Transplantation of a Tissue-Engineered Corneal Endothelium Reconstructed on a Devitalized Carrier in the Feline Model
Bibliographic record
Abstract
PURPOSE: To evaluate the functional outcome of tissue-engineered corneal endothelium reconstructed on a devitalized carrier and transplanted in the living feline model. METHODS: Eighteen healthy adult cats underwent full-thickness corneal transplantation. In 11 animals, the donor cornea was reconstructed from cultured allogeneic feline corneal endothelial cells seeded on the denuded Descemet's membrane of a devitalized human cornea. The reconstructed corneal endothelium was cultured for 2 weeks before transplantation. Five control animals received autologous (n = 1), allogeneic (n = 3), or human xenogeneic (n = 1) native cornea. Two other control animals were grafted with the devitalized carrier only (no cells). Animals were observed daily by slit lamp until euthanatization on day 7. Postmortem analysis included optical coherence tomography (OCT), alizarin red staining, histology, fluorescence microscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). RESULTS: Nine of the 11 reconstructed corneal endothelial grafts and all five native (autologous, allogeneic, xenogeneic) control grafts were clear and thin 7 days after grafting. In contrast, the two control grafts consisting of the carrier only (without endothelium) remained thick and opaque. Alizarin red staining, histology, SEM, and TEM showed that the transplanted reconstructed endothelium maintained a normal morphology and ultrastructure and expressed the function-related proteins Na(+)/K(+)-ATPase alpha1, Na(+)/HCO(3), and ZO-1. CONCLUSIONS: This study provides evidence for the short-term (7-day) anatomic and functional success of corneal transplantation with a tissue-engineered corneal endothelium reconstructed on a devitalized carrier.
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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 | 0.001 | 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".