The GluN3-containing NMDA receptors
Bibliographic record
Abstract
N-methyl-D-aspartate receptors (NMDARs) are heterotetrameric ion channels that play crucial roles in brain function. Among all the NMDAR subtypes, GluN1-N3 receptors exhibit unique agonist binding and gating properties. Unlike “conventional” GluN1-N2 receptors, which require both glycine and glutamate for activation, GluN1-N3 receptors are activated solely by glycine. Furthermore, GluN1-N3 receptors display faster desensitization, reduced Ca2+ permeability, and lower sensitivity to Mg2+ blockage compared to GluN1-N2 receptors. Due to these characteristics, GluN1-N3 receptors are thought to play critical roles in eliminating redundant synapses and pruning spines in early stages of brain development. Recent studies have advanced pharmacological tools for specifically targeting GluN1-N3 receptors and provided direct evidence of these glycine-activated excitatory receptors in native brain tissue. The structural basis of GluN1-N3 receptors has also been elucidated through cryo-EM and artificial intelligence. These findings highlight that GluN1-N3 receptors are not only involved in essential brain functions but also present potential targets for drug development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".