Running to remember: The effects of exercise on perineuronal nets, microglia, and hippocampal angiogenesis in female and male mice
Bibliographic record
Abstract
Exercise is accepted as a positive health behaviour; however, the mechanisms of exercise on neuroprotection and cognitive health are not completely understood. The purpose of this study was to explore the neurobiological benefits of chronic treadmill exercise in female and male mice through its role in microglial content and morphology, cerebral vascularization, and perineuronal net (PNN) expression. We further examined how these neurobiological changes relate to spatial memory outcomes. Adult mice were assigned to a sedentary or treadmill exercise group for eight weeks. During the final week, all mice were trained on a spatial memory task (Barnes maze) and brains were collected for immunohistochemistry. Exercised mice made fewer errors than sedentary mice during the first two days of training and probe trial. Females, regardless of exercise training, made fewer errors during Barnes maze training and demonstrated a greater frequency of spatial strategy use compared to males. Exercised mice, regardless of sex, had fewer PNNs in the dentate gyrus of the hippocampus compared to sedentary controls. The number of PNNs in the dorsal dentate gyrus was positively correlated with total errors during training. During the probe, greater errors correlated with more PNNs among the exercised group only. Microglia count and cerebral vascularization were not affected by exercise, although proportions of microglia type (ameboid, stout/thick, and thick/thin) were regulated by exercise in the ventral dentate gyrus. We conclude that exercise decreases PNNs in the dentate gyrus in both sexes and this may be related to better spatial learning and memory.
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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) | 0.000 | 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".