Functionalized Acupuncture Needle as Surface-Enhanced Resonance Raman Spectroscopy Sensor for Rapid and Sensitive Detection of Dopamine in Serum and Cerebrospinal Fluid

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

SERS microscopy as a tool for comprehensive biochemical characterization in complex samples

Surface enhanced Raman scattering (SERS) spectra of biomaterials such as cells or tissues can be used to obtain biochemical information from nanoscopic volumes in these heterogeneous samples. This tutorial review discusses the factors that determine the outcome of a SERS experiment in complex bioorganic samples. They are related to the SERS process itself, the possibility to selectively probe certain regions or constituents of a sample, and the retrieval of the vibrational information in order to identify molecules and their interaction. After introducing basic aspects of SERS experiments in the context of biocompatible environments, spectroscopy in typical microscopic settings is exemplified, including the possibilities to combine SERS with other linear and non-linear microscopic tools, and to exploit approaches that improve lateral and temporal resolution. In particular the great variation of data in a SERS experiment calls for robust data analysis tools. Approaches will be introduced that have been originally developed in the field of bioinformatics for the application to omics data and that show specific potential in the analysis of SERS data. They include the use of simulated data and machine learning tools that can yield chemical information beyond achieving spectral classification.

Machine Learning-Driven SERS Nanoendoscopy and Optophysiology

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic efficacy, and fundamental biochemical function of the host. Following the completion of the Human Genome Project, current research aims to link genes to functions of an organism and investigate how the environment modulates functional properties of organisms. New analytical methods have been developed to detect chemical changes with high spatial and temporal resolution, including minimally invasive surface-enhanced Raman scattering (SERS) nanofibers using the principles of endoscopy (SERS nanoendoscopy) or optical physiology (SERS optophysiology). Given the large spectral data sets generated from these experiments, SERS nanoendoscopy and optophysiology benefit from advances in data science and machine learning to extract chemical information from complex vibrational spectra measured by SERS. This review highlights new opportunities for intracellular, extracellular, and in vivo chemical measurements arising from the combination of SERS nanosensing and machine learning.

SERS Sensing of Dopamine with Fe(III)-Sensitized Nanogaps in Recleanable AuNP Monolayer Films

Sensing of neurotransmitters (NTs) down to nm concentrations is demonstrated by utilizing self-assembled monolayers of plasmonic 60 nm Au nanoparticles in close-packed arrays immobilized onto glass substrates. Multiplicative surface-enhanced Raman spectroscopy enhancements are achieved by integrating Fe(III) sensitizers into the precisely-defined <1 nm nanogaps, to target dopamine (DA) sensing. The transparent glass substrates allow for efficient access from both sides of the monolayer aggregate films by fluid and light, allowing repeated sensing in different analytes. Repeated reusability after analyte sensing is shown through oxygen plasma cleaning protocols, which restore pristine conditions for the nanogaps. Examining binding competition in multiplexed sensing of two catecholamine NTs, DA and epinephrine, reveals their bidentate binding and their interactions. These systems are promising for widespread microfluidic integration enabling a wide range of continuous biofluid monitoring for applications in precision health.

Fabrication of an Ag-based SERS nanotag for histamine quantitative detection

A crucial issue in analytical science and physiology is the detection of histamine with high sensitivity, specificity and credibility, which served as an important neurotransmitter in biofluids. Despite the high sensitivity of surface-enhanced Raman spectroscopy (SERS) at the level of single molecule, there are still challenges in providing high sensitivity for histamine with a small cross section. For the selective detection of histamine using SERS, a highly sensitive sandwich structure substrate combining Fe₃O₄ and an Ag-based SERS nanotag was developed. The Fe₃O₄@SiO₂-COOH served as a capture component for enriching histamine. Upon functionalized Ag nanoparticles with glycine (Gly) and (3-Aminopheyonyl) boronic acid (APBA), they were then used to connect with histamine and serve as a SERS nanotag, respectively. A linear relationship between the Raman intensity and the histamine concentration was observed over the range 10^-4-10^-8 M with a limit of detection of 7.24 × 10^-9 M. This methodology also exhibited good selectivity in the presence of other neurotransmitters. With our new approach, histamine can be detected sensitively and reliably in fish samples, which indicates the potential prospect of an effective method for analyzing histamine in complex specimens.

