scholarly journals Identification of Synthetic Cannabinoid 5F-ADB (5F-MDMB-PINACA) and Its Metabolite in Urine Sample Using Liquid Chromatography – High Resolution Mass Spectrometer (LC-HRMS)

2020 ◽  
Vol 9 (2) ◽  
pp. 91-97
Author(s):  
Rieska Dwi Widayati ◽  
◽  
Tanti Tanti ◽  
Erlana Nindya Maulida ◽  
Martin Luther Silubun ◽  
...  
Keyword(s):  
Urine Sample ◽  
Drug Testing ◽  
Synthetic Cannabinoids ◽  
Routine Method ◽  
Paper Report ◽  
Biological Specimen ◽  
Conventional Drug ◽  
Method Analysis ◽  
High Resolution Mass Spectrometer ◽  
Resolution Mass

Synthetic cannabinoids are commonly known as Gorillas Tobacco, Hanomans Tobacco or Ganeshas Tobacco in Indonesia. Those products are camouflaged as a tobacco related to the number of smokers in Indonesia. The 5F-ADB (5F-MDMB-PINACA) has become an issue since 2016. It was undetectable by conventional drug testing methodology such as immunoassay method. GC-MS as a routine method analysis is not recommended also for detecting the metabolites from biological specimen with low concentration. The paper report LC-HRMS based method for identification of 5F-ADB and its metabolites in urine sample. Various of volume injections (1, 3, and 6 µL) was studied. Sample was acidified with concentrate of HCl, then undergo extraction with EXtrelut® Column NT3 prior to LC-HRMS analysis. The full method was operated for MS/dd-MS2 identification. The 5F-ADB and its ester hydrolysis metabolite, 5F-ADB metabolite 7 (C19H27FN3O3+) was detected in urine sample.

scholarly journals Complexes with Atomic Gold Ions: Efficient Bis-Ligand Formation

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3484
Author(s):  
Felix Duensing ◽  
Elisabeth Gruber ◽  
Paul Martini ◽  
Marcelo Goulart ◽  
Michael Gatchell ◽  
...  
Keyword(s):  
Polyatomic Molecules ◽  
Rare Gas ◽  
Abundance Distribution ◽  
Degree Of Ionization ◽  
Covalent Bonds ◽  
Helium Nanodroplets ◽  
Order Of Magnitude ◽  
High Resolution Mass Spectrometer ◽  
Dumbbell Structure ◽  
Resolution Mass

Complexes of atomic gold with a variety of ligands have been formed by passing helium nanodroplets (HNDs) through two pickup cells containing gold vapor and the vapor of another dopant, namely a rare gas, a diatomic molecule (H2, N2, O2, I2, P2), or various polyatomic molecules (H2O, CO2, SF6, C6H6, adamantane, imidazole, dicyclopentadiene, and fullerene). The doped HNDs were irradiated by electrons; ensuing cations were identified in a high-resolution mass spectrometer. Anions were detected for benzene, dicyclopentadiene, and fullerene. For most ligands L, the abundance distribution of AuLn+ versus size n displays a remarkable enhancement at n = 2. The propensity towards bis-ligand formation is attributed to the formation of covalent bonds in Au+L2 which adopt a dumbbell structure, L-Au+-L, as previously found for L = Xe and C60. Another interesting observation is the effect of gold on the degree of ionization-induced intramolecular fragmentation. For most systems gold enhances the fragmentation, i.e., intramolecular fragmentation in AuLn+ is larger than in pure Ln+. Hydrogen, on the other hand, behaves differently, as intramolecular fragmentation in Au(H2)n+ is weaker than in pure (H2)n+ by an order of magnitude.

Interpretable machine learning model to detect chemically adulterated urine samples analyzed by high resolution mass spectrometry

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Gabriel L. Streun ◽  
Andrea E. Steuer ◽  
Lars C. Ebert ◽  
Akos Dobay ◽  
Thomas Kraemer
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
High Resolution ◽  
Retention Time ◽  
Drug Testing ◽  
High Resolution Mass Spectrometry ◽  
Urine Samples ◽  
Machine Learning Model ◽  
Resolution Mass

