scholarly journals Novel Surface-Enhanced Raman Spectroscopy Techniques for DNA, Protein and Drug Detection

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1712 ◽  
Author(s):  
Chuanpin Chen ◽  
Wenfang Liu ◽  
Sanping Tian ◽  
Tingting Hong
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Spectroscopic Technique ◽  
Machine Learning Techniques ◽  
Drug Detection ◽  
Learning Techniques ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Sers Detection ◽  
Scattering Signal

Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopic technique in which the Raman scattering signal strength of molecules, absorbed by rough metals or the surface of nanoparticles, experiences an exponential growth (103–106 times and even 1014–1015 times) because of electromagnetic or chemical enhancements. Nowadays, SERS has attracted tremendous attention in the field of analytical chemistry due to its specific advantages, including high selectivity, rich informative spectral properties, nondestructive testing, and the prominent multiplexing capabilities of Raman spectroscopy. In this review, we present the applications of state-of-the-art SERS for the detection of DNA, proteins and drugs. Moreover, we focus on highlighting the merits and mechanisms of achieving enhanced SERS signals for food safety and clinical treatment. The machine learning techniques, combined with SERS detection, are also indicated herein. This review concludes with recommendations for future studies on the development of SERS.

Identification of methicillin-resistant Staphylococcus aureus bacteria using surface-enhanced Raman spectroscopy and machine learning techniques

The Analyst ◽  
2020 ◽  
Vol 145 (23) ◽  
pp. 7559-7570
Author(s):  
Fatma Uysal Ciloglu ◽  
Ayse Mine Saridag ◽  
Ibrahim Halil Kilic ◽  
Mahmut Tokmakci ◽  
Mehmet Kahraman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Staphylococcus Aureus ◽  
Raman Spectroscopy ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Surface Enhanced Raman Spectroscopy ◽  
Machine Learning Techniques ◽  
Methicillin Resistant ◽  
Learning Techniques ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Herein, surface-enhanced Raman spectroscopy (SERS) combined with supervised and unsupervised machine learning techniques were used for the identification of methicillin-resistant and methicillin-sensitive Staphylococcus aureus.

Multivariate Analysis Aided Surface-Enhanced Raman Spectroscopy (MVA-SERS) Multiplex Quantitative Detection of Trace Fentanyl in Illicit Drug Mixtures Using a Handheld Raman Spectrometer

2021 ◽  
pp. 000370282110329
Author(s):  
Ling Wang ◽  
Mario O. Vendrell-Dones ◽  
Chiara Deriu ◽  
Sevde Doğruer ◽  
Peter de B. Harrington ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Principal Component ◽  
Surface Enhanced Raman Spectroscopy ◽  
Quantitative Detection ◽  
Least Squares Regression ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Sers Detection ◽  
Current Screening

Recently there has been upsurge in reports that illicit seizures of cocaine and heroin have been adulterated with fentanyl. Surface-enhanced Raman spectroscopy (SERS) provides a useful alternative to current screening procedures that permits detection of trace levels of fentanyl in mixtures. Samples are solubilized and allowed to interact with aggregated colloidal nanostars to produce a rapid and sensitive assay. In this study, we present the quantitative determination of fentanyl in heroin and cocaine using SERS, using a point-and-shoot handheld Raman system. Our protocol is optimized to detect pure fentanyl down to 0.20 ± 0.06 ng/mL and can also distinguish pure cocaine and heroin at ng/mL levels. Multiplex analysis of mixtures is enabled by combining SERS detection with principal component analysis and super partial least squares regression discriminate analysis (SPLS-DA), which allow for the determination of fentanyl as low as 0.05% in simulated seized heroin and 0.10% in simulated seized cocaine samples.

scholarly journals Progress of the applications of surface-enhanced Raman spectroscopy in illicit drug detection

2020 ◽  
Vol 51 (3) ◽  
pp. 294-309
Author(s):  
Ronglu Dong ◽  
Shaofei Li ◽  
Dongyue Lin ◽  
Hui Chen ◽  
Liangbao Yang
Keyword(s):  
Raman Spectroscopy ◽  
Illicit Drug ◽  
Surface Enhanced Raman Spectroscopy ◽  
Drug Detection ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

scholarly journals Optimization of Surface-Enhanced Raman Spectroscopy Detection Conditions for Interaction between Gonyautoxin and Its Aptamer

