Literature DB >> 25350871

Raman spectroscopy of blood for species identification.

Gregory McLaughlin1, Kyle C Doty, Igor K Lednev.   

Abstract

The species identification of a blood stain is an important and immediate challenge for forensic science, veterinary purposes, and wildlife preservation. The current methods used to identify the species of origin of a blood stain are limited in scope and destructive to the sample. We have previously demonstrated that Raman spectroscopy can reliably differentiate blood traces of human, cat, and dog (Virkler et al. Anal. Chem. 2009, 81, 7773 - 7777) and, most recently, built a binary model for differentiating human vs animal blood for 11 species integrated with human existence ( McLaughlin et al. Forensic Sci. Int. 2014, 238, 91 - 95). Here we report a satisfactory classification of blood obtained from 11 animal classes and human subjects by statistical analysis of Raman spectra. Classification of blood samples was achieved according to each sample's species of origin, which enhanced previously observed discrimination ability. The developed approach does not require the knowledge of a specific (bio)chemical marker for each individual class but rather relies on a spectroscopic statistical differentiation of various components. This approach results in remarkable classification ability even with intrinsically heterogeneous classes and samples. In addition, the obtained spectroscopic characteristics could potentially provide information about specific changes in the (bio)chemical composition of samples, which are responsible for the differentiation.

Entities:  

Mesh:

Year:  2014        PMID: 25350871     DOI: 10.1021/ac5026368

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  11 in total

1.  Dual-model analysis for improving the discrimination performance of human and nonhuman blood based on Raman spectroscopy.

Authors:  Haiyi Bian; Peng Wang; Ning Wang; Yubing Tian; Pengli Bai; Haowen Jiang; Jing Gao
Journal:  Biomed Opt Express       Date:  2018-07-05       Impact factor: 3.732

2.  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

3.  Species identification of bloodstains by ATR-FTIR spectroscopy: the effects of bloodstain age and the deposition environment.

Authors:  Hancheng Lin; Yinming Zhang; Qi Wang; Bing Li; Shuanliang Fan; Zhenyuan Wang
Journal:  Int J Legal Med       Date:  2017-08-18       Impact factor: 2.686

4.  Efficiency enhancement of Raman spectroscopy at long working distance by parabolic reflector.

Authors:  Yao Tian; Joshua Weiming Su; Jian Ju; Quan Liu
Journal:  Biomed Opt Express       Date:  2017-10-26       Impact factor: 3.732

5.  Blood species identification based on deep learning analysis of Raman spectra.

Authors:  Shan Huang; Peng Wang; Yubing Tian; Pengli Bai; DaQing Chen; Ce Wang; JianSheng Chen; ZhaoBang Liu; Jian Zheng; WenMing Yao; JianXin Li; Jing Gao
Journal:  Biomed Opt Express       Date:  2019-11-06       Impact factor: 3.732

6.  Blood identification at the single-cell level based on a combination of laser tweezers Raman spectroscopy and machine learning.

Authors:  Ziqi Wang; Yiming Liu; Weilai Lu; Yu Vincent Fu; Zhehai Zhou
Journal:  Biomed Opt Express       Date:  2021-11-12       Impact factor: 3.732

7.  Analyzing the serum of hemodialysis patients with end-stage chronic kidney disease by means of the combination of SERS and machine learning.

Authors:  Lyudmila A Bratchenko; Sahar Z Al-Sammarraie; Elena N Tupikova; Daria Y Konovalova; Peter A Lebedev; Valery P Zakharov; Ivan A Bratchenko
Journal:  Biomed Opt Express       Date:  2022-08-24       Impact factor: 3.562

8.  PCA as a practical indicator of OPLS-DA model reliability.

Authors:  Bradley Worley; Robert Powers
Journal:  Curr Metabolomics       Date:  2016

9.  Estimation of the age of human bloodstains under the simulated indoor and outdoor crime scene conditions by ATR-FTIR spectroscopy.

Authors:  Hancheng Lin; Yinming Zhang; Qi Wang; Bing Li; Ping Huang; Zhenyuan Wang
Journal:  Sci Rep       Date:  2017-10-16       Impact factor: 4.379

10.  Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis.

Authors:  Ayari Takamura; Ken Watanabe; Tomoko Akutsu; Takeaki Ozawa
Journal:  Sci Rep       Date:  2018-05-31       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.