Surface enhanced Raman spectroscopy (SERS): Potential applications for disease detection and treatment

Plasmonics-enhanced spikey nanorattle-based biosensor for direct SERS detection of mRNA cancer biomarkers

We present a plasmonics-enhanced spikey nanorattle-based biosensor for direct surface-enhanced Raman scattering (SERS) detection of mRNA cancer biomarkers. Early detection of cancers such as head and neck squamous cell carcinoma (HNSCC) is critical for improving patient outcomes in regions with limited access to traditional diagnostic methods. Our method targets Keratin 14 (KRT14), a promising diagnostic mRNA biomarker for HNSCC, using a sandwich hybridization approach with magnetic beads and SERS spikey nanorattles (SpNR). We synthesized SpNR with a core-gap-shell structure to enhance SERS signals, achieving a limit of detection of 90 femtomolar. A pilot study using clinical samples demonstrated the efficacy of our biosensor in distinguishing between tissue with positive or negative diagnosis for HNSCC, highlighting its potential for rapid and sensitive cancer diagnostics in low-resource settings. This plasmonic assay offers a promising avenue for portable and high-specificity detection of nucleic acid biomarkers, with implications for early cancer detection and improved patient care, especially in middle and low-resource settings.

Visualization-enhanced under-oil open microfluidic system for in situ characterization of multi-phase chemical reactions

Under-oil open microfluidic system, utilizing liquid-liquid boundaries for confinements, offers inherent advantages including clogging-free flow channels, flexible access to samples, and adjustable gas permeation, making it well-suited for studying multi-phase chemical reactions that are challenging for closed microfluidics. However, reports on the novel system have primarily focused on device fabrication and functionality demonstrations within biology, leaving their application in broader chemical analysis underexplored. Here, we present a visualization-enhanced under-oil open microfluidic system for in situ characterization of multi-phase chemical reactions with Raman spectroscopy. The enhanced system utilizes a semi-transparent silicon (Si) nanolayer over the substrate to enhance visualization in both inverted and upright microscope setups while reducing Raman noise from the substrate. We validated the system's chemical stability and capability to monitor gas evolution and gas-liquid reactions in situ. The enhanced under-oil open microfluidic system, integrating Raman spectroscopy, offers a robust open-microfluidic platform for label-free molecular sensing and real-time chemical/biochemical process monitoring in multi-phase systems.

A novel approach for rapid and sensitive detection of Zika virus utilizing silver nanoislands as SERS platform

To control the spread of the disease, the Zika virus (ZIKV), a flavivirus infection spread by mosquitoes and common in across the world, needs to be accurately and promptly diagnosed. This endeavour gets challenging when early-stage illnesses have low viral loads. As a result, we have created a biosensor based on surface-enhanced Raman scattering (SERS) for the quick, accurate, and timely diagnosis of the Zika virus. In this study, a glass coverslip was coated with silver nanoislands, which were then utilized as the surface for creating the sensing platform. Silver nanoislands exhibit strong plasmonic activity and good conductive characteristics. It enhances the Raman signals as a result and gives the SERS platform an appropriate surface. The created platform has been applied to Zika virus detection. With a limit of detection (LOD) of 0.11 ng/mL, the constructed sensor exhibits a linear range from 5 ng/mL to 1000 ng/mL. Hence, even at the nanogram scale, this technique may be a major improvement over clinical diagnosis approaches for making proper, precise, and accurate Zika virus detection.

Using Machine Learning and Silver Nanoparticle-Based Surface-Enhanced Raman Spectroscopy for Classification of Cardiovascular Disease Biomarkers

Characterizing complex biofluids using surface-enhanced Raman spectroscopy (SERS) coupled with machine learning (ML) has been proposed as a powerful tool for point-of-care detection of clinical disease. ML is well-suited to categorizing otherwise uninterpretable, patient-derived SERS spectra that contain a multitude of low concentration, disease-specific molecular biomarkers among a dense spectral background of biological molecules. However, ML can generate false, non-generalizable models when data sets used for model training are inadequate. It is thus critical to determine how different SERS experimental methodologies and workflow parameters can potentially impact ML disease classification of clinical samples. In this study, a label-free, broadband, Ag nanoparticle-based SERS platform was coupled with ML to assess simulated clinical samples for cardiovascular disease (CVD), containing randomized combinations of five key CVD biomarkers at clinically relevant concentrations in serum. Raman spectra obtained at 532, 633, and 785 nm from up to 300 unique samples were classified into physiological and pathological categories using two standard ML models. Label-free SERS and ML could correctly classify randomized CVD samples with high accuracies of up to 90.0% at 532 nm using as few as 200 training samples. Spectra obtained at 532 nm produced the highest accuracies with no significant increase achieved using multiwavelength SERS. Sample preparation and measurement methodologies (e.g., different SERS substrate lots, sample volumes, sample sizes, and known variations in randomization and experimental handling) were shown to strongly influence the ML classification and could artificially increase classification accuracies by as much as 27%. This detailed investigation into the proper application of ML techniques for CVD classification can lead to improved data set acquisition required for the SERS community, such that ML on labeled and robust SERS data sets can be practically applied for future point-of-care testing in patients.

