‘Silent’ priming of translation-dependent LTP by β-adrenergic receptors involves phosphorylation and recruitment of AMPA receptors
Bibliographic record
Abstract
The capacity for long-term changes in synaptic efficacy can be altered by prior synaptic activity, a process known as "metaplasticity." Activation of receptors for modulatory neurotransmitters can trigger downstream signaling cascades that persist beyond initial receptor activation and may thus have metaplastic effects. Because activation of β-adrenergic receptors (β-ARs) strongly enhances the induction of long-term potentiation (LTP) in the hippocampal CA1 region, we examined whether activation of these receptors also had metaplastic effects on LTP induction. Our results show that activation of β-ARs induces a protein synthesis-dependent form of metaplasticity that primes the future induction of late-phase LTP by a subthreshold stimulus. β-AR activation also induced a long-lasting increase in phosphorylation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) GluA1 subunits at a protein kinase A (PKA) site (S845) and transiently activated extracellular signal-regulated kinase (ERK). Consistent with this, inhibitors of PKA and ERK blocked the metaplastic effects of β-AR activation. β-AR activation also induced a prolonged, translation-dependent increase in cell surface levels of GluA1 subunit-containing AMPA receptors. Our results indicate that β-ARs can modulate hippocampal synaptic plasticity by priming synapses for the future induction of late-phase LTP through up-regulation of translational processes, one consequence of which is the trafficking of AMPARs to the cell surface.
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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) | 0.002 | 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".