Role of a Urinary Biomarker in the Common Mechanism of Physical Performance and Cognitive Function
Bibliographic record
Abstract
INTRODUCTION: Healthy aging is described as a process of developing and maintaining intrinsic abilities, including physical and cognitive functions. Although oxidative stress is a common mechanism shared by loss of muscle strength and dementia, its relationship with decreased physical performance and cognitive impairment remains unclear. We aimed to investigate the role of urinary 8-oxo-7, 8-dihydroguanosine (8-oxoGsn), a biomarker of oxidative damage to RNA, in physical and cognitive decline. METHODS: The study followed a cross-sectional design and recruited 40-94-year-old inhabitants of Beijing, China (471 men and 881 women). The physical performance of the participants was assessed using handgrip strength, walking speed, and the repeated chair stand test. The cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) 5-min protocol. Urinary 8-oxoGsn levels were measured for all participants. RESULTS: Participants with high urinary 8-oxoGsn levels were more likely to have low grip strength, slow walking speed, poor performance in the repeated chair stand test, and low scores on the MoCA 5-min protocol (odds ratio [OR] 3.43, 95% confidence interval [CI]: 1.52-7.76; OR 1.71, 95% CI: 1.16-2.53; OR 2.06, 95% CI: 0.92-4.63; OR 1.75, 95% CI: 1.18-2.58), after adjusting for age, sex, smoking habits, alcohol consumption, hypertension, diabetes, cerebro-cardiovascular disease, and chronic kidney disease. CONCLUSION: Elevated levels of oxidative stress are independently associated with cognitive and physical impairment. Thus, these results can help in the early identification and development of strategies for the prevention and treatment of intrinsic capacity decline.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".