Estrogen Supplementation Reduces Leucine Oxidation at Rest and During Moderate Intensity Endurance Exercise in Men
Bibliographic record
Abstract
1370 Healthy active men exhibit higher rates of leucine oxidation as compared with their female counterparts both at rest and during moderate intensity endurance exercise. We postulated that this reduced dependence on amino acids as a fuel source in women was due to the female sex hormone estrogen (ES). PURPOSE: To investigate the effect of supplementing recreationally active men with ES on leucine oxidation at rest and during moderate intensity endurance exercise. METHODS: In a randomized, doubleblind, cross-over design, we measured leucine oxidation in eleven men after eight days of either ES supplementation (2 mg 17β-estradiol/day) or placebo (PL, polycose) prior to and during 90 min of cycling at an intensity of 65% VO2max. Following a two-week washout period, they repeated the test after eight days on the alternate treatment. On the test day, following a primed continuous infusion of L-[13C]leucine, VCO2 and steady state breath 13CO2 and plasma [13C]α-KIC enrichments were measured at rest and 60, 75 and 90 min during exercise in the postabsorptive state. RESULTS: ES supplementation significantly decreased leucine oxidation, whereas exercise increased it 2.3 fold (see table). CONCLUSION: We conclude that estrogen influences fuel source selection at rest and during endurance exercise in recreationally active men characterized by a reduced dependence on amino acids as a fuel source. (This research was funded by Hamilton Health Sciences Corporation, NSERC and National Institute of Nutrition).Table: No Caption available.Data are leucine oxidation in μmol/kg/h (mean ± SEM, n = 11). Two-way repeated measures ANOVA; * main effect of estrogen, P = 0.019; † main effect of exercise, P < 0.0001.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".