Inhibition of miR-15a Promotes BDNF Expression and Rescues Dendritic Maturation Deficits in MeCP2-Deficient Neurons
Bibliographic record
Abstract
In both the embryonic and adult brain, a critical step in neurogenesis is neuronal maturation. Deficiency of MeCP2 leads to Rett syndrome, a severe neurodevelopmental disorder. We have previously shown that MeCP2 plays critical roles in the maturation step of new neurons during neurogenesis. MeCP2 is known to regulate the expression of brain-derived neurotrophic factor (BDNF), a potent neurotrophic factor for neuronal maturation. Nevertheless, how MeCP2 regulates BDNF expression and how MeCP2 deficiency leads to reduced BDNF expression remain unclear. Here, we show that MeCP2 regulates the expression of a microRNA, miR-15a. We find that miR-15a plays a significant role in the regulation of neuronal maturation. Overexpression of miR-15a inhibits dendritic morphogenesis in immature neurons. Conversely, a reduction in miR-15a has the opposite effect. We further show that miR-15a regulates expression levels of BDNF, and exogenous BDNF could partially rescue the neuronal maturation deficits resulting from miR-15a overexpression. Finally, inhibition of miR-15a could rescue neuronal maturation deficits in MeCP2-deficient adult-born new neurons. These results demonstrate a novel role for miR-15a in neuronal development and provide a missing link in the regulation of BDNF by MeCP2.
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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) | 0.001 | 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".