Forskolin induction of late‐LTP and up‐regulation of 5′ TOP mRNAs translation via mTOR, ERK, and PI3K in hippocampal pyramidal cells
Bibliographic record
Abstract
The late phase of long-term potentiation (LTP) requires activation of the mammalian target of rapamycin (mTOR) pathway and synthesis of new proteins. mTOR regulates protein synthesis via phosphorylation of 4E-binding proteins (4E-BPs) and S6K, and via selective up-regulation of 5' terminal oligopyrimidine (5' TOP) mRNAs that encode components of the translational machinery. In this study, we explored the regulation of 5' TOP mRNAs during late-LTP (L-LTP). Synaptic plasticity was studied at Schaffer collateral--CA1 pyramidal cell synapses in rat organotypic hippocampal slices. Forskolin, an adenylate cyclase activator, induced L-LTP in organotypic slices that was mTOR-dependent. To determine if 5' TOP mRNAs are specifically up-regulated during L-LTP, we generated a 5' TOP-myr-dYFP reporter to selectively monitor 5' TOP translation. Confocal imaging experiments in cultured slices revealed an increase in somatic and dendritic fluorescence after forskolin treatment. This up-regulation was dependent on an intact TOP sequence and was mTOR, extracellular signal-regulated kinase (ERK), and phosphatidylinositol 3-kinase (PI3K)-dependent. Our findings indicate that forskolin induces L-LTP in hippocampal neurons and up-regulates 5' TOP mRNAs translation via mTOR, suggesting that up-regulation of the translational machinery is a candidate mechanism for the stabilization of LTP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".