Season of Birth and Vulnerability to the Pathology of Alzheimer’s Disease: an in Vivo Positron Emission Tomography Study
Bibliographic record
Abstract
Abstract This study used positron emission tomography to examine whether the seasonal birth effect as an exogenic indicator of early life environmental factors influenced vulnerability to Alzheimer’s disease (AD) pathology in the elderly. We analyzed datasets from the Alzheimer’s Disease Neuroimaging Initiative, which included the data for 234 cognitively normal individuals and patients with mild cognitive impairment (n = 115) and AD dementia (n = 38). As an index of amyloid β (Aβ)/tau accumulation, the AV-45/AV-1451-standardized uptake value ratios (SUVRs) were compared between groups of spring-to-summer births and fall-to-winter births by analysis of covariance. Seasonal birth difference was a good predictor of AV-1451 SUVR. We found that participants with a fall-to-winter birth showed lower AV-1451 SUVRs than those with a spring-to-summer birth, after accounting for the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS) score and other factors that could possibly affect tau accumulation. Our findings showed a vulnerability to tau pathology in participants with a fall-to-winter birth, which may be caused by perinatal or postnatal brain damage due to the risk factors associated with the cold season.
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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 | 0.002 |
| 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) | 0.001 | 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".