Cells seeded on MBG scaffold survive impaction grafting technique: Potential application of cell‐seeded biomaterials for revision arthroplasty
Bibliographic record
Abstract
The objective of this study was to investigate the potential application of cell-seeded biomaterials for revision arthroplasty and the reconstruction of major joints using the impaction grafting technique. Using morselized cancellous bone graft as a porous scaffold, MG63 cells were seeded on the scaffold and impacted into an acetabulum cup model using a mechanical device constructed from data obtained during impaction grafting by an orthopedic surgeon. Immediately after impaction, cells were trypsinized from the scaffold and processed for cell survival rates using the double-stranded DNA PicoGreen assay. Significant reductions in viable cells were observed between the fifth impact and both the first and second impacts (p < 0.01 and p < 0.05, respectively). Cell survival rate was 21.5% after five impacts. The biological performance of cell-seeded biomaterials may be enhanced by these surviving cells. Compared to allograft bone that is not osteogenic, a cell-seeded biomaterial might also be a suitable substitute for allograft bone for major joint reconstruction at revision arthroplasty.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".