White matter integrity changes in mild cognitive impairment associated with Aspirin use
Bibliographic record
Abstract
Objectives: Alzheimer's disease (AD) represents a significant public health challenge, particularly as its prevalence is projected to rise sharply. Aspirin, known for its anti-inflammatory and antiplatelet properties, has been hypothesized to affect AD progression, although findings from observational studies and clinical trials remain inconsistent.Methods: This study utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to investigate the potential association between aspirin use and white matter (WM) microstructural changes in a cohort of 148 mild cognitive impairment (MCI) subjects. Diffusion tensor imaging (DTI) was employed to assess WM integrity, with fractional anisotropy (FA) and diffusivity metrics serving as primary outcomes. Statistical analyses were conducted using ANCOVA, adjusting for age, sex, APOE ε4 genotype, and MMSE score.Results: Aspirin users exhibited significantly higher FA values in the anterior corona radiata and left external capsule, alongside lower axial and radial diffusivity values in the right cingulum, indicating better-preserved WM microstructure compared to non-users.Conclusion: These findings suggest that aspirin may confer neuroprotective effects on WM in early AD, potentially delaying cognitive decline. Further research is warranted to confirm these results and explore the underlying mechanisms. Aspirin is widely prescribed to millions of adults, yet its impact on WM regions in the brain remains largely unclear. Further research is necessary to replicate these findings and to assess whether the effects of aspirin on WM structure could contribute to delaying or preventing cognitive decline.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".