Brain Function Is Linked to <scp>LDL</scp> Cholesterol in Older Adults with Cardiovascular Risk
Bibliographic record
Abstract
OBJECTIVES: To determine how cardiovascular risk is associated with working memory task performance and task-related suppression of default-mode network (DMN) activity in cognitively intact older adults. DESIGN: A cross-sectional functional magnetic resonance imaging study of older adults with cardiovascular risk factors. SETTING: Rotman Research Institute, Baycrest Health Sciences. PARTICIPANTS: Thirty older adults with cardiovascular risk factors. MEASUREMENTS: Participants provided health information and a blood sample, and underwent functional magnetic resonance imaging during a working memory task and during a breath-hold task to assess cerebrovascular reactivity. RESULTS: Higher plasma low-density lipoprotein cholesterol (LDL-C) was associated with poorer working memory task performance (P = 0.008) and reduced task-related DMN suppression (P = 0.005). A composite index of cardiovascular risk, the Framingham General Cardiovascular Risk Profile, showed no associations with task performance or task-related DMN suppression. These findings were independent of white matter burden and cerebrovascular reactivity and thus cannot be accounted for by individual differences in neurovascular health. CONCLUSION: These findings suggest a deleterious effect of elevated LDL-C on working memory task performance and task-related DMN suppression in older adults with cardiovascular risk. The relations between the Framingham General Cardiovascular Risk Profile, cognitive task performance, and DMN function require further study.
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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 | 0.000 | 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".