Procognitive and neurotrophic benefits of α5-GABA-A receptor positive allosteric modulation in a β-amyloid deposition mouse model of Alzheimer’s disease pathology
Bibliographic record
Abstract
Reduced somatostatin (SST) and SST-expressing GABAergic neurons are well-replicated findings in Alzheimer's disease (AD) and are associated with cognitive deficits. SST cells inhibit pyramidal cell dendrites through α5-GABA-A receptors (α5-GABAA-R). α5-GABAAR positive allosteric modulation (α5-PAM) has procognitive and neurotrophic effects in stress and aging models. We tested whether α5-PAM (GL-II-73) could prevent cognitive deficits and neuronal spine loss in early stages, and reverse them in late stages of β-amyloid deposition in the 5xFAD model (N = 48/study; 50 % female). Acute administration of GL-II-73 prevented spatial working memory deficits in 5xFAD mice at 2 months of age, while chronic administration reversed the deficits at 5 months of age. Chronic GL-II-73 treatment prevented 5xFAD-induced loss of spine density, spine count and dendritic length at both time points, despite β-amyloid accumulation. These results demonstrate procognitive and neurotrophic effects of GL-II-73 in early and late stages of Alzheimer-related β-amyloid deposition. This suggests α5-PAM as a novel β-amyloid-independent symptomatic therapeutic approach.
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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 | 0.000 | 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".