MEK/mTOR-dependent D1 dopamine receptor activation induces local protein synthesis via eEF2 dephosphorylation in neurons
Bibliographic record
Abstract
Abstract Neuromodulators in general, and dopamine in particular, define brain and neuronal states in different ways including regulation of global and local mRNA translation. Yet, the signaling pathways underlying the effects of dopamine on mRNA translation are not clear. Here, using genetic, pharmacologic, biochemical, and imaging methods, we tested the hypothesis that dopamine regulates phosphorylation of the eukaryotic elongation factor 2 (eEF2). We found that activation of dopamine receptor D1 but not D2 leads to rapid dephosphorylation of eEF2 at Thr 56 in cortical primary neuronal culture and in vivo in a time-dependent manner. Additionally, NMDA receptor, mTOR, and ERK pathways are upstream to the D1 receptor-dependent eEF2 dephosphorylation and essential for it. Furthermore, D1 receptor activation resulted in a major reduction in dendritic eEF2 phosphorylation levels together with a correlative increase in local mRNA translation. These results reveal the role of eEF2 in dopamine regulation of local mRNA translation in neurons. One-sentence summary D1 receptor activation increases protein synthesis in dendrites by inactivating eEF2K in an ERK2/mTOR-dependent manner.
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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) | 0.005 | 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".