Potential of triacylglycerol profiles in latent fingerprints to reveal individual diet, exercise, or health information for forensic evidence

O'Neill, Kelly C.; Hinners, Paige; Lee, Young Jin

doi:10.1039/c9ay02652e

Cited by 17 publications

(17 citation statements)

References 31 publications

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“…The relative composition can vary depending on variables such as amount of contact between fingertips and other parts of the body and thus the level of sebum-contamination picked up. As such inter-and intra-donor variation has been demonstrated in many studies (Archer, Charles, Elliott, & Jickells, 2005;Bailey et al, 2012;Croxton et al, 2010;Dorakumbura, Busetti, & Lewis, 2019;Emmerson, Gidden, Lay, & Durham, 2011;Ferguson, Creasey, Wolstenholme, Clench, & Francese, 2013;Frick & Weyermann, 2019;O'Neill, Hinners, & Lee, 2020;Weyermann, Roux, & Champod, 2011). The substrate has been shown to affect the amount of material deposited (Weyermann et al, 2011).…”

Section: Sebaceous Sweatmentioning

confidence: 87%

The forensic exploitation of fingermark chemistry: A review

Bleay

Bailey

Croxton

et al. 2020

WIREs Forensic Science

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The substances deposited from the fingertip onto a surface during contact between them represent a highly complex range of chemicals that can be exploited in a variety of ways in a forensic investigation. An overview is given of the multitude of chemicals that have been detected in fingermarks, including those occurring in endogenous sweat, metabolites of ingested substances, and exogenous substances picked up on the fingertip. Changes in chemistry that may occur between deposition of the fingermark and its subsequent forensic analysis are discussed, with particular reference to the ways in which these changes have been considered as a means of dating fingermarks. The ways in which fingermark enhancement reagents utilize the different chemicals present to reveal ridge is reviewed, together with how different classes of chemical can be sequentially targeted to optimize the number of fingermarks recovered.A field of increasing interest is the use of advanced analytical techniques incorporating mass spectrometry and imaging capability to simultaneously obtain additional contextual information about the donor of the mark while visualizing the fingermark ridge pattern. Examples are given of how such information can be applied in forensic investigations. It is concluded that an extensive "tool kit" of fingermark enhancement processes is already available to utilize the different chemicals present, and the advances that can be made in this field using conventional approaches are limited. There is, instead, significant potential to utilize analytical techniques to forensically exploit the chemical information within fingermarks but there are also significant barriers to their implementation in this way.

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Section: Sebaceous Sweatmentioning

confidence: 87%

The forensic exploitation of fingermark chemistry: A review

Bleay

Bailey

Croxton

et al. 2020

WIREs Forensic Science

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show abstract

“…For example, unsaturated lipid molecules present in sebum are susceptible to ozonolysis and over time, their amount decreases (Archer et al, 2005;Pleik et al, 2016;Pleik et al, 2018;Hinners et al, 2020). Additionally, fingerprints may be able to assist law enforcement in developing a profile, as their composition can possibly indicate identifying characteristics like age, sex, and lifestyle (Zhou and Zare, 2017;Hinners et al, 2018;O'Neill et al, 2020;Bouslimani et al, 2016;van Helmond et al, 2019;Ferguson et al, 2012). Fingerprints have also been considered for clinical applications (Shetage et al, 2018), such as assays for diagnosing and monitoring metabolic disorders like diabetes (O'Neill et al, 2020;Hyde and Runyon, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, fingerprints may be able to assist law enforcement in developing a profile, as their composition can possibly indicate identifying characteristics like age, sex, and lifestyle (Zhou and Zare, 2017;Hinners et al, 2018;O'Neill et al, 2020;Bouslimani et al, 2016;van Helmond et al, 2019;Ferguson et al, 2012). Fingerprints have also been considered for clinical applications (Shetage et al, 2018), such as assays for diagnosing and monitoring metabolic disorders like diabetes (O'Neill et al, 2020;Hyde and Runyon, 2020). To harness the full power and potential of fingerprint analysis, machine learning tools need to be incorporated into the analysis workflow.…”

Section: Introductionmentioning

confidence: 99%

Leveraging R (LevR) for fast processing of mass spectrometry data and machine learning: Applications analyzing fingerprints and glycopeptides

2022

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Applying machine learning strategies to interpret mass spectrometry data has the potential to revolutionize the way in which disease is diagnosed, prognosed, and treated. A persistent and tedious obstacle, however, is relaying mass spectrometry data to the machine learning algorithm. Given the native format and large size of mass spectrometry data files, preprocessing is a critical step. To ameliorate this challenge, we sought to create an easy-to-use, continuous pipeline that runs from data acquisition to the machine learning algorithm. Here, we present a start-to-finish pipeline designed to facilitate supervised and unsupervised classification of mass spectrometry data. The input can be any ESI data set collected by LC-MS or flow injection, and the output is a machine learning ready matrix, in which each row is a feature (an abundance of a particular m/z), and each column is a sample. This workflow provides automated handling of large mass spectrometry data sets for researchers seeking to implement machine learning strategies but who lack expertise in programming/coding to rapidly format the data. We demonstrate how the pipeline can be used on two different mass spectrometry data sets: 1) ESI-MS of fingerprint lipid compositions acquired by direct infusion and, 2) LC-MS of IgG glycopeptides. This workflow is uncomplicated and provides value via its simplicity and effectiveness.

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“…Triacylglycerols have been recently tentatively proposed to have potential for providing information on diet and exercise as well as health related information. 4…”

Section: Introductionmentioning

confidence: 99%

Exploring the problem of determining human age from fingermarks using MALDI MS-machine learning combined approaches

et al. 2022

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Potential of triacylglycerol profiles in latent fingerprints to reveal individual diet, exercise, or health information for forensic evidence

Abstract: Relative levels of triacylglycerols found in latent fingerprints have the potential to provide health information, diet, and exercise.

Cited by 17 publications

References 31 publications

The forensic exploitation of fingermark chemistry: A review

The forensic exploitation of fingermark chemistry: A review

Leveraging R (LevR) for fast processing of mass spectrometry data and machine learning: Applications analyzing fingerprints and glycopeptides

Exploring the problem of determining human age from fingermarks using MALDI MS-machine learning combined approaches

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