Application of sensitive SERS plasmonic biosensor for high detection of metabolic disorders

Due to the importance of early detection of metabolic diseases in newborns, it is essential to measure organoacids; L-Tryptophan, Sebacic acid, and Glutaric acid in very low concentrations. Therefore, the necessity of the construction of a powerful nondestructive biosensor just like the surface-enhanced Raman scattering (SERS) sensor is demonstrated. Through the growth of silver dendritic nanostructures on different substrates like aluminum (Al), copper (Cu), indium tin oxide (ITO), and silicon (Si), a new SERS-based biosensor was developed. Because the Raman signal of molecules adsorbed on dendritic nanostructures is significantly increased, SERS biosensors based on these nanostructures can be used to detect very low concentrations of materials. In this study, first, the organoacid L-Lysine was detected up to a concentration of 10^-12 M, by using a biosensor based on Al, Cu, ITO, and Si substrates. Then, by comparing the results obtained from different substrates, the silicon substrate as the most successful substrate with the best results was used in the SERS biosensor to detect the organoacids, L-Tryptophan, Sebacic acid, and Glutaric acid up to a concentration of 10^-12 M. SEM imaging was used to characterize silver dendritic nanostructures on solid substrates. The successful performance of the SERS biosensor based on silver dendrites in this study promises to be effective in diagnostic applications such as cancer diagnosis (the limit of single molecular detection).

Identification of geographic origins of Morus alba Linn. through surfaced enhanced Raman spectrometry and machine learning algorithms

The leaves of Morus alba Linn., which is also known as white mulberry, have been commonly used in many of traditional systems of medicine for centuries. In traditional Chinese medicine (TCM), mulberry leaf is mainly used for anti-diabetic purpose due to its enrichment in bioactive compounds such as alkaloids, flavonoids and polysaccharides. However, these components are variable due to the different habitats of the mulberry plant. Therefore, geographic origin is an important feature because it is closely associated with bioactive ingredient composition that further influences medicinal qualities and effects. As a low-cost and non-invasive method, surface enhanced Raman spectrometry (SERS) is able to generate the overall fingerprints of chemical compounds in medicinal plants, which holds the potential for the rapid identification of their geographic origins. In this study, we collected mulberry leaves from five representative provinces in China, namely, Anhui, Guangdong, Hebei, Henan and Jiangsu. SERS spectrometry was applied to characterize the fingerprints of both ethanol and water extracts of mulberry leaves, respectively. Through the combination of SERS spectra and machine learning algorithms, mulberry leaves were well discriminated with high accuracies in terms of their geographic origins, among which the deep learning algorithm convolutional neural network (CNN) showed the best performance. Taken together, our study established a novel method for predicting the geographic origins of mulberry leaves through the combination of SERS spectra with machine learning algorithms, which strengthened the application potential of the method in the quality evaluation, control and assurance of mulberry leaves.

Microcontact printing of gold nanoparticle at three-phase interface as flexible substrate for SERS detection of MicroRNA

The rigidity of traditional solid-state surface-enhanced Raman spectroscopy (SERS) substrate hampers their application in the curved structure for nonplanar surface test and in-situ detection. Traditionally, the flexible Raman substrates are often prepared by transferring printing of patterned nanoparticles on the flexible materials such as polymer, paper, etc. However，the replicate patterns are often produced by high-cost instruments. In this study, a low-cost and flexible SERS substrate is prepared by using a microcontact printing technology to transfer three-phase-assembled nanoparticles on a polydimethylsiloxane film, which can stabilize the assembled nanoparticles. Combining with the endonuclease Nt.BbvCI assisted amplification method, a SERS biosensor is constructed for microRNA 21 (miRNA 21) assay. This platform presents a wide dynamic range (100 fM ∼1 nM), achieving a fabulous sensitivity with limit of detection of 11.96 fM for miRNA 21. Furthermore, after being bent 90° for 50 times, the Raman intensity of the flexible substrate shows a negligible change. This versatile flexible substrate exhibits considerable potential for SERS analysis, which also opens a new avenue for preparing flexible devices.

Research on the difference between patients with coronary heart disease and healthy controls by surface enhanced Raman spectroscopy

Coronary heart disease (CHD) is one of the primary causes of death globally. There are several diagnostic techniques for CHD at present, but they are invasive and with limited accuracy. In the work, measurement of human urine based on surface-enhanced Raman spectroscopy (SERS) was proposed to diagnose CHD. Urine samples of 157 CHD patients and 63 healthy controls (HC) were investigated by SERS. Statistical analysis of the measured data was then performed. It was found that there were intensity differences in nine Raman peaks (1223/1243/1272/1463/1481/1516/1536/1541/1550 cm^-1) between CHD and HC in their average SERS spectrum. Furthermore, principal component analysis (PCA)-linear discriminant analysis (LDA) was then utilized to establish a prediction model to classify CHD and HC. It revealed that the accuracy, specificity and sensitivity of the prediction model validated by leave-one-patient-out cross validation (LOPOCV) were 84.09%, 92.06% and 80.89%, respectively. Therefore, the proposed method can be employed as a non-invasive, rapid and accurate tool for CHD diagnosis in clinical application.

