Surface Enhanced Raman Spectroscopy Analysis of Fentanyl in Urine Based on Voigt Line
HE Yao1, 2, LI Wei1, 2, DONG Rong-lu2, QI Qiu-jing3, LI Ping5, LIN Dong-yue2*, MENG Fan-li4, YANG Liang-bao2*
1. Institute of Physical Science and Information Technology, Anhui University, Hefei 230039, China
2. Institute of Health & Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
3. Anhui Provincial Public Security Bureau Physical Evidence Identification Management Office, Hefei 230000, China
4. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
5. Center for Disease Control and Prevention in Dongying, Dongying 257091, China
Abstract:Fentanyl substance abuse and death cases frequently occur worldwide, and the detection and identification of fentanyl substances in the human body are becoming increasingly important. After some time in the human body, some of the fentanyl substances are still discharged with urine, so the history of drug abuse can be reflected by detecting fentanyl substances in the urine. Surface Enhanced Raman Spectroscopy ( SERS ) is fast, sensitive and easy to operate, which is suitable for the field detection and analysis of fentanyl in urine. However, the background peaks of urea and other substances in urine are highly coincident with the SERS characteristic peaks of fentanyl, and the characteristic peaks of fentanyl are covered by the background peaks of urine, which causes great interference with the spectral identification of fentanyl in urine.In this paper, the spectral peak analysis model is established based on the Voigt line, and the spectral peak analysis of the overlapping part of urine and fentanyl is carried out. Because of the interference of SERS spectral noise and fluorescence on the peak analytical model, the unconstrained Nelder-Mead algorithm is used to optimize and calculate the model. The algorithm is insensitive to the initial value of iterative parameters to improve the accuracy of the peak analytical model. According to the characteristics of the half-peak width of the SERS spectrum, the analytical peak set was screened, and the urine background peak of the SERS spectrum was deducted to restore the spectral peak characteristics of the fentanyl SERS spectrum at 1 000 and 1 030 cm-1.The experimental results and phenomena show that the spectral peak analysis model established by the Voigt line shape has a fitting degree of more than 99% for the SERS spectrum of fentanyl in urine and can restore the SERS spectrum characteristics of fentanyl in urine through the screening of the peak solution set. The characteristics of the half-peak width and peak ratio of the reduced spectrum and the characteristic peaks of fentanyl are highly consistent. When the SERS spectrum of blank urine is analyzed, the analytical peak set does not contain the characteristic peaks of fentanyl substances, which can effectively distinguish blank urine from urine containing fentanyl substances. The reduced spectral fragment (935~1 100 cm-1) was identified by the hit quality index (HQI), which can effectively distinguish Ofentanyl, Furanyl and Acetylfentanyl in urine and improve the discrimination between spectra. This analytical model is expected to provide a way to solve practical problems for the identification and judgment of fentanyl in urine.
何 遥,李 伟,董荣录,祁秋景,李 萍,林东岳,孟凡利,杨良保. 基于Voigt线型的尿液中芬太尼类表面增强拉曼光谱解析[J]. 光谱学与光谱分析, 2023, 43(01): 85-92.
HE Yao, LI Wei, DONG Rong-lu, QI Qiu-jing, LI Ping, LIN Dong-yue, MENG Fan-li, YANG Liang-bao. Surface Enhanced Raman Spectroscopy Analysis of Fentanyl in Urine Based on Voigt Line. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 85-92.
[1] Comer S D, Pravetoni M, Coop A, et al. Drug and Alcohol Dependence, 2021, 221(3): 108530.
[2] O’donnell J, Gladden R M, Kariisa M, et al. Addiction, 2022, 117(5): 1483.
[3] Jannetto P J, Helander A, Garg U, et al. Clinical Chemistry, 2019, 65(2): 242.
[4] WANG Ji-fen, LÜ Yu-fan, FAN Lin-yuan, et al(王继芬, 吕昱帆, 范琳媛, 等). Science Technology and Engineering(科学技术与工程), 2020, 20(6): 2105.
[5] CHEN Shuai-feng, ZHEN Cheng, SHI Lu-wen(陈帅锋, 甄 橙, 史录文). Chinese Journal of New Drugs(中国新药杂志), 2021, 30(11): 989.
[6] Busardo F P, Carlier J, Giorgetti R, et al. Frontiers in Chemistry, 2019, 7: 184.
[7] Kumar S, Tokunaga K, Namura K, et al. Journal of Physical Chemistry C, 2020, 124(38): 21215.
[8] Yang X, Zhou Z, Qi J, et al. IEEE Access, 2021, 9: 121279.
[9] Seo M J, Kim G W, Tsalu P V, et al. Nanoscale Horizons, 2020, 5(2): 345.
[10] Dao D Q, Ngo T C, Le T T H, et al. Journal of Physical Chemistry A, 2021, 125(39): 8529.
[11] Smith M, Logan M, Bazley M, et al. Journal of Forensic Sciences, 2021, 66(2): 505.
[12] Fan D, Li S S, Li X X, et al. Remote Sensing, 2021, 13(1): 64.
[13] LIU Cai-zheng, ZHU Qi-bing, HUANG Min, et al(刘财政, 朱启兵, 黄 敏, 等). Laser & Optoelectronics Progress(激光与光电子学进展), 2019, 56(8): 083004.
[14] Barton S, Alakkari S, O’dwyer K, et al. Sensors, 2021, 21(14): 4623.
[15] Luo S H, Wang X, Chen G Y, et al. Analytical Chemistry, 2021, 93(24): 8408.
[16] Goncalves M L N, Menezes T C. Journal of Complexity, 2020, 58: 101459.
[17] Galantai A. Acta Polytechnica Hungarica, 2021, 18(5): 93.
[18] YAN Fan, ZHU Qi-bing, HUANG Min, et al(颜 凡, 朱启兵, 黄 敏, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(11): 3599.
[19] Zhang R Q, Shang Z C, Lu S Q, et al. Chemometrics and Intelligent Laboratory Systems, 2021, 215: 104353.
[20] Wang L, Deriu C, Wu W S, et al. Journal of Raman Spectroscopy, 2019, 50(10): 1405.