Toxins ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 49
Author(s):  
Yan Liu ◽  
Lijuan He ◽  
Yunli Zhao ◽  
Yongbing Cao ◽  
Zhiguo Yu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Colloid Solution ◽  
Silver Colloid ◽  
Enrichment Technique ◽  
Surface Enhanced ◽  
G Quadruplex ◽  
Surface Enhanced Raman ◽  
Sers Detection ◽  
Exponential Enrichment

This study aimed to optimize the detection conditions for surface-enhanced Raman spectroscopy (SERS) of single-stranded DNA (ssDNA) in four different buffers and explore the interaction between gonyautoxin (GTX1/4) and its aptamer, GO18. The influence of the silver colloid solution and MgSO4 concentration (0.01 M) added under four different buffered conditions on DNA SERS detection was studied to determine the optimum detection conditions. We explored the interaction between GTX1/4 and GO18 under the same conditions as those in the systematic evolution of ligands by exponential enrichment technique, using Tris-HCl as the buffer. The characteristic peaks of GO18 and its G-quadruplex were detected in four different buffer solutions. The change in peak intensity at 1656 cm−1 confirmed that the binding site between GTX1/4 and GO18 was in the G-quadruplex plane. The relative intensity of the peak at 1656 cm−1 was selected for the GTX1/4–GO18 complex (I1656/I1099) to plot the ratio of GTX1/4 in the Tris-HCl buffer condition (including 30 μL of silver colloid solution and 2 μL of MgSO4), and a linear relationship was obtained as follows: Y = 0.1867X + 1.2205 (R2 = 0.9239). This study provides a basis for subsequent application of SERS in the detection of ssDNA, as well as the binding of small toxins and aptamers.

scholarly journals Inhibiting Analyte Theft in Surface-Enhanced Raman Spectroscopy Substrates: Subnanomolar Quantitative Drug Detection

ACS Sensors ◽  
2019 ◽  
Vol 4 (11) ◽  
pp. 2988-2996 ◽  
Author(s):  
Bart de Nijs ◽  
Cloudy Carnegie ◽  
István Szabó ◽  
David-Benjamin Grys ◽  
Rohit Chikkaraddy ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Drug Detection ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Branched gold nanoparticles on ZnO 3D architecture as biomedical SERS sensors

RSC Advances ◽  
2015 ◽  
Vol 5 (113) ◽  
pp. 93644-93651 ◽  
Author(s):  
S. Picciolini ◽  
N. Castagnetti ◽  
R. Vanna ◽  
D. Mehn ◽  
M. Bedoni ◽  
...  
Keyword(s):  
Gold Nanoparticles ◽  
Raman Spectroscopy ◽  
Cancer Cells ◽  
Biomedical Application ◽  
Surface Enhanced Raman Spectroscopy ◽  
Drug Detection ◽  
3D Surface ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
3D Architecture

We present a new 3D surface-enhanced Raman spectroscopy substrate made of branched gold nanoparticles supported on ZnO tetrapods that was proved to be effective in different biomedical application such as drug detection and cancer cells analysis.

scholarly journals Multifunctional self-assembled composite colloids and their application to SERS detection

Nanoscale ◽  
2015 ◽  
Vol 7 (23) ◽  
pp. 10377-10381 ◽  
Author(s):  
Andrea La Porta ◽  
Ana Sánchez-Iglesias ◽  
Thomas Altantzis ◽  
Sara Bals ◽  
Marek Grzelczak ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Surface Enhanced Raman Spectroscopy ◽  
Colloidal System ◽  
Spectroscopy Analysis ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Sers Detection ◽  
Self Assembled

Development of a novel hybrid colloidal system suitable for surface-enhanced Raman spectroscopy analysis.

scholarly journals Detection of a Sudan dye at low concentrations by surface-enhanced Raman spectroscopy using silver nanoparticles

2019 ◽  
Vol 29 (4) ◽  
pp. 521
Author(s):  
Tran Cao Dao ◽  
Truc Quynh Ngan Luong ◽  
Tuan Anh Cao ◽  
Ngoc Minh Kieu
Keyword(s):  
Raman Spectroscopy ◽  
Silver Nanoparticles ◽  
Good Method ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Substrate ◽  
Sudan Dyes ◽  
Sudan I ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Sers Detection

Sudan dyes are red colorants banned from use for food due to their toxic properties. However, because of the cheapness, they are sometimes adulterated into food illegally. Currently surface-enhanced Raman spectroscopy (SERS) is emerging as a good method to detect residues (including trace amounts) of Sudan dyes in food. In this report we present the SERS detection of Sudan I (a type of Sudan dyes) to concentrations as low as 1 ppb, using a very simple SERS substrate, which is made from silver nanoparticles chemically deposited on silicon surface.

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