Multimodal neuroimaging study of cerebrovascular disease, amyloid deposition, and neurodegeneration in Alzheimer's disease progression
Bibliographic record
Abstract
INTRODUCTION: Cerebrovascular disease (CVD) is not currently considered a core pathological feature of Alzheimer's disease (AD), but mounting evidence suggests that concurrent CVD may exacerbate AD progression. The purpose of this study was first to examine the relationship among amyloid, CVD, and neurodegeneration and second to examine the extent to which amyloid and CVD pathology drive subsequent neurodegeneration over time. METHODS: Six hundred eight (224 normal controls, 291 mild cognitive impairment, 93 AD) subjects from the Alzheimer's Disease Neuroimaging Initiative with longitudinal AV45 positron emission tomography imaging and MR imaging were investigated. RESULTS: Amyloid and white matter hyperintensity (WMH) burden increased across clinical diagnosis groups (normal control < mild cognitive impairment < AD). Amyloid pathology and WMH volume were related to lower cortical thickness, while WMH burden was associated with neurodegenerative/atrophic changes over time in key AD-related brain regions. DISCUSSION: CVD and AD may be etiologically independent, but our findings suggest that CVD should be considered explicitly for its effect on AD progression.
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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 | 0.001 | 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".