Alterations in human muscle protein metabolism with aging: Protein and exercise as countermeasures to offset sarcopenia
Bibliographic record
Abstract
Aging is associated with a reduction in skeletal muscle mass-sarcopenia-the etiology of which is multifactorial. One mechanism is that aging has, as one of its hallmarks, a reduced sensitivity of skeletal muscle to the normally potent anabolic effects of protein feeding and resistance exercise, and to the anticatabolic effects of insulin, the combination of which has been termed "anabolic resistance." However, this reduced sensitivity of skeletal muscle to anabolic stimuli may, in some cases, be overcome by providing a greater quantity of the nutrition and/or exercise stimulus. Daily habitual physical activity appears to be a primary determinant of anabolic resistance as we have recently shown that as little as 14 days of reduced ambulatory activity was sufficient to induce anabolic resistance in the elderly by attenuating the postprandial increase in muscle protein synthesis (MPS). The etiology of anabolic resistance is complex and may include alterations in amino acid uptake/utilization, cell signaling status, muscle blood flow, and microvascular perfusion (impacting amino acid delivery and availability). Further, there appears to be sexual dimorphism with advancing age in the response of MPS to amino acid/insulin provision. Maintenance of physical activity during aging is of fundamental importance for skeletal muscle to allow it to appropriately respond to the anabolic effects of nutrition.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".