Publications by authors named "Aldo E Polettini"

Although the use, structural variety, and prevalence of synthetic cannabinoids (SCs) have steadily increased on the drug market, they are rarely analyzed in abstinence control programs for driver's license regranting. The aim of this study was to determine the SC prevalence in these programs by analyzing hair samples collected between March 2020 and March 2021 from various regions in Germany, mainly Bavaria (40%). Specimens were analyzed quantitatively for drugs of abuse and qualitatively for 107 SCs.

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Background And Aims: Retrospective analysis of hair testing data provides insights in drugs abuse patterns and improves results interpretation. Cases from subjects undergoing driving fitness assessment (2010-2020) were examined to evidence patterns in methamphetamine (MA) abuse.

Materials And Methods: All cases with positive MA (≥0.

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The application of Quantitative Structure-Property Relationship (QSPR) modeling to the prediction of reversed-phase liquid chromatography retention behavior of synthetic cannabinoids (SC), and its use in aiding the untargeted identification of unknown SC are described in this paper. 1D, 2D molecular descriptors and fingerprints of 105 SC were calculated with PaDEL-Descriptor, selected with Boruta algorithm in R environment, and used to build-up a multiple linear regression model able to predict retention times, relative to JWH-018 N-pentanoic acid-d5 as internal standard, under the following conditions: Agilent ZORBAX Eclipse Plus C18 (100 mm × 2.1 mm I.

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Despite liquid chromatography-high-resolution tandem mass spectrometry (MS2) enables untargeted acquisition, data processing in toxicological screenings is almost invariably performed in targeted mode. We developed a computational approach based on open source chemometrics software that, starting from a suspected synthetic cannabinoid (SC) determined formula, searches for isomers in different new psychoactive substances web databases, predicts retention time (RT) and high-resolution MS2 spectrum, and compares them with the unknown providing a rank-ordered candidates list. R was applied on 105 SC measured data to develop and validate a multiple linear regression quantitative structure-activity relationship model predicting RT.

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Aims: The aim of this study was to examine urine creatinine concentrations in drivers submitted to controlled alcohol abstinence programs.

Methods: Urine samples (n = 32,210) were screened for ethyl glucuronide (EtG) by immunoassay during a 2-year period. Non-negatives underwent EtG and ethyl sulfate (EtS) confirmation by coupled-column Liquid Chromatography-Tandem Mass Spectrometry.

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