Effects of physical conditioning on lipids and arachidonic acid metabolites in untrained boys: a longitudinal study
Bibliographic record
Abstract
In addition to a variety of lipids, 2 products of the arachidonic acid cascade, prostacyclin and thromboxane, are involved in the pathogenesis of atherosclerosis as a result of their effects on platelet function and on the vascular endothelium. The aim of the present investigation was to ascertain if a sub-maximal 8 week endurance training period followed by a 4 week detraining period would have any effects on high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), triglycerides (TG), 2,3-dinor-6-keto-prostaglandin F(1alpha) (2,3-dinor-6-keto-PGF(1alpha)), the urinary metabolite of prostacyclin, 2,3-dinor-thromboxane B2 (2,3-dinor-TXB2), the urinary metabolite of thromboxane, and the ratios of TC to HDL-C and of 2,3 dinor-6-keto-PGF(1alpha) to 2,3-dinor-TXB2. Thirty-eight boys aged 10-14 were randomly divided into exercise (n = 21) and control (n = 17) groups. The exercise group trained on a bicycle ergometer 4 times/week, 1 h/session, at 80% of their physical working capacity at a heart rate of 170 beats/min (PWC(170)), for 8 weeks. The control group did not participate in any specific physical exercise program. The results showed that relative to the control group, the exercise group had a significant increase in HDL-C and 2,3-dinor-6-keto-PGF(1alpha) concentrations at the end of the 4th (p < 0.05 and p < 0.001, respectively) and the 8th week (p < 0.01 and p < 0.001) of training, respectively; a significant increase in the 2,3 dinor-6-keto-PGF(1alpha) - 2,3-dinor-TXB2 ratio (p < 0.05 and p < 0.01 at the same intervals); a significant decrease in TG at the end of the 8th week of training (p < 0.05); and a significant decrease in the TC--HDL-C ratio at the end of the 4th (p < 0.05) and 8th weeks of training (p < 0.001).
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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) | 0.001 | 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 | 0.001 |
| 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".