A systematic evaluation of hippocampal GABA levels in transgenic mouse models of amyloid and tau
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) is characterized by the extracellular accumulation of amyloid‐β (Aβ) plaques and neuronal deposition of tau tangles, mainly in cortical regions and the hippocampus. Beyond these neuropathological hallmarks, it is suggested that neurotransmission dysfunctions, such as in the γ‐aminobutyric acid (GABA)ergic system, contribute to AD pathophysiology. However, the impact of Aβ and tau in the GABAergic system is still unknown. Thus, we aimed to examine GABA levels in the hippocampus of transgenic mouse models of Aβ and tau. Method We systematically reviewed the literature following the PRISMA 2020 guidelines. We searched PubMed and Web of Science databases for studies reporting GABA levels in the 3xTg‐AD and 5xFAD mouse models. These models present APP and PSEN1 mutations, but the 3xTg‐AD also harbors the MAPT P310L tau mutation, which is found in frontotemporal dementia. Result The search identified 3,576 articles. Six met the inclusion criteria (n = 26 3xTg‐AD and 26 wild‐type (WT); n = 16 5xFAD and 17 WT). The studies reported no significant differences in the levels of GABA in the hippocampus of 3xTg‐AD mice compared to their WT, but GABA levels decreased as a function of age. By contrast, the 5xFAD mouse model presented higher levels of GABA than their WT littermates. Conclusion Here, we show no significant changes in GABA levels in the hippocampus of 3xTg‐AD mice, whereas the levels of GABA were increased in the 5xFAD. Interestingly, the model harboring APP, PSEN1, and MAPT P310L mutations does not present changes in hippocampal levels of GABA. Our results suggest that Aβ alters GABA levels in the hippocampus, which may be an early change in AD. In addition, hippocampal GABAergic changes seem sensitive to different pathological features of AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".