Classification of condom lubricants in cyanoacrylate treated fingerprints by desorption electrospray ionization mass spectrometry

Ward van Helmond, Mark P.V. Begieneman, Roos Kniest, Marcel de Puit

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
42 Downloads (Pure)

Abstract

Traces of condom lubricants in fingerprints can be valuable information in cases of sexual assault. Ideally, not only confirmation of the presence of the condom but also determination of the type of condom brand used can be retrieved. Previous studies have shown to be able to retrieve information about the condom brand and type from fingerprints containing lubricants using various analytical techniques. However, in practice fingerprints often appear latent and need to be detected first, which is often achieved by cyanoacrylate fuming. In this study, we developed a desorption electrospray ionization mass spectrometry (DESI-MS) method which, combined with principal component analysis and linear discriminant analysis (PCA-LDA), allows for high accuracy classification of condom brands and types from fingerprints containing condom lubricant traces. The developed method is compatible with cyanoacrylate (CA) fuming. We collected and analyzed a representative dataset for the Netherlands comprising 32 different condoms. Distinctive lubricant components such as polyethylene glycol (PEG), polydimethylsiloxane (PDMS), octoxynol-9 and nonoxynol-9 were readily detected using the DESI-MS method. Based on the analysis of lubricant spots, a 99.0% classification accuracy was achieved. When analyzing lubricant containing fingerprints, an overall accuracy of 90.9% was obtained. Full chemical images could be generated from fingerprints, showing the distribution of lubricant components such as PEG and PDMS throughout the fingerprint, while still allowing for classification. The developed method shows potential for the development of DESI-MS based analyses of CA treated exogenous compounds from fingerprints for use in forensic science.

Original languageEnglish
Article number110005
JournalForensic Science International
Volume305
DOIs
Publication statusPublished - 2019

Keywords

  • DESI-MSI
  • Linear discriminant analysis
  • Mass Spectrometry Imaging
  • Polydimethylsiloxane
  • Polyethylene glycol
  • Principal component analysis

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