Bone Response Inside Free‐Form Fabricated Macroporous Hydroxyapatite Scaffolds with and without an Open Microporosity
Bibliographic record
Abstract
BACKGROUND: The technique of free-form fabrication enables the production of controlled macroporous geometry inside ceramic scaffolds. Using scaffolds with identical macropore design makes it possible to study a relevant biological response linked to other specific changes of the material. PURPOSE: This study investigates the role of open micropores in hydroxyapatite (HA) scaffold during early bone healing to quantitatively ascertain whether microporosity in otherwise identical macroporous HA scaffolds can influence the bone response in rabbit tibia and femur at 6 weeks. MATERIALS AND METHODS: HA scaffolds (Ø: 3.8 mm) with and without microporosity were randomly installed in both cortical and trabecular bone sites of New Zealand White rabbits. The animals were sacrificed 6 weeks after surgery. Ground sections obtained from en bloc tissues containing scaffold and recipient bone were subjected to histological evaluation and histomorphometric analysis. RESULTS: Microscopy showed elevated amounts of bone ingrowth and bone contact inside the microporous HA (mHA) group as compared with non-mHA. CONCLUSION: The current study indicates that the presence of open scaffold microporosity in HA, as determined by the fabrication process, enhances the ability of ceramic scaffolds to promote bone ingrowth and bone contact.
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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) | 0.000 | 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".