Nutrient-dense protein as a primary dietary strategy in healthy ageing: please sir, may we have more?
Bibliographic record
Abstract
A progressive decrement in muscle mass and muscle function, sarcopoenia, accompanies ageing. The loss of skeletal muscle mass and function is the main feature of sarcopoenia. Preventing the loss of muscle mass is relevant since sarcopoenia can have a significant impact on mobility and the quality of life of older people. Dietary protein and physical activity have an essential role in slowing muscle mass loss and helping to maintain muscle function. However, the current recommendations for daily protein ingestion for older persons appear to be too low and are in need of adjustment. In this review, we discuss the skeletal muscle response to protein ingestion, and review the data examining current dietary protein recommendations in the older subjects. Furthermore, we review the concept of protein quality and the important role that nutrient-dense protein (NDP) sources play in meeting overall nutrient requirements and improving dietary quality. Overall, the current evidence endorses an increase in the daily ingestion of protein with emphasis on the ingestion of NDP choices by older 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".