Effect of Physical Fitness and Endurance Exercise on Indirect Biomarkers of Recombinant Growth Hormone Misuse: Insulin-Like Growth Factor I and Procollagen Type III Peptide
Bibliographic record
Abstract
Serum insulin-like growth factor-I (IGF-I) and procollagen type III peptide (P-III-P) have been proposed as indirect biomarkers of rhGH misuse in sports. The purpose of the present study was to investigate concentrations of these biomarkers in athletes at different levels of physical fitness and endurance exercise. Serum total IGF-I and P-III-P were measured in 96 elite athletes of various sports along the training season; in 21 recreational athletes at baseline non-exercising conditions and in another 129 recreational athletes before and after long-distance races (10 and 21 km). No differences were evidenced for IGF-I concentrations, but statistically higher values of serum P-III-P were found in elite athletes compared to recreational ones. Among elite athletes, the specific sport did not affect serum IGF-I. However, P-III-P was statistically higher in the sport performed by the youngest athletes (rhythmic gymnastics), even after correction of the logarithm of the concentration by the reciprocal of age. Over the training season, the within-athlete variabilities of IGF-I and P-III-P in elite athletes were low (22.8 % and 21.7 %, respectively). Recreational athletes taking part in a 21 km competition race showed a significant increase in serum values of IGF-I and P-III-P immediately after the event. Exercise workload and age had a significant effect on serum concentration of P-III-P, while age alone affected IGF-I serum concentrations. Therefore, athlete's reference concentration ranges for doping detection should include subjects from as many different ages and sports as possible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".