ArticleAnalytical and bioanalytical chemistry2024
Screening anabolic androgenic steroids in human urine: an application of the state-of-the-art gas chromatography-Orbitrap high-resolution mass spectrometry.
Article in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Metabolomics and metabolites in cancer diagnosis and treatment.Molecular biomedicine · 2025Pooled it
- Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026Review
- Integrating Advanced Metabolomics and Machine Learning for Anti-Doping in Human Athletes.Metabolites · 2025Review
- Characterization and metabolic profiling of oxymetholone and methasterone metabolites studied with human liver S9 model using GC-Orbitrap-HRMS for anti-doping purposes.Analytical and bioanalytical chemistry · 2025Article
- Mass spectrometry-based metabolomic as a powerful tool to unravel the component and mechanism in TCM.Chinese medicine · 2025Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Over the past few decades, anabolic androgenic steroids (AASs) have been abused in and out of competition for their performance-enhancing and muscle-building properties. Traditionally, AASs were commonly detected using gas chromatography-mass spectrometry in the initial testing procedure for doping control purposes. Gas chromatography-Orbitrap high-resolution mass spectrometry (GC-Orbitrap-HRMS) is a new technology that has many advantages in comparison with GC-MS (e.g., a maximum resolving power of 240,000 (FWHM at m/z 200), excellent sub-ppm mass accuracy, and retrospective data analysis after data acquisition). Anti-doping practitioners are encouraged to take full advantage of the updated techniques of chromatography-mass spectrometry to develop sensitive, specific, and rapid screening methods for AASs. A new method for screening a wide range of AASs in human urine using GC-Orbitrap-HRMS was developed and validated. The method can qualitatively determine 70 anabolic androgenic steroids according to the minimum required performance limit of the World Anti-Doping Agency. Moreover, the validated method was successfully applied to detect six metabolites in urine after the oral administration of metandienone, and their excretion curves in vivo were studied. Metandienone M6 (17β-hydroxymethyl-17α-methyl-18-nor-androst-1,4,13-trien-3-one) has been identified as a long-term urinary metabolite which can be detected up to 7 weeks, thus providing a longer detection window compared with previous studies. This study provides a rationale for GC-Orbitrap-HRMS in drug metabolism and non-targeted screening.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.