Voluntary long-term exercise by female mice modulates anxiety-like behavior and motor function but minimally impacts acute oxidative injury in the central nervous system
Bibliographic record
Abstract
Physical and cognitive decline from a sedentary lifestyle and aging are detrimental to the health and function of the central nervous system (CNS). As people living in developed societies adopt more sedentary lifestyles with age, identifying cost-efficient strategies to mitigate physical and cognitive decline is critical for improving long-term health care outcomes. While accumulating evidence suggests that moderate aerobic exercise can acutely enhance cognitive decline and improve physical function, the ability of voluntary long-term exercise (VLTE) to improve CNS health and resilience remains less well understood. Here, we assessed how VLTE affected the health and function of the CNS by comparing female mice with access to a functional or disabled running wheel for 6-months. Notably, VLTE limited weight gain in mice and significantly upregulated gene expression in pathways related to synapse function and ion transport in neuroglial cells from the brain. While mice with VLTE had similar short-term memory performance as sedentary mice, VLTE significantly reduced anxiety-like behavior and altered motor function by 6 months. Despite these transcriptomic and behavioral changes, VLTE did not modulate acute oxidative injury induced by oxidized phosphatidylcholine in the spinal cord white matter of mice, suggesting that VLTE may not be sufficient to overcome severe oxidative injury in the CNS.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".