Ingestion of low‐dose ibuprofen following resistance exercise in postmenopausal women
Bibliographic record
Abstract
BACKGROUND: Postmenopausal women typically experience accelerated muscle loss which has a negative effect on strength. The maximum daily recommended dosage of ibuprofen (1,200 mg) following resistance exercise has been shown to increase muscle hypertrophy and strength in older adults. This study aimed to determine the effects of low-dose ibuprofen (400 mg) immediately following resistance exercise sessions on muscle mass and strength in postmenopausal women. METHODS: Participants were randomized to ingest ibuprofen (IBU: n = 15, 57.8 ± 5.1 years, 75.9 ± 9.0 kg, 165.9 ± 6.2 cm, BMI = 28 ± 4 kg/m(2)) or placebo (PLA: n = 13, 56.5 ± 4.4 years, 73.0 ± 10.4 kg, 163.1 ± 5.9 cm, BMI = 26 ± 9 kg/m(2)) immediately following resistance exercise (11 whole-body exercises), which was performed 3 days/week, on nonconsecutive days, for 9 weeks. Prior to and following training, measures were taken for lean tissue mass (dual-energy X-ray absorptiometry), muscle size of the elbow and knee flexors and extensors and ankle dorsiflexors and plantar flexors (ultrasound), and strength (one-repetition maximum leg press and chest press). RESULTS: Over the 9 weeks of training, there were significant changes (p < 0.05) in lean tissue mass (IBU, -1.1 ± 1.0 kg; PLA, -0.7 ± 1.4 kg), muscle size of the knee extensors (IBU, 0.3 ± 0.6 cm; PLA, 0.2 ± 0.7 cm), ankle dorsiflexors (IBU, 0.5 ± 0.8 cm; PLA, 0.1 ± 0.5 cm), and ankle plantar flexors (IBU, 0.3 ± 0.9 cm; PLA, 0.5 ± 0.9 cm), leg press strength (IBU, 20.6 ± 18.0 kg; PLA, 20.0 ± 20.0 kg), and chest press strength (IBU, 5.1 ± 9.5 kg; PLA, 8.1 ± 7.6 kg), with no differences between groups. CONCLUSION: Low-dose ibuprofen following resistance exercise has no greater effect on muscle mass or strength over exercise alone in postmenopausal women.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".