Abstract Objectives Urine sample manipulation including substitution, dilution, and chemical adulteration is a continuing challenge for workplace drug testing, abstinence control, and doping control laboratories. The simultaneous detection of sample manipulation and prohibited drugs within one single analytical measurement would be highly advantageous. Machine learning algorithms are able to learn from existing datasets and predict outcomes of new data, which are unknown to the model. Methods Authentic human urine samples were treated with pyridinium chlorochromate, potassium nitrite, hydrogen peroxide, iodine, sodium hypochlorite, and water as control. In total, 702 samples, measured with liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, were used. After retention time alignment within Progenesis QI, an artificial neural network was trained with 500 samples, each featuring 33,448 values. The feature importance was analyzed with the local interpretable model-agnostic explanations approach. Results Following 10-fold cross-validation, the mean sensitivity, specificity, positive predictive value, and negative predictive value was 88.9, 92.0, 91.9, and 89.2%, respectively. A diverse test set (n=202) containing treated and untreated urine samples could be correctly classified with an accuracy of 95.4%. In addition, 14 important features and four potential biomarkers were extracted. Conclusions With interpretable retention time aligned liquid chromatography high-resolution mass spectrometry data, a reliable machine learning model could be established that rapidly uncovers chemical urine manipulation. The incorporation of our model into routine clinical or forensic analysis allows simultaneous LC-MS analysis and sample integrity testing in one run, thus revolutionizing this field of drug testing.

scholarly journals Human Hepatocyte Metabolism of Novel Synthetic Cannabinoids MN-18 and Its 5-Fluoro Analog 5F-MN-18

2017 ◽  
Vol 63 (11) ◽  
pp. 1753-1763 ◽  
Author(s):  
Xingxing Diao ◽  
Jeremy Carlier ◽  
Mingshe Zhu ◽  
Marilyn A Huestis
Keyword(s):  
Carboxylic Acid ◽  
High Resolution ◽  
High Resolution Mass Spectrometry ◽  
Synthetic Cannabinoids ◽  
Human Hepatocytes ◽  
Binding Affinities ◽  
High Resolution Mass ◽  
Full Scan ◽  
Resolution Mass

Abstract BACKGROUND In 2014, 2 novel synthetic cannabinoids, MN-18 and its 5-fluoro analog, 5F-MN-18, were first identified in an ongoing survey of novel psychoactive substances in Japan. In vitro pharmacological assays revealed that MN-18 and 5F-MN-18 displayed high binding affinities to human CB1 and CB2 receptors, with Ki being 1.65–3.86 nmol/L. MN-18 and 5F-MN-18 were scheduled in Japan and some other countries in 2014. Despite increasing prevalence, no human metabolism data are currently available, making it challenging for forensic laboratories to confirm intake of MN-18 or 5F-MN-18. METHODS We incubated 10 μmol/L of MN-18 and 5F-MN-18 in human hepatocytes for 3 h and analyzed the samples on a TripleTOF 5600+ high-resolution mass spectrometer to identify appropriate marker metabolites. Data were acquired via full scan and information-dependent acquisition-triggered product ion scans with mass defect filter. RESULTS In total, 13 MN-18 metabolites were detected, with the top 3 abundant metabolites being 1-pentyl-1H-indazole-3-carboxylic acid, pentyl-carbonylated MN-18, and naphthalene-hydroxylated MN-18. For 5F-MN-18, 20 metabolites were observed, with the top 3 abundant metabolites being 5′-OH-MN-18, MN-18 pentanoic acid, and 1-(5-fluoropentyl)-1H-indazole-3-carboxylic acid. CONCLUSIONS We have characterized MN-18 and 5F-MN-18 metabolism with human hepatocytes and high-resolution mass spectrometry, and we recommend characteristic major metabolites for clinical and forensic laboratories to identify MN-18 and 5F-MN-18 intake and link observed adverse events to these novel synthetic cannabinoids.

scholarly journals Immunochemical Screening for Synthetic Cannabinoids in Workplace Drug Testing

2016 ◽  
Vol 02 (04) ◽  
Author(s):  
Nadia De Giovanni ◽  
Vincenzo Lorenzo Pascali ◽  
Sonia Giacometti
Keyword(s):  
Drug Testing ◽  
Synthetic Cannabinoids ◽  
Workplace Drug Testing

High-resolution mass spectrometer for protein chemistry

Nature ◽  
1994 ◽  
Vol 370 (6488) ◽  
pp. 393-395 ◽  
Author(s):  
Yunzhi Li ◽  
Richard L. Hunter ◽  
Robert T. Mclver
Keyword(s):  
High Resolution ◽  
Mass Spectrometer ◽  
Protein Chemistry ◽  
High Resolution Mass ◽  
High Resolution Mass Spectrometer ◽  
Resolution Mass
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