miR-218 Promotes Dopaminergic Differentiation and Controls Neuron Excitability and Neurotransmitter Release through the Regulation of a Synaptic-Related Genes Network
Bibliographic record
Abstract
In the brain, microRNAs (miRNAs) are believed to play a role in orchestrating synaptic plasticity at a higher level by acting as an additional mechanism of translational regulation, alongside the mRNA/polysome system. Despite extensive research, our understanding of the specific contribution of individual miRNA to the function of dopaminergic neurons (DAn) remains limited. By performing a dopaminergic-specific miRNA screening, we have identified miR-218 as a critical regulator of DAn activity in male and female mice. We have found that miR-218 is specifically expressed in mesencephalic DAn and is able to promote dopaminergic differentiation of embryonic stem cells and functional maturation of transdifferentiated induced DA neurons. Midbrain-specific deletion of both genes encoding for miR-218 (referred to as miR-218-1 and mir218-2) affects the expression of a cluster of synaptic-related mRNAs and alters the intrinsic excitability of DAn, as it increases instantaneous frequencies of evoked action potentials, reduces rheobase current, affects the ionic current underlying the action potential after hyperpolarization phase, and reduces dopamine efflux in response to a single electrical stimulus. Our findings provide a comprehensive understanding of the involvement of miR-218 in the dopaminergic system and highlight its role as a modulator of dopaminergic transmission. SIGNIFICANCE STATEMENT In the past decade, several miRNAs have emerged as potential regulators of synapse activity through the modulation of specific gene expression. Among these, we have identified a dopaminergic-specific miRNA, miR-218, which is able to promote dopaminergic differentiation and regulates the translation of an entire cluster of synapse related mRNAs. Deletion of miR-218 has notable effects on dopamine release and alters the intrinsic excitability of dopaminergic neurons, indicating a direct control of dopaminergic activity by miR-218.
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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 | 0.000 |
| 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".