Cardiac energy metabolism is positively associated with skeletal muscle energy metabolism in physically active adolescents and young adults
Bibliographic record
Abstract
(31)Phosphorus Magnetic Resonance Spectroscopy ((31)P MRS) is a well-validated, noninvasive magnetic resonance imaging technique that has been used to determine cardiac and skeletal muscle energy metabolism in vivo. Few studies have documented cardiac energy metabolism in adolescents and young adult cohorts. This cross-sectional study sought to explore the association among cardiac energy metabolism, skeletal muscle energy metabolism, moderate-to-vigorous physical activity (MVPA), and age in adolescents and young adults. Ten healthy, active participants (40% male) with a mean ± SD age of 18.6 ± 4.9 years, body mass index of 21.1 ± 2.4 kg·m(-2), and median MVPA level of 83 min per weekday (lower quartile: 45 min per weekday; upper quartile: 114 min per weekday) completed the following study assessments: a (31)P MRS scan to determine cardiac and skeletal muscle energy metabolism, cardiopulmonary exercise testing to determine aerobic power, and accelerometry to determine MVPA over 7 days. Resting cardiac energy metabolism, as measured by the ratio of phosphocreatine to adenosine triphosphate (PCr/ATPβ, mean ± SD: 2.76 ± 0.65), was positively associated with skeletal muscle aerobic oxidative function (Estimate (SE): -0.1(0.01), p < 0.001), as measured by PCr recovery half-time following 60 s of exercise (34 ± 9 s). This association, which was adjusted for peak aerobic power, MVPA, age, and sex, suggests the development of an association between cardiac and skeletal muscle health at any early age. Larger studies are needed to establish normative data for both physically active and sedentary males and females that may be used for comparison in future studies involving clinical cohorts.
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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".