Evidence map›Paper›PMID 39774298›Full record

ArticleScientific reports2025

Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Yingbin Wang, Yulong Huang, Xiaobao Liu, Chishan Kang, Wenjie Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026
    Review
  2. Review
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

5 authors.

Yingbin WangDepartment of Ophthalmology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, 134 Dongjie Rd, Fuzhou, 350001, Fujian, China.
Yulong HuangShengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China.
Xiaobao LiuShengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China.
Chishan KangShengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China.
Wenjie WuDepartment of Ophthalmology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, 134 Dongjie Rd, Fuzhou, 350001, Fujian, China. wenjie_wu@foxmail.com.

Funding

Medical Innovation Project of Fujian Province 2023CXA001Natural Science Foundation of Fujian Province 2022J01121889
6 · The paper itself

Abstract

With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tears using drop coating deposition-surface enhanced Raman spectroscopy (DCD-SERS) combined with machine learning (ML). Using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), the average concentration of EPH in tear fluid of Sprague-Dawley (SD) rats, measured over 3 h post-injection, was 1235 ng/mL. DCD-SERS effectively identified EPH in tear samples, with distinct Raman peaks observed at 1001 cm

Indexed as

Machine LearningRats, Sprague-DawleySpectrum Analysis, RamanSubstance Abuse DetectionTearsAlgorithmsAnimalsDiscriminant AnalysisMaleRatsSubstance-Related DisordersTandem Mass SpectrometryDrug abuseEphedrineMachine learningSurface enhanced Raman spectroscopyTear

Identifiers

PMID39774298
PMCPMC11707011

What OpenQuestion holds

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Registered trials

None linked

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.