Detection and Direct Readout of Drugs in Human Urine Using Dynamic Surface-Enhanced Raman Spectroscopy and Support Vector Machines

Dong, Ronglu; Weng, Shizhuang; Yang, Liangbao; Liu, Jinhuai

doi:10.1021/acs.analchem.5b00137

Cited by 159 publications

(81 citation statements)

References 39 publications

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“…The concept of dynamic SERS has been recently proposed to achieve the simple and sensitive SERS detection with plasmonic nanoparticles at metastable state during volatilization process as the SERS enhancing substrates. [19,20] Herein, dynamic SERS method is utilized to detect the pesticides in vegetables, with silver nanoparticles (AgNPs) serving as the SERS substrates. In this method, silver nanoparticles capped with citrate ions are mixed with the pesticides solution, and the mixed solution is dropped onto the silicon wafer.…”

Section: Introductionmentioning

confidence: 99%

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

Chen

Long

Song

et al. 2020

J Raman Spectroscopy

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Pesticide residues are one of the major food safety concerns for consumers all over the world, and it is crucial to develop simple, rapid, and effective method for the detection of pesticide residues. In the study, we report the sensitive detection of pesticides with the dynamic surface‐enhanced Raman spectroscopy (dynamic SERS) method. The dynamic SERS method provides excellent detection sensitivity at the metastable state of plasmonic nanoparticles in the sessile drop, which is a critical state between the wet state and dry state during the volatilization process. With this simple and rapid method, the SERS performance towards four pesticides, paraquat, thiabendazole, tricyclazole, and isocarbophos, is investigated with silver nanoparticles (AgNPs) as the enhancing reagents. The characteristic SERS spectra of paraquat, thiabendazole, tricyclazole, and isocarbophos can be detected at concentrations down to 1 × 10−9 M, 5 × 10−9 M, 5.28 × 10−9 M, and 3.45 × 10−7 M, respectively. The pesticides are also discriminable at the same concentrations as the standard solution counterparts from the pesticides spiked vegetable extracts, and linear relationship can be drawn from the characteristic peak intensities and negative logarithm of concentrations of the four pesticides. Therefore, the simple and rapid dynamic SERS method shows great potential in the practical detection of pesticide residues.

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Section: Introductionmentioning

confidence: 99%

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

Chen

Long

Song

et al. 2020

J Raman Spectroscopy

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“…27 Dong et al employed (dynamic) D-SERS and support vector machines for the quanti-tative detection of methamphetamine in human urine. 28 Andreou et al also reported the detection of methamphet-amine in saliva samples using a microfluidic device which controlled the interaction between the drug, Ag nanoparticles, and the aggregation agent. 29 Finally, in a more recent study, we have also demonstrated SERS as a powerful technique for the quantitative detection of the beta-blocker propranolol in human biofluids (serum, plasma, urine) when combined with chemometric approaches.…”

Section: Introductionmentioning

confidence: 99%

Quantitative detection of codeine in human plasma using surface-enhanced Raman scattering via adaptation of the isotopic labelling principle

Subaihi

Muhamadali

Mutter

et al. 2017

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aIn this study surface enhanced Raman scattering (SERS) combined with the isotopic labelling (IL) principle has been used for the quantification of codeine spiked into both water and human plasma. Multivariate statistical approaches were employed for the analysis of these SERS spectral data, particularly partial least squares regression (PLSR) which was used to generate models using the full SERS spectral data for quantification of codeine with, and without, an internal isotopic labelled standard. The PLSR models provided accurate codeine quantification in water and human plasma with high prediction accuracy (Q 2 ). In addition, the employment of codeine-d6 as the internal standard further improved the accuracy of the model, by increasing the Q 2 from 0.89 to 0.94 and decreasing the low root-mean-square error of predictions (RMSEP) from 11.36 to 8.44. Using the peak area at 1281 cm −1 assigned to C-N stretching, C-H wagging and ring breathing, the limit of detection was calculated in both water and human plasma to be 0.7 µM (209.55 ng mL −1) and 1.39 µM (416.12 ng mL −1 ), respectively. Due to a lack of definitive codeine vibrational assignments, density functional theory (DFT) calculations have also been used to assign the spectral bands with their corresponding vibrational modes, which were in excellent agreement with our experimental Raman and SERS findings. Thus, we have successfully demonstrated the application of SERS with isotope labelling for the absolute quantification of codeine in human plasma for the first time with a high degree of accuracy and reproducibility. The use of the IL principle which employs an isotopolog (that is to say, a molecule which is only diff erent by the substitution of atoms by isotopes) improves quantifi-cation and reproducibility because the competition of the codeine and codeine-d6 for the metal surface used for SERS is equal and this will off set any diff erence in the number of particles under analysis or any fluctuations in laser fluence. It is our belief that this may open up new exciting opportunities for testing SERS in real-world samples and applications which would be an area of potential future studies.

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“…Examples of SERS based metabolomics include the work that identified and quantified nicotine and two of its major metabolites, 13 that separated and identified pyrimidine and purine bases following liquid chromatography, 14 and that detected methamphetamines in urine using Au nanorods and a portable Raman detector. 15 …”

Section: Introductionmentioning

confidence: 99%

Sheath flow SERS for chemical profiling in urine

et al. 2016

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The molecular specificity and sensitivity of surface enhanced Raman scattering (SERS) makes it an attractive method for biomedical diagnostics. Here we present results demonstrating the utility and complications for SERS characterization in urine. The chemical fingerprint characteristic of Raman spectra suggests use as a label free diagnostic; however, the complex composition of biological fluids presents a tremendous challenge. In particular, the limited number of surface sites and competing absorption tend to mask the presence of analytes in solution, particularly when the solution contains multiple analytes. To address these problems and characterize biological fluids we have demonstrated a sheath-flow interface for SERS detection. This sheath-flow SERS interface uses hydrodynamic focusing to confine analyte molecules eluting out of a column onto a planar SERS substrate where the molecules are detected by their intrinsic SERS signal. In this report we compare direct detection of benzoylecgonine in urine using DSERS with chemical profiling by capillary zone electrophoresis and sheath-flow SERS detection. The SERS spectrum from the observed migration peaks can identify benzoylecgonine and other distinct spectra are also observed, suggesting improved chemical diagnostics in urine. With over 2000 reported compounds in urine, identification of each of the detected species is an enormous task. Nonetheless, these samples provide a benchmark to establish the potential clinical utility of sheath-flow SERS detection.

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Detection and Direct Readout of Drugs in Human Urine Using Dynamic Surface-Enhanced Raman Spectroscopy and Support Vector Machines

Cited by 159 publications

References 39 publications

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

Rapid and sensitive detection of pesticide residues using dynamic surface‐enhanced Raman spectroscopy

Quantitative detection of codeine in human plasma using surface-enhanced Raman scattering via adaptation of the isotopic labelling principle

Sheath flow SERS for chemical profiling in urine

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