Evidence map›Paper›PMID 38589994›Full record

ArticleDrug testing and analysis2025

A direct analysis method using sheath flow probe electrospray ionisation-mass spectrometry (sfPESI-MS) to detect drug residues from fingerprint forensic gel lifts.

Ayoung Kim, Paul F Kelly, Matthew A Turner, James C Reynolds

Abstract read
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Article in Drug testing and analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ayoung KimCentre for Analytical Science, Department of Chemistry, Loughborough University, Loughborough, UK.ORCID https://orcid.org/0000-0001-7117-7338
Paul F KellyCentre for Analytical Science, Department of Chemistry, Loughborough University, Loughborough, UK.
Matthew A TurnerCentre for Analytical Science, Department of Chemistry, Loughborough University, Loughborough, UK.
James C ReynoldsCentre for Analytical Science, Department of Chemistry, Loughborough University, Loughborough, UK.ORCID https://orcid.org/0000-0003-1176-3030

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Latent fingerprints at crime scenes are frequently recovered using forensic gel-lifters, which can help to preserve the crime scene and to enhance visualisation of traces such as blood or paint. In addition to providing fingerprint ridge detail, additional chemical information can also be recovered from gel lifts that may prove pertinent to an investigation. However, while DNA and metal ions have been shown to be able to be detected in gel-lifted fingerprints, the determination of other types of chemical information such as the presence of drugs in gel-lifted prints has not been previously shown. This study demonstrates the application of an ambient ionisation method, sheath flow probe electrospray ionisation-mass spectrometry (sfPESI-MS), to the direct analysis of gel-lifted fingerprints. A model drug compound (zolpidem) is successfully detected from gel-lifted prints from three different surface types: glass, metal, and paper. The surface activity-based separation associated with probe electrospray approaches is shown to resolve zolpidem ions from background phthalate species, significantly enhancing the response obtained from the gel-lifter. A depletion series experiment shows that the drug residue can be detected with up to 100% efficiency after eight consecutive contacts; however, detection efficiency drops to 20% after 30 contacts. The developed approach has potential application to analysis of historical gel-lifters to obtain additional chemical information.

Indexed as

DermatoglyphicsDrug ResiduesPyridinesSpectrometry, Mass, Electrospray IonizationGelsHumansGelsPyridinesambient ionisationdirect analysisfingerprintsforensic analysisprobe electrospray

Identifiers

PMID38589994
PMCPMC11729265

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.