Impact of smoking on neurodegeneration and cerebrovascular disease markers in cognitively normal men
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Smoking is a major risk factor for cognitive decline and dementia. However, the exact pathobiology of smoking remains unknown. The effects of smoking on cortical thickness as a biomarker of neurodegeneration or white matter hyperintensities and lacunes as biomarkers of cerebrovascular burden were concurrently evaluated. METHODS: Our study included 977 cognitively normal men who visited a health promotion centre and underwent medical check-ups, including 3.0 T magnetic resonance imaging. Participants were categorized into never smoker, past smoker or current smoker groups and pack-years and the years of smoking cessation were used as continuous variables. RESULTS: The current smoker group exhibited cortical thinning in frontal and temporo-parietal regions compared with the never smoker group. These effects were particularly prominent in smokers with a high cumulative exposure to smoking in the current smoker group. However, there was no association between smoking and the severity of white matter hyperintensity or number of lacunes. CONCLUSION: Our findings indicate that smoking might impact on neurodegeneration rather than cerebrovascular burdens in cognitively normal men, suggesting that smoking might be an important modifiable risk factor for the development of Alzheimer's disease.
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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 | 0.001 | 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 | 0.000 |
| 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".