Surface-enhanced Raman probes based on gold nanomaterials for in vivo diagnosis and imaging

Surface-enhanced Raman scattering (SERS) has received considerable attention from researchers due to its high molecular specificity, high sensitivity, non-invasive and multiplexing. Recently, various metal substrates have been exploited for SERS analysis and imaging. Among them, gold nanomaterials are important SERS substrates with outstanding surface plasmon resonance effects, structural adjustability and good biocompatibility, making them widely used in biomedical diagnosis and clinical fields. In this minireview, we discuss the latest progress about the application of gold-based nanomaterials as SERS probes in biomedical research, primarily for in vivo disease diagnosis and imaging. This review mainly includes the basic shapes and morphologies of gold based SERS probes, such as gold nanoparticles (AuNPs), gold nanorods (AuNRs), gold nanostars (AuNSs), as well as other gold nanostructures. Finally, a brief outlook for the future development of SERS technique in the context of efficient diagnostics and therapy guidance is provided. We hope that this minireview will facilitate the design and future development of Surface-enhanced Raman probes based on gold nanomaterials.

Microfluidics and surface-enhanced Raman spectroscopy, a win-win combination?

With the continuous development in nanoscience and nanotechnology, analytical techniques like surface-enhanced Raman spectroscopy (SERS) render structural and chemical information of a variety of analyte molecules in ultra-low concentration. Although this technique is making significant progress in various fields, the reproducibility of SERS measurements and sensitivity towards small molecules are still daunting challenges. In this regard, microfluidic surface-enhanced Raman spectroscopy (MF-SERS) is well on its way to join the toolbox of analytical chemists. This review article explains how MF-SERS is becoming a powerful tool in analytical chemistry. We critically present the developments in SERS substrates for microfluidic devices and how these substrates in microfluidic channels can improve the SERS sensitivity, reproducibility, and detection limit. We then introduce the building materials for microfluidic platforms and their types such as droplet, centrifugal, and digital microfluidics. Finally, we enumerate some challenges and future directions in microfluidic SERS. Overall, this article showcases the potential and versatility of microfluidic SERS in overcoming the inherent issues in the SERS technique and also discusses the advantage of adding SERS to the arsenal of microfluidics.

Raman Scattering-Based Biosensing: New Prospects and Opportunities

The growing interest in the development of new platforms for the application of Raman spectroscopy techniques in biosensor technologies is driven by the potential of these techniques in identifying chemical compounds, as well as structural and functional features of biomolecules. The effect of Raman scattering is a result of inelastic light scattering processes, which lead to the emission of scattered light with a different frequency associated with molecular vibrations of the identified molecule. Spontaneous Raman scattering is usually weak, resulting in complexities with the separation of weak inelastically scattered light and intense Rayleigh scattering. These limitations have led to the development of various techniques for enhancing Raman scattering, including resonance Raman spectroscopy (RRS) and nonlinear Raman spectroscopy (coherent anti-Stokes Raman spectroscopy and stimulated Raman spectroscopy). Furthermore, the discovery of the phenomenon of enhanced Raman scattering near metallic nanostructures gave impetus to the development of the surface-enhanced Raman spectroscopy (SERS) as well as its combination with resonance Raman spectroscopy and nonlinear Raman spectroscopic techniques. The combination of nonlinear and resonant optical effects with metal substrates or nanoparticles can be used to increase speed, spatial resolution, and signal amplification in Raman spectroscopy, making these techniques promising for the analysis and characterization of biological samples. This review provides the main provisions of the listed Raman techniques and the advantages and limitations present when applied to life sciences research. The recent advances in SERS and SERS-combined techniques are summarized, such as SERRS, SE-CARS, and SE-SRS for bioimaging and the biosensing of molecules, which form the basis for potential future applications of these techniques in biosensor technology. In addition, an overview is given of the main tools for success in the development of biosensors based on Raman spectroscopy techniques, which can be achieved by choosing one or a combination of the following approaches: (i) fabrication of a reproducible SERS substrate, (ii) synthesis of the SERS nanotag, and (iii) implementation of new platforms for on-site testing.

Recent advances in plasmonic Prussian blue-based SERS nanotags for biological application

The reliability and reproducibility of surface-enhanced Raman scattering (SERS) technology is still a great challenge in bio-related analysis. Prussian blue (PB)-based SERS tags have attracted increasing interest for improving these deficiencies due to its unique Raman band (near 2156 cm-1) in the Raman-silent region, providing zero-background bio-Raman labels without interference from endogenous biomolecules. Moreover, the stable PB shell consisting of multiple layers of CN- reporters ensure a stable and strong Raman signal output, avoiding the desorption of the Raman reporter from the plasmonic region by the competitive adsorption of the analyte. More importantly, they possess outstanding multiplexing potential in biological analysis owing to the adjustable Raman shift with unique narrow spectral widths. Despite more attention having been attracted to the structure and preparation of PB-based SERS tags for their better biological applications over the past five years, there is still a great challenge for SERS suitable for applications in the actual environment. The biological applications of PB-based SERS tags are comprehensively recounted in this minireview, mainly focusing on quantification analysis, multiple-spectral analysis and cell-imaging joint phototherapy. The prospects of PB-based SERS tags in clinical diagnosis and treatment are also discussed. This review aims to draw attention to the importance of SERS tags and provide a reference for the design and application of PB-based SERS tags in future bio-applications.

