Comparison of the pig and feline models for full thickness corneal transplantation
Bibliographic record
Abstract
PURPOSE: The goal of this study was to report on the advantages and limitations of the pig and feline models for experimental in vivo corneal transplantation. METHODS: Ten healthy domestic pigs and ten healthy cats were used. Full thickness penetrating keratoplasty was performed using autologous (eight cases), allogeneic (seven cases) or human xenogeneic (three cases) tissue. In two other cases, the inflammatory response to partial thickness trephination (without transplantation) was evaluated. Eyes were assessed daily before and after surgery by slit-lamp, pachymetry, and tonometry. A transparency score ranging from 0 (opaque graft) to 4 (clear graft) was used, based on the slit-lamp examination. Optical coherence tomography, histology, and electron microscopy were performed postmortem. RESULTS: In the pig, the mean (±SD) transparency score for the eight full thickness grafts was 0.88 ± 0.99, ranging from 0 to 3. In the feline model, the mean transparency score for the seven uncomplicated grafts was 3.93 ± 0.19, ranging from 3.5 to 4. Both negative controls without endothelium remained opaque at all time. Intraoperative tendency for iris incarceration into the wound, rapid corneal swelling, suture cheese wiring, and postoperative intraocular inflammation were the main factors jeopardizing the functional success of the corneal transplant in the pig model. CONCLUSION: Suboptimal functional results were obtained after full thickness corneal transplantation in the pig model, while in the feline model, the same protocol yielded uneventful surgeries and clear transplants, with functional results similar to those achieved in human subjects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".