MicroRNA dysregulation in response to RARβ2 inhibition reveals a negative feedback loop between MicroRNAs 1, 133a, and RARβ2 during tail and spinal cord regeneration in the adult newt
Bibliographic record
Abstract
BACKGROUND: The molecular events underlying epimorphic regeneration of the adult urodele amphibian tail and caudal spinal cord are undetermined. Given the dynamic nature of gene expression control by retinoic acid (RA) signaling and the pleiotropic effects of microRNAs (miRNAs) on multiple mRNA targets in this complex system, we examined whether RA signaling through a specific receptor, RARβ2, alters expression of select miRNAs during spinal cord regeneration. RESULTS: An initial screen identified 18 highly conserved miRNAs dysregulated in regenerating tail and spinal cord tissues after inhibition of RARβ2 signaling with a selective antagonist, LE135. miRNAs let-7c, miR-1, and miR-223 were expressed within the ependymoglial cells, coincident spatially with the expression of RARβ2. Altering the expression pattern of these three miRNAs led to a significant inhibition of caudal ependymal tube outgrowth by 21 days post tail amputation. We demonstrated that miR-1 targets the 3'-untranslated region of RARβ2 mRNA in vitro; and in vivo, up-regulation of miR-1 led to a significant decrease in RARβ2 protein. CONCLUSIONS: These and previous data suggest that miR-1 and miR-133a, both members of the same miRNA gene cluster, may participate with RARβ2 in a negative feedback loop contributing to the regulation of the ependymal response after tail amputation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".