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                            Library & Multimedia
 Revealing the presence of tryptamine new psychoactive substances using fused "neutral loss" spectra derived from DART high-resolution mass spectra
NCJ Number
              305165
Journal

*Talanta* Volume: 246 Dated: August 2022
Author(s)
          Mónica I. Ventura;
                        Samira Beyramysoltan;
                        Rabi A. Musah
Date Published

August 2022
Annotation
              A data fusion approach for the rapid extraction of core scaffold information that can be used to facilitate structure determination for new psychoactive substance (NPS) tryptamines is described.
Abstract
              The method involves the screening of DART-HRMS data of new tryptamines against a partial least squares-discriminant analysis (PLS-DA) model that predicts the core tryptamine structure class into which the compound can be grouped. The PLS-DA prediction model was created and trained using neutral loss spectra derived from collision-induced dissociation (CID) DART mass spectral analysis of 50 tryptamine structures acquired at 60 V and 90 V, in which the sample groups were revealed by hierarchical clustering analysis (HCA). HCA of the fused neutral loss data clustered the 50 tryptamines into 10 groups based on the identities of the neutral fragments lost during fragmentation. “Leave-one-structure-out” validation of the PLS-DA model gave 100% accuracy, precision, sensitivity, and specificity. For external validation, the ability of the model to classify four compounds that were unfamiliar to it was tested, and the model was found to correctly predict the skeletal framework in each case. The results show proof of concept for how this approach can aide in the identification of new emerging psychoactive compounds. (Publisher abstract provided)
      
  
          Additional Details
Grant Number(s)
        2017-R2-CX-0020
                                2019-DU-BX-0026


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Chemometric Processing of DART-HRMS-derived Dark Matter for the Identification of New Psychoactive Substances
                                Research to Develop Validated Methods for THC Quantification in Complex Matrices by High-resolution DART-MSFocus on Edibles and Plant Materials
    
  
  
Date Published: August 1, 2022
    
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