Epithelial activity of hexokinase and glucose-6-phosphate dehydrogenase in cultured bovine lenses recovering from pharmaceutical-induced optical damage.
Bibliographic record
Abstract
PURPOSE: In a previous toxicological study, cultured bovine lenses exposed to three topical anesthetics displayed distinct patterns of optical damage and recovery. This work investigated the epithelial activity of the metabolic enzymes hexokinase (HK) and glucose-6-phosphate dehydrogenase (G6PD) in lenses recovering from anesthetic-induced damage. METHODS: Cultured bovine lenses were exposed to the anesthetics Alcaine, Fluress and Fluoracaine for 2 h. An automated laser scanner was used to determine the focal length variability (FLV) of the lenses at time-points up to 24 h following their return to fresh culture medium. The epithelial enzyme activities for HK and G6PD were then assayed at the 24 h time-point. RESULTS: Lenses exposed to Alcaine displayed an abrupt increase in FLV, while Fluoracaine treated lenses exhibited optical damage at a slower rate. The FLV in these two groups recovered to near-control levels after 24 h. Fluress treated lenses did not differ in FLV from controls at any time. The activities of both HK and G6PD were significantly reduced in epithelial samples from each of the three anesthetic treatment groups, relative to controls. CONCLUSIONS: These results show that lens optical quality can recover despite a severe reduction in epithelial HK and G6PD activity, indicating that the optical function of the lens may not be directly related to epithelial metabolic activity. The ScanTox In Vitro Assay System provides an objective measure of lens optical quality, enabling a direct comparison of optical damage and recovery to lens biochemical changes.
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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 | 0.000 | 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 | 0.000 | 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".