Reconstruction of a human cornea by the self-assembly approach of tissue engineering using the three native cell types.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to produce and characterize human tissue-engineered corneas reconstructed using all three corneal cell types (epithelial, stromal, and endothelial cells) by the self-assembly approach. METHODS: Fibroblasts cultured in medium containing serum and ascorbic acid secreted their own extracellular matrix and formed sheets that were superposed to reconstruct a stromal tissue. Endothelial and epithelial cells were seeded on each side of the reconstructed stroma. After culturing at the air-liquid interface, the engineered corneas were fixed for histology and transmission electron microscopy (TEM). Immunofluorescence labeling of epithelial keratins, basement membrane components, Na+/K+-ATPase α1, and collagen type I was also performed. RESULTS: Epithelial and endothelial cells adhered to the reconstructed stroma. After 10 days at the air-liquid interface, the corneal epithelial cells stratified (4 to 5 cell layers) and differentiated into well defined basal and wing cells that also expressed Na+/K+-ATPase α1 protein, keratin 3/12, and basic keratins. Basal epithelial cells from the reconstructed epithelium formed many hemidesmosomes and secreted a well defined basement membrane rich in laminin V and collagen VII. Endothelial cells formed a monolayer of tightly-packed cells and also expressed the function related protein Na+/K+-ATPase α1. CONCLUSIONS: This study demonstrates the feasibility of producing a complete tissue-engineered human cornea, similar to native corneas, using untransformed fibroblasts, epithelial and endothelial cells, without the need for exogenous biomaterial.
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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) | 0.000 | 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 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".