Associations of Serum Liver Function with Cerebral Blood Flow in Patients with Alzheimer’s Disease
Bibliographic record
Abstract
Background: Increasing evidence suggests that both amyloid-β metabolism disorders in the liver and cerebral hypoperfusion play an important role in the pathogenesis of Alzheimer's disease (AD). However, the relevance of liver function alterations to cerebral blood flow (CBF) of patients with AD remains unclear. Objective: We aimed to investigate the associations between liver function changes and CBF of patients with AD. Methods: We recruited 17 patients with sporadic AD. In addition to physical and neurological examinations, detection of AD biomarkers in cerebrospinal fluid by enzyme-linked immunosorbent assay and CBF assessment by arterial spin labeling sequence of magnetic resonance image scans as well as measure of liver function markers in serum by routine laboratory testing were conducted. Neuropsychological tests were evaluated, including Mini-Mental State Examination and Montreal Cognitive Assessment. Linear and rank correlations were performed to test the associations of liver function alterations with regional CBF of AD. Results: We found that liver function markers, especially total protein, the ratio of albumin to globin, globin, alkaline phosphatase, and aspartate aminotransferase were significantly associated with regional CBF of AD patients. Conclusions: These findings demonstrated significant associations between perfusion in certain brain regions of AD and alterations of liver function markers, particularly proteins and liver enzymes, which might provide implications to the pathogenesis and treatment of AD.
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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 | 0.001 |
| 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".