Healing of Osteochondral Defects via Endochondral Ossification in an Ovine Model
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe the mechanism of healing of osteochondral defects of the distal femur in the sheep, a commonly used translational model. Information on the healing mechanism be useful to inform the design of tissue engineering devices for joint surface defect repair. DESIGN: A retrospective study was conducted examining 7-mm diameter osteochondral defects made in the distal medial femoral condyle of 40 adult female sheep, comprising control animals from 3 separate structures. The healing of the defects was studied at post mortem at up to 26 weeks. RESULTS: Osteochondral defects of the distal femur of the sheep heal through endochondral ossification as evidenced by chondrocyte hypertrophy and type X collagen expression. Neocartilage is first formed adjacent to damaged cartilage and then streams over the damaged underlying bone before filling the defect from the base upward. No intramembranous ossification or isolated mesenchymal stem cell aggregates were detected in the healing tissue. No osseous hypertrophy was detected in the defects. CONCLUSIONS: Osteochondral defects of the medial femoral condyle of the sheep heal via endochondral ossification, with neocartilage first appearing adjacent to damaged cartilage. Unlike the mechanism of healing in fracture repair, neocartilage is eventually formed directly onto damaged bone. There was most variability between animals between 8 and 12 weeks postsurgery. These results should be considered when designing devices to promote defect healing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".