Simple and Rapid Determination of Amphetamine, Methamphetamine, and Their Methylenedioxy Derivatives in Urine by Automated In-Tube Solid-Phase Microextraction Coupled with Liquid Chromatography-Electrospray Ionization Mass Spectrometry
Bibliographic record
Abstract
A simple and rapid method for the determination of amphetamine, methamphetamine, and their 3,4-methylenedioxy derivatives in urine samples was developed using automated in-tube solid-phase microextraction (SPME) coupled with liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS). In-tube SPME is an extraction technique for organic compounds in aqueous samples in which analytes are extracted from the sample directly into an open tubular capillary by repeated draw/eject cycles of sample solution. LC-MS analyses of stimulants were initially performed by liquid injection onto an LC column to determine spectra. Five stimulants tested in this study gave very simple ESI mass spectra, and strong signals corresponding to [M+H]+ were observed for all stimulants. The stimulants were well separated with a Supelcosil LC-CN column using acetonitrile/50mM ammonium acetate (15:85) as a mobile phase. In order to optimize the extraction of stimulants, several in-tube SPME parameters were examined. The optimum extraction conditions were 15 draw/eject cycles of 35 microL of sample in 50mM Tris-HCI (pH 8.5) at a flow rate of 100 microL/min using an Omegawax 250 capillary column. The stimulants extracted by the capillary were easily desorbed by mobile phase flow, and carryover of stimulants was not observed. Using in-tube SPME-LC-ESI-MS with selected ion monitoring, the calibration curves of stimulants were linear in the range from 2 to 100 ng/mL with correlation coefficients above 0.9985 (n = 18) and detection limits (S/N = 3) of 0.38-0.82 ng/mL. This method was successfully applied to the analysis of human urine samples without interference peaks. The recoveries of stimulants spiked into urine samples were above 81%.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".