Literature DB >> 32134419

Detection of mephedrone and its metabolites in fingerprints from a controlled human administration study by liquid chromatography-tandem mass spectrometry and paper spray-mass spectrometry.

Joanna Czerwinska1, Min Jang, Catia Costa, Mark C Parkin, Claire George, Andrew T Kicman, Melanie J Bailey, Paul I Dargan, Vincenzo Abbate.   

Abstract

The use of synthetic stimulants, including designer cathinones, remains a significant concern worldwide. Thus, the detection and identification of synthetic cathinones in biological matrices is of paramount importance for clinical and forensic laboratories. In this study, distribution of mephedrone and its metabolites was investigated in fingerprints. Following a controlled human mephedrone administration (100 mg nasally insufflated), two mass spectrometry-based methods for fingerprint analysis have been evaluated. The samples deposited on triangular pieces of chromatography paper were directly analysed under ambient conditions by paper spray-mass spectrometry (PS-MS) while those deposited on glass cover slips were extracted and analysed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The LC-MS/MS method was 5-6 times more sensitive than PS-MS but required sample preparation and longer analysis time. Mephedrone was detected in 62% and in 38% of all post-administration samples analysed by LC-MS/MS and PS-MS, respectively. Nor-mephedrone was the only metabolite detected in 3.8% of all samples analysed by LC-MS/MS. A large inter- and intra-subject variation was observed for mephedrone which may be due to several factors, such as the applied finger pressure, angle and duration of contact with the deposition surface and inability to control the 'amount' of collected fingerprint deposits. Until these limitations are addressed, we suggest that the sole use of fingerprints can be a useful diagnostic tool in qualitative rather than quantitative analysis, and requires a confirmatory analysis in a different biological matrix.

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Year:  2020        PMID: 32134419     DOI: 10.1039/c9an02477h

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  6 in total

1.  A Quantitative LC-MS/MS Method for the Detection of 16 Synthetic Cathinones and 10 Metabolites and Its Application to Suspicious Clinical and Forensic Urine Samples.

Authors:  Abdulaziz A Aldubayyan; Erika Castrignanò; Simon Elliott; Vincenzo Abbate
Journal:  Pharmaceuticals (Basel)       Date:  2022-04-22

2.  Comparative Untargeted Metabolomics Analysis of the Psychostimulants 3,4-Methylenedioxy-Methamphetamine (MDMA), Amphetamine, and the Novel Psychoactive Substance Mephedrone after Controlled Drug Administration to Humans.

Authors:  Andrea E Steuer; Daria Kaelin; Martina I Boxler; Lisa Eisenbeiss; Friederike Holze; Patrick Vizeli; Joanna Czerwinska; Paul I Dargan; Vincenzo Abbate; Matthias E Liechti; Thomas Kraemer
Journal:  Metabolites       Date:  2020-07-27

3.  Investigation of Biotransformation Products of p-Methoxymethylamphetamine and Dihydromephedrone in Wastewater by High-Resolution Mass Spectrometry.

Authors:  Juliet Kinyua; Aikaterini K Psoma; Nikolaos I Rousis; Maria-Christina Nika; Adrian Covaci; Alexander L N van Nuijs; Νikolaos S Τhomaidis
Journal:  Metabolites       Date:  2021-01-25

4.  Development of an Electrochemical Sensor Using a Modified Carbon Paste Electrode with Silver Nanoparticles Capped with Saffron for Monitoring Mephedrone.

Authors:  Georgios Christos Papaioannou; Sophia Karastogianni; Stella Girousi
Journal:  Sensors (Basel)       Date:  2022-02-18       Impact factor: 3.576

5.  Excretion of mephedrone and its phase I metabolites in urine after a controlled intranasal administration to healthy human volunteers.

Authors:  Joanna Czerwinska; Mark C Parkin; Claire George; Andrew T Kicman; Paul I Dargan; Vincenzo Abbate
Journal:  Drug Test Anal       Date:  2022-01-11       Impact factor: 3.234

6.  Probabilistic quotient's work and pharmacokinetics' contribution: countering size effect in metabolic time series measurements.

Authors:  Mathias Gotsmy; Julia Brunmair; Christoph Büschl; Christopher Gerner; Jürgen Zanghellini
Journal:  BMC Bioinformatics       Date:  2022-09-16       Impact factor: 3.307

  6 in total

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