Gamma‐patterned sensory stimulation reverses synaptic plasticity deficits in rat models of early Alzheimer's disease
Bibliographic record
Abstract
Non-invasive sensory stimulation in the range of the brain's gamma rhythm (30-100 Hz) is emerging as a new potential therapeutic strategy for the treatment of Alzheimer's disease (AD). Here, we investigated the effect of repeated combined exposure to 40 Hz synchronized sound and light stimuli on hippocampal long-term potentiation (LTP) in vivo in three rat models of early AD. We employed a very complete model of AD amyloidosis, amyloid precursor protein (APP)-overexpressing transgenic McGill-R-Thy1-APP rats at an early pre-plaque stage, systemic treatment of transgenic APP rats with corticosterone modelling certain environmental AD risk factors and, importantly, intracerebral injection of highly disease-relevant AD patient-derived synaptotoxic beta-amyloid and tau in wild-type animals. We found that daily treatment with 40 Hz sensory stimulation for 2 weeks fully abrogated the inhibition of LTP in all three models. Moreover, there was a negative correlation between the magnitude of LTP and the level of active caspase-1 in the hippocampus of transgenic APP animals, which suggests that the beneficial effect of 40 Hz stimulation was dependent on modulation of pro-inflammatory mechanisms. Our findings support ongoing clinical trials of gamma-patterned sensory stimulation in early AD.
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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 | 0.000 |
| 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 | 0.001 |
| 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".