Development of an engineering autologous palatal mucosa‐like tissue for potential clinical applications
Bibliographic record
Abstract
The goal of this study was to optimize key processes in recreating functional and viable palatal mucosa-like tissue that would be easy to handle and would promote wound healing. Normal human gingival fibroblasts and epithelial cells and a clinically useful biomaterial, CollaTape, were used. Structural and ultrastructural analyses showed that the gingival fibroblasts and epithelial cells adhered to the biomaterial and proliferated. Following a 6-day culture, using 10(5) fibroblasts and 10(6) epithelial cells, a well-organized palatal mucosa-like tissue was engineered. The engineered epithelium displayed various layers, including a stratum corneum, and contained cytokeratin 16-positive cells located in the supra-basal layer. This palatal mucosa-like engineered tissue was designed to meet a variety of surgical needs. The biodegradable collagen membrane (CollaTape) contributed to the flexibility of the engineered tissue. This engineered innovative tissue may contribute to the reconstruction of oral soft-tissue defects secondary to trauma, congenital defects, and acquired diseases.
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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) | 0.002 | 0.001 |
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".