Essential Role of α5‐GABAA Positive Allosteric Modulation in Cognitive Functions in a Mouse Model of Amyloid Deposition
Bibliographic record
Abstract
BACKGROUND: Despite extensive drug development efforts, efficacious treatment options for Alzheimer's Disease (AD) are still lacking. Studies identified the α5-containing GABAA receptor (α5-GABAAR) as essential for the regulation of cognitive function and a promising therapeutic target. GL-II-73, a positive allosteric modulator at the α5-GABAAR, showed efficacy at reversing working memory deficits and neuronal shrinkage induced by amyloid load in preclinical models. However, its mechanism of action through the benzodiazepine-binding pocket of the α5-GABAARs remains to be demonstrated. This project proposes to show the requirement of positive allosteric modulation of GL-II-73 at the α5-GABAARs in the regulation of cognitive functions in a double transgenic mouse model of AD. We hypothesize that, following chronic treatment, the drug-sensitive strain will show improved cognitive performance compared to the drug-insensitive strain, despite both groups having amyloid pathology. METHODS: 5xFAD mice were bred with α5-KI (Knock-in) mice to generate double transgenic animals. Four-to-five-month-old double transgenic mice were used, which show amyloid deposition (5xFAD) and insensitivity to drug binding in the benzodiazepine-binding pocket. Double transgenic animals and their wild-type littermates (n=12/group, 50% female) underwent three weeks of drug treatment (GL-II-73, 30 mg/kg), administered through drinking water. Y-maze alternation task and Morris Water Maze were conducted to assess working memory and spatial cognition. RESULTS: Drug-sensitive mice receiving GL-II-73 showed better cognitive performance than the control group in both Morris Water Maze and Y-Maze alternation task, while such facilitation was not observed in the drug-insensitive mice. CONCLUSION: Our findings demonstrated that the effects of GL-II-73 are mediated by allosteric modulation of the benzodiazepine-binding site of α5-GABAARs, as expected, specifically at improving working memory and spatial cognition.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".