Novel Translational Control in Arc-dependent Long Term Potentiation Consolidation in Vivo
Bibliographic record
Abstract
Regulation of translation factor activity plays a major role in protein synthesis-dependent forms of synaptic plasticity. We examined translational control across the critical period of Arc synthesis underlying consolidation of long term potentiation (LTP) in the dentate gyrus of intact, anesthetized rats. LTP induction by high frequency stimulation (HFS) evoked phosphorylation of the cap-binding protein eukaryotic initiation factor 4E (eIF4E) and dephosphorylation of eIF2alpha on a protracted time course matching the time-window of Arc translation. Local infusion of the ERK inhibitor U0126 inhibited LTP maintenance and Arc protein expression, blocked changes in eIF4E and eIF2alpha phosphorylation state, and prevented initiation complex (eIF4F) formation. Surprisingly, inhibition of the mTOR protein complex 1 (mTORC1) with rapamycin did not impair LTP maintenance or Arc synthesis nor did it inhibit eIF4F formation or phosphorylation of eIF4E. Rapamycin nonetheless blocked mTOR signaling to p70 S6 kinase and ribosomal protein S6 and inhibited synthesis of components of the translational machinery. Using immunohistochemistry and in situ hybridization, we show that Arc protein expression depends on dual, ERK-dependent transcription and translation. Arc translation is selectively blocked by pharmacological inhibition of mitogen-activated protein kinase-interacting kinase (MNK), the kinase coupling ERK to eIF4E phosphorylation. Furthermore, MNK signaling was required for eIF4F formation. These results support a dominant role for ERK-MNK signaling in control of translational initiation and Arc synthesis during LTP consolidation in the dentate gyrus. In contrast, mTORC1 signaling is activated but nonessential for Arc synthesis and LTP. The work, thus, identifies translational control mechanisms uniquely tuned to Arc-dependent LTP consolidation in live rats.
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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) | 0.001 | 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".