Rapid screening of polysaccharide‐based plasma volume expanders dextran and hydroxyethyl starch in human urine by liquid chromatography–tandem mass spectrometry
Bibliographic record
Abstract
The increasing number of samples and target substances in doping control requires continuously improved screening methods, combining high-throughput analysis, simplified sample preparation, robustness and reliability. Hence, a rapid screening procedure based on liquid chromatography-electrospray ionization-tandem mass spectrometry with in-source collision-induced dissociation was developed. The detection of the polysaccharide-based plasma volume expanders dextran and hydroxyethyl starch (HES) in human urine was established without further sample preparation. The in-source fragmentation strategy of the approach represented a valuable tool in the analysis of the polysaccharide-based compounds, allowing the use of tandem mass spectrometry. After direct injection of urine specimens, analytes were chromatographically separated on a monolithic reverse-phase column and detected via multiple reaction monitoring of diagnostic ions at detection limits of 10 microg/mL for HES and 30 microg/mL for dextran. Validation was performed regarding the parameters specificity, linearity, precision (8-18%) and accuracy (77-105%) and the method was applied to the investigation of approximately 400 doping control samples and seven dextran and two hydroxyethyl starch post-administration samples. The approach demonstrated its capability as a rapid screening tool for the detection of dextran and hydroxyethyl starch and represents an alternative to existing screening procedures since time consuming hydrolysis or derivatization steps were omitted.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".