Enhancing Composite Freeze-Dried Chitosan/TPP Hydrogel Scaffolds with nGO and nHAp for Bone Tissue Engineering
Bibliographic record
Abstract
Bone tissue engineering seeks to create methods for repairing sick or injured bone by combining cells, growth factors, and biomaterials.This work studies the creation and improvement of freeze-dried chitosan-based hydrogel scaffolds crosslinked with tripolyphosphate TPP and enriched with graphene oxide nGO and nanohydroxyapatite nHAp for bone tissue engineering applications.Swelling ratio, FTIR, degradation, contact angle, SEM, and antibacterial test were among the physical, chemical, and biological examinations used to characterize the scaffolds, which were made in varying compositions.With higher chitosan and nGO/nHAp concentrations, the results showed enhanced degradation resistance, good swelling behavior, and the chemical bonding was improved.Good mechanical enhancement, biocompatibility, and antibacterial activity specially against Gram-positive bacteria are achieved by the inclusion of nGO and nHAp.The suggested scaffolds' structural stability, advantageous hydrophilicity, and effective bioactivity make them promising candidates for bone regeneration applications, according to these findings.
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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".