Mass spectrometric determination of gonadotrophin‐releasing hormone (GnRH) in human urine for doping control purposes by means of LC–ESI‐MS/MS
Bibliographic record
Abstract
The decapeptide gonadotrophin-releasing hormone (GnRH) is endogenously produced in the hypothalamus and secreted into the microcirculation between hypothalamus and pituitary gland. Here, the bioactive hormone is responsible for the release of luteinizing hormone (LH) and follicle-stimulating hormone (FSH) into the systemic circulation. Because an intermittent application of exogenous GnRH in young males increases the testosterone plasma level by stimulation of the Leydig cells, the potential misuse of the administered substance offers a reasonable relevancy for doping controls and is prohibited in accordance to the list of banned substances of the World Anti-Doping Agency (WADA). The presented method provides a mass spectrometric approach to determine the nondegraded hormone in regular doping control samples by utilizing a sample preparation procedure with solid phase extraction, immunoaffinity purification and a subsequent separation by liquid chromatography with ESI-MS/MS detection. For liquid chromatography/mass spectrometry two alternative instrumental equipments were tested: the first consisted of an Agilent 1100 liquid chromatograph coupled to an Applied Biosystem Q Trap 4000 mass spectrometer, the second equipment was assembled by a Waters Aquity nano-UPLC coupled to a Thermo LTQ Orbitrap high resolution/high accuracy mass spectrometer. In urine specimens provided from healthy volunteers GnRH was not detected in accordance to the recent literature, but in postadministration samples urinary concentrations between 20 to 100 pg/ml of the intact peptide were determined. The method offered good validation results considering the parameter specificity, linearity (5-300 pg/ml), limit of detection (LOD, approx. 5 pg/ml), precision (inter/intraday, < 20%) and accuracy (105%) using Des-pGlu(1)-GnRH as internal standard to control each sample preparation step.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".