Life Experience Matters: Enrichment and Stress Can Influence the Likelihood of Developing Alzheimer’s Disease via Gut Microbiome
Bibliographic record
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease, characterized by the presence of β-amyloid (Aβ) plaques and neurofibrillary tangles (NFTs) formed from abnormally phosphorylated tau proteins (ptau). To date, there is no cure for AD. Earlier therapeutic efforts have focused on the clinical stages of AD. Despite paramount efforts and costs, pharmaceutical interventions including antibody therapies targeting Aβ have largely failed. This highlights the need to alternate treatment strategies and a shift of focus to early pre-clinical stages. Approximately 25-40% of AD cases can be attributed to environmental factors including chronic stress. Gut dysbiosis has been associated with stress and the pathogenesis of AD and can increase both Aβ and NFTs in animal models of the disease. Both stress and enrichment have been shown to alter AD progression and gut health. Targeting stress-induced gut dysbiosis through probiotic supplementation could provide a promising intervention to delay disease progression. In this review, we discuss the effects of stress, enrichment, and gut dysbiosis in AD models and the promising evidence from probiotic intervention studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".