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Title

The potential of Raman and FT-IR spectroscopic methods for the detection of chlorine in human nail samples.

Authors

Toprak, Sadik; Kahriman, Fatih; Dogan, Zekeriya; Ersoy, Gokhan; Can, Emine Yilmaz; Akpolat, Meryem; Can, Murat

Abstract

Although chlorine (Cl2) has been used as a chemical warfare agent since World War I there is no known specific and reliable biomarker to indicate the presence of chlorine. We distinguished chlorinated human nails from unchlorinated ones using Raman spectroscopy and Fourier Transform Infrared (FT-IR) Spectroscopy. This research was carried out between October 2018 and July 2019 on two nail samples taken from 55 male and 104 female volunteers. One sample from each participant was chlorinated, while the second sample was used as a control. Spectral data were collected from chlorinated and unchlorinated (control) human nails using Raman and FT-IR spectroscopy. Raman measurements were made between 100 and 3200 cm−1, while FT-IR measurements were recorded over the range of 650 to 4000 cm−1. Partial least squares regression-discriminant analysis (PLS-DA) was used to develop classification models for each spectral instrument. Results showed that the control and chlorinated nail samples were successfully discriminated with similar results achieved with both instruments. Minor differences were observed in the performance of classification models. The FT-IR spectroscopy model (sensitivity = 95%, specificity = 99%, accuracy = 97%) was found to be more successful with a smaller margin of error (sensitivity = 95%, specificity = 99%, accuracy = 96%) compared to the Raman spectroscopy model. This method can be used successfully for both ante-mortem and post-mortem diagnosis of chlorine exposure.

Subjects

PARTIAL least squares regression; NAILS (Anatomy); CHEMICAL warfare agents; CHLORINE; RAMAN spectroscopy; WORLD War I

Publication

Forensic Science, Medicine & Pathology, 2020, Vol 16, Issue 4, p633

ISSN

1547-769X

Publication type

Academic Journal

DOI

10.1007/s12024-020-00313-5

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