Quantitative detection of dopamine in human serum with surface-enhanced Raman scattering (SERS) of constrained vibrational mode

Dopamine (DA) is a crucial neurotransmitter involved in the hormonal, nervous, and vascular systems being considered as an index to diagnose neurodegenerative diseases, including Parkinson's and Alzheimer's disease. Herein, we demonstrate the quantitative sensing of DA using the peak shift in surface-enhanced Raman scattering (SERS) of 4-mercaptophenylboronic acid (4-MPBA), resulting from the concentration of DA. To enable the signal enhancement of Raman scattering, Ag nanostructure was built with one-step gas-flow sputtering. 4-MPBA was then introduced using vapor-based deposition, acting as a reporter molecule for bonding with DA. The gradual peak-shift from 1075.6 cm^-1 to 1084.7 cm^-1 was observed with the increasing concentration of DA from 1 pM to 100nM. The numerical simulation revealed that DA bonding induced a constrained vibrational mode corresponding to 1084.7 cm^-1 instead of a C-S-coupled C-ring in-plane bending mode of 4-MPBA corresponding to 1075.6 cm^-1. Proposed SERS sensors depicted reliable DA detection in human serum and good selectivity against other analytes, including glucose, creatinine, and uric acid.

Plasmonic Sensing Assay for Long-Term Monitoring (PSALM) of Neurotransmitters in Urine

A liquid-based surface-enhanced Raman spectroscopy assay termed PSALM is developed for the selective sensing of neurotransmitters (NTs) with a limit of detection below the physiological range of NT concentrations in urine. This assay is formed by quick and simple nanoparticle (NP) "mix-and-measure" protocols, in which Fe^III bridges NTs and gold NPs inside the sensing hotspots. Detection limits of NTs from PreNP PSALM are significantly lower than those of PostNP PSALM, when urine is pretreated by affinity separation. Optimized PSALM enables the long-term monitoring of NT variation in urine in conventional settings for the first time, allowing the development of NTs as predictive or correlative biomarkers for clinical diagnosis.

Single-model multi-tasks deep learning network for recognition and quantitation of surface-enhanced Raman spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy analysis has long been the central task of nanoscience and nanotechnology to realize the ultrasensitive recognition/quantitation applications. Recently, the blooming of artificial intelligence algorithms provides an edge tool to revolutionize the spectroscopy analysis, especially for multiple substances analysis and large-scale data handling. In this study, a single-model multi-tasks deep learning network is proposed to simultaneously achieve the qualitative recognition and quantitative analysis of SERS spectroscopy. The SERS spectra of two kinds of hypoglycemic drugs (PHE, ROS) and the corresponding mixtures are collected, respectively, with the concentration grade from 10^-4 M to 10^-8 M. Based on the SERS spectroscopy dataset, the loss functions and hyperparameters of the multi-tasks classifications model are optimized, and the recognition accuracies are tested by simulation experiments. It is demonstrated that the accuracy rates of qualitative and quantitative analysis can reach up to 99.0% and 98.4%, respectively. Moreover, the practical feasibility of this multi-tasks model is demonstrated by using it to achieve qualitative and quantitative analysis of PHE and ROS in complex serum matrix. Overall, this single-model multi-tasks deep learning network shows significant potential for the recognition and quantitation of SERS spectroscopy, which provides the algorithmic and experimental basis for large-scale and multiple substances SERS spectra analysis.

