Characterizing the role of eukaryotic elongation factor 2 and eukaryotic initiation factor 4E binding protein in rapamycin-sensitive signaling in Aplysia
Bibliographic record
Abstract
In Aplysia, serotonin mediates behavioral sensitization partly by increasing the strength of the synapse between sensory and motor neurons, a process known as facilitation. The retention of long term facilitation of sensory-motor neuron synapses requires local translation. Indeed, retention of long term facilitation is blocked by rapamycin, an inhibitor of a specific translational pathway. One rapamycin-sensitive target is S6 kinase. S6 kinase activation and the subsequent increased translation of 5 ' terminal oligopyrimidine (TOP) mRNAs that encode components of the translational machinery has been proposed to be important for retention of long term facilitation (Khan et al., 2001). We have cloned one of these TOP mRNAs, the elongation factor eEF2 and showed that serotonin increased the translation of this mRNA in synaptosomes. The phosphorylation of eEF2 may also be regulated by the rapamycin-sensitive system. eEF2 phosphorylation is mediated by the calcium-sensitive eEF2 kinase and blocks translational elongation. Serotonin application decreased eEF2 phosphorylation in synaptosomes and in isolated neurites and this was blocked by rapamycin. This suggests that serotonin-mediated increases in the translation rate can be independent of the regulation of TOP mRNAs. We propose a mechanism involving eEF2 for increasing synaptic specificity of translational control. Stimulation blocks translation at all synapses through calcium entry and phosphorylation of eEF2. This block can be reversed at specific synapses through activation of the rapamycin-sensitive system and dephosphorylation of eEF2.
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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 | 0.001 | 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".