Twelve weeks’ progressive resistance training combined with protein supplementation beyond habitual intakes increases upper leg lean tissue mass, muscle strength and extended gait speed in healthy older women
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
Abstract The age-related decline in functional capability is preceded by a reduction in muscle quality. The purpose of this study was to assess the combined effects of progressive resistance training (PRT) and protein supplementation beyond habitual intakes on upper leg lean tissue mass (LTM), muscle quality and functional capability in healthy 50–70 years women. In a single-blinded, randomized, controlled design, 57 healthy older women (age 61.1 ± 5.1 years, 1.61 ± 0.65 m, 65.3 ± 15.3 kg) consumed 0.33 g/kg body mass of a milk-based protein matrix (PRO) for 12 weeks. Of the 57 women, 29 also engaged in a PRT intervention (PRO + PRT). In comparison to the PRO group (n = 28), those in the PRO + PRT group had an increase in upper leg LTM [0.04 (95% CI −0.07 to 0.01) kg vs. 0.13 (95% CI 0.08–0.18) kg, P = 0.027], as measured by Dual-energy X-ray absorptiometry; an increase in knee extensor (KE) torque [−1.6 (95% CI −7.3 to 4.4 N m) vs. 10.2 (95% CI 4.3–15.8 N m), P = 0.007], as measured from a maximal voluntary isometric contraction (Con-Trex MJ; CMV AG); and an increase in extended gait speed [-0.01 (95% CI −0.52–0.04) m s −1 vs. 0.10 (95% CI 0.05–0.22) m s −1 , P = 0.001] as measured from a maximal 900 m effort. There was no difference between groups in the time taken to complete 5 chair rises or the number of chair rises performed in 30 s ( P > 0.05). PRT in healthy older women ingesting a dietary protein supplement is an effective strategy to improve upper leg LTM, KE torque and extended gait speed in healthy older women.
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) | 0.000 | 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 | 0.000 | 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