No effect of short-term 17β-estradiol supplementation in healthy men on systemic inflammatory responses to exercise
Why this work is in the frame
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Bibliographic record
Abstract
Sex-based differences in inflammatory responses to exercise may be mediated by estrogen through increased muscle membrane stability and/or inhibited cytokine production. In this study, in vivo effects of estrogen on systemic inflammation-related responses to exercise were assessed in healthy men. In a double-blind, placebo-controlled, crossover design, 11 men cycled for 90 min at 65% Vo2 max after 8 days of 17beta-estradiol supplementation (ES; 2 mg/day) or placebo (PL; glucose polymer). After a 2-wk washout, exercise was repeated after 8 days on the alternate treatment. Blood was collected pre- and postexercise to determine IL-6, soluble intercellular adhesion molecule-1 (sICAM-1), neutrophil counts, and cortisol. Preexercise serum was assayed for sex hormones. ES increased estradiol (133+/-71 to 840+/-633 pmol/l, P=0.005) and reduced testosterone (19.9+/-3.7 to 16.1+/-3.9 nmol/l, P=0.007). Exercise increased cortisol (P=0.02), IL-6 (P<0.001) and neutrophil counts (P<0.001) with no influence on sICAM-1 (P=0.34) and no effect of ES on these changes. Postexercise IL-6 and neutrophil counts were correlated (r=0.58, P=0.005); postexercise IL-6 and cortisol (r=0.18, P=0.43) and postexercise cortisol and neutrophil counts (r=0.06, P=0.78) were not. Postexercise sICAM-1 was not correlated with the above variables (P>or=0.79). In conclusion, 8 days of ES in healthy men did not influence systemic inflammation-related responses to acute exercise. Future studies should investigate 17beta-estradiol effects on IL-6 production and neutrophil infiltration within skeletal muscle during and after exercise.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it