GluN2B-specific NMDAR positive allosteric modulation reverses cognitive and behavioral abnormalities in Mecp2 and Disc1 transgenic mice
Bibliographic record
Abstract
The GluN2B subunit of N-methyl-D-aspartate receptors (NMDAR) plays a central role in synaptic development and plasticity, and its hypofunction is linked to autism spectrum disorder, severe neurodevelopmental delay, and other neuropsychiatric diseases. Therefore, enhancing the function of this NMDAR subunit may provide an effective therapeutic strategy for correcting synaptic and behavioral deficits associated with GluN2B-hypofunction. Here, we developed a class of GluN2B-selective positive allosteric modulators and characterized the pharmacological properties and binding site of the lead compound, 175. Systemic application of 175 facilitates hippocampal long-term depression in rats. Importantly, 175 restores performances in open-field exploration and three-chamber test in Mecp2 overexpression mice. Treatment with 175 also reverses behavioral abnormalities in open-field, Y-maze spontaneous alternation, three-chamber test, and pre-pulse inhibition in Disc1 mutant mice. Our findings introduce a pharmacological tool for selectively potentiating GluN2B-NMDARs function and highlight its therapeutic potential for cognitive and behavioral symptoms associated with GluN2B hypofunction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".