Literature DB >> 23175461

Raman spectroscopy coupled with advanced statistics for differentiating menstrual and peripheral blood.

Aliaksandra Sikirzhytskaya1, Vitali Sikirzhytski, Igor K Lednev.   

Abstract

Body fluids are a common and important type of forensic evidence. In particular, the identification of menstrual blood stains is often a key step during the investigation of rape cases. Here, we report on the application of near-infrared Raman microspectroscopy for differentiating menstrual blood from peripheral blood. We observed that the menstrual and peripheral blood samples have similar but distinct Raman spectra. Advanced statistical analysis of the multiple Raman spectra that were automatically (Raman mapping) acquired from the 40 dried blood stains (20 donors for each group) allowed us to build classification model with maximum (100%) sensitivity and specificity. We also demonstrated that despite certain common constituents, menstrual blood can be readily distinguished from vaginal fluid. All of the classification models were verified using cross-validation methods. The proposed method overcomes the problems associated with currently used biochemical methods, which are destructive, time consuming and expensive.
Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Raman spectroscopy; forensic identification; menstrual blood; peripheral blood; statistics

Mesh:

Year:  2012        PMID: 23175461     DOI: 10.1002/jbio.201200191

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  3 in total

1.  Discrimination of menstrual and peripheral blood traces using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and chemometrics for forensic purposes.

Authors:  Ewelina Mistek-Morabito; Igor K Lednev
Journal:  Anal Bioanal Chem       Date:  2021-02-13       Impact factor: 4.142

2.  Raman spectroscopy of blood serum for Alzheimer's disease diagnostics: specificity relative to other types of dementia.

Authors:  Elena Ryzhikova; Oleksandr Kazakov; Lenka Halamkova; Dzintra Celmins; Paula Malone; Eric Molho; Earl A Zimmerman; Igor K Lednev
Journal:  J Biophotonics       Date:  2014-09-25       Impact factor: 3.207

3.  Analysis of dengue infection based on Raman spectroscopy and support vector machine (SVM).

Authors:  Saranjam Khan; Rahat Ullah; Asifullah Khan; Noorul Wahab; Muhammad Bilal; Mushtaq Ahmed
Journal:  Biomed Opt Express       Date:  2016-05-18       Impact factor: 3.732

  3 in total

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