ERK and mTOR Signaling Couple β-Adrenergic Receptors to Translation Initiation Machinery to Gate Induction of Protein Synthesis-dependent Long-term Potentiation
Bibliographic record
Abstract
beta-Adrenergic receptors critically modulate long-lasting synaptic plasticity and long-term memory in the mammalian hippocampus. Persistent long-term potentiation of synaptic strength requires protein synthesis and has been correlated with some forms of hippocampal long-term memory. However, the intracellular processes that initiate protein synthesis downstream of the beta-adrenergic receptor are unidentified. Here we report that activation of beta-adrenergic receptors recruits ERK and mammalian target of rapamycin signaling to facilitate long-term potentiation maintenance at the level of translation initiation. Treatment of mouse hippocampal slices with a beta-adrenergic receptor agonist results in activation of eukaryotic initiation factor 4E and the eukaryotic initiation factor 4E kinase Mnk1, along with inhibition of the translation repressor 4E-BP. This coordinated activation of translation machinery requires concomitant ERK and mammalian target of rapamycin signaling. Taken together, our data identify distinct signaling pathways that converge to regulate beta-adrenergic receptor-dependent protein synthesis during long-term synaptic potentiation in the hippocampus. We suggest that beta-adrenergic receptors play a crucial role in gating the induction of long-lasting synaptic plasticity at the level of translation initiation, a mechanism that may underlie the ability of these receptors to influence the formation of long-lasting memories.
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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".