Analysis of β-Methylphenethylamine (BMPEA) and Its Novel Metabolites in Rat Blood Using MMSPE and UPLC-qTOF-MS
Bibliographic record
Abstract
β-Methylphenethylamine (BMPEA), a positional isomer of amphetamine increasingly detected in dietary supplements and weight-loss products, poses significant analytical challenges in forensic and doping control due to its structural similarity to amphetamine. This study presents a validated analytical workflow combining mixed-mode solid-phase extraction (MMSPE) with ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-qTOF-MS) for the selective quantification of BMPEA and identification of its metabolites in rat cardiac blood. Blood was taken at 20 and 90 min after injection from twelve adult male Sprague-Dawley rats that were randomly assigned to four groups (n = 3): an untreated control, a low-dose cohort (10 mg/kg, i.p.), and two high-dose cohorts (30 mg/kg, i.p.). The technique demonstrated strong differentiation between BMPEA and amphetamine isomers, excellent linearity over 20–1000 ng/mL (R2 > 0.99), and quantification limits appropriate for forensic applications. A short biological half-life and quick elimination kinetics are consistent with related phenethylamines, as evidenced by the peak BMPEA concentrations of 899 ng/mL at 20 min and 22 ng/mL at 90 min. Comprehensive low- and high-energy mass spectrometric analyses revealed a novel BMPEA metabolite, characterized as 1-amino-2-phenylpropan-2-ol, based on fragmentation patterns and retention time comparison with reference standards. This work delivers a rigorous, high-sensitivity analytical tool for BMPEA detection in biological matrices and enhances understanding of its metabolic fate, offering critical biomarkers for forensic toxicology and anti-doping investigations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".