Detection of lifestyle-related metabolites in humans from fingerprint analysis

Fingerprints have been used to identify individuals in forensic investigations since the late 19th century. However, recent research have shown that fingerprints can provide significantly more details about an individual, such as an individual’s personal traits including ethnicity, gender, age, heal...

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Main Author: Loo, Song Wei
Other Authors: Ng Kee Woei
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/172420
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1724202023-12-11T01:25:47Z Detection of lifestyle-related metabolites in humans from fingerprint analysis Loo, Song Wei Ng Kee Woei School of Materials Science and Engineering KWNG@ntu.edu.sg Engineering::Materials Fingerprints have been used to identify individuals in forensic investigations since the late 19th century. However, recent research have shown that fingerprints can provide significantly more details about an individual, such as an individual’s personal traits including ethnicity, gender, age, health states, personal habits or diet. Others have demonstrated that fingerprint residues before and after coffee consumption displayed significant differences and a few coffee-specific metabolites have been proposed as biomarkers as a result. This project therefore investigates the hypothesis that metabolites resulting from caffeine consumption can be detected in latent fingerprints using MALDI-ToF-MS. Results showed that MALDI-ToF-MS can detect standard solutions of caffeine and its metabolites with satisfactory coefficient of determination. It can also detect individual compounds present in a mixture, with the exception of compounds that share similar molecular masses, for instance, 1X and 3X, 17U and 37U. As an approach to replace conventional liquid matrices with fingerprint dusting powders for MALDI-ToF-MS, APTES- and PTEOS- functionalized particles were synthesized and characterized via TEM, DLS and BET analysis. Both particles were able to ionize caffeine and its metabolites for detection via MALDI-ToF-MS analysis with low limit of detection. However from MALDI-ToF-MS analysis, caffeine could only be detected in overlapped prints spiked with 200 μg of caffeine when DHB was used as matrix. Both APTES- and PTEOS-functionalized particles were not able to support the detection of caffeine in actual fingerprints based on current protocol. Expected analyte peaks were not detected in fingerprint residues of different volunteers upon coffee consumption. This could be due to the large size and unfavorable surface properties of the particles, along with the relatively low sensitivity of the MALDI-ToF system. Master of Engineering 2023-12-11T01:25:47Z 2023-12-11T01:25:47Z 2023 Thesis-Master by Research Loo, S. W. (2023). Detection of lifestyle-related metabolites in humans from fingerprint analysis. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172420 https://hdl.handle.net/10356/172420 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Materials
spellingShingle Engineering::Materials
Loo, Song Wei
Detection of lifestyle-related metabolites in humans from fingerprint analysis
description Fingerprints have been used to identify individuals in forensic investigations since the late 19th century. However, recent research have shown that fingerprints can provide significantly more details about an individual, such as an individual’s personal traits including ethnicity, gender, age, health states, personal habits or diet. Others have demonstrated that fingerprint residues before and after coffee consumption displayed significant differences and a few coffee-specific metabolites have been proposed as biomarkers as a result. This project therefore investigates the hypothesis that metabolites resulting from caffeine consumption can be detected in latent fingerprints using MALDI-ToF-MS. Results showed that MALDI-ToF-MS can detect standard solutions of caffeine and its metabolites with satisfactory coefficient of determination. It can also detect individual compounds present in a mixture, with the exception of compounds that share similar molecular masses, for instance, 1X and 3X, 17U and 37U. As an approach to replace conventional liquid matrices with fingerprint dusting powders for MALDI-ToF-MS, APTES- and PTEOS- functionalized particles were synthesized and characterized via TEM, DLS and BET analysis. Both particles were able to ionize caffeine and its metabolites for detection via MALDI-ToF-MS analysis with low limit of detection. However from MALDI-ToF-MS analysis, caffeine could only be detected in overlapped prints spiked with 200 μg of caffeine when DHB was used as matrix. Both APTES- and PTEOS-functionalized particles were not able to support the detection of caffeine in actual fingerprints based on current protocol. Expected analyte peaks were not detected in fingerprint residues of different volunteers upon coffee consumption. This could be due to the large size and unfavorable surface properties of the particles, along with the relatively low sensitivity of the MALDI-ToF system.
author2 Ng Kee Woei
author_facet Ng Kee Woei
Loo, Song Wei
format Thesis-Master by Research
author Loo, Song Wei
author_sort Loo, Song Wei
title Detection of lifestyle-related metabolites in humans from fingerprint analysis
title_short Detection of lifestyle-related metabolites in humans from fingerprint analysis
title_full Detection of lifestyle-related metabolites in humans from fingerprint analysis
title_fullStr Detection of lifestyle-related metabolites in humans from fingerprint analysis
title_full_unstemmed Detection of lifestyle-related metabolites in humans from fingerprint analysis
title_sort detection of lifestyle-related metabolites in humans from fingerprint analysis
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/172420
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