Regulation of Eukaryotic Initiation Factor 4E by Converging Signaling Pathways during Metabotropic Glutamate Receptor-Dependent Long-Term Depression
Bibliographic record
Abstract
Long-term depression (LTD) is an activity-dependent decrease in synaptic efficacy that can be induced in hippocampal area CA1 by pharmacological application of the selective group I metabotropic glutamate receptor (mGluR) agonist 3,5-diyhroxyphenylglycine (DHPG). Recent work has demonstrated that DHPG-induced LTD recruits at least two signal transduction pathways known to couple to translation, the mitogen-activated protein kinase kinase (MEK)-extracellular signal-regulated kinase (ERK) signaling pathway and the phosphoinositide 3-kinase (PI3K)-Akt-mammalian target of rapamycin (mTOR) signaling pathway. However, it remains unclear which translation factors are engaged by these two signaling pathways during mGluR-LTD. In this study, we investigated whether the group I mGluRs couple to the cap-dependent translation proteins: Mnk1, eIF4E, and 4E-BP. We found that both the MEK-ERK and PI3K-mTOR signaling pathways are critical for the DHPG-induced regulation of these translation factors. Furthermore, we demonstrate that increasing eIF4F complex availability via the genetic elimination of 4E-BP2 can enhance the degree of LTD achieved by DHPG application in an ERK-dependent manner. Our results provide direct evidence that cap-dependent translation is engaged during mGluR-LTD and demonstrate that the MEK-ERK and PI3K-mTOR signaling pathways converge to regulate eIF4E activity after induction of DHPG-LTD.
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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 | 0.000 |
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".