1. Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.
- Author
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Wang Y, Huang Y, Liu X, Kang C, and Wu W
- Subjects
- Animals, Rats, Tandem Mass Spectrometry methods, Male, Substance-Related Disorders diagnosis, Discriminant Analysis, Algorithms, Spectrum Analysis, Raman methods, Machine Learning, Rats, Sprague-Dawley, Tears chemistry, Substance Abuse Detection methods
- 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
-1 and 1242 cm-1 . To enable rapid analysis of complex SERS data, three ML algorithms-linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), and random forest (RF)-were employed. These algorithms achieved over 90% accuracy in distinguishing between EPH-injected and non-injected SD rats, with area under the ROC curve (AUC) values ranging from 0.9821 to 0.9911. This approach offers significant potential for law enforcement by being easily accessible, non-invasive and ethically appropriate for examinees, while being rapid, accurate, and affordable for examiners., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval: The Institutional Animal Care and Use Committee of Fujian Provincial Hospital approved all procedures involving animals (IACUC-FPH-SL-20230911[0093]). This study was performed in accordance with relevant guidelines and regulations. All methods are reported in accordance with ARRIVE guidelines., (© 2025. The Author(s).)- Published
- 2025
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