Metal coordination induced SERS nanoprobe for sensitive and selective detection of histamine in serum

Sensitivity and credibility detecting histamine (HA) as an important neurotransmitter in biofluids is of importance in analytical science and physiology. Surface-enhanced Raman spectroscopy (SERS) is able to realize the high sensitivity with single molecules level, but providing the high sensitivity for HA with a small cross section remains a challenge. Here we develop the metal complex-based SERS nanoprobe nitrilotriacetic acid-Ni²⁺ (NTA-Ni²⁺) combined with self-assemble Au NPs active substrates for sensitive detection of HA. The NTA-Ni²⁺ can capture the HA molecules close to Au NPs substrates and then amplify the Raman signals of HA owing to the formation of a complex of NTA-Ni²⁺-HA. The self-assemble Au film through the evaporation-driven method can provide the high-density hot spots substrate with high stability and reproducibility. The NTA-Ni²⁺ decorated Au NPs as nanoprobe responds to HA with 1 μM level of sensitivity. More importantly, the developed SERS nanoprobe composing of NTA-Ni²⁺ and self-assemble Au NPs can be utilized to detect and monitor the HA spiked into serum, indicating the potential prospect in analysis of HA in complex specimen.

Femtomolar detection of dopamine using surface plasmon resonance sensor based on chitosan/graphene quantum dots thin film

Due to the crucial role of dopamine (DA) in health and peripheral nervous systems, it is particularly important to develop an efficient and accurate sensor to monitor and determine DA concentrations for diagnostic purposes and diseases prevention. Up to now, using surface plasmon resonance (SPR) sensors in DA determination is very limited and its application still at the primary stage. In this work, a simple and ultra-sensitive SPR sensor was constructed for DA detection by preparation of chitosan- graphene quantum dots (CS-GQDs) thin film as the sensing layer. Other SPR measurements were conducted using different sensing layers; GQDs, CS for comparison. The proposed thin films were prepared by spin coating technique. The developed CS-GQDs thin film-based SPR sensor was successfully tested in DA concentration range from 0 fM to 1 pM. The designed SPR sensor showed outstanding performance in detecting DA sensitively (S = 0.011°/fM, R² = 0.8174) with low detection limit of 1.0 fM has been achieved for the first time. The increased angular shift of SPR dip, narrow full width half maximum of the SPR curves, excellent signal-to-noise ratio and figure of merit, and a binding affinity constant (K_A) of 2.962 PM^-1 demonstrated the potential of this sensor to detect DA with high accuracy. Overall, it was concluded that the proposed sensor would serve as a valuable tool in clinical diagnostic for the serious neurological disorders. This in turns has a significant socio-economic impact.

Construction of Optimal SERS Hotspots Based on Capturing the Spike Receptor-Binding Domain (RBD) of SARS-CoV-2 for Highly Sensitive and Specific Detection by a Fish Model

It is highly challenging to construct the best SERS hotspots for the detection of proteins by surface-enhanced Raman spectroscopy (SERS). Using its own characteristics to construct hotspots can achieve the effect of sensitivity and specificity. In this study, we built a fishing mode device to detect the receptor-binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at low concentrations in different detection environments and obtained a sensitive SERS signal response. Based on the spatial resolution of proteins and their protein-specific recognition functions, SERS hotspots were constructed using aptamers and small molecules that can specifically bind to RBD and cooperate with Au nanoparticles (NPs) to detect RBD in the environment using SERS signals of beacon molecules. Therefore, two kinds of AuNPs modified with aptamers and small molecules were used in the fishing mode device, which can specifically recognize and bind RBD to form a stable hotspot to achieve high sensitivity and specificity for RBD detection. The fishing mode device can detect the presence of RBD at concentrations as low as 0.625 ng/mL and can produce a good SERS signal response within 15 min. Meanwhile, we can detect an RBD of 0.625 ng/mL in the mixed solution with various proteins, and the concentration of RBD in the complex environment of urine and blood can be as low as 1.25 ng/mL. This provides a research basis for SERS in practical applications for protein detection work.

A digital SERS sensing platform using 3D nanolaminate plasmonic crystals coupled with Au nanoparticles for accurate quantitative detection of dopamine