Universal Fabrication of Highly Efficient Plasmonic Thin-Films for Label-Free SERS Detection

The development of novel, highly efficient, reliable, and robust surface enhanced Raman scattering (SERS) substrates containing a large number of hot spots with programmed size, geometry, and density is extremely interesting since it allows the sensing of numerous (bio-)chemical species. Herein, an extremely reliable, easy to fabricate, and label-free SERS sensing platform based on metal nanoparticles (NPs) thin-film is developed by the layer-by-layer growth mediated by polyelectrolytes. A systematic study of the effect of NP composition and size, as well as the number of deposition steps on the substrate's performance, is accomplished by monitoring the SERS enhancement of 1-naphtalenethiol (532 nm excitation). Distinct evidence of the key role played by the interlayer (poly(diallyldimethylammonium chloride) (PDDA) or PDDA-functionalized graphene oxide (GO@PDDA)) on the overall SERS efficiency of the plasmonic platforms is provided, revealing in the latter the formation of more uniform hot spots by regulating the interparticle distances to 5 ± 1 nm. The SERS platform efficiency is demonstrated via its high analytical enhancement factor (≈10⁶ ) and the detection of a prototypical substance(tamoxifen), both in Milli-Q water and in a real matrix, viz. tap water, opening perspectives towards the use of plasmonic platforms for future high-performance sensing applications.

Characterisation of estrogen receptor alpha (ERα) expression in breast cancer cells and effect of drug treatment using targeted nanoparticles and SERS

The detection and identification of estrogen receptor alpha (ERα), one of the main biomarkers in breast cancer, is crucial for the clinical diagnosis and therapy of the disease. Here, we use a non-destructive approach for detecting and localising ERα expression at the single cell level using surface enhanced Raman spectroscopy (SERS) combined with functionalised gold nanoparticles (AuNPs). Antibody functionalised nanotags (ERα-AuNPs) showed excellent biocompatibility and enabled the spatial and temporal understanding of ERα location in breast cancer cell lines with different ERα expression status. Additionally, we developed an approach based on the percentage area of SERS response to qualitatively measure expression level in ERα positive (ERα+) breast cancer cells. Specifically, the calculation of relative SERS response demonstrated that MCF-7 cells (ERα+) exhibited higher nanotag accumulation resulting in a 4.2-times increase in SERS signal area in comparison to SKBR-3 cells (ERα-). These results confirmed the strong targeting effect of ERα-AuNPs towards the ERα receptor. The functionalised ERα-AuNP nanotags were also used to investigate the activity of fulvestrant, the first-in-class approved selective estrogen receptor degrader (SERD). SERS mapping confirmed that ERα degradation occurred after fulvestrant treatment since a weaker SERS signal, and hence accumulation of nanotags, was observed in MCF-7 cells treated with fulvestrant. Most importantly, a correlation coefficient of 0.9 between the SERS response and the ERα expression level, obtained by western blot, was calculated. These results confirmed the strong relationship between the two approaches and open up the possibilities of using SERS as a tool for the estimation of ERα expression levels, without the requirement of destructive and time-consuming techniques. Therefore, the potential of using SERS as a rapid and sensitive method to understand the activity of SERDs in breast cancer is demonstrated.

Detection of Estrogen Receptor Alpha and Assessment of Fulvestrant Activity in MCF-7 Tumor Spheroids Using Microfluidics and SERS

Breast cancer is one of the leading causes of cancer death in women. Novel in vitro tools that integrate three-dimensional (3D) tumor models with highly sensitive chemical reporters can provide useful information to aid biological characterization of cancer phenotype and understanding of drug activity. The combination of surface-enhanced Raman scattering (SERS) techniques with microfluidic technologies offers new opportunities for highly selective, specific, and multiplexed nanoparticle-based assays. Here, we explored the use of functionalized nanoparticles for the detection of estrogen receptor alpha (ERα) expression in a 3D tumor model, using the ERα-positive human breast cancer cell line MCF-7. This approach was used to compare targeted versus nontargeted nanoparticle interactions with the tumor model to better understand whether targeted nanotags are required to efficiently target ERα. Mixtures of targeted anti-ERα antibody-functionalized nanotags (ERα-AuNPs) and nontargeted (against ERα) anti-human epidermal growth factor receptor 2 (HER2) antibody-functionalized nanotags (HER2-AuNPs), with different Raman reporters with a similar SERS signal intensity, were incubated with MCF-7 spheroids in microfluidic devices and spectroscopically analyzed using SERS. MCF-7 cells express high levels of ERα and no detectable levels of HER2. 2D and 3D SERS measurements confirmed the strong targeting effect of ERα-AuNP nanotags to the MCF-7 spheroids in contrast to HER2-AuNPs (63% signal reduction). Moreover, 3D SERS measurements confirmed the differentiation between the targeted and the nontargeted nanotags. Finally, we demonstrated how nanotag uptake by MCF-7 spheroids was affected by the drug fulvestrant, the first-in-class approved selective estrogen receptor degrader (SERD). These results illustrate the potential of using SERS and microfluidics as a powerful in vitro platform for the characterization of 3D tumor models and the investigation of SERD activity.

