Glutathione Peroxidase Activity Is Altered in Vascular Cognitive Impairment-No Dementia and Is a Potential Marker for Verbal Memory Performance
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease (CAD) increases risk for vascular cognitive impairment-no dementia (VCIND), a precursor to dementia, potentially through persistent oxidative stress. OBJECTIVE: This study assessed peripheral glutathione peroxidase activity (GPX), which is protective against oxidative stress, in VCIND versus cognitively normal CAD controls (CN). GPX activity was also evaluated as a biomarker of cognition, particularly verbal memory. METHODS: 120 CAD patients with VCIND (1SD below norms on executive function or verbal memory (VM)) or without (CN) participated in exercise rehabilitation for 24 weeks. Neurocognitive and cardiopulmonary fitness (VO2peak) assessments and plasma were collected at baseline and 24-weeks. RESULTS: GPX was higher in VCIND compared to CN (F1,119 = 3.996, p = 0.048). Higher GPX was associated with poorer baseline VM (β= -0.182, p = 0.048), and longitudinally with VM decline controlling for sex, body mass index, VO2peak, and education (b[SE] = -0.02[0.01], p = 0.004). Only CN participants showed improved VM performance with increased fitness (b[SE] = 1.30[0.15], p < 0.005). CONCLUSION: GPX was elevated in VCIND consistent with a compensatory response to persistent oxidative stress. Increased GPX predicted poorer cognitive outcomes (verbal memory) in VCIND patients despite improved fitness.
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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 | 0.000 | 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".