Compact SERS detection system enabling automated assay on disc combined with advanced data analysis – A case study of methotrexate

Surface enhanced Raman scattering (SERS) mapping of biomarkers has shown great promise in determining the distribution of proteins of interest in cells and tissues. Metallic nanoparticle (NP) probes are generally used in such mapping. Since SERS intensities from NPs are dependent on size, shape, and interparticle distance/distribution, it is unclear if this method can provide reliable biomarker quantification. To address this problem, we investigated a statistical approach to the quantification of SERS from SERS probe clusters. The investigation began by considering multiple biotinylated surfaces that had been exposed to pegylated NPs (designed for biological SERS mapping) functionalized with streptavidin (defined as SERS probes). The surfaces were imaged with a scanning electron microscope and SERS-mapped with a Raman microscope. Statistical distributions of the SERS probe clusters and mapped SERS intensities on the surfaces were developed. It was found that there was a smooth polynomial relationship between SERS intensity and probe cluster size. Our result is in contrast to the sharp, highly variable intensity increases observed in studies of unmodified NPs. Based on the polynomial relationship found, it is clear that pegylated NP SERS probes might be useful for quantification in the SERS mapping of biological material, as the SERS intensity can be potentially related back to the number of probes at the acquisition point.

In nuclear magnetic resonance (NMR) spectroscopy, the signal from nuclear spins is extremely weak, and thus, it has been desired to improve the signal-to-noise ratio (SNR). In this study, we designed a compact low-noise probe and peripheral detection system optimized for low-temperature solid-state NMR spectroscopy. We confirmed the operation of a Tx/Rx switch composed of radio frequency microelectromechanical system (RF MEMS) switches and a preamplifier using high electron mobility transistors (HEMTs), which can operate even at 20 K and under a high magnetic field of ∼10 T. In our compactly designed NMR system, we succeeded in sufficiently reducing both thermal noise and external noise. As a result, the 195Pt- and 27Al-NMR measurements for Pt and Al solid powder samples were performed at 12 T and down to 20 K, showing that the SNR was improved by 40%–50% compared with the conventional system. These experiments also provide information on the low temperature properties and operational characteristics of integrated RF electronic devices, such as the RF MEMS switch, the HEMT, and their combined circuit system.

pH-controllable drug carrier with SERS activity for targeting cancer cells

Highly sensitive SERS platform using sub-10-nm Ag nanoparticles on GaN distributed Bragg reflector for detecting organic pollutants

A novel surface-enhanced raman scattering strategy integrating spectral and mapping data for stable and rapid detection of aflatoxin B1 via supervised learning.

This study introduces a convenient and ultra-sensitive method of detection and quantification of the antiviral drug, tenofovir (TFV), by surface-enhanced Raman spectroscopy (SERS). Novel spatially resolved instrumentation for spectral acquisition and subsequent statistical analysis for hot spot selection was developed for convenient quantification of TFV in an aqueous matrix. Methods of statistical analysis include the use of partial least squares (PLS) regression vector analysis and spectral ranking by quality indices computed using CHAOS theory. Hydroxylamine-reduced Ag colloidal nanoparticles evaporated to dryness on an aluminum well-plate were used as the SERS substrate. To our knowledge, quantification of TFV down to 25 ng/mL by SERS, comprising clinically relevant concentrations, has not been previously reported. Furthermore, in this work we propose a novel method of quantification of aqueous TFV standards by SERS using statistical treatment of data by PLS and CHAOS theory. Based on these data, we propose future studies to develop a method of TFV detection and quantification in biological samples, beneficial to clinicians for rapid assessment of drug adherence during the treatment and prevention of viral diseases.

Recent advance in SERS techniques for food safety and quality analysis: a brief review

