<scp>NMDA</scp> receptor‐deficient mice display sexual dimorphism in the onset and severity of behavioural abnormalities
Bibliographic record
Abstract
N-methyl-d-aspartate (NMDA) receptor-deficient mice can be used to understand the role that NMDA receptors (NMDARs) play in the pathophysiology of neurodevelopmental disorders such as schizophrenia. Genetically modified mice with low levels of NR1 subunit (NR1 knockdown mice) have reduced receptor levels throughout development, and have robust abnormalities in behaviours that are relevant to schizophrenia. We traced the onset and severity of these behaviours at three developmental stages to understand when in development the underlying circuits depend on intact NMDAR function. We examined social behaviour, working memory, executive function, locomotor activity and stereotypy at 3, 6 and 12 weeks of age in NR1 knockdown mice and their wild-type littermates. We discovered that each of these behaviours had a unique developmental trajectory in mutant mice, and males showed an earlier onset and severity than females in several behaviours. Hyperlocomotion was most substantial in juvenile mice and plateaued in adult mice, whereas stereotypy progressively worsened with age. Impairments in working memory and sociability were sexually dimorphic, with deficits first detected in peri-adolescent males but only detected in adult females. Interestingly, executive function was most impaired in peri-adolescent mice of either sex. Furthermore, while juvenile mutant mice had some ability to problem solve in the puzzle box test, the same mice lost this ability when tested 4 weeks later. Our studies highlight key developmental periods for males and females in the expression of behaviours that are relevant to psychiatric disorders.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".