The Influence of the ACTN3 R577X Genotype on Performance in Brazilian National-Level Decathlon Athletes: A Pilot Study
Bibliographic record
Abstract
Background: Decathlon is a multimodality sport that requires the combination of endurance, strength, speed, and agility. A polymorphism present in the gene encoding for alpha-actinin-3 (ACTN3) potentially influences sports performance, since this protein is a structural component of skeletal muscle contributing to muscle contraction effectiveness. Aim: To investigate whether the presence of the ACTN3 R577X polymorphism is associated with decathlon athletes’ performance in the different modalities of decathlon. Methods: Thirty-one male athletes from the Brazilian national federation of decathlon aged between 18 and 50 years were genotyped for the ACTN3 R577X polymorphism using real-time polymerase chain reaction (RT-PCR). The athletes’ latest decathlon performances were recorded over ten competitions. The Hardy–Weinberg equilibrium was verified. Pearson’s correlation coefficient was utilized to assess the relationship between the obtained sports performance (score) by event and sets of events (speed events, jumps, and throws) with significance considered at p < 0.05. Results: Strong and significant correlations were identified between the speed events, the jumping, and the launching performances. Among the athletes, the distribution of ACTN3 genotypes was as follows: R577R—51.6%, R577X—48.4%, and X577X—0%, indicating a complete absence of homozygosity for the non-functional X allele in this cohort. No significant differences in sports performance (score) could be observed based on the genotype. Conclusions: Our results may support the importance of the ACTN3 genotype, specifically, the presence of the 577R allele, as one of the contributive factors for athletes’ performance in modalities that involve muscle strength, power, and speed. However, given the small sample size and the retrospective nature of this study, further research is warranted.
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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) | 0.000 | 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) | 0.002 | 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".