15
doubt’. This is because many of the analytical methods used today to identify bodily fl uids are presumptive (i.e., can be either inconclusive or produce false-positive results) rather than confi rmatory (i.e., 100% positive identifi cation). In addition, most in-fi eld methods rely on enzymatic or immunologic testing, which are often destructive or consumptive in nature, preventing further analyses. The process of running multiple fl uid-specifi c tests further complicates analytical workfl ow, adding time and cost to forensic lab operation.
Figure 2. Workfl ow for body fl uid identifi cation
This solution has the potential to signifi cantly advance crime scene analysis by replacing the plethora of single body fl uid-specifi c chemical tests, which are inaccurate and destructive, with a single statistical analysis software able to positively identify all bodily fl uids, be it in the forms of stains, solids, or liquid traces on interfering substrates. This will allow crime labs to speed up decisions regarding sample content and further analyses from days to minutes. The application of a statistical method removes the subjectiveness of reading the results that occurs with standard colorimetric tests, and produces results with an error/uncertainty rate, which is important when presented in judicial proceedings.
Since forensic scientists today must conduct several individual tests for different body fl uids, this runs the risk of damaging or destroying samples. This is especially challenging when only trace amounts of bodily fl uids are present, or when bodily fl uids are found in mixed samples, as this may prevent accurate identifi cation of these fl uids, and limit or even prevent the extraction and/or identifi cation of DNA. Without being able to identify which type of bodily fl uid the DNA was derived from, it is not always possible to conclusively recreate a full crime scene and the actions of those involved. A 2017 NIJ report on sexual assault cases indicated that non-DNA evidence (such as bodily fl uids) was a key to conviction in 80% of cases [18]. Currently, in cases when multiple DNA and fl uids are present in a sample, DNA analysis cannot be linked to a single individual. In addition, only half of the biological stains collected at crime scenes contain DNA evidence, of which only 38% is eligible to be entered into the Combined DNA Index System (CODIS) database. As such, the absence of testing capabilities that can provide confi rmatory identifi cation of biological evidence from crime scenes critically prevents ongoing investigations. Due to the nondestructive and noncontact nature of this technique, practitioners will be able to use Raman spectroscopy to analyse body fl uids in situ when brought to the laboratory. The preservation of DNA evidence, as well as the reduction of non-biological samples sent for DNA analysis, will have benefi cial overall effect on multiple sections of forensic laboratories.
References
1. Takamura, A. and T. Ozawa, Recent advances of vibrational spectroscopy and chemometrics for forensic biological analysis. Analyst, 2021. 146(24): p. 7431-7449. 2. Li, R., Forensic biology. 2015: CRC press. 3. Skoog, D.A., et al., Fundamentals of analytical chemistry. 2013: Cengage learning.
4. Muro, C.K., et al., Forensic body fl uid identifi cation and differentiation by Raman spectroscopy. Forensic Chemistry, 2016. 1: p. 31-38.
5. Virkler, K. and I.K. Lednev, Analysis of body fl uids for forensic purposes: from laboratory testing to non- destructive rapid confi rmatory identifi cation at a crime scene. Forensic science international, 2009. 188(1-3): p. 1-17.
6. Vyas, B., L. Halámková, and I.K. Lednev, A universal test for the forensic identifi cation of all main body fl uids including urine. Forensic Chemistry, 2020. 20: p. 100247.
7. Khandasammy, S.R., et al., Bloodstains, paintings, and drugs: Raman spectroscopy applications in forensic science. Forensic Chemistry, 2018. 8: p. 111-133.
Figure 3. Major pain points in forensic science that SupreMEtric’s technology aims to address.
The highly sensitive technology does not require any sample preparation, which complements the non-destructive analyses and ensures the preservation of forensic evidence. The fi rst-generation technology will be able to be integrated with benchtop Raman instruments for easy and convenient applications in crime laboratories (federal, state, or private). Raman spectroscopy is the most selective spectroscopic technique and a technology of choice for in-fi eld trace analysis for other forms of forensic evidence, which can be adapted for analysis of biological samples. In the future, SupreMEtric plans to integrate the technology with portable Raman instruments, which are already used in a variety of fi eld applications, to enable real-time identifi cation of bodily fl uids at the crime scene.
Recent advances in forensic DNA analysis have signifi cantly improved accuracy of suspect identifi cation. However, solving crimes, particularly violent ones, relies heavily on forensic evidence collected at a crime scene. Biological stains from bodily fl uids such as blood, saliva, sweat, urine, semen, and vaginal fl uid are the most sought-after pieces of evidence, as they can not only provide DNA evidence, but also help identify the perpetrator and uncover crime events. Currently only a small fraction of bodily fl uid analyses is admitted as probative evidence in court, and even fewer can withstand scrutiny of criminal defence, which demands admissions that are ‘beyond reasonable
8. McLaughlin, G., et al., Universal detection of body fl uid traces in situ with Raman hyperspectroscopy for forensic purposes: Evaluation of a new detection algorithm (HAMAND) using semen samples. Journal of Raman Spectroscopy, 2019. 50(8): p. 1147-1153.
9. Kistenev, Y.V., et al., A novel Raman spectroscopic method for detecting traces of blood on an interfering substrate. Sci Rep, 2023. 13(1): p. 5384.
10. Sikirzhytskaya, A., V. Sikirzhytski, and I.K. Lednev, Raman spectroscopy coupled with advanced statistics for differentiating menstrual and peripheral blood. Journal of biophotonics, 2014. 7(1‐2): p. 59-67.
11. McLaughlin, G., K.C. Doty, and I.K. Lednev, Discrimination of human and animal blood traces via Raman spectroscopy. Forensic science international, 2014. 238: p. 91-95.
12. Doty, K.C. and I.K. Lednev, Differentiating donor age groups based on Raman spectroscopy of bloodstains for forensic purposes. ACS central science, 2018. 4(7): p. 862-867.
13. Muro, C.K. and I.K. Lednev, Race differentiation based on Raman spectroscopy of semen traces for forensic purposes. Analytical chemistry, 2017. 89(8): p. 4344-4348.
14. Sikirzhytskaya, A., V. Sikirzhytski, and I.K. Lednev, Determining gender by Raman spectroscopy of a bloodstain. Analytical chemistry, 2017. 89(3): p. 1486-1492.
15. Doty, K.C., G. McLaughlin, and I.K. Lednev, A Raman “spectroscopic clock” for bloodstain age determination: the fi rst week after deposition. Analytical and bioanalytical chemistry, 2016. 408: p. 3993-4001.
16. Doty, K.C., C.K. Muro, and I.K. Lednev, Predicting the time of the crime: Bloodstain aging estimation for up to two years. Forensic Chemistry, 2017. 5: p. 1-7.
17. Weber, A.R. and I.K. Lednev, Crime clock–analytical studies for approximating time since deposition of bloodstains. Forensic Chemistry, 2020. 19: p. 100248.
18. Waltke, H., et al., Sexual assault cases: Exploring the importance of non-DNA forensic evidence. Natl Institute Justice, 2017. 279.
Read, Share and Comment on this Article, visit:
www.labmate-online.com/article
Interested in publishing a Technical Article?
WWW.LABMATE-ONLINE.COM
Contact Gwyneth on +44 (0)1727 855574
or email:
gwyneth@intlabmate.com Our articles are read by over 73,000 readers in print, online and via our Mobile App.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56
