Comparison of 2 Different Formulations of Artificial Bone for a Hybrid Implant With a Tissue-Engineered Construct Derived From Synovial Mesenchymal Stem Cells: A Study Using a Rabbit Osteochondral Defect Model
Bibliographic record
Abstract
BACKGROUND: Previously, we developed a hybrid implant composed of hydroxyapatite (HA)-based artificial bone coupled with a mesenchymal stem cell (MSC)-based scaffold-free tissue-engineered construct (TEC) and demonstrated its feasibility for osteochondral repair. Beta-tricalcium phosphate (βTCP) may be a promising alternative to HA, as it is a highly biocompatible material and is resorbed more rapidly than HA in vivo. HYPOTHESIS: A βTCP-based hybrid TEC implant will exhibit superior osteochondral repair when directly compared with an HA-based hybrid implant, as tested using a rabbit osteochondral defect model. STUDY DESIGN: Controlled laboratory study. METHODS: Osteochondral defects were created in the femoral groove of skeletally mature rabbits. The TEC and artificial bone, using either HA or βTCP with the same porosities and similar mechanical properties, were hybridized and then implanted in the defects. A histological evaluation and microindentation testing were performed for the assessment of repair tissue. RESULTS: Osteochondral defects treated with the TEC/βTCP implants showed more rapid subchondral bone repair at 1 month, but the cartilaginous tissue deteriorated over time out to 6 months after implantation. Osteochondral defects treated with the TEC/HA implants maintained good histological quality out to 6 months after implantation and also exhibited better biomechanical properties at 6 months as compared with the TEC/βTCP implants. CONCLUSION: Contrary to our hypothesis, the TEC/HA hybrid implant facilitated better osteochondral repair than did the TEC/βTCP implant. The results of the present study suggest the importance of a stable restoration of subchondral bone for long-term effective osteochondral repair rather than rapid remodeling of subchondral bone. CLINICAL RELEVANCE: This study contributes to the future selection of suitable materials for patients with osteochondral lesions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".