Carbon isotope ratios of phenethylamine and its urinary metabolite phenylacetylglutamine
Bibliographic record
Abstract
Phenethylamine (PEA) is a naturally occurring trace amine that acts as a modulator in the central nervous system. It is widely sold as a dietary supplement and advertised for its mood enhancing effects and should support weight loss. It is prohibited in sports and itemized as a stimulant on the Prohibited List issued by the World Anti-Doping Agency (WADA). After oral administration of PEA, its urinary concentration is found only slightly elevated while metabolites of PEA show a significant increase. Besides 2-(2-hydroxyphenyl)acetamide sulfate, especially phenylacetylglutamine (PAG) was found at significantly elevated urinary concentrations after the administration. Due to large inter- and intra-individual variations in urinary concentrations of all metabolites, establishing a concentration or concentration ratio-based threshold remained complicated to unambiguously identify post-administration samples. In accordance with the approach employed in detecting testosterone misuse, the applicability of isotope ratio mass spectrometry to differentiate between endogenously elevated concentrations and PEA administrations was investigated. A method encompassing solid-phase extraction combined with acetylation and high-performance liquid chromatography (HPLC)-based clean-up was developed and validated for PEA. The more abundant metabolite PAG was purified by a direct injection approach on the HPLC and could be analyzed without the need for derivatization. Both methods were validated considering applicable WADA regulations. A reference population encompassing n = 57 samples was investigated to establish population-based thresholds considering the carbon isotope ratios (CIRs) found at natural abundance for PAG. The derived threshold was tested for its applicability by re-analysis of numerous post-administration samples encompassing single- and multi-dose trials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".