Bilayer Implants
Bibliographic record
Abstract
OBJECTIVE: To compare the regenerative capacity of 2 distinct bilayer implants for the restoration of osteochondral defects in a preliminary sheep model. METHODS: Critical sized osteochondral defects were treated with a novel biomimetic poly-ε-caprolactone (PCL) implant (Treatment No. 2; n = 6) or a combination of Chondro-Gide and Orthoss (Treatment No. 1; n = 6). At 19 months postoperation, repair tissue (n = 5 each) was analyzed for histology and biochemistry. Electromechanical mappings (Arthro-BST) were performed ex vivo. RESULTS: Histological scores, electromechanical quantitative parameter values, dsDNA and sGAG contents measured at the repair sites were statistically lower than those obtained from the contralateral surfaces. Electromechanical mappings and higher dsDNA and sGAG/weight levels indicated better regeneration for Treatment No. 1. However, these differences were not significant. For both treatments, Arthro-BST revealed early signs of degeneration of the cartilage surrounding the repair site. The International Cartilage Repair Society II histological scores of the repair tissue were significantly higher for Treatment No. 1 (10.3 ± 0.38 SE) compared to Treatment No. 2 (8.7 ± 0.45 SE). The parameters cell morphology and vascularization scored highest whereas tidemark formation scored the lowest. CONCLUSION: There was cell infiltration and regeneration of bone and cartilage. However, repair was incomplete and fibrocartilaginous. There were no significant differences in the quality of regeneration between the treatments except in some histological scoring categories. The results from Arthro-BST measurements were comparable to traditional invasive/destructive methods of measuring quality of cartilage repair.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.017 |
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".