The impact of exercise on growth factors (VEGF and FGF2): results from a 12-month randomized intervention trial
Bibliographic record
Abstract
BACKGROUND: Vascular endothelial growth factor (VEGF) and Fibroblast growth factor-2 (FGF2) are angiogenic cytokines in normal tissues and tumors. Evidence suggests that increased growth factor expression in adipose tissue leads to improved vascularity and decreased hypoxia, fibrosis, and inflammation, which may, in turn, reduce post-menopausal breast cancer risk. OBJECTIVE: We investigated whether or not exercise had dose-response effects on levels of plasma VEGF and FGF2 in postmenopausal women. METHODS: Four hundred previously inactive but healthy postmenopausal women aged 50-74 years of age were randomized to 150 or 300 min per week of aerobic exercise in a year-long exercise intervention. VEGF and FGF2 were measured from fasting serum samples with a custom-plex multiplex assay. RESULTS: A high compared to moderate volume of aerobic exercise did not cause chronic changes in plasma VEGF or FGF2 levels in intention-to-treat or per-protocol analyses. CONCLUSIONS: We did not detect differences in growth factor levels related to increasing doses of exercise. It is unlikely that changes in VEGF and FGF2 levels mediate the reduction in risk of post-menopausal breast cancer development in associated with increased levels of exercise. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT01435005.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".