Toward the Use of a Molecularly Imprinted Polymer in Doping Analysis: Selective Preconcentration and Analysis of Testosterone and Epitestosterone in Human Urine
Bibliographic record
Abstract
A molecularly imprinted polymer (MIP), templated with methyltestosterone, has been synthesized for the cleanup of hydrolyzed urine samples for subsequent testosterone (T) quantification by LC-MS/MS. A concentration of 2 ng/mL testosterone could be quantified after a single step extraction on the MIP. The limit of detection and quantification with the criteria of a signal-to-noise ratio of 3 and 5 were 0.3 and 2 ng/mL, respectively. These values meet the conditions set by the World Anti-Doping Agency for the minimum required performance limits for doping controls, between 2 and 10 ng/mL. Epitestosterone (E) was also separated on this polymer and could be detected at concentrations down to 0.3 ng/mL. The quantification of T and E gives access to the determination of the T/E ratio, essential in doping analysis. Hence, our polymers can offer a more specific extraction procedure, resulting in increased sensitivity with limits of detection 10 times lower than the ones achieved by the standard SPE C(18) sorbents employed in official testing laboratories.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".