Effects of exercise on markers of oxidative stress: an Ancillary analysis of the Alberta Physical Activity and Breast Cancer Prevention Trial
Bibliographic record
Abstract
BACKGROUND: Oxidative stress may contribute to cancer aetiology through several mechanisms involving damage to DNA, proteins and lipids leading to genetic mutations and genomic instability. The objective of this study was to determine the effects of aerobic exercise on markers of oxidative damage and antioxidant enzymes in postmenopausal women. METHODS: The Alberta Physical Activity and Breast Cancer Prevention Trial (ALPHA) was a two-centre, two-armed randomised trial of 320 inactive, healthy, postmenopausal women aged 50-74 years. Participants were randomly assigned to a year-long exercise intervention (225 min/week) or a control group while being asked to maintain a normal diet. Fasting blood samples were obtained and plasma concentrations of two oxidative damage markers (8-hydroxy-2'-deoxyguanosine (8-OHdG) and 8-isoprostaglandin F2α (8-Iso-PGF2α)) and two antioxidant enzymes (superoxide dismutase and catalase) were measured at baseline, 6 months and 12 months. Intention-to-treat (ITT) and per-protocol analyses were performed using linear mixed models adjusted for baseline biomarker concentrations. A further exercise adherence analysis, based on mean minutes of exercise per week, was also performed. RESULTS: In the ITT and per-protocol analyses, the exercise intervention did not have any statistically significant effect on either oxidative damage biomarkers or antioxidant enzyme activity. CONCLUSIONS: A year-long aerobic exercise intervention did not have a significant impact on oxidative stress in healthy, postmenopausal women. TRIAL REGISTRATION NUMBER: NCT00522262.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".