Thiabendazole is widely used in sclerotium blight, downy mildew and black rot prevention and treatment in rape. Accurate monitoring of thiabendazole pesticides in plants will prevent potential adverse effects to the Environment and human health. Surface Enhanced Raman Spectroscopy (SERS) is a highly sensitive fingerprint with the advantages of simple operation, convenient portability and high detection efficiency. In this paper, a rapid determination method of thiabendazole pesticides in rape was conducted combining SERS with chemometric methods. The original SERS were pretreated and the partial least squares (PLS) was applied to establish the prediction model between SERS and thiabendazole pesticides in rape. As a result, the SERS enhancing effect based on silver Nano-substrate was better than that of gold Nano-substrate, where the detection limit of thiabendazole pesticides in rape could reach 0.1 mg/L. Moreover, 782, 1007 and 1576 cm−1 could be determined as thiabendazole pesticides Raman characteristic peaks in rape. The prediction effect of thiabendazole pesticides in rape was the best ( = 0.94, RMSEP = 3.17 mg/L) after the original spectra preprocessed with 1st-Derivative, and the linear relevance between thiabendazole pesticides concentration and Raman peak intensity at 782 cm−1 was the highest (R2 = 0.91). Furthermore, five rape samples with unknown thiabendazole pesticides concentration were used to verify the accuracy and reliability of this method. It was showed that prediction relative standard deviation was 0.70–9.85%, recovery rate was 94.71–118.92% and t value was −1.489. In conclusion, the thiabendazole pesticides in rape could be rapidly and accurately detected by SERS, which was beneficial to provide a rapid, accurate and reliable scheme for the detection of pesticides residues in agriculture products.

Alcohol consumption triggers toxic effect to organs and tissues in the human body. The risks are essentially thought to be related to ethanol content in alcoholic beverages. The identification of ethanol in blood samples requires rapid, minimal sample handling, and non-destructive analysis, such as Raman Spectroscopy. This study aims to apply Raman Spectroscopy for identification of ethanol in blood samples. Silver nanoparticles were synthesized to obtain Surface Enhanced Raman Spectroscopy (SERS) spectra of blood samples. The SERS spectra were used for Partial Least Square (PLS) for determining ethanol quantitatively. To apply PLS method, 920~820 cm−1 band interval was chosen and the spectral changes of the observed concentrations statistically associated with each other. The blood samples were examined according to this model and the quantity of ethanol was determined as that: first a calibration method was established. A strong relationship was observed between known concentration values and the values obtained by PLS method (R2 = 1). Second instead of then, quantities of ethanol in 40 blood samples were predicted according to the calibration method. Quantitative analysis of the ethanol in the blood was done by analyzing the data obtained by Raman spectroscopy and the PLS method.

Rapid, sensitive, and specific detection of pathogenic Escherichia coli serotypes is crucial for food safety and public health. Here, we present a surface-enhanced Raman scattering (SERS) platform utilizing highly ordered silver nanorod (AgNR) arrays functionalized with vancomycin for efficient and selective bacterial capture. The system enables multiplexed, high-throughput analysis using a portable Raman spectrometer, achieving direct molecular fingerprinting of seven clinically relevant E. coli serotypes. Systematic optimization of AgNR length and vancomycin coating maximized SERS enhancement and capture efficiency. Advanced data analysis with linear discriminant analysis (LDA) provided robust discrimination among all serotypes and concentrations, achieving up to 100% classification accuracy in single-concentration models and an overall accuracy of 98.41% when all concentrations and serotypes were evaluated jointly. This integrated SERS approach demonstrates significant promise for rapid, on-site bacterial diagnostics and quantitative pathogen monitoring, paving the way for practical applications in food safety and clinical microbiology.

Abstract4‐aminothiophenol‐modified gold nanoparticles (PATP‐AuNPs) were used as colorimetric and Surface Enhanced Raman Scattering (SERS) probes for the sensitive detection of Escherichia coliDH5α, as a model for Gram‐negative bacteria. The nano‐probes were easy to prepare through Au‐S bonding. Under optimized conditions, the PATP‐AuNPs surface with positive charge can bind with negatively charged E.coliDH5α via electrostatic adhesion, resulting in a quick color change from red to blue, and also a dramatic SERS signal enhancement from thousands of AuNPs aggregated on the surface of bacteria, which was utilized for both colorimetric and SERS detection of E.coliDH5α. For colorimetric analysis, it is the first time that the classical partial least square (PLS) regression was utilized to deal with the relationship between adsorption and E.coliDH5α concentrations. Excellent linear relationship was observed from 1.1 x 107 to 1.3 x 108 cfu mL‐1 with the average relative error (ARE) of 5.430, which was more accurate than the traditional extinction ration method. When coupled with confocal Raman microscope, this PATP‐AuNPs probes could be used to detection SERS signals produced from even one single bacterium. This bioassay is rapid, less expensive and convenient for bacteria detection and analysis. Therefore, PATP‐AuNPs system as a novel, versatile, on‐site and real‐time Gram‐negative bacteria sensor, would have a wide range of practical applications.

