Tissue Engineering of Feline Corneal Endothelium Using a Devitalized Human Cornea as Carrier
Bibliographic record
Abstract
The difficulties in obtaining good quality tissue for the replacement of corneas of patients suffering from endothelial dysfunctions have prompted us to evaluate the feasibility of producing a tissue-engineered (TE) corneal endothelium using devitalized human stromal carriers. Thus, corneal substitutes were produced by seeding cultured feline corneal endothelial cells on top of previously frozen human corneal stromas. After two weeks of culture to allow attachment and spreading of the seeded cells, the TE corneal endothelium was stained with alizarin red for endothelial cell count and fixed for histology, immunofluorescence labeling, scanning and transmission electron microscopy. Histology and Hoechst staining showed that there were no remaining cells in the devitalized stroma. After seeding, histology and transmission electron microscopy showed that the TE corneal endothelium formed a monolayer of tightly packed cells that were well adhered to Descemet's membrane. Scanning electron microscopy corroborated that the cells covered the entire posterior corneal surface and had an endothelial morphology. Alizarin staining showed that mean cell counts were 2272 +/- 344 cells/mm(2), indicating that the cell density was appropriate for grafting. The TE feline corneal endothelium also expressed the function-related proteins Na(+)/HCO(3)(-), ZO-1, and Na(+)/K(+)-ATPase alpha1, and could easily be marked with a fluorescent tracker. This study demonstrates the feasibility of reconstructing a highly cellular and healthy corneal endothelium on devitalized human corneal stromas.
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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) | 0.001 | 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".