Dramatic impacts on brain pathology, anxiety, and cognitive function in the knock-in APPNL-G-F mouse model of Alzheimer disease following long-term voluntary exercise
Bibliographic record
Abstract
Abstract Background An active lifestyle is associated with improved cognitive functions in aged people and may prevent or slow down the progression of various neurodegenerative diseases including Alzheimer’s disease (AD). To investigate these protective effects, male APPNL-G-F mice were exposed to long-term voluntary exercise. Methods Three-month-old AD mice were housed in a cage supplemented with a running wheel for 9 months for long-term exercise. At the age of 12 months, behavioral tests were completed for all groups. After completing behavioral testing, their brains were assessed for amyloid pathology, microgliosis, and cholinergic cells. Results The results showed that APPNL-G-F mice allowed to voluntarily exercise showed an improvement in cognitive functions. Furthermore, long-term exercise also improved anxiety in APPNL-G-F mice as assessed by measuring thigmotaxis in the Morris water task. We also found reductions in amyloid load and microgliosis, and a preservation of cholinergic cells in the brain of APPNL-G-F mice allowed to exercise in their home cages. These profound reductions in brain pathology associated with AD are likely responsible for the observed improvement of learning and memory functions following extensive and regular exercise. Conclusion These findings suggest the potential of physical exercise to mitigate the cognitive deficits in 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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".