The labelling of target biomolecules followed by detection using some form of optical spectroscopy has become common practice to aid in their detection. This approach has allowed the field of bioanalysis to dramatically expand; however, most methods suffer from the lack of the ability to discriminate between the components of a complex mixture. Currently, fluorescence spectroscopy is the method of choice but its ability to multiplex is greatly hampered by the broad overlapping spectra which are obtained. Surface enhanced resonance Raman scattering (SERRS) holds many advantages over fluorescence both in sensitivity and, more importantly here, in its ability to identify components in a mixture without separation due to the sharp fingerprint spectra obtained. Here the first multiplexed simultaneous detection of six different DNA sequences, corresponding to different strains of the Escherichia coli bacterium, each labelled with a different commercially available dye label (ROX, HEX, FAM, TET, Cy3, or TAMRA) is reported. This was achieved with the aid of multivariate analysis, also known as chemometrics, which can involve the application of a wide range of statistical and data analysis methods. In this study, both exploratory discriminant analysis and supervised learning, by partial least squares (PLS) regression, were used and the ability to discriminate whether a particular labelled oligonucleotide was present or absent in a mixture was achieved using PLS with very high sensitivity (0.98-1), specificity (0.98-1), accuracy (range 0.99-1), and precision (0.98-1).

Surface enhanced Raman spectroscopy (SERS) and spatial characterization of quartz-bound Au nanoparticle substrates has been used to assist the improvement of analytical sensitivity and limits of detection. SERS enhancement is significantly affected not only by a substrate's surface morphology but also laser-analyte orientation as well as matrix effects caused by non-analyte and non-metal substrate compounds. The use of Au hydrosols to fabricate better performing SERS substrates to detect chemical and/or biological agents has been an area of active and widespread research, but to date, the impact of matrix effects from spectral interferers introduced during fabrication on analytical sensitivity and limits of detection is not well understood. Experiments varying the depth of collection (observation) volume with respect to R6G on the substrate show high variability in analyte signal to noise ratios (S/N) well as high variability in background due to matrix effects from varying influences of the substrate non-metal components. Of the many post-fabrication design factors affecting SERS substrate sensitivity, characterization of matrix effects caused by vertical changes in observation volume near the analyte-substrate interface will improve analytical sensitivity and limits of detection.

While surface enhanced Raman spectroscopy (SERS) may not compete with the standard central lab approaches for chemical and biological sensing, SERS may have the potential to provide unique capabilities for analytics away from the central lab. Raman spectrometers have evolved from benchtop systems to high-performing handheld instruments that are compatible with analysis of samples in the field. However, for SERS to truly succeed as a “point-of-sample” analytical technique, the SERS sensor must fit the needs of analysis in the field, including little or no sample preparation, minimal peripheral equipment, and ease of use. Traditional plasmonically-active rigid devices do not meet these requirements. Even microfluidic SERS devices generally are not compatible with point-of-sample analysis, as the world-to-chip interface presents challenges, and peripheral equipment is generally required. In this review we will discuss the advances in plasmonic substrates fabricated on porous membranes, leading to SERS sensors that can collect samples via swabbing or dipping, clean up samples through separation, concentrate analytes by lateral flow focusing, and avoid the need for peripheral equipment. In particular, we will focus on inkjet-fabricated devices, which may present the best opportunity for scale-up via roll-to-roll manufacturing. We will also discuss the directions that flexible SERS sensors are moving the field, such as simple fabrication techniques, new support materials, SERS swabs, and SERS-active tapes and films.

In this study, we have applied Surface Enhanced Resonance Raman Scattering (SERRS) technology to the specific detection of DNA. We present an innovative SERRS sandwich-hybridization assay that allows specific DNA detection without any enzymatic amplification, such as is the case with Polymerase Chain Reaction (PCR). In some substrates, such as ancient or processed remains, enzymatic amplification fails due to DNA alteration (degradation, chemical modification) or to the presence of inhibitors. Consequently, the development of a non-enzymatic method, allowing specific DNA detection, could avoid long, expensive and inconclusive amplification trials. Here, we report the proof of concept of a SERRS sandwich-hybridization assay that leads to the detection of a specific chamois DNA. This SERRS assay reveals its potential as a non-enzymatic alternative technology to DNA amplification methods (particularly the PCR method) with several applications for species detection. As the amount and type of damage highly depend on the preservation conditions, the present SERRS assay would enlarge the range of samples suitable for DNA analysis and ultimately would provide exciting new opportunities for the investigation of ancient DNA in the fields of evolutionary biology and molecular ecology, and of altered DNA in food frauds detection and forensics.