Post‐Exercise Consumption of Whole Eggs or Egg Whites Improves Whole Body Leucine Balance but Does Not Differentially Modulate Leucine Kinetics in Resistance‐Trained Young Men
Bibliographic record
Abstract
The consumption of isolated proteins and/or crystalline amino acids enhances the anabolic effect of resistance exercise during recovery. However, the effect of consuming dietary amino acids within their natural nutrient‐dense food matrix to support whole body recovery from resistance exercise has received little attention. Therefore, we determined the effects of whole egg versus egg white ingestion on whole body leucine metabolism in resistance‐trained young males. In crossover trials, six resistance‐trained men (21±1 y; 90±5 kg) received primed constant L‐[1‐ 13 C]leucine infusions with repeated breath and blood samples collected before and 5 h after resistance exercise to determine whole body leucine endogenous rate of appearance (Endo Ra; estimate of protein breakdown), oxidation (OX), non‐oxidative leucine disposal (NOLD; estimate of protein synthesis) and net balance (NB). Immediately after resistance exercise, participants ingested intrinsically L‐[5,5,5‐ 2 H 3 ]leucine labeled whole eggs (18 g protein, 17 g fat; 1.6 g leucine) or egg whites (18 g protein, 0 g fat; 1.6 g leucine) in scrambled form. Endo Ra declined (P<0.001) from fasting values after whole egg (15±1%) and egg white (22±3%) ingestion with no difference between conditions ( P= 0.14). Similarly, OX decreased over the 5 h period after whole egg and egg white ingestion ( P< 0.001) with no differences between conditions (P =0.62). NOLD tended to increase ( P =0.08) after ingestion of whole egg (10±2%) and egg white (6±3%) with no differences between conditions ( P =0.17). As such, NB was negative before exercise but improved similarly (P<0.001) after whole egg (97±6%) and egg white (102±9%) ingestion ( P= 0.36). In summary, there was a similar increase in whole body NB after the ingestion of whole eggs and egg whites, which was primarily modulated by changes in postprandial whole body protein breakdown rather than protein synthesis during post‐exercise recovery. These data demonstrate that consuming high‐quality protein within a complete food matrix is an effective nutritional strategy to improve whole body net protein balance after resistance exercise in trained young men. Support or Funding Information Vision 20/20 Grant, Division of Nutritional Sciences, University of Illinois at Urbana ‐ Champaign
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".