and predifferentiated rbSF-MSCs were injected into the synovial cavity. The intra-articular injection was performed once a week for 4 weeks. The animals were euthanized and the articular surfaces were subjected to macroscopic and histological evaluations at 8 and 12 weeks after the first intra-articular injection. RESULTS: Hyaline-like cartilage was detected in the defects treated with rbSF-MSCs, while fibrocartilage tissue formed in the defects treated with chondrocytes induced from rbSF-MSCs. CONCLUSIONS: Our results suggest that autologous undifferentiated rbSF-MSCs are favorable to articular cartilage regeneration in treating cartilage defects.
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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 | 0.001 | 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 | 0.001 |
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".