Inflammatory Marker Changes in Postmenopausal Women after a Year-long Exercise Intervention Comparing High Versus Moderate Volumes
Bibliographic record
Abstract
This randomized dose comparison trial examined if higher exercise volume decreased inflammatory biomarkers, associated with postmenopausal breast cancer risk, more than moderate exercise volume. The Breast Cancer and Exercise Trial in Alberta was a two-center, two-armed randomized trial in 400 inactive, healthy, postmenopausal women, aged 50 to 74 years, with a body mass index of 22 to 40 kg/m(2). Participants were randomized to high (300 minutes/week) or moderate (150 minutes/week) volumes of aerobic exercise while maintaining usual diet. Fasting blood concentrations of C-reactive protein (CRP), IL6, and TNFα were measured at baseline, 6 and 12 months. Intention-to-treat (ITT) analysis was performed using linear mixed models adjusted for baseline biomarker concentrations. ITT analyses of 386 (97%) participants showed no statistically significant group differences for changes in biomarker levels at 6 and 12 months. In addition, we did not observe any modification of this effect by baseline characteristics of participants. In post hoc analyses based on self-selected exercise level (measured in minutes/week), CRP decreased by 22.45% for participants who exercised >246 minutes/week (highest quintile) and increased by 0.07% for those who exercised <110 minutes/week (lowest quintile, Ptrend = 0.04), adjusted for baseline covariates. When this analysis was restricted to include exercise time in the target heart rate zone only, statistically significant trends were observed for both CRP (P < 0.01) and IL6 (P = 0.04). Prescribing 300 minutes/week of moderate-to-vigorous aerobic exercise did not improve inflammatory markers compared with 150 minutes/week in postmenopausal women. Decreases in CRP were observed with higher self-selected exercise volume.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".