Biocompatibility of Contact Lens Solutions Using Confocal Laser Scanning Microscopy and the In Vitro Bovine Cornea
Bibliographic record
Abstract
PURPOSE: This study used high-resolution research confocal laser scanning microscopy to study the epithelium of fresh bovine corneas treated with two contact lens solutions. METHODS: Fresh bovine corneal buttons were stained with a combination of the cell-permeable mitochondrial- and nuclear-specific dyes rhodamine 123 and Hoechst 33342 or acridine orange and imaged with a confocal laser scanning microscope. High-resolution X,Y images of the corneal epithelium were taken with a Zeiss 510 confocal laser scanning microscope at a 0.44-062 -microm Z step, and three-dimensional images of the entire thickness of the corneal epithelium were reconstructed. Semiautomated quantitative MatLab software analysis was applied to count the mitochondria in each optical slice. The effects of treatment for 30 minutes with OPTI-FREE Express and ReNu MultiPlus No Rub were investigated and compared to Hanks' balanced salt solution controls. RESULTS: This study showed the feasibility of using the confocal laser scanning microscope with fluorescent dyes to study organelles throughout the epithelial layers of fresh unfixed bovine corneas. The mitochondria in the intermediate and basal epithelium are abundant and range in length from less than 1 microm to threads greater than 15 microm, with a tendency to accumulate around the nuclei. Image analysis indicated significantly fewer mitochondria only in the superficial epithelium after treatment with ReNu MultiPlus No Rub treatment. OPTI-FREE Express treatment produced significantly fewer mitochondria not only in the superficial but also in the intermediate epithelial layers. CONCLUSIONS: OPTI-FREE Express has the potential for deeper mitochondrial effects compared to ReNu MultiPlus No Rub and Hanks' balanced salt solution controls.
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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 | 0.000 |
| 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".