Hydroxyapatite Granule/Carrier Composites Promote New Bone Formation in Cortical Defects
Bibliographic record
Abstract
BACKGROUND: A great deal of interest has been focused on finding substitutes for autogenous bone grafts. Among the most interesting materials are different calcium phosphate compositions (e.g., hydroxyapatite [HA]), due to their biocompatible properties in hard and soft tissue. PURPOSE: The bone response to porous ceramic HA granules in combination with two lipid and one polysaccharide carrier was evaluated in an experimental bone defect model in rabbits. MATERIALS AND METHODS: Circular defects (Ø 4 mm) were made in both tibias of 32 rabbits. The 64 defects were divided into four groups. Group A was augmented with a composite of HA granules and a phospholipid-diacetyl-glycerol carrier, group B with HA granules and a phospholipid carrier, group C received HA granules and a sodium hyaluronan carrier, and group D served as control. The animals were killed after 6 weeks and ground sections were evaluated using light microscopic morphometry. X-ray microfluorescence (XRF) was applied in order to evaluate the suitability of this method to examine bone-biomaterial interfaces. Calcium distribution was studied using x-ray fluorescence line scans at selected interface regions of two sections in group B. RESULTS: The HA/phospholipid composites were easier to shape and handle than the HA/hyaluronan composite. Group A had 36% newly formed bone area within the defect. Groups B and C showed significantly more newly formed bone within the defect (47% and 49%, respectively) compared to the control group (31%). The XRF analysis revealed that the amount of calcium in the newly formed bone was similar to that observed for the HA granules and slightly lower when compared to the mature, lamellar bone. CONCLUSIONS: Synchrotron radiation may be a new, suitable technique to study the interface between bone and biomaterials with regard to mineral content. The results suggest that HA granule/lipid and HA granule/hyaluronan composites have interesting properties as bone-substitute materials.
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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".