Effect of Surgical Technique on Corneal Implant Performance
Bibliographic record
Abstract
PURPOSE: Our aim was to determine the effect of a surgical technique on biomaterial implant performance, specifically graft retention. METHODS: Twelve mini pigs were implanted with cell-free, 1-ethyl-3-(3-dimethyl aminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) cross-linked recombinant human collagen type III (RHCIII) hydrogels as substitutes for donor corneal allografts using overlying sutures with or without human amniotic membrane (HAM) versus interrupted sutures with HAM. The effects of the retention method were compared as well as the effects of collagen concentration (13.7% to 15% RHCIII). RESULTS: All implanted corneas showed initial haze that cleared with time, resulting in corneas with optical clarity matching those of untreated controls. Biochemical analysis showed that by 12 months post operation, the initial RHCIII implants had been completely remodeled, as type I collagen, was the major collagenous protein detected, whereas no RHCIII could be detected. Histological analysis showed all implanted corneas exhibited regeneration of epithelial and stromal layers as well as nerves, along with touch sensitivity and tear production. Most neovascularization was seen in corneas stabilized by interrupted sutures. CONCLUSIONS: This showed that the surgical technique used does have a significant effect on the overall performance of corneal implants, overlying sutures caused less vascularization than interrupted sutures. TRANSLATIONAL RELEVANCE: Understanding the significance of the suturing technique can aid the selection of the most appropriate procedure when implanting artificial corneal substitutes. The same degree of regeneration, despite a higher collagen content indicates that future material development can progress toward stronger, more resistant implants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.003 | 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".