Regulation of the lncRNA <i>malat1</i> /Egr1 Axis by Wnt, Notch and TGF-β signaling: A Key Mechanism in Retina Regeneration
Bibliographic record
Abstract
Abstract Adult zebrafish retinas rely on the resident Müller glia to maintain homeostasis and enable regeneration. Retina regeneration remains incomplete in mammals despite extensive efforts to emulate zebrafish regenerative conditions. Many studies have examined the reprogramming of zebrafish Müller glia cells, which is necessary for regeneration driven by regeneration-associated gene expression. Here, we show that the lncRNA malat1 , crucial for many biological functions, plays essential roles during retina regeneration. We demonstrate that malat1 functions through an Egr-dependent axis, modulated by Wnt, Notch, and TGF-β signaling pathways, and is necessary for effective retina regeneration. Moreover, we uncover that the antisense lncRNA talam1 , which regulates malat1 availability, is differentially regulated in zebrafish and mice, highlighting species-specific gene regulatory mechanisms after retinal injury. Cells with active TGF-β signaling stabilize Malat1 in mice while the same signaling destabilizes malat1 in zebrafish. Taken together, our work uncovers a new role for the malat1 /Egr1 axis in necessitating retina regeneration, which may have important implications for differential regenerative ability in vertebrates.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".