The Dependence of Retinal Degeneration Caused by the Rhodopsin P23H Mutation on Light Exposure and Vitamin A Deprivation
Bibliographic record
Abstract
PURPOSE: To characterize the influence of light and vitamin A on retinal degeneration in an animal model of retinitis pigmentosa caused by the rhodopsin P23H mutation. METHODS: Retinal degeneration was examined in transgenic Xenopus laevis expressing P23H rhodopsin, in which retinal degeneration is completely rescued by preventing light exposure. The sensitivity of this retinal degeneration to varying intensities, wavelengths, and durations of light exposure, and to vitamin A deprivation was characterized. RESULTS: Green light was the most effective inducer of retinal degeneration in this model. Retinal degeneration was induced by prolonged exposure to green light and was prevented by filters that block short wavelengths. Reducing the duration of light exposure prevented retinal degeneration, even when the light intensity was proportionally increased. Vitamin A deprivation also induced retinal degeneration associated with defects in P23H rhodopsin biosynthesis. Vitamin A deprivation did not cause retinal degeneration in nontransgenic animals. CONCLUSIONS: The mechanism of retinal degeneration in this animal model of RP involves the interaction of light with rhodopsin rather than with free chromophore or bleached rhodopsin. These results may explain the clinical benefits of vitamin A for patients with retinitis pigmentosa and may indicate that pharmacological chaperones are a viable approach to RP therapy. Results also suggest strategies for minimizing RD in patients through controlling light exposure duration or wavelengths.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".