Comparable amino acid & intramuscular signalling responses following consumption of a novel microflora compared to whey protein post-resistance exercise in young adults
Bibliographic record
Abstract
There is growing interest in alternative protein sources to reduce the intake of animal foods, although the quality of non-animal-based proteins has been questioned. In a double-blind, crossover, randomised and counter-balanced trial, we investigated the anabolic potential of a microflora (bacterial) protein designed to mimic ‘high-quality' whey protein. Twelve, physically-active young adults (sex: M = 6, F = 6; age: 21.1 ± 3.0 years; body fat: 21.1 ± 7.3%; fasting glucose: 4.3 ± 0.4 mmol L −1 ) consumed 0.3 g kg −1 (of body mass) of either whey protein (WHEY; dose: 27.7 ± 7.5 g) or microflora protein (MIC; dose: 29.8 ± 7.3 g) concentrate in an overnight postabsorptive state immediately following single-leg resistance exercise (∼80% of 1 repetition maximum). The amino acid (AA) composition of protein supplements was analysed by mass spectrometry. Postprandial plasma AA concentrations (0–4 h, by liquid chromatography mass spectrometry) and intramuscular signalling responses (1 h postprandial, by Western Blot) to exercise were determined. Diet and physical activity were monitored prior to each experimental visit and replicated in a cross-over fashion. A comparable pattern of AA composition was observed between sources. Postprandial plasma AA, glucose and insulin concentrations and intramuscular signalling responses (i.e., p-mTOR, p-4E-BP1, p-Akt, p-RPS6) were largely not different between WHEY and MIC (p > 0.05) with the exception of leucine whereby significantly higher plasma concentrations were observed with MIC across the postprandial period (p = 0.024). Therefore, MIC may represent a viable alternative protein source of comparable quality to traditional whey protein that may support skeletal muscle remodelling in young healthy adults.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".