Advances in Exercise, Fitness, and Performance Genomics
Bibliographic record
Abstract
An annual review publication of the most significant articles in exercise, fitness, and performance genomics begins with this article, which covers 2 yr, 2008 and 2009. The review emphasizes the strongest articles as defined by sample size, quality of phenotype measurements, quality of the exercise program or physical activity exposure, study design, adjustment for multiple testing, quality of genotyping, and other related study characteristics. With this avowed focus on the highest quality articles, only a small number of published articles are reviewed. Among the most significant findings reported here are a brief overview of the first genome-wide association study of the genetic differences between exercisers and nonexercisers. In addition, the latest results on the actinin alpha 3 (ACTN3) R577X nonsense polymorphism are reviewed, emphasizing that no definitive conclusion can be reached at this time. Recent studies that have dealt with mitochondrial DNA haplogroups and endurance performance are described. Published reports indicating that physical activity may attenuate the effect of the fat mass and obesity associated (FTO) gene risk allele on body mass index are reviewed. Articles that have tested the contributions of specific genes to the response of glucose and insulin metabolism traits to regular exercise or physical activity level are considered and found to be generally inconclusive at this stage. Studies examining ethnic differences in the response of blood lipids and lipoproteins to exercise training cannot unequivocally relate these to apolipoprotein E (APOE) genotypes. Hemodynamic changes with exercise training were reported to be associated to sequence variation in kinesin heavy chain (KIF5B), but no replication study is available as of yet. We conclude from this first installment that exercise scientists need to prioritize high-quality research designs and that replication studies with large sample sizes are urgently needed.
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.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".