Muscle Protein Synthesis in Response to Plant-Based Protein Isolates With and Without Added Leucine Versus Whey Protein in Young Men and Women
Bibliographic record
Abstract
Background Plant-based protein supplements often contain lower amounts of leucine and other essential amino acids (EAAs), potentially making them less effective in stimulating muscle protein synthesis (MPS) than animal-based proteins. Combining plant proteins could improve the EAA profile and more effectively support MPS. Objectives The aim of this study was to determine the effect of a novel plant-based blend protein (PBP), PBP with added leucine (PBP + Leu) to levels equivalent to whey protein isolate (WHEY) on aminoacidemia and MPS responses in young men and women. We hypothesized that PBP + Leu would stimulate MPS equivalent to WHEY, and both would be greater than PBP. Methods We employed a randomized, double-blind, crossover study consisting of 3 separate study visits to compare PBP, PBP + Leu, and WHEY. To measure MPS response to ingestion of the supplements, a primed continuous infusion of L-[ring 13 C 6 ] phenylalanine was administered for 8 h at each study visit. Skeletal muscle tissue and blood samples were collected to measure aminoacidemia and MPS. Results All protein supplements increased mixed MPS above postabsorptive levels ( P < 0.001). However, MPS increase following ingestion of PBP was less than that following ingestion of PBP + Leu ( P = 0.002) and WHEY ( P = 0.046). There were no differences in MPS between PBP + Leu and WHEY ( P = 0.052). Conclusions Consumption of PBP isolate with added leucine stimulated MPS to a similar extent as whey protein in young men and women. PBPs containing higher leucine content promote anabolism to a similar extent as animal-based proteins. This study was registered at clinicaltrials.gov as NCT05139160.
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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 | 0.001 |
| 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".