ACTN3 R577X polymorphism related to sarcopenia and physical fitness in active older women
Bibliographic record
Abstract
Background As the population is getting older, physical activity promotion becomes a good strategy to increase quality of life in the elderly; but genetic condition also plays an important role. The purpose of this study was to examine the association of the ACTN3 R577X polymorphism with physical fitness and muscle mass in physically active older women.Methods A cross-sectional study was performed with two groups of older women who practiced physical exercise regularly. The first cohort comprised 164 women (age 69.7 ± 3.2 years) and the second cohort 131 women (age 78.5 ± 3.0 years). The main outcome measures were anthropometric measures with assessment of sarcopenia and sarcopenic obesity, self-reported physical activity EXERNET questionnaire (EEPAQ), evaluation of physical fitness (muscle strength and flexibility test), and ACTN3 genotyping.Results Women above 75 years old with allele R presented a higher risk of experiencing sarcopenia compared to ACTNR XX homozygous women (odds ratio 0.356, 95% confidence interval 0.139–0.915, p = 0.026). Furthermore, statistically significant differences were found in the chair stand test (p = 0.04), as well as in the sit and reach test (p = 0.01), with better results for women below 75 years old with the ACTN3 XX genotype.Conclusions Sarcopenia and physical fitness show differences based on the ACTN3 R577X genotype in active older 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) | 0.000 | 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".