Characterization of Rhodopsin P23H-Induced Retinal Degeneration in a<i>Xenopus laevis</i>Model of Retinitis Pigmentosa
Bibliographic record
Abstract
PURPOSE: To investigate the pathogenic mechanisms that underlie retinal degeneration induced by the rhodopsin mutation P23H in a Xenopus laevis model of RP. METHODS: Transgenic X. laevis were generated that expressed the rhodopsin mutants rhoP23H and rhoP23H/K29R (a variant incapable of transducin activation). Using quantitative dot blot assay, transgenic rhodopsin levels and the extent of retinal degeneration were determined. The contribution of rhodopsin signal transduction to cell death was assessed by comparison of rhoP23H and rhoP23H/K296R effects and by dark rearing of rhoP23H tadpoles. Intracellular localization and the oligomeric state of rhoP23H were determined by confocal immunofluorescence microscopy and Western blot analysis. RESULTS: RhoP23H induced retinal degeneration in a dose-dependent manner whereas expression of a control rhodopsin did not, indicating that rod photoreceptor death was specific to the P23H mutation and was not caused by the overexpression of rhodopsin. Neither abolishment of rhoP23H photosensitivity and ability to activate transducin nor dark rearing rescued rod viability. RhoP23H was localized primarily to the endoplasmic reticulum (ER) of inner segments. Western blot analysis of transgenic retinas showed that rhoP23H was prone to form dimers and higher molecular weight oligomers. However, aggresomes were not observed in rhoP23H transgenic retinal sections, despite their being reported in cultured cells expressing rhoP23H. CONCLUSIONS: These results support a role for rhoP23H misfolding and inner segment accumulation in rod death, possibly by ER overload or other cellular stress pathways rather than by altered rhodopsin signal transduction or aggresome formation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".