Collagen-Based Fillers as Alternatives to Cyanoacrylate Glue for the Sealing of Large Corneal Perforations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To describe the use of collagen-based alternatives to cyanoacrylate glue for the sealing of acute corneal perforations. METHODS: A collagen analog comprising a collagen-like peptide conjugated to polyethylene glycol (CLP-PEG) and its chemical crosslinker were tested for biocompatibility. These CLP-PEG hydrogels, which are designed to act as a framework for corneal tissue regeneration, were then tested as potential fillers in ex vivo human corneas with surgically created full-thickness perforations. Bursting pressures were measured in each of 3 methods (n = 10 for each condition) of applying a seal: 1) cyanoacrylate glue with a polyethylene patch applied ab externo (gold standard); 2) a 100-μm thick collagen hydrogel patch applied ab interno, and 3) the same collagen hydrogel patch applied ab interno supplemented with CLP-PEG hydrogel molded in situ to fill the remaining corneal stromal defect. RESULTS: Cyanoacrylate gluing achieved a mean bursting pressure of 325.9 mm Hg, significantly higher than the ab interno patch alone (46.3 mm Hg) and the ab interno patch with the CLP-PEG filler (86.6 mm Hg). All experimental perforations were sealed effectively using 100 μm hydrogel sheets as an ab interno patch, whereas conventional ab externo patching with cyanoacrylate glue failed to provide a seal in 30% (3/10) cases. CONCLUSIONS: An ab interno patch system using CLP-PEG hydrogels designed to promote corneal tissue regeneration may be a viable alternative to conventional cyanoacrylate glue patching for the treatment of corneal perforation. Further experimentation and material refinement is required in advance of clinical trials.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it