Effect of grain size and microporosity on the in vivo behaviour of β-tricalcium phosphate scaffolds
Bibliographic record
Abstract
Defining the most adequate architecture of a bone substitute scaffold is a topic that has received much attention over the last 40 years. However, contradictory results exist on the effect of grain size and microporosity. Therefore, the aim of this study was to determine the effect of these two factors on the in vivo behaviour of β-tricalcium phosphate (β-TCP) scaffolds. For that purpose, β-TCP scaffolds were produced with roughly the same macropore size (≈ 150 μm), and porosity (≈ 80 %), but two levels of microporosity (low: 10 % / high: ≈ 25 %) and grain size (small: 1.3 μm /large: ≈ 3.3 μm). The sample architecture was characterised extensively using materialography, Hg porosimetry, micro-computed tomography (μCT), and nitrogen adsorption. The scaffolds were implanted for 2, 4 and 8 weeks in a cylindrical 5-wall cancellous bone defect in sheep. The histological, histomorphometrical and μCT analysis of the samples revealed that all four scaffold types were almost completely resorbed within 8 weeks and replaced by new bone. Despite the three-fold difference in microporosity and grain size, very few biological differences were observed. The only significant effect at p < 0.01 was a slightly faster resorption rate and soft tissue formation between 4 and 8 weeks of implantation when microporosity was increased. Past and present results suggest that the biological response of this particular defect is not very sensitive towards physico-chemical differences of resorbable bone graft substitutes. As bone formed not only in the macropores but also in the micropores, a closer study at the microscopic and localised effects is necessary.
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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".