In vivo evaluation of β‐CS/n‐HA with different physical properties as a new bone graft material
Bibliographic record
Abstract
BACKGROUND: Natural polymer composite materials are becoming increasingly important as scaffolds for bone tissue engineering. Composite materials based on combinations of biodegradable polymers and bioactive ceramics, including CTS and Hap. PURPOSE: β-Chitosan/n-HA composite with different percentages was prepared. Some of the physical and mechanical properties were examined by using (scanning electron microscope and transmission electron microscope). Histological evaluation of in vivo implantation of β-Chitosan/n-HA composite as bone graft material was done. MATERIAL AND METHODS: β-type chitosan was obtained through a modified procedure from squid pens (Loligo vulgaris). It was used in combination with different proportions of nano-hydroxyapatite (n-HA), to develop new series of β-CS/n-HA nanocomposites. Sample were obtained in a powder form with the ratio of 30 CH to 70% nHA. The product was implanted in the femoral condyle of the animals (adult rabbits). RESULTS: Compact strength was 13.05 MPa for the weight ratio of 30/70. Histological examinations showed that the implant not only biological compatible but also its presence promotes and accelerate bone growth. CONCLUSIONS: The composite β-CS/HPa (30/70) as biodegradable bone substitute that not only enhance bone generation but also accelerate the formation of Haversian system. We used the composite in a powder form and examined its suitability as artificial bone graft; yet the mechanical properties have shown that 30/70 ratio of β-CS/HPa offer suitable mechanical strength to be employed as a solid-shaped implants.
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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".