Essential Amino Acid Ingestion Facilitates Leucine Retention and Attenuates Myofibrillar Protein Breakdown following Bodyweight Resistance Exercise in Young Adults in a Home-Based Setting
Bibliographic record
Abstract
Home-based resistance exercise (RE) has become increasingly prevalent, but its effects on protein metabolism are understudied. We tested the effect of an essential amino acid formulation (EAA+: 9 g EAAs, 3 g leucine) and branched-chain amino acids (BCAAs: 6 g BCAAs, 3 g leucine), relative to a carbohydrate (CHO) placebo, on exogenous leucine retention and myofibrillar protein breakdown following dynamic bodyweight RE in a home-based setting. Twelve recreationally active adults (nine male, three female) participated in a double-blind, placebo-controlled, crossover study with four trial conditions: (i) RE and EAA+ (EX-EAA+); (ii) RE and BCAAs (EX-BCAA); (iii) RE and CHO placebo (EX-CHO); and (iv) rest and CHO placebo (REST-CHO). Total exogenous leucine oxidation and retention (estimates of whole-body anabolism) and urinary 3-methylhistidine:creatinine ratio (3MH:Cr; estimate of muscle catabolism) were assessed over 5 h post-supplement. Total exogenous leucine oxidation and retention in EX-EAA+ and EX-BCAA did not significantly differ (p = 0.116) but were greater than EX-CHO (p < 0.01). There was a main effect of condition on urinary 3MH:Cr (p = 0.034), with post hoc analysis revealing a trend (p = 0.096) for reduced urinary 3MH:Cr with EX-EAA+ (32%) compared to EX-CHO. By direct comparison, urinary 3MH:Cr was significantly lower (23%) in EX-EAA+ than EX-BCAA (p = 0.026). In summary, the ingestion of EAA+ or BCAA provided leucine that was ~60% retained for protein synthesis following home-based bodyweight RE, but EAA+ most effectively attenuated myofibrillar protein breakdown.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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".