The relationships of lifetime physical activity and diet with salivary cell telomere length in current ultra-endurance exercisers
Bibliographic record
Abstract
BACKGROUND: Physical activity and a healthy diet may delay the aging process and ultra-endurance exercise is an extreme form of physical activity. Telomeres are protective DNA sequences located at the ends of eukaryotic chromosomes which shorten as we age. OBJECTIVE: The aim of this study was to investigate the relationships of lifetime physical activity and diet with salivary cell telomere length in current ultra-endurance exercisers ( n = 49; % female = 37, age range 26–74 years). METHODS: Physical activity and dietary intake were measured using the Lifetime Physical Activity and Diet Questionnaire (LPADQ) and salivary cell telomere length was measured using quantitative polymerase chain reaction. RESULTS: In this group of current ultra-endurance exercisers there was no relationship between lifetime physical activity or diet (according to food category scores) and telomere length. In contrast to the expected age-related decrease in telomere length, there was no relationship between age and telomere length (95% confidence interval [CI]: –38.86, 14.54, p = 0.359) in this group of current ultra-endurance exercisers. CONCLUSIONS: The relationships of lifetime physical activity and diet with telomere length remain uncertain. It is possible that lifetime physical activity (including ultra-endurance exercise) and lifetime diet may independently, or in combination, contribute to a decrease in the rate of age-related telomere shortening in current ultra-endurance exercisers.
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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 | 0.001 | 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".