Detection and identification of drug traces in latent fingermarks using Raman spectroscopy
Abstract Recent advancements in analytical techniques have greatly contributed to the analysis of latent fingermarks’ (LFMs) “touch chemistry” and identification of materials that a suspect might have come into contact with. This type of information about the FM donor is valuable for criminal invest...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-07168-6 |
| _version_ | 1818491717127503872 |
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| author | Mohamed O. Amin Entesar Al-Hetlani Igor K. Lednev |
| author_facet | Mohamed O. Amin Entesar Al-Hetlani Igor K. Lednev |
| author_sort | Mohamed O. Amin |
| collection | DOAJ |
| description | Abstract Recent advancements in analytical techniques have greatly contributed to the analysis of latent fingermarks’ (LFMs) “touch chemistry” and identification of materials that a suspect might have come into contact with. This type of information about the FM donor is valuable for criminal investigations because it narrows the pool of suspects. It is estimated that at least 30 million people around the world take over-the-counter and prescription nonsteroidal anti-inflammatory drugs (NSAIDs) for pain relief, headaches and arthritis every day. The daily use of such drugs can lead to an increased risk of their abuse. In the present study, Raman spectroscopy combined with multivariate statistical analysis was used for the detection and identification of drug traces in LFMs when NSAID tablets of aspirin, ibuprofen, diclofenac, ketoprofen and naproxen have been touched. Partial least squares discriminant analysis of Raman spectra showed an excellent separation between natural FMs and all NSAID-contaminated FMs. The developed classification model was externally validated using FMs deposited by a new donor and showed 100% accuracy on a FM level. This proof-of-concept study demonstrated the great potential of Raman spectroscopy in the chemical analysis of LFMs and the detection and identification of drug traces in particular. |
| first_indexed | 2024-12-10T17:34:41Z |
| format | Article |
| id | doaj.art-3b616ce54cd644d4af34ee64856b9757 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-10T17:34:41Z |
| publishDate | 2022-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-3b616ce54cd644d4af34ee64856b97572022-12-22T01:39:35ZengNature PortfolioScientific Reports2045-23222022-02-011211910.1038/s41598-022-07168-6Detection and identification of drug traces in latent fingermarks using Raman spectroscopyMohamed O. Amin0Entesar Al-Hetlani1Igor K. Lednev2Department of Chemistry, Kuwait University, Faculty of ScienceDepartment of Chemistry, Kuwait University, Faculty of ScienceDepartment of Chemistry, University at Albany, SUNYAbstract Recent advancements in analytical techniques have greatly contributed to the analysis of latent fingermarks’ (LFMs) “touch chemistry” and identification of materials that a suspect might have come into contact with. This type of information about the FM donor is valuable for criminal investigations because it narrows the pool of suspects. It is estimated that at least 30 million people around the world take over-the-counter and prescription nonsteroidal anti-inflammatory drugs (NSAIDs) for pain relief, headaches and arthritis every day. The daily use of such drugs can lead to an increased risk of their abuse. In the present study, Raman spectroscopy combined with multivariate statistical analysis was used for the detection and identification of drug traces in LFMs when NSAID tablets of aspirin, ibuprofen, diclofenac, ketoprofen and naproxen have been touched. Partial least squares discriminant analysis of Raman spectra showed an excellent separation between natural FMs and all NSAID-contaminated FMs. The developed classification model was externally validated using FMs deposited by a new donor and showed 100% accuracy on a FM level. This proof-of-concept study demonstrated the great potential of Raman spectroscopy in the chemical analysis of LFMs and the detection and identification of drug traces in particular.https://doi.org/10.1038/s41598-022-07168-6 |
| spellingShingle | Mohamed O. Amin Entesar Al-Hetlani Igor K. Lednev Detection and identification of drug traces in latent fingermarks using Raman spectroscopy Scientific Reports |
| title | Detection and identification of drug traces in latent fingermarks using Raman spectroscopy |
| title_full | Detection and identification of drug traces in latent fingermarks using Raman spectroscopy |
| title_fullStr | Detection and identification of drug traces in latent fingermarks using Raman spectroscopy |
| title_full_unstemmed | Detection and identification of drug traces in latent fingermarks using Raman spectroscopy |
| title_short | Detection and identification of drug traces in latent fingermarks using Raman spectroscopy |
| title_sort | detection and identification of drug traces in latent fingermarks using raman spectroscopy |
| url | https://doi.org/10.1038/s41598-022-07168-6 |
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