Osteogenic potency of dental stem cell-composite scaffolds in an animal cleft palate model
Bibliographic record
Abstract
Objective: -glycolic acid)-bioactive glass composite (PLGA-bioactive glass (BG)) scaffolds after implantation in a rat cleft model. Methods: Cleft palate-like lesions were induced in Sprague-Dawley rats by extracting the right maxillary first molars and drilling the intact alveolar bone. Rats were then divided into five groups: Control, PCL-GE, PCL-GE-SHED, PLGA-BG, and PLGA-BG-SHED, and received corresponding composite scaffolds with/without SHED at the extraction site. Tissue samples were collected at 2, 3, and 6 months post-implantation (4 rats per group). Gross and histological analyses were conducted to assess osteoid or bone formation. Immunohistochemistry for osteocalcin and human mitochondria was performed to evaluate bone components and human stem cell viability in the tissue. Results: Bone tissue formation was observed in the PCL-GE and PLGA-BG groups compared to the control, where no bone formation occurred. PLGA-BG scaffolds demonstrated greater bone regeneration potential than PCL-GE over 2-6 months. Additionally, scaffolds with SHED accelerated bone formation compared to scaffolds alone. Osteocalcin expression was detected in all rats, and positive immunoreactivity for human mitochondria was observed in the regenerated bone tissue with PCL-GE-SHED and PLGA-BG-SHED. Conclusion: PCL-GE and PLGA-BG composite scaffolds effectively repaired and regenerated bone tissue in rat cleft palate defects. Moreover, scaffolds supplemented with SHED exhibited enhanced osteogenic potency. Clinical significance: PCL-GE and PLGA-BG scaffolds, augmented with SHED, emerge as promising biomaterial candidates for addressing cleft repair and advancing bone tissue engineering endeavors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".