Reduced expression of α5GABAA receptors elicits autism-like alterations in EEG patterns and sleep-wake behavior
Bibliographic record
Abstract
A reduction in the activity of GABAA receptors, particularly α5 subunit-containing GABAA receptors (α5GABAARs), has been implicated in the etiology of Autism Spectrum Disorders (ASD). Genetically modified mice that lack α5GABAARs (Gabra5−/−) exhibit autism-like behaviors and both enhanced and impaired learning and memory, depending on the behavioral task. The aim of this study was to examine the electroencephalogram (EEG) activity and sleep-wake behaviors in Gabra5−/− mice and wild-type mice. In addition, since some individuals with ASD can exhibit elevated innate immune response, mice were treated with lipopolysaccharide (LPS; 125 mg/kg intraperitoneal injection) or vehicle and EEG and sleep-wake patterns were assessed. The results showed that Gabra5−/− mice (n = 3) exhibited elevated 0–2 Hz EEG activity during all sleep-wake states (all p < 0.04), decreased 8–12 Hz EEG activity during REM sleep (p = 0.04), and decreased sleep spindles under baseline conditions compared to wild-type controls (n = 4) (all p ≤ 0.03). Alterations in EEG activity and sleep-wake behavior were identified in Gabra5−/− mice following treatment with LPS, however these changes were similar to those in wild-type mice. Our findings support the hypothesis that reduced α5GABAAR activity contributes to an ASD phenotype. The results also suggest that Gabra5−/− mice may serve as an animal model for ASD, as assessed through EEG activity and sleep-wake behaviors.
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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 | 0.000 |
| 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 | 0.000 |
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".