Characterization of the thyroid hormones level in urine by liquid chromatography coupled to mass spectrometry focus in the antidoping field
Bibliographic record
Abstract
This paper aims to study the metabolism of thyroid hormones (TH) in urine by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was applied to samples collected before and after the administration of sodium triiodothyronine (T3) and sodium levothyroxine (T4) to a euthyroid volunteer and to samples of athletes declaring and not declaring thyroid supplementation. Samples were analyzed by LC-MS/MS after enzymatic hydrolysis, liquid-liquid, and solid-phase extractions. Ratios between T3/thyronine and T4/3,3'-T2 may be used for the detection of the administration of exogenous T3 in urine. Meanwhile, 3-T1 concentrations may be used to detect exogenous T4 administration. Nevertheless, these markers may not work properly in hypothyroid population, as athletes seem to be. The levels of T3 and T4 of athletes were lower than those of a euthyroid state even when they are under administration of TH supplements. The HTP axis high efficiency does not allow observing differences between athletes who do not declare and those who declare having used TH supplementation by direct measurements of T3 and T4 in urine. The detection of TH administration in urine (triiodothyronine and levothyroxine) may work when dealing with euthyroid individuals. Nevertheless, in individuals with hypothyroidism where the tendency is toward the maintenance of homeostasis, and it may be not possible to detect their consumption by applying cut-off values.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".