We report a digital surface-enhanced Raman spectroscopy (SERS) sensing platform using the arrays of 3D nanolaminate plasmonic crystals (NLPC) coupled with Au nanoparticles and digital (on/off) SERS signal analysis for the accurate quantitative detection of dopamine (DA) at ultralow concentrations. 3D NLPC SERS substrates were fabricated to support the optically dense arrays of vertically-stacked multi-nanogap hotspots and combined with Raman tag-conjugated Au nanoparticles for NLPC-based dual-recognition structures. We demonstrate that the 3D NLPC-based dual-recognition structures including Au nanoparticle-induced additional hotspots can enable more effective SERS enhancement through the molecular recognition of DA. For the accurate quantification of DA at ultralow concentrations, we conducted digital SERS analysis to reduce stochastic signal variation due to various microscopic effects, including molecular orientation/position variation and the spatial distribution of nanoparticle-coupled hotspots. The digital SERS analysis allowed the SERS mapping results from the DA-specific dual-recognition structures to be converted into binary "On/Off" states; the number of "On" events was directly correlated with low-abundance DA molecules down to 1 pM. Therefore, the digital SERS platform using the 3D NLPC-based dual-recognition structures coupled with Au nanoparticles and digital SERS signal analysis can be used not only for the ultrasensitive, accurate, and quantitative determination of DA, but also for the practical and rapid analysis of various molecules on nanostructured surfaces.

Brain neurochemical monitoring

Brain neurochemical monitoring aims to provide continuous and accurate measurements of brain biomarkers. It has enabled significant advances in neuroscience for application in clinical diagnostics, treatment, and prevention of brain diseases. Microfabricated electrochemical and optical spectroscopy sensing technologies have been developed for precise monitoring of brain neurochemicals. Here, a comprehensive review on the progress of sensing technologies developed for brain neurochemical monitoring is presented. The review provides a summary of the widely measured clinically relevant neurochemicals and commonly adopted recognition technologies. Recent advances in sampling, electrochemistry, and optical spectroscopy for brain neurochemical monitoring are highlighted and their application are discussed. Existing gaps in current technologies and future directions to design industry standard brain neurochemical sensing devices for clinical applications are addressed.

Identification of N-methylaniline based on azo coupling reaction by combining TLC with SERRS

The objective of this study was to establish a novel method for the determination of N-methylaniline (NMA) based on azo coupling reaction in infant pacifiers prepared with food contact silicone materials by combining thin layer chromatography (TLC) with surface-enhanced resonance Raman scattering (SERRS). TLC was used to separate the azo reaction products to confirm the component spot of azo compound, then the spot of azo compound mixed with silver sol on the TLC plate was qualitatively detected by SERRS. The limit of detection (LOD) of the method is as low as 0.50 ppm for NMA. The influence of sample matrix about the TLC-SERRS detection of NMA was investigated by experiment of simulated positive sample, and the NMA in infant pacifiers exposed to silica gel products was detected. The method of TLC-SERRS for the determination of NMA in infant pacifiers prepared with food contact silicone materials was established, and the real samples were detected. Compared with the methods ever reported, the method has the advantages of high sensitivity, specificity and low cost. It provides a new reference method for establishing a safety system for food contact silicone materials.

Noble metal sensitized invasive porous bioelectrodes: advanced medical device for enhanced neuronal activity and chronic alcohol treatment

Invasive bioelectrodes are widely used as an effective treatment for several acute and chronic diseases. In earlier work using high surface area invasive porous bioelectrodes evaluated in an animal model of alcoholism withdrawal, we demonstrated significantly improved electrophysiological and behavioral responses. In this study, we further modify the surface of these invasive porous bioelectrodes with noble metal (Ag, Au, Pt) nanoparticles. Compared to both conventional and porous bioelectrodes, noble metal sensitized invasive porous bioelectrodes show markedly increased low threshold (LT) and wide dynamic range (WDR) neuronal activity. In particular, Pt-sensitized invasive porous bioelectrodes show the highest WDR neuronal activity only upon insertion. In addition, Ag-sensitized invasive porous bioelectrodes, whose surface area is about 37 times greater than that of conventional bioelectrodes, show improved electrochemical properties with higher LT and WDR neuronal activity when stimulated. In an animal model of chronic alcoholism, using normal and alcohol-treated Sprague-Dawley (SD) rats evaluated with the elevated plus maze (EPM) test, the Ag-sensitized invasive porous bioelectrodes show about 20% higher open arms time. These results suggest that these noble metal-sensitized invasive bioelectrodes may offer improved therapeutic outcomes for the treatment of chronic alcoholism, and given these enhanced electrophysiological properties, for other conditions as well.

