Tissue engineered endothelial keratoplasty in rabbit: tips and tricks
Bibliographic record
Abstract
PURPOSE: To report a detailed surgical procedure of tissue engineered endothelial keratoplasty (TEEK) in a rabbit model and its postoperative evaluation. METHODS: TEEKs were prepared 7 days before transplantation by seeding human or rabbit corneal endothelial cells on either femtosecond laser-cut ultrathin human stromal lamellae (fs-UTSL) or femtosecond laser-cut human anterior lens capsule (fs-HALC). Thirty transplantations were performed on aphakic eyes. Recombinant tissue plasminogen activator (rTPA) was used throughout the surgery. The native endothelium was removed by full-surface scraping and central descemetorhexis. The transplantation was performed as a human Descemet's membrane endothelial keratoplasty. Controls included Descemetorhexis only and transplantation of carrier alone. Postoperative follow-up was performed by slit lamp and optical coherence tomography, followed by histology. RESULTS: Controls remained oedematous. No fibrin occurred during surgery. All but three TEEKs adhered immediately. One/6 fs-UTSL and 9/16 fs-HALC cleared perfectly (p = 0.161). All failures could be explained by at least one of the following causes intraoperative bleeding, vitreous prolapsus, early partial detachment, postoperative irido corneal synechiea/angle closure. Presumed immune rejection was observed in three rabbits only after 4 weeks. Immunostaining with anti-human CD166 allowed to perfectly differentiate human cells from rabbit cells. In successful TEEK at 3 or 4 weeks, human cells formed a normal endothelium and started migrating outside the carrier. CONCLUSION: Though the transplantation of a TEEK in rabbits is a complex model with many causes of failure, established procedure including use of rTPA allows reliable preclinical study. In addition, we suggest that fs-HALC might be a potential carrier for TEEK.
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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 | 0.001 |
| 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 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".