Biomarkers of Oxidative Stress in Vascular Dementia Patients
Bibliographic record
Abstract
OBJECTIVE: Little is known about the role of oxidative stress in the pathogenesis of vascular dementia (VaD). The aim of this study was to investigate the biomarkers of oxidative stress in urine, as reflected by 8-hydroxydeoxyguanosine (8-OHdG), 8-isoprostaglandin F(2a) (8-isoPGF(2a)) and nitrotyrosine (NT) levels, in a group of well characterized VaD patients and in two control groups of Vascular Not Demented (VaND) patients and health y subjects. METHODS: Ninety-six subjects from the Tianjin municipality in China were recruited. Forty-six patients were in the VaD group, 24 patients with VaND and 26 persons with no signs of cognitive disorder were employed as control groups. Urinary 8-OHdG and 8-isoPGF(2a) was performed using enzyme-linked immunosorbent assay (ELISA), and urinary NT levels were measured by chemiluminescence detection. RESULTS: Significantly higher urinary 8-OHdG levels were detected in VaD patients compared to VaND patients and healthy control subjects. In contrast, urinary 8-isoPGF(2a) levels were significantly lower in VaD patients compared with two control groups. For NT levels, no statistically significant differences were observed among the three groups. CONCLUSION: Increased urinary 8-OHdG level was a potential marker of oxidative stress in VaD patients. Furthermore, it is also important to take into account potential confounders in order to improve the identification of changes in the status of oxidative stress as related to VaD.
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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".