A Review of Chinese Raman Spectroscopy Research Over the Past Twenty Years

This paper introduces the major Chinese research groups in the fields of biomedicine, food safety, environmental testing, material research, archaeological and cultural relics, gem identification, forensic science, and other research areas of Raman spectroscopy and combined methods spanning the two decades from 1997 to 2017. Briefly summarized are the research directions and contents of the major Chinese Raman spectroscopy research groups, giving researchers engaged in Raman spectroscopy research a more comprehensive understanding of the state of Chinese Raman spectroscopy research and future development trends to further develop Raman spectroscopy and its applications.

Present and Future of Surface-Enhanced Raman Scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

Ultrasonic-Assisted Synthesis of Highly Defined Silver Nanodimers by Self-Assembly for Improved Surface-Enhanced Raman Spectroscopy

Considerable research efforts have been devoted to surface-enhanced Raman spectroscopy (SERS), due to its excellent performance in biosensing and imaging. Here, a novel and facile strategy for the fabrication of well-defined and uniform nanodimers as SERS substrates is presented. By the assistance of ultrasound, the violent polyol process for particle generation becomes controllable, enabling the self-assembly of nanostars to nanodimers. Moreover, the aggregation of nanodimers can be easily tuned by post-ultrasonic treatment, which gives a sensitive substrate for SERS.

High-affinity Fe3O4/Au probe with synergetic effect of surface plasmon resonance and charge transfer enabling improved SERS sensing of dopamine in biofluids

Development of analytical methods allowing sensitive detection of neurotransmitters in various biofluids is vital. However, limitations of these methods include interference of impurities and stringent requirements concerning sample purity. In the current work, we developed a strategy for the rapid and sensitive analysis of dopamine (DA) in various biofluids with a smart surface-enhanced Raman spectroscopy (SERS) probe composed of magnetite Fe₃O₄ and Au nanoparticles (Fe₃O₄/Au NPs). Besides the simple and quick separation of DA from the specimen, Fe₃O₄ not only enabled a specific chemical interaction with DA molecules, but also acted as a SERS substrate capable of electromagnetically enhancing the Raman signal of DA. Therefore, the Fe₃O₄/Au NP composite with its coexisting electric-field effect and charger transfer (CT) enhancement was found to be beneficial for capturing the target molecules in biological environments and then enhancing the DA sensitivity. To understand the strong binding interaction between Fe₃O₄/Au and DA, X-ray photoelectron spectroscopy (XPS) was carried out, specifically to illuminate the chemical adsorption or possible CT complex. Moreover, a rapid purification strategy for further separating DA from serum was developed, and thus a high nanometer-level sensitivity was achieved. In addition, the feasibility of using Fe₃O₄/Au combined with the developed purification method was also verified using various tissue homogenates spiked with DA molecules. Such a nanocomposite can offer the possibility of efficiently separating DA from the complex specimen and then providing the sensitive detection of DA for various tissues. Accordingly, the smart SERS Fe₃O₄/Au nanocomposite probe, with its advantages of simple pre-treatment and synergetic enhanced mechanisms, shows great promise for the rapid and sensitive detection of DA in complicated specimens.

Fiber-Enhanced Raman Sensing of Cefuroxime in Human Urine

Fiber-enhanced Raman spectroscopy was developed for the chemically selective and sensitive quantification of the important antibiotic cefuroxime in human urine. A novel optical sensor fiber was drawn and precisely prepared. In this fiber structure, light is strongly confined in the selectively filled liquid core, and the Raman scattered signal is collected with unprecedented efficiency over an extended interaction length. The filling, emptying, and robustness are highly improved due to the large core size (>30 μm). Broadband step-index guidance allows the free choice of the most suitable excitation wavelength in complex body fluids. The limit of detection of cefuroxime in human urine was improved by 2 orders of magnitude (to μM level). The quantification of cefuroxime was achieved in urine after oral administration. This method has great potential for the point-of-care monitoring of antibiotics concentrations and is an important step forward to enable clinicians to rapidly adjust doses.

Antimicrobial peptide based magnetic recognition elements and Au@Ag-GO SERS tags with stable internal standards: a three in one biosensor for isolation, discrimination and killing of multiple bacteria in whole blood

A SERS based biosensor has been developed for isolation, detection and killing of multiple bacterial pathogens.

