Protective effect of halothane anesthesia on retinal light damage: inhibition of metabolic rhodopsin regeneration.
Bibliographic record
Abstract
PURPOSE: To determine whether the volatile anesthetic halothane protects against light-induced photoreceptor degeneration in the rodent retina. METHODS: Albino mice and rats were anesthetized with halothane and exposed to high levels of white or blue light. Nonanesthetized animals served as controls. Retinal morphology was assessed by light microscopy, and apoptosis of photoreceptor cells was verified by detection of fragmented genomic DNA and in situ staining of apoptotic nuclei (TUNEL assay). Rhodopsin regeneration after bleaching was determined by measuring rhodopsin levels in retinas of mice or rats at different time points in darkness. RESULTS: Halothane anesthesia reversibly inhibited metabolic rhodopsin regeneration and thus prevented rhodopsin from absorbing high numbers of photons during light exposure. Consequently, photoreceptors of mice and rats anesthetized with halothane were completely protected against degeneration induced by white light. In remarkable contrast, however, halothane anesthesia did not protect against blue-light-induced photoreceptor cell death. CONCLUSIONS: After the initial bleach, halothane impeded photon absorption by rhodopsin by inhibiting metabolic rhodopsin regeneration. Apparently, the rhodopsin-mediated uptake of the critical number of photons to initiate white light-induced retinal degeneration was prevented. In contrast, halothane did not protect the retina against blue light. Blue light can efficiently restore functional rhodopsin from bleaching intermediates through a process termed photoreversal of bleaching. This process does not depend on the visual cycle via the pigment epithelium but nevertheless enables rhodopsin molecules to absorb the critical number of photons required to induce retinal degeneration.
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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) | 0.001 | 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) | 0.001 | 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".