Characterising the muscle anabolic potential of dairy, meat and plant-based protein sources in older adults
Bibliographic record
Abstract
The age-related loss of skeletal muscle mass and function is caused, at least in part, by a reduced muscle protein synthetic response to protein ingestion. The magnitude and duration of the postprandial muscle protein synthetic response to ingested protein is dependent on the quantity and quality of the protein consumed. This review characterises the anabolic properties of animal-derived and plant-based dietary protein sources in older adults. While approximately 60 % of dietary protein consumed worldwide is derived from plant sources, plant-based proteins generally exhibit lower digestibility, lower leucine content and deficiencies in certain essential amino acids such as lysine and methionine, which compromise the availability of a complete amino acid profile required for muscle protein synthesis. Based on currently available scientific evidence, animal-derived proteins may be considered more anabolic than plant-based protein sources. However, the production and consumption of animal-derived protein sources is associated with higher greenhouse gas emissions, while plant-based protein sources may be considered more environmentally sustainable. Theoretically, the lower anabolic capacity of plant-based proteins can be compensated for by ingesting a greater dose of protein or by combining various plant-based proteins to provide a more favourable amino acid profile. In addition, leucine co-ingestion can further augment the postprandial muscle protein synthetic response. Finally, prior exercise or n-3 fatty acid supplementation have been shown to sensitise skeletal muscle to the anabolic properties of dietary protein. Applying one or more of these strategies may support the maintenance of muscle mass with ageing when diets rich in plant-based protein are consumed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".