Comparison of surface enhanced Raman spectroscopy and Raman spectroscopy for the detection of breast cancer based on serum samples

In this study, surface enhanced Raman spectroscopy (SERS) and Raman spectroscopy (RS), are employed for the classification of different stages of breast cancer using clinically diagnosed serum samples from breast cancer patients and healthy individuals. These serum samples are compared for their spectral features acquired by SERS and RS to establish spectral features that can be considered as spectral markers of breast cancer diagnosis and classification. SERS features related to DNA, proteins and lipids were observed which are solely observed in the serum samples of patients at different stages of breast cancer as compared to healthy samples. In order to explore the capability of SERS and RS and their comparison as an analytical tool for the efficient understanding of the progression of breast cancer, Principal Component Analysis (PCA) is done for the SERS and RS spectra of control, stage 2, stage 3 and stage 4. Furthermore, the Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to compare the diagnostic performance of SERS and Raman spectroscopy for the classification of disease positive samples and healthy ones. The sensitivity and specificity and area under receiver operating characteristic (AUROC) curve values for SERS data were 90%, 98.4%, and 94% respectively which were higher as compared to Raman spectral data for which these values were found to be 88.2%, 97.7%, and 83.4% respectively.

Applications of surface-enhanced Raman spectroscopy in detection fields

Surface-enhanced Raman spectroscopy (SERS) is a Raman spectroscopy technique that has been widely used in food safety, environmental monitoring, medical diagnosis and treatment and drug monitoring because of its high selectivity, sensitivity, rapidness, simplicity and specificity in identifying molecular structures. This review introduces the detection mechanism of SERS and summarizes the most recent progress concerning the use of SERS for the detection and characterization of molecules, providing references for the later research of SERS in detection fields.

Smart Gold Nanostructures for Light Mediated Cancer Theranostics: Combining Optical Diagnostics with Photothermal Therapy

Nanotheranostics, which combines optical multiplexed disease detection with therapeutic monitoring in a single modality, has the potential to propel the field of nanomedicine toward genuine personalized medicine. Currently employed mainstream modalities using gold nanoparticles (AuNPs) in diagnosis and treatment are limited by a lack of specificity and potential issues associated with systemic toxicity. Light-mediated nanotheranostics offers a relatively non-invasive alternative for cancer diagnosis and treatment by using AuNPs of specific shapes and sizes that absorb near infrared (NIR) light, inducing plasmon resonance for enhanced tumor detection and generating localized heat for tumor ablation. Over the last decade, significant progress has been made in the field of nanotheranostics, however the main biological and translational barriers to nanotheranostics leading to a new paradigm in anti-cancer nanomedicine stem from the molecular complexities of cancer and an incomplete mechanistic understanding of utilization of Au-NPs in living systems. This work provides a comprehensive overview on the biological, physical and translational barriers facing the development of nanotheranostics. It will also summarise the recent advances in engineering specific AuNPs, their unique characteristics and, importantly, tunability to achieve the desired optical/photothermal properties.

Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma

Objective

The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma.

Patients and Methods

We proposed a membrane filter SERS technology for the differentiation between benign thyroid tumor and thyroid cancer. That is to say, by using filter membranes with optimal pore size, the blood plasma samples from thyroid tumor patients were pretreated with the macromolecular proteins being filtered out prior to SERS measurement. The SERS spectra of blood plasma ultrafiltrate obtained using filter membranes from 102 patients with thyroid tumors (70 thyroid cancers and 32 benign thyroid tumors) were then analyzed and compared. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA), were performed on the SERS spectral data after background subtraction and normalization, as well as the first derivative processing, to analyze and compare the differential diagnosis of benign thyroid tumors and thyroid cancer.

Results

SERS measurements were performed in blood plasma acquired from a total of 102 thyroid tumor patients (benign thyroid tumor N=32; thyroid cancer N=70). By using filter membranes, the macromolecular proteins in blood plasma were effectively filtered out to yield high-quality SERS spectra. 84.3% discrimination accuracy between benign and malignant thyroid tumor was achieved using PCA-LDA method, while Lasso-PLS-DA yields a discrimination accuracy of 90.2%.

Conclusion

Our results demonstrate that SERS spectroscopy, coupled with ultrafiltration and multivariate analysis has the potential of providing a non-invasive, rapid, and objective detection and differentiation of benign and malignant thyroid tumors.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.

A review on recent advances in the applications of surface-enhanced Raman scattering in analytical chemistry

This review is focused on recent developments of surface-enhanced Raman scattering (SERS) applications in Analytical Chemistry. The work covers advances in the fabrication methods of SERS substrates, including nanoparticles immobilization techniques and advanced nanopatterning with metallic features. Recent insights in quantitative and sampling methods for SERS implementation and the development of new SERS-based approaches for both qualitative and quantitative analysis are discussed. The advent of methods for pre-concentration and new approaches for single-molecule SERS quantification, such as the digital SERS procedure, has provided additional improvements in the analytical figures-of-merit for analysis and assays based on SERS. The use of metal nanostructures as SERS detection elements integrated in devices, such as microfluidic systems and optical fibers, provided new tools for SERS applications that expand beyond the laboratory environment, bringing new opportunities for real-time field tests and process monitoring based on SERS. Finally, selected examples of SERS applications in analytical and bioanalytical chemistry are discussed. The breadth of this work reflects the vast diversity of subjects and approaches that are inherent to the SERS field. The state of the field indicates the potential for a variety of new SERS-based methods and technologies that can be routinely applied in analytical laboratories.

Suppression of coffee-ring effect via periodic oscillation of substrate for ultra-sensitive enrichment towards surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) has attracted extensive interest due to excellent molecule recognition and sensitive concentration detection. Nevertheless, the coffee ring effect (CR) during the analyte evaporation always causes an uneven distribution of the assembled hot-spots, and hence the unreliable SERS signal is produced. In this study, for the first time, we present a suppressed coffee ring (SCR) system via a combination of a magnetically functionalized membrane and reciprocating magnetic field to dynamically suppress the CR for highly reliable and ultra-sensitive SERS detection. The enrichment mechanism of the nanoparticles and the analyte molecules within the sessile droplet based on the proposed system was studied. We experimentally observed that the driving frequency could well affect the final pattern, and typically a higher driving frequency facilitated a smaller coverage area with better enrichment performance. With the use of R6G molecule and (100 nm) gold nanoparticles, we examined the uniformity and SERS of the assembled 'hot-spots' in the SCR system. The results indicate that the uniformity can be greatly improved via SCR in comparison of ring stain, with the RSD of a Raman signal as low as 7.1% even at a low concentration of 10^-12 mol L^-1. Such system also enables the further enhancement in the SERS signal, with the detection limit down to 10^-16 mol L^-1, the enhancement factor magnitude up to 10¹³, and the linear relationship between the SERS intensity and the analyte concentrations within the range of 10^-6-10^-12 and 10^-12-10^-16 mol L^-1, respectively. The applicability of the SCR-based SERS detection for diverse analytes was also proved with a similar but further enhanced signal of MB and 4-ATP. We believe that the excellent SCR-based SERS performance via the proposed system has great potentials for ultra-sensitive detection and/or precise quantitative analysis in various research fields and applications.

Subsurface Chemically Specific Measurement of pH Levels in Biological Tissues Using Combined Surface-Enhanced and Deep Raman

There is much interest in using nanosensors to monitor biologically relevant species such as glucose, or cellular pH, as these often become dysregulated in diseases such as cancer. This information is often inaccessible at depth in biological tissue, due to the highly scattering nature of tissue. Here we show that gold nanoparticles labeled with pH-sensitive reporter molecules can monitor pH at depth in biological tissues. This was achieved using deep Raman spectroscopy (spatially offset Raman and transmission Raman) in combination with surface-enhanced Raman spectroscopy, allowing chemical information to be retrieved significantly deeper than conventional Raman spectroscopy permits. Combining these approaches with chemometrics enabled pH changes to be monitored with an error of ±∼0.1 pH units noninvasively through 22 mm of soft tissue. This development opens the opportunity for the next generation of light-based medical diagnostic methods, such as monitoring of cancers, known to significantly alter pH levels.

Antibody modified gold nanoparticles for fast colorimetric screening of rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic joint inflammation and one of the main causes of chronic disability worldwide with high prevalence in the ageing population. RA is characterized by autoantibody production, synovial inflammation and bone destruction, and the most accepted biomarker is rheumatoid factor (RF) autoantibodies. In this work, we developed a low-cost approach for the detection and quantification of the RF marker. This colorimetric immunosensor is based on gold nanoprobe crosslinking that results in extensive aggregation in the presence of the pentameric IgM RF. Aggregation of the nanoconjugates yields a color change from red to purple that can be easily observed by the naked eye. The interaction between nanoconjugates and the specific target was confirmed via dynamic light scattering (DLS), Raman spectroscopy and atomic force microscopy (AFM) imaging. This conceptual system shows a LOD of 4.15 UA mL^-1 IgM RF (clinical threshold is set for 20 IU mL^-1). The one-step biosensor strategy herein proposed is much faster than conventional detection techniques, without the need for secondary antibodies, additional complex washing or signal amplification protocols. To the best of our knowledge this is the first report on target induced aggregation of gold nanoprobes for quantitative colorimetric autoantibody detection.

Promising methods for noninvasive medical diagnosis based on the use of nanoparticles: surface-enhanced raman spectroscopy in the study of cells, cell organelles and neurotransmitter metabolism markers

Application of advances in nanomedicine and materials science to medical diagnostics is a promising area of research. Surface-enhanced Raman spectroscopy (SERS) is an innovative analytical method that exploits noble metal nanoparticles to noninvasively study cells, cell organelles and protein molecules. Below, we summarize the literature on the methods for early clinical diagnosis of some neurodegenerative and neuroendocrine diseases. We discuss the specifics, advantages and limitations of different diagnostic techniques based on the use of low- and high molecular weight biomarkers. We talk about the prospects of optical methods for rapid diagnosis of neurotransmitter metabolism disorders. Special attention is paid to new approaches to devising optical systems that expand the analytical potential of SERS, the tool that demonstrates remarkable sensitivity, selectivity and reproducibility of the results in determining target analytes in complex biological matrices.

Applications of Raman spectroscopy in cancer diagnosis

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

APTES Duality and Nanopore Seed Regulation in Homogeneous and Nanoscale-Controlled Reduction of Ag Shell on SiO2 Microparticle for Quantifiable Single Particle SERS

Noble-metal nanoparticles size and packing density are critical for sensitive surface-enhanced Raman scattering (SERS) and controlled preparation of such films required to achieve reproducibility. Provided that they are made reliable, Ag shell on SiO₂ microscopic particles (Ag/SiO₂) are promising candidates for lab-on-a-bead analytical measurements of low analyte concentration in liquid specimen. Here, we selected nanoporous silica microparticles as a substrate for reduction of AgNO₃ with 3-aminopropyltriethoxysilane (APTES). In a single preparation step, homogeneous and continuous films of Ag nanoparticles are formed on SiO₂ surfaces with equimolar concentration of APTES and silver nitrate in ethanol. It is discussed that amine and silane moieties in APTES contribute first to an efficient reduction on the silica and second to capping the Ag nanoparticles. The high density and homogeneity of nanoparticle nucleation is further regulated by the nanoporosity of the silica. The Ag/SiO₂ microparticles were tested for SERS using self-assembled 4-aminothiophenol monolayers, and an enhancement factor of ca. 2 × 10⁶ is measured. Importantly, the SERS relative standard deviation is 36% when a single microparticle is considered and drops to 11% when sets of 10 microparticles are considered. As prepared, the microparticles are highly suitable for state-of-the-art quantitative lab-on-a-bead interrogation of specimens.

iSERS microscopy guided by wide field immunofluorescence: analysis of HER2 expression on normal and breast cancer FFPE tissue sections

Surface-enhanced Raman scattering (SERS) microscopy is an emerging imaging technique for tissue-based cancer diagnostics. Specifically, immuno-SERS (iSERS) microscopy employs antibodies labelled by molecularly functionalized noble metal colloids for antigen localization on tissue specimen. Spectrally resolved iSERS acquisition schemes are typically rather time-consuming when large tissue areas must be scanned. Here, we demonstrate the application of iSERS imaging guided by wide field immunofluorescence (IF) for localization of the human epidermal growth factor receptor 2 (HER2) on breast tissue sections. The addition of unlabelled anti-HER2 primary antibodies to the tissue is followed by the incubation with secondary antibodies labelled with both Alexa-647 (for IF) and hydrophilically stabilized gold nanostars coated with aromatic thiols (for iSERS). False-color iSERS images clearly reveal the different HER2 expression levels on normal and breast cancer tissue, respectively. A series of negative controls confirms that the binding specificity of the secondary antibody is maintained after conjugation to the SERS nanoparticles.

Rapid, accurate, and comparative differentiation of clinically and industrially relevant microorganisms via multiple vibrational spectroscopic fingerprinting

Despite the fact that various microorganisms (e.g., bacteria, fungi, viruses, etc.) have been linked with infectious diseases, their crucial role towards sustaining life on Earth is undeniable. The huge biodiversity, combined with the wide range of biochemical capabilities of these organisms, have always been the driving force behind their large number of current, and, as of yet, undiscovered future applications. The presence of such diversity could be said to expedite the need for the development of rapid, accurate and sensitive techniques which allow for the detection, differentiation, identification and classification of such organisms. In this study, we employed Fourier transform infrared (FT-IR), Raman, and surface enhanced Raman scattering (SERS) spectroscopies, as molecular whole-organism fingerprinting techniques, combined with multivariate statistical analysis approaches for the classification of a range of industrial, environmental or clinically relevant bacteria (P. aeruginosa, P. putida, E. coli, E. faecium, S. lividans, B. subtilis, B. cereus) and yeast (S. cerevisiae). Principal components-discriminant function analysis (PC-DFA) scores plots of the spectral data collected from all three techniques allowed for the clear differentiation of all the samples down to sub-species level. The partial least squares-discriminant analysis (PLS-DA) models generated using the SERS spectral data displayed lower accuracy (74.9%) when compared to those obtained from conventional Raman (97.8%) and FT-IR (96.2%) analyses. In addition, whilst background fluorescence was detected in Raman spectra for S. cerevisiae, this fluorescence was quenched when applying SERS to the same species, and conversely SERS appeared to introduce strong fluorescence when analysing P. putida. It is also worth noting that FT-IR analysis provided spectral data of high quality and reproducibility for the whole sample set, suggesting its applicability to a wider range of samples, and perhaps the most suitable for the analysis of mixed cultures in future studies. Furthermore, our results suggest that while each of these spectroscopic approaches may favour different organisms (sample types), when combined, they would provide complementary and more in-depth knowledge (structural and/or metabolic state) of biological systems. To the best of our knowledge, this is the first time that such a comparative and combined spectroscopic study (using FT-IR, Raman and SERS) has been carried out on microbial samples.

Through tissue imaging of a live breast cancer tumour model using handheld surface enhanced spatially offset resonance Raman spectroscopy (SESORRS)

Detection of a live 3D tumour model through 15 mm of tissue using SESORRS.

In order to improve patient survival and reduce the amount of unnecessary and traumatic biopsies, non-invasive detection of cancerous tumours is of imperative and urgent need. Multicellular tumour spheroids (MTS) can be used as an ex vivo cancer tumour model, to model in vivo nanoparticle (NP) uptake by the enhanced permeability and retention (EPR) effect. Surface enhanced spatially offset Raman spectroscopy (SESORS) combines both surface enhanced Raman spectroscopy (SERS) and spatially offset Raman spectroscopy (SORS) to yield enhanced Raman signals at much greater sub-surface levels. By utilizing a reporter that has an electronic transition in resonance with the laser frequency, surface enhanced resonance Raman scattering (SERRS) yields even greater enhancement in Raman signal. Using a handheld SORS spectrometer with back scattering optics, we demonstrate the detection of live breast cancer 3D MTS containing SERRS active NPs through 15 mm of porcine tissue. False color 2D heat intensity maps were used to determine tumour model location. In addition, we demonstrate the tracking of SERRS-active NPs through porcine tissue to depths of up to 25 mm. This unprecedented performance is due to the use of red-shifted chalcogenpyrylium-based Raman reporters to demonstrate the novel technique of surface enhanced spatially offset resonance Raman spectroscopy (SESORRS) for the first time. Our results demonstrate a significant step forward in the ability to detect vibrational fingerprints from a tumour model at depth through tissue. Such an approach offers significant promise for the translation of NPs into clinical applications for non-invasive disease diagnostics based on this new chemical principle of measurement.

Simultaneous quantification of multiple endogenous biothiols in single living cells by plasmonic Raman probes

Three endogenous biothiols in single cells were simultaneously quantified by plasmonic Raman probes and quantitative principal component analysis (qPCA).

Intracellular biothiols mediate many important physiological and pathological processes. Due to their low content and competing thiol-reactivity, it is still an unmet challenge to quantify them within a complicated intracellular environment. Herein, we demonstrated a strategy to discriminate three biothiols, i.e. cysteine (Cys), homo-cysteine (Hcy) and glutathione (GSH), and quantify their concentrations within single living cells, using one platform of Raman probe. By monitoring the reaction kinetics of biothiols with Raman probes and discriminating their products with a quantitative principal component analysis (qPCA) method, these three biothiols could be simultaneously quantified in both cell lysis and single living cells. The concentrations of Cys, Hcy and GSH in single Hela cells were 158 ± 19 μM, 546 ± 67 μM and 5.07 ± 0.62 mM, respectively, which gives the precise concentrations of these three biothiols at a single cell level for the first time. This method provides a general strategy for discriminating each component from a mixed system and has potential for quantifying any biomolecules within an in vitro or in vivo biological environment.

Recent advances in different modal imaging-guided photothermal therapy

Photothermal therapy (PTT) has recently attracted considerable attention owing to its controllable treatment process, high tumour eradication efficiency and minimal side effects on non-cancer cells. PTT can melt cancerous cells by localising tissue hyperthermia induced by internalised therapeutic agents with a high photothermal conversion efficiency under external laser irradiation. Numerous in vitro and in vivo studies have shown the significant potential of PTT to treat tumours in future practical applications. Unfortunately, the lack of visualisation towards agent delivery and internalisation, as well as imaging-guided comprehensive evaluation of therapeutic outcome, limits its further application. Developments in combined photothermal therapeutic nanoplatforms guided by different imaging modalities have compensated for the major drawback of PTT alone, proving PTT to be a promising technique in biomedical applications. In this review, we introduce recent developments in different imaging modalities including single-modal, dual-modal, triple-modal and even multi-modal imaging-guided PTT, together with imaging-guided multi-functional theranostic nanoplatforms.

Raman scattering mediated by neighboring molecules

Raman scattering is most commonly associated with a change in vibrational state within individual molecules, the corresponding frequency shift in the scattered light affording a key way of identifying material structures. In theories where both matter and light are treated quantum mechanically, the fundamental scattering process is represented as the concurrent annihilation of a photon from one radiation mode and creation of another in a different mode. Developing this quantum electrodynamical formulation, the focus of the present work is on the spectroscopic consequences of electrodynamic coupling between neighboring molecules or other kinds of optical center. To encompass these nanoscale interactions, through which the molecular states evolve under the dual influence of the input light and local fields, this work identifies and determines two major mechanisms for each of which different selection rules apply. The constituent optical centers are considered to be chemically different and held in a fixed orientation with respect to each other, either as two components of a larger molecule or a molecular assembly that can undergo free rotation in a fluid medium or as parts of a larger, solid material. The two centers are considered to be separated beyond wavefunction overlap but close enough together to fall within an optical near-field limit, which leads to high inverse power dependences on their local separation. In this investigation, individual centers undergo a Stokes transition, whilst each neighbor of a different species remains in its original electronic and vibrational state. Analogous principles are applicable for the anti-Stokes case. The analysis concludes by considering the experimental consequences of applying this spectroscopic interpretation to fluid media; explicitly, the selection rules and the impact of pressure on the radiant intensity of this process.

Plasmonic nanostructures for surface enhanced spectroscopic methods

The development within the last five years in the field of surface enhanced spectroscopy methods was comprehensively reviewed.

Prospects for point-of-care pathogen diagnostics using surface-enhanced Raman scattering (SERS)

This review highlights recent advances in the application of surface-enhanced Raman scattering (SERS) in pathogen detection and discusses many of the challenges in moving this technology to the point-of-care (POC) arena.

Quantitative surface-enhanced Raman spectroscopy for kinetic analysis of aldol condensation using Ag–Au core–shell nanocubes

Ag–Au core–shell nanocube-based surface-enhanced Raman scattering (SERS) probes utilizing internal standard calibration for quantitative kinetic analysis of the aldol condensation reaction.

Magnetic and noble metal nanocomposites for separation and optical detection of biological species

Nanoalloys and nanocomposites are widely studied classes of nanomaterials within the context of biological systems. They are of immense interest because of the possibility of tuning the optical, magnetic, electronic and chemical properties through particle composition and internal architecture. In principle these properties can therefore be optimized for application in biological detections such as of DNA sequences, bacteria, viruses, antibodies, antigens, and cancer cells. This article presents an overview of methods currently used for nanoalloy and nanocomposite synthesis and characterisation, focusing on Au-Ag and FexOy@Au structures as primary components in detection platforms for plasmonic and magnetically enabled plasmonic bio