Literature DB >> 27885430

Blood species discrimination using proton nuclear magnetic resonance spectroscopy.

Elina Zailer1, Bernd W K Diehl2, Yulia B Monakhova1,3.   

Abstract

Blood species identification is an important challenge in forensic science. Conventional methods used for blood species analysis are destructive and associated with time-consuming sample preparation steps. Nuclear magnetic resonance (NMR) spectroscopy is known for its nondestructive properties and fast results. This research study presents a proton (1H) NMR method to discriminate blood species including human, cat, dog, elephant, and bison. Characteristic signals acting as markers are observed for each species. Moreover, the data are evaluated by principle component analysis (PCA) and support vector machines (SVM). A 100% correct species recognition between human and nonhuman species is achieved using radial basis kernel function (RBF) and standardized data. The research study shows that 1H NMR spectroscopy is a powerful tool for differentiating human and nonhuman blood showing a great significance to forensic science.

Entities:  

Keywords:  Blood species identification; Forensic science; Nuclear magnetic resonance (NMR); Principle component analysis

Mesh:

Year:  2016        PMID: 27885430     DOI: 10.1007/s00414-016-1500-7

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  11 in total

1.  Electrospray ionization mass spectrometric analysis of blood for differentiation of species.

Authors:  E O Espinoza; N C Lindley; K M Gordon; J A Ekhoff; M A Kirms
Journal:  Anal Biochem       Date:  1999-03-15       Impact factor: 3.365

2.  Alternative determination of blood alcohol concentration by (1)H NMR spectroscopy.

Authors:  Elina Zailer; Bernd W K Diehl
Journal:  J Pharm Biomed Anal       Date:  2015-11-28       Impact factor: 3.935

Review 3.  What is a support vector machine?

Authors:  William S Noble
Journal:  Nat Biotechnol       Date:  2006-12       Impact factor: 54.908

4.  Identification of species' blood by attenuated total reflection (ATR) Fourier transform infrared (FT-IR) spectroscopy.

Authors:  Ewelina Mistek; Igor K Lednev
Journal:  Anal Bioanal Chem       Date:  2015-07-21       Impact factor: 4.142

5.  Blood identification and discrimination between human and nonhuman blood using portable Raman spectroscopy.

Authors:  J Fujihara; Y Fujita; T Yamamoto; N Nishimoto; K Kimura-Kataoka; S Kurata; Y Takinami; T Yasuda; H Takeshita
Journal:  Int J Legal Med       Date:  2016-06-05       Impact factor: 2.686

6.  Quantitative real-time PCR (qPCR) assay for human-dog-cat species identification and nuclear DNA quantification.

Authors:  S Kanthaswamy; A Premasuthan; J Ng; J Satkoski; V Goyal
Journal:  Forensic Sci Int Genet       Date:  2011-07-20       Impact factor: 4.882

7.  31P-nuclear magnetic resonance spectroscopy of blood: a species comparison.

Authors:  M Horn; M Kadgien; K Schnackerz; S Neubauer
Journal:  J Cardiovasc Magn Reson       Date:  2000       Impact factor: 5.364

8.  Forensic application of the luminol reaction as a presumptive test for latent blood detection.

Authors:  Filippo Barni; Simon W Lewis; Andrea Berti; Gordon M Miskelly; Giampietro Lago
Journal:  Talanta       Date:  2007-01-09       Impact factor: 6.057

9.  Species identification of blood and bloodstains by enzyme-linked immunosorbent assay (ELISA) using anti-human immunoglobulin kappa light chain monoclonal antibody.

Authors:  Y Yamamoto; A Tsutsumi; H Ishizu
Journal:  Forensic Sci Int       Date:  1989-01       Impact factor: 2.395

10.  Development of a radioimmunoassay technique for the detection of human hemoglobin in dried bloodstains.

Authors:  L Quarino; L Kobilinsky
Journal:  J Forensic Sci       Date:  1988-11       Impact factor: 1.832

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  1 in total

Review 1.  Forensic NMR metabolomics: one more arrow in the quiver.

Authors:  Emanuela Locci; Giovanni Bazzano; Alberto Chighine; Francesco Locco; Ernesto Ferraro; Roberto Demontis; Ernesto d'Aloja
Journal:  Metabolomics       Date:  2020-11-07       Impact factor: 4.290

  1 in total

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