Mislocalized Rhodopsin Does Not Require Activation to Cause Retinal Degeneration and Neurite Outgrowth in<i>Xenopus laevis</i>
Bibliographic record
Abstract
Mutations in the C terminus of rhodopsin disrupt a rod outer segment localization signal, causing rhodopsin mislocalization and aggressive forms of retinitis pigmentosa (RP). Studies of cultured photoreceptors suggest that activated mislocalized rhodopsin can cause cell death via inappropriate G-protein-coupled signaling. To determine whether this pathway occurs in vivo, we developed a transgenic Xenopus laevis model of RP based on the class I rhodopsin mutation Q344Ter (Q350Ter in X. laevis). We used a second mutation, K296R, to block the ability of rhodopsin to bind chromophore and activate transducin. We compared the effects of expression of both mutants on X. laevis retinas alone and in combination. K296R did not significantly alter the cellular distribution of rhodopsin and did not induce retinal degeneration. Q350Ter caused rhodopsin mislocalization and induced an RP-like degeneration, including loss of rods and development of sprouts or neurites in some remaining rods, but did not affect the distribution of endogenous rhodopsin. The double mutant K296R/Q350Ter caused a similar degeneration and neurite outgrowth. In addition, we found no protective effects of dark rearing in these animals. Our results demonstrate that the degenerative effects of mislocalized rhodopsin are not mediated by the activated form of rhodopsin and therefore do not proceed via conventional G-protein-coupled signaling.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".