Cleft Palate Reconstruction Using Collagen and Nanofiber Scaffold Incorporating Bone Morphogenetic Protein in Rats
Bibliographic record
Abstract
BACKGROUND: Absorbable collagen sponge (ACS) loaded with bone morphogenetic protein-2 (BMP-2) is approved for selected clinical applications; however, burst release limits its widespread use. Therefore, nanofiber (NF)-based scaffold with ACS backbone was developed to sustain release of loaded BMP-2 to improve the outcomes of bone grafting in a rodent model of cleft palate. METHODS: BMP-2 was loaded on ACS scaffold and then NF hydrogel with different densities (1-2%) was added to sustain the BMP-2 release. The release profiles of BMP-2 from constructs with different NF densities were evaluated in vitro to explore the optimum NF density that could recapitulate physiological bone healing process. Subsequently, scaffold with the appropriate NF density was implanted into a rodent model of cleft palate. Wistar rats, with surgically induced maxillary cleft defects, were then assigned to one of the following groups (n=6/group): no scaffold (control), ACS, ACS+BMP-2, NF+ACS, and NF+ACS+BMP-2. Micro-computed tomography (μCT) was utilized to evaluate percent bone filling (%BF) at defect site as well as changes in anteroposterior and transverse dimensions of the maxilla at weeks 0, 4, and 8. Histological assessment of bone healing was performed at week 8. RESULTS: In vitro release experiments showed that scaffolds containing 2% NF exhibited a release profile conducive to the natural stages of bone healing and, hence, it was utilized for subsequent in vivo studies. Bone healing occurred at the defect margins leaving a central bone void in the control, ACS, and NF+ACS groups over the 8-week study period. BMP-2-treated groups demonstrated higher %BF as compared with other groups at week 8 (p<0.05). Whereas the NF+ACS+BMP-2 group showed bone bridging of the defect as early as 4 weeks, which was not evident in ACS+BMP-2 group. In all groups, bone grafts did not disrupt anteroposterior and transverse growth of maxilla. Based on histological evaluations together with μCT data, NF+ACS+BMP-2 treatment resulted in clinically significant and consistent bone healing throughout the implanted scaffold when compared with the ACS+BMP-2 group. CONCLUSION: NF+ACS+BMP-2 constructs exhibited osteoinductive properties together with preparation simplicity, which makes it a novel approach for BMP-2 delivery for cleft palate reconstruction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".