Mitigating disuse‐induced skeletal muscle atrophy in ageing: Resistance exercise as a critical countermeasure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The gradual deterioration of physiological systems with ageing makes it difficult to maintain skeletal muscle mass (sarcopenia), at least partly due to the presence of 'anabolic resistance', resulting in muscle loss. Sarcopenia can be transiently but markedly accelerated through periods of muscle disuse-induced (i.e., unloading) atrophy due to reduced physical activity, sickness, immobilisation or hospitalisation. Periods of disuse are detrimental to older adults' overall quality of life and substantially increase their risk of falls, physical and social dependence, and early mortality. Disuse events induce skeletal muscle atrophy through various mechanisms, including anabolic resistance, inflammation, disturbed proteostasis and mitochondrial dysfunction, all of which tip the scales in favour of a negative net protein balance and subsequent muscle loss. Concerningly, recovery from disuse atrophy is more difficult for older adults than their younger counterparts. Resistance training (RT) is a potent anabolic stimulus that can robustly stimulate muscle protein synthesis and mitigate muscle losses in older adults when implemented before, during and following unloading. RT may take the form of traditional weightlifting-focused RT, bodyweight training and lower- and higher-load RT. When combined with sufficient dietary protein, RT can accelerate older adults' recovery from a disuse event, mitigate frailty and improve mobility; however, few older adults regularly participate in RT. A feasible and practical approach to improving the accessibility and acceptability of RT is through the use of resistance bands. Moving forward, RT must be prescribed to older adults to mitigate the negative consequences of disuse atrophy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it