Effects of voluntary exercise on cognition, neurogenesis, and plaque load in a mouse model of Alzheimers disease.
Bibliographic record
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder leading to cognitive impairment and disruption of adult neurogenesis. It has been shown that exercise influences adult neurogenesis, synaptic plasticity, and cognitive functions in animal models. In healthy adults and AD patients, studies are suggesting that exercise has potential benefits on cognitive functions. However, we only begin to understand the global effects that exercise can have on amyloid pathology, neuronal plasticity, and cognition in AD mouse models. Here we evaluated the effects of moderate voluntary exercise on cognition, neurogenesis, and plaque burden by giving mice access to running wheels for 1 and 2 months and assessing their functional recovery. We used an AD mouse model of amyloid pathology and their non‐transgenic littermates as control. Our results show an improvement in hippocampal‐dependent spatial and non‐spatial memory in transgenic mice exercising for 2 months compared to non‐running transgenic mice. Transgenic exercising animals also showed significantly greater levels of hippocampal adult neurogenesis (increase in BrdU/NeuN positive cells), and increase in survival of newborn cells (increase in BrdU positive cells). Plaque burden, evaluated as the mean plaque size and plaque number, in the hippocampus was not statistically different in runners compared to non‐runners transgenic mice. In summary, exercise improved spatial working memory in an AD mouse model of amyloidoisis without reducing plaque burden. This improvement was accompanied by an increase in neurogenesis. We conclude that physical voluntary exercise has the potential to improve cognition even in presence of high levels of amyloid pathology.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".