The regeneration-responsive element careg monitors activation of Müller glia after MNU-induced damage of photoreceptors in the zebrafish retina
Bibliographic record
Abstract
In contrast to mammals, zebrafish can regenerate their damaged photoreceptors. This capacity depends on the intrinsic plasticity of Müller glia (MG). Here, we identified that the transgenic reporter careg , a marker of regenerating fin and heart, also participates in retina restoration in zebrafish. After methylnitrosourea (MNU) treatment, the retina became deteriorated and contained damaged cell types including rods, UV-sensitive cones and the outer plexiform layer. This phenotype was associated with the induction of careg expression in a subset of MG until the reconstruction of the photoreceptor synaptic layer. Single-cell RNA sequencing (scRNAseq) analysis of regenerating retinas revealed a population of immature rods, defined by high expression of rhodopsin and the ciliogenesis gene meig1 , but low expression of phototransduction genes. Furthermore, cones displayed deregulation of metabolic and visual perception genes in response to retina injury. Comparison between careg:EGFP expressing and non-expressing MG demonstrated that these two subpopulations are characterized by distinct molecular signatures, suggesting their heterogenous responsiveness to the regenerative program. Dynamics of ribosomal protein S6 phosphorylation showed that TOR signaling became progressively switched from MG to progenitors. Inhibition of TOR with rapamycin reduced the cell cycle activity, but neither affected careg:EGFP expression in MG, nor prevented restoration of the retina structure. This indicates that MG reprogramming, and progenitor cell proliferation might be regulated by distinct mechanisms. In conclusion, the careg reporter detects activated MG, and provides a common marker of regeneration-competent cells in diverse zebrafish organs, including the retina.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".