Octacalcium phosphate combined with collagen orthotopically enhances bone regeneration
Bibliographic record
Abstract
Octacalcium phosphate (OCP) is resorbable bone regenerative material, but its brittleness makes it difficult to maintain its shape without restraint. We have engineered a scaffold constructed of synthetic OCP and porcine collagen sponge (OCP/Collagen) and investigated whether OCP/Collagen composite could improve bone regeneration. To examine this hypothesis, bone regeneration by the implantation of OCP/Collagen was compared with those by OCP and collagen. Radiographic and histological examination was performed and the percentage of newly formed bone (n-Bone%) in the defect was determined by a histomorphometrical analysis. OCP/Collagen, OCP, or collagen was implanted into the critical-sized defects in rat crania and fixed at 2, 4, or 8 weeks after implantation. OCP/Collagen improved the handling performance than the granules of OCP, and synergistically enhanced the bone regeneration beyond expectation, which were composed of bone nucleation by OCP and cell infiltration by collagen. Histomorphometrical analysis showed that n-Bone% +/- standard error treated with OCP/Collagen (48.4 +/- 5.14) was significantly higher than those with OCP (27.6 +/- 4.04) or collagen (27.4 +/- 5.69) in week 8. The present study suggests that the combination OCP with collagen elicited the synergistic effect for bone regeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".