In this study, a new biosensor based on a sandwich structure has been developed for the isolation and detection of multiple bacterial pathogens via magnetic separation and SERS tags. This novel assay relies on antimicrobial peptide (AMP) functionalized magnetic nanoparticles as “capturing” probes for bacteria isolation and gold coated silver decorated graphene oxide (Au@Ag-GO) nanocomposites modified with 4-mercaptophenylboronic acid (4-MPBA) as SERS tags. When different kinds of bacterial pathogens are combined with the SERS tags, the “fingerprints” of 4-MPBA show corresponding changes due to the recognition interaction between 4-MPBA and different kinds of bacterial cell wall. Compared with the label-free SERS detection of bacteria, 4-MPBA here can be used as an internal standard (IS) to correct the SERS intensities with high reproducibility, as well as a Raman signal reporter to enhance the sensitivity and amplify the differences among the bacterial “fingerprints”. Thus, three bacterial pathogens (Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa) were successfully isolated and detected, with the lowest concentration for each of the strains detected at just 10¹ colony forming units per mL (CFU mL^–1). According to the changes in the “fingerprints” of 4-MPBA, three bacterial strains were successfully discriminated using discriminant analysis (DA). In addition, the AMP modified Fe₃O₄NPs feature high antibacterial activities, and can act as antibacterial agents with low cellular toxicology in the long-term storage of blood for future safe blood transfusion applications. More importantly, this novel method can be applied in the detection of bacteria from clinical patients who are infected with bacteria. In the validation analysis, 97.3% of the real blood samples (39 patients) could be classified effectively (only one patient infected with E. coli was misclassified). The multifunctional biosensor presented here allows for the simultaneous isolation, discrimination and killing of bacteria, suggesting its high potential for clinical diagnosis and safe blood transfusions.

Development of surface-enhanced Raman spectroscopy application for determination of illicit drugs: Towards a practical sensor

Surface-enhanced Raman spectroscopy (SERS) has been widely applied to identify or detect illicit drugs, because of the ability for highly specific molecular fingerprint and independence of aqueous solutions impact. We summarize the progress in determination of illicit drugs using SERS, including trace illicit drugs, suspicious objects and drugs or their metabolites in real biological system (urine, saliva and so on). Even though SERS detection of illicit drugs in real samples still remains a huge challenge because of the complex unknown environment, the efficient sample separation and the improved hand-held Raman analyzer will provide the possibility to make SERS a practically analytical technique. Moreover, we put forward a prospective overview for future perspectives of SERS as a practical sensor for illicit drugs determination. Perhaps the review is not exhaustive, we expect to help researchers to understand the evolution and challenges in this field and further interest in promoting Raman and SERS as a practical analyzer for convenient and automated illicit drugs identification.

Conformational sensitivity of surface selection rules for quantitative Raman identification of small molecules in biofluids

Biofluid analysis by surface-enhanced Raman scattering (SERS) is usually hindered by nonspecific interferences. It is challenging to drive targeted molecules towards sensitive areas with specific capture and quantitative recognition in complex biofluids. Herein, a highly specific and quantitative SERS analyzer for small molecule dopamine (DA) in serum is demonstrated on a portable Raman device by virtue of a transducer of mercaptophenylboronic acid (MPBA) and a site-directed decoration of plasmonic Ag dendrites on a superhydrophobic surface. Theoretical simulations of molecular vibrations and charge distributions demonstrate the predomination of Raman surface selection rules in molecular reorientation upon the binding of DA. This recognition event is translated into ratiometric changes in the spectral profile which evidences excellent capability on SERS quantitation. The rules can well distinguish DA from its common interferents including fructose, glucose, sucrose and ascorbic acid which all generate weak but completely opposite spectral changes. Moreover, benefitting from the wettability difference, the target DA in diluted serum can be specifically enriched on a transducer-capped Ag surface, and the adsorption of other interferences is resisted by superhydrophobic features. It paves a new way for labelling a single SERS tag to simultaneously realize the identification and quantification of small molecules in complex biological media.