Determination of GnRH and its synthetic analogues' abuse in doping control: Small bioactive peptide UPLC–MS/MS method extension by addition of <i>in vitro</i> and <i>in vivo</i> metabolism data; evaluation of LH and steroid profile parameter fluctuations as suitable biomarkers
Why this work is in the frame
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Bibliographic record
Abstract
Gonadotropin-releasing hormone (GnRH) and its small peptide synthetic analogues are included in Section S2 of the World Anti-Doping Agency (WADA) Prohibited List as they stimulate pituitary luteinizing hormone (LH) and testicular testosterone (T) secretion. Both the following approaches can be applied for determination of abuse of these peptides: direct identification of intact compounds and their metabolites in athletes' biofluids and evaluation of LH and T concentrations as mediate markers of drug intake. To develop an effective concept for GnRH and its analogues determination in anti-doping control, in vitro and in vivo studies were conducted. A new method was applied to the evaluation of the slow-release profile of buserelin, goserelin, and leuprolide biodegradable microspheres after the intramuscular injection in male volunteers. Eight metabolites of 10 GnRH analogues were identified after incubation with human kidney microsomes, most of them were leuprolide degradation products. Obtained data were added into ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for GnRH analogues determination. The detection time windows for administered peptides and their metabolites in urine samples were evaluated with 2 sample preparation techniques: dilute-and-shoot and solid-phase extraction. To support the second hypothesis, the measurement of LH and the main parameters of the steroid profile were performed in urine samples. Just 1 compound among those investigated resulted in the LH concentration dropping to non-physiological levels. Thus, for doping-control purposes, monitoring of hormone levels fluctuations could be applied only together with longitudinal passport steroid profile data.
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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 | 0.003 | 0.004 |
| 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 | 0.000 |
| 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 it