N1 cassette-lacking NMDA receptors mediate the antidepressant activity of ketamine
Bibliographic record
Abstract
Summary Ketamine has emerged as a rapid-acting and robust antidepressant 1,2 . However, the mechanism of its antidepressant action remains enigmatic. The core issue that has yet to be resolved is whether NMDA receptors (NMDARs), which are subject to open channel blockade by ketamine 3,4 , mediate the antidepressant effect. NMDARs naturally undergo alternative splicing of the obligatory GluN1 subunit 5 , producing receptor diversity in the brain that has not been considered in the actions of ketamine. Here we discover that alternative splicing of Grin1 exon 5, which leads to exclusion (GluN1a) or inclusion (GluN1b) of the N1 cassette, located in the N-terminal domain of GluN1 distant from the pore, unexpectedly dictates the level and dynamics of NMDAR blockade by ketamine and gates its antidepressant activity. We find that ketamine prevents NMDAR-dependent long-term potentiation (LTP) in the CA1 region of the hippocampus in mice engineered to exclude Grin1 exon 5 (GluN1a mice), but ketamine has no effect on LTP in mice engineered to include this exon (GluN1b mice). Ketamine inhibits synaptic NMDARs in CA1 pyramidal neurons in both GluN1a and GluN1b mice, with the level of steady-state blockade marginally greater in GluN1a- than in GluN1b-containing NMDARs. However, the rate of relief of ketamine blockade upon membrane depolarization is markedly slower in GluN1a than in GluN1b neurons such that GluN1a-containing receptors remain blocked during bursting activity, whereas those containing GluN1b escape the ketamine blockade. Furthermore, ketamine treatment, either via systemic administration or local infusion into the hippocampus, induces an antidepressant effect in GluN1a mice but has no effect in GluN1b mice. Collectively, we identify GluN1a-containing NMDARs, which are persistently blocked by ketamine during neuronal firing activity, to be selectively responsible for the antidepressant effect.
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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 | 0.001 |
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".