Cardiorespiratory Fitness and Components of the Metabolic Syndrome in Sedentary Men
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationships between fitness and components of the metabolic syndrome in sedentary men. SUBJECTS AND METHODS: 39 subjects (34-53 years) were evaluated for fitness (VO(2max)) and anthropometric, metabolic, and skeletal muscle phenotypes. VO(2max) was assessed on a bicycle ergometer whereas other variables were obtained from an oral glucose tolerance test (OGTT), hydrostatic weighing, and a muscle biopsy. RESULTS: Pearson and partial correlations adjusted for fat mass (FM), waist circumference (WC), muscle enzyme activities (citrate synthase (CS), cytochrome c oxidase (COX)), and capillary density were used to investigate the independent relationships be tween variables. Negative correlations between VO(2max) and WC as well as blood pressure and OGTT test were observed. When adjusted for FM, correlations remained between VO(2max) and WC (r = -0.46, p < 0.01) and systolic blood pressure (r = -0.35, p < 0.05). When adjusted for WC and CS activity, all correlations were lost except for high-sensitivity C-reactive protein (hs-CRP) (r = -0.34, p < 0.05) which remained when adjusted for CS activity. Adjustment for COX activity failed to remove correlations with hs-CRP (r = -0.36, p < 0.05), age (r = 0.34, p < 0.05), WC (r = -0.35, p < 0.05), and blood pressure. Negative correlations persisted when fitness was adjusted for the mean number of capillaries. CONCLUSION: The effects of fitness on components of the metabolic syndrome in sedentary men are explained by abdominal obesity and muscle phenotypes.
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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) | 0.002 | 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".