Serum levels of non-enzymatic antioxidants in female dementia patients with respect to the degree of cognitive impairment
Bibliographic record
Abstract
The aim of this study was to investigate the correlation between the severity of cognitive impairment in Alzheimer’s disease (AD) and vascular dementia (VD) and the serum antioxidant status of uric acid (UA), albumin (ALB) and bilirubin (BIL) in female patients. The cross-sectional study included 90 subjects, aged ≥65, divided into three groups: 30 patients with AD, 30 patients with VD and 30 control subjects. For cognitive assessment, all participants underwent the Montreal Cognitive Assessment (MoCA). Serum concentrations of ALB, UA and BIL were determined spectrophotometrically. The AD patients had a significant decrease of UA and increase of serum BIL. Upon stratification according to the degree of cognitive impairment, lower UA concentrations were found in patients with severe cognitive impairment, whereas increased BIL was found in patients with moderate cognitive impairment. Patients with VD were characterized by hypoalbuminemia and upon stratification this finding was evident among patients with severe cognitive impairment. The MoCA score correlated positively with BIL in AD patients. The obtained data supports the protective role of serum antioxidants in the pathogenesis of dementia. Further on, we suggest further longitudinal research to confirm the combined use of these parameters as potential biomarkers in AD and VD.
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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 | 0.000 |
| 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".