An Investigation of Cerebral Vascular Functional Properties in Middle‐to‐Old Age Community People With High Vascular Risk Profiles
Bibliographic record
Abstract
Background Vascular degeneration is an important cause of brain damage in aging. Assessing the functional properties of the cerebral vascular system may aid early diagnosis and prevention. Purpose To investigate the relationships between potential vascular functional markers and vascular risks, brain parenchymal damage, and cognition. Study Type Retrospective. Subjects Two hundred two general community subjects (42–80 years, males/females: 127/75). Field Strength/Sequence 3 T, spin echo T1W/T2W/FLAIR, resting‐state functional MRI with an echo‐planar sequence (rsfMRI), pseudo‐continuous arterial spin labeling (pCASL) with a three‐dimensional gradient‐spin echo sequence. Assessment Cerebral blood flow (CBF) in gray matter calculated using pCASL, blood transit times calculated using rsfMRI, and the SD of internal carotid arteries signal (ICAstd) calculated using rsfMRI; visual assessment for lacunes; quantification of white matter hyperintensity volume; permutation test for quality control; collection of demographic and clinical data, Montreal Cognitive Assessment, Mini‐Mental State Examination. Statistical Tests Kolmogorov–Smirnov test; Spearman rank correlation analysis; Multivariable linear regression analysis controlling for covariates; The level of statistical significance was set at P < 0.05. Results Age was negatively associated with ICAstd (β = −0.180). Diabetes was associated with longer blood transit time from large arteries to capillary bed (β = 0.185, adjusted for age, sex, and intracranial volume). Larger ICAstd was associated with less presence of lacunes (odds ratio: 0.418, adjusted for age and sex). Higher gray matter CBF (β = 0.154) and larger ICAstd (β = 0.136) were associated with better MoCA scores (adjusted for age, sex, and education). Data Conclusion Prolonged blood transit time, decreased ICAstd, and diminished CBF were associated with vascular dysfunction and cognitive impairment. They may serve as vascular functional markers in future studies. Evidence Level 3 Technical Efficacy Stage 3
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".