The impact of post-exercise protein-leucine ingestion on subsequent performance and the systematic, metabolic and skeletal muscle molecular responses associated with recovery and regeneration : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy (Health), Massey University
Bibliographic record
Abstract
The objective was to determine the effect of post-exercise protein-leucine coingestion with carbohydrate and fat on subsequent endurance performance and investigate whole-body and skeletal-muscle responses hypothesised to guide adaptive-regeneration. Methods. Study-JA Twelve trained-men ingested protein/leucine/carbohydrate/fat (20/7.5/89/22 g· h- 1 ) or carbohydrate/fat (control, 119/22 g· h- 1 ) supplements after intense cycling over six days. Glucose and leucine turnover, metabolomics, nitrogen balance and performance were examined. Study-] B Immune-function responses to supplementation were investigated via neutrophil 0 2- production, differential immune-cell count, hormones and cytokines. Study-2A Twelve trained-men ingested low-dose protein/leucine/carbohydrate/fat (23 .3/51180/30 g), high-dose (70115/180/30 g) or carbohydrate/fat control (274/30 g) beverages following 100- min of intense cycling. Vastus lateralis biopsies were taken during recovery (30-min/4-h) to determine the effect of dose on myofibrillar protein synthesis (FSR), and mTOR-pathway activity infened by western blot. Study-2B The transcriptome was intenogated to determine acute-phase biology differentially affected by protein-leucine dose. Results. Protein-leucine increased day-1 recovery leucine oxidation and synthesis, plasma and urinary branch-chain amino acids (BCAAs), products of their metabolism, and neutrophil-priming plasma metabolites versus control. Protein-leucine lowered serum creatine kinase 21-25% (±90% confidence limits 14%) and day 2-5 nitrogen balance was positive for both conditions, yet the impact on sprint power was trivial. Protein-leucine reduced day-1 neutrophil 02- production (15-17 ±20 mmol·02-·celr1 ) but on day-6 increased post-exercise production (33 ±20 mmol·02-·celr1 ) having lowered pre-exercise cortisol (21% ±15%). The increase in FSR with high-dose (0.103%· h-1 ± 0.027%· h-1 ) versus low-dose (0.092%· h-1 ± 0.017%· h-1 ) was likely equivalent. High-dose increased serum insulin (1.44-fold x/+90% confidence limits 1.18), 30- min phosphorylation ofmTOR (2.21-fold x/+1.59) and p70S6K (3.51-fold x/+1.93), and ii 240-min phosphorylation of rpS6 ( 4.85-fold x/-d .37) and 4E-BP1-a (1.99-fold x/-d .63) versus low-dose. Bioinformatics revealed a biphasic dose-responsive inflammatory transcriptome centred on interleukin (IL)-1~ at 30-min (high-dose) and IL6 at 240-min (highdose, low-dose) consistent with regulation of early-phase myeloid-cell associated muscle regeneration. Conclusions. Protein-leucine effects on performance during intense training may be inconsequential when in positive nitrogen balance, despite saturating BCAA metabolism, protein synthesis, and attenuating cell-membrane damage. 24 g of protein and 5 g leucine near saturated post-exercise myofibrillar FSR and simulated an early inflammatory promyogenic transcriptome common to skeletal muscle regeneration that was accentuated with 3-fold higher protein-leucine dose.
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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) | 0.004 | 0.001 |
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".