A systematic evaluation of cortical GABA levels in transgenic mouse models of amyloid
Bibliographic record
Abstract
Abstract Background Rodent models that overexpress mutations in the amyloid precursor protein (APP) and presenilin 1 (PSEN1) genes have been widely applied in Alzheimer’s disease (AD) research. These models classically present amyloid plaque deposition in cortical and hippocampal areas and neurotransmission changes. Although amyloid‐related glutamatergic abnormalities have been extensively described, little is known about its effects on the GABAergic system. Thus, we aimed to examine GABA levels in the cortex of two transgenic amyloid mouse models. Method We systematically reviewed the literature following the PRISMA 2020 guidelines. PubMed and Web of Science databases were searched for studies reporting GABA levels in the cortex of APPswe/PSEN1dE9 and Tg2576 mice. We opted to evaluate only animals with mature amyloid plaques in their cortices, according to each mouse model previous characterization. Result The search identified 3576 papers. Seven records met the inclusion criteria (Tg2576: n = 21, mean age ± standard deviation (SD) = 14.7 ± 3.7 months; controls: n = 21; APPswe/PSEN1dE9: n = 25, mean age ± SD = 8.5 ± 4.1 months; controls: n = 25). Five out of seven results reported non‐significant differences in the GABA levels in multiple cortical regions, such as the frontal, pre‐frontal, and rhinal cortices of the Tg2576 mouse model, but two studies described that GABA is significantly decreased. Furthermore, all studies with the APP/PSEN1 model consistently reported decreased cortical GABA levels. Figure 1 provides a summary of our findings. Conclusion Our results suggest that APP and PSEN1 mutations may contribute to the decrease in the levels of GABA in cortical regions of amyloid models. Future meta‐analyses and clinical studies are needed to ascertain the consistency of the reported results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".