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Molecular imaging of humain hair with MeV-SIMS: A case study of cocaine detection and distribution in the hair of a cocaine user.

Authors :
Luka Jeromel
Nina Ogrinc
Zdravko Siketić
Primož Vavpetič
Zdravko Rupnik
Klemen Bučar
Boštjan Jenčič
Mitja Kelemen
Matjaž Vencelj
Katarina Vogel-Mikuš
Janez Kovač
Ron M A Heeren
Bryn Flinders
Eva Cuypers
Žiga Barba
Primož Pelicon
Source :
PLoS ONE, Vol 17, Iss 3, p e0263338 (2022)
Publication Year :
2022
Publisher :
Public Library of Science (PLoS), 2022.

Abstract

Human hair absorbs numerous biomolecules from the body during its growth. This can act as a fingerprint to determine substance intake of an individual, which can be useful in forensic studies. The cocaine concentration profile along the growth axis of hair indicates the time evolution of the metabolic incorporation of cocaine usage. It could be either assessed by chemical extraction and further analysis of hair bundels, or by direct single hair fibre analysis with mass spectroscopy imaging (MSI). Within this work, we analyzed the cocaine distribution in individual hair samples using MeV-SIMS. Unlike conventional surface analysis methods, we demonstrate high yields of nonfragmented molecular ions from the surface of biological materials, resulting in high chemical sensitivity and non-destructive characterisation. Hair samples were prepared by longitudinally cutting along the axis of growth, leaving half-cylindrical shape to access the interior structure of the hair by the probing ion beam, and attached to the silicon wafer. A focused 5.8 MeV 35Cl6+ beam was scanned across the intact, chemically pristine hair structure. A non-fragmented protonated [M+ H]+ cocaine molecular peak at m/z = 304 was detected and localized along the cross-section of the hair. Its intensity exhibits strong fluctuations along the direction of the hair's growth, with pronounced peaks as narrow as 50 micrometres, corresponding to a metabolic incorporation time of approx. three hours.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
17
Issue :
3
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.fa9989da49f64686aaf0434eb3c8991b
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0263338