Src dependency of the regulation of LTP by alternative splicing of <i>GRIN1</i> exon 5
Bibliographic record
Abstract
Alternative splicing of Grin1 exon 5 regulates induction of long-term potentiation (LTP) at Schaffer collateral-CA1 synapses: LTP in mice lacking the GluN1 exon 5-encoded N1 cassette (GluN1a mice) is significantly increased compared with that in mice compulsorily expressing this exon (GluN1b mice). The mechanism underlying this difference is unknown. Here, we report that blocking the non-receptor tyrosine kinase Src prevents induction of LTP in GluN1a mice but not in GluN1b. We find that activating Src enhances pharmacologically isolated synaptic N -methyl- d -aspartate receptor (NMDAR) currents in GluN1a mice but not in GluN1b. Moreover, we observe that Src activation increases the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor component of Schaffer collateral-evoked excitatory post-synaptic potentials in GluN1a mice, but this increase is prevented by blocking NMDARs. We conclude that at these synapses, NMDARs in GluN1a mice are subject to upregulation by Src that mediates induction of LTP, whereas NMDARs in GluN1b mice are not regulated by Src, leading to Src-resistance of LTP. Thus, we have uncovered that a key regulatory mechanism for synaptic potentiation is gated by differential splicing of exon 5 of Grin1 . This article is part of a discussion meeting issue ‘Long-term potentiation: 50 years on’.
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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".