Investigation of the Physiological and Post‐training Effects of Ecdysteroid Supplementation by Multivariate Analysis of the Human Serum Metabolome
Bibliographic record
Abstract
ABSTRACT This work aims to characterize the serum profile of athletes after the administration of ecdysteroids, natural steroid hormones recently reported to enhance athletic performance. The combination of mass spectrometry and chemometric tools may allow to differentiate physiological effects from post‐training and intake‐driven effects. Serum samples were collected from 46 healthy male volunteers and divided into four groups: control (two capsules/day of Peak Ecdysone without training), placebo (two capsules without ecdysteroids with training), Ec1 (two capsules/day Peak Ecdysone with training), and Ec2 (eight capsules/day Peak Ecdysone with training). Metabolic profiling was measured using a SCIEX Triple Quadrupole LC‐MS/MS system coupled with the Biocrates AbsoluteIDQ p180 kit, which allows quantitation of a large panel of metabolites that were subjected to multivariate analysis. Unsupervised analysis of the data found no significant differences between the placebo and the ecdysteroid supplementation groups. By merging Ec1 and Ec2 into a single group, coded as treated, a clear discrimination between the control and placebo groups was observed. Phosphatidylcholines were among the most significant features of ecdysteroids administration, showing a dose‐dependent effect in Ec1 and Ec2 groups. As specific metabolic phenotypes can result from years of training, the discrimination of physiological effects from those caused by the administration of banned substances can be a valuable analytical strategy for the interpretation of adverse analytical findings in the anti‐doping field.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".