Carotid Atherosclerosis Associated with Tau Pathology and Cognitive Function in Cognitively Intact Adults: The Chinese Alzheimer's Biomarker and Lifestyle (CABLE) Study
Bibliographic record
Abstract
Background: Carotid atherosclerosis has been implicated in cognitive decline, but the evidence from current studies is insufficient and the detailed mechanism remains unclear. Objective: This study aimed to explore the association of carotid atherosclerosis with cognitive function and Cerebrospinal Fluid (CSF) Alzheimer's Disease (AD) biomarkers, as well as attempted to investigate the underlying mechanisms. Methods: This study included 365 participants with objective normal cognition from the Chinese Alzheimer’s Biomarker and Lifestyle (CABLE) database. Multiple linear regression models were utilized to assess the associations of carotid atherosclerosis Carotid Intima-Media Roughness (CIMR), Carotid Intima-Media Thickness (CIMT), carotid plaque and CIMT level with CSF AD biomarkers and cognitive function. The mediation analyses were used to explore whether CSF AD biomarkers mediated the carotid atherosclerosis and cognitive function. Result: We found that CIMR, carotid plaque and CIMT level were significantly associated with tau pathology (T-tau (Total Tau) and P-tau (Phosphorylated Tau), p<0.05); all markers of carotid atherosclerosis were associated with cognitive function (CM-MMSE (China-Modied Mini-Mental State Examination) and MoCA (Montreal Cognitive Assessment), p<0.05). Furthermore, mediation analyses revealed that the effect of carotid plaque on cognitive decline was partially mediated by tau pathology (proportion of mediation=19.7%, p=0.012). Conclusion: This study indicated that carotid atherosclerosis was associated with tau pathology and cognitive function and tau pathology partially mediated the association between carotid atherosclerosis and cognitive function. Keywords : Alzheimer's disease; Biomarkers; Carotid atherosclerosis; Cerebrospinal fluid; Cognitive function
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".