Physical Exercise and Mechanism Related to Alzheimer’s Disease: Is Gut–Brain Axis Involved?
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease is a progressive neurodegenerative disease characterized by structural changes in the brain, including hippocampal atrophy, cortical thinning, amyloid plaques, and tau tangles. Due to the aging of the global population, the burden of Alzheimer's disease is expected to increase, making the exploration of non-pharmacological interventions, such as physical exercise, an urgent priority. RESULTS: There is emerging evidence that regular physical exercise may mitigate the structural and functional declines associated with Alzheimer's disease. The underlying mechanisms, however, remain poorly understood. Gut-brain axis research is a promising area for further investigation. This system involves bidirectional communication between the gut microbiome and the brain. According to recent studies, the gut microbiome may influence brain health through modulating neuroinflammation, producing neuroactive compounds, and altering metabolic processes. Exercise has been shown to alter the composition of the gut microbiome, potentially impacting brain structure and function. In this review, we aim to synthesize current research on the relationship between physical exercise, structural brain changes in Alzheimer's disease, and the gut-brain axis. CONCLUSIONS: In this study, we will investigate whether changes in the gut microbiome induced by physical exercise can mediate its neuroprotective effects, offering new insights into the prevention and treatment of Alzheimer's disease. By integrating findings from neuroimaging studies, clinical trials, and microbiome research, this review will highlight potential mechanisms. It will also identify key gaps in the literature. This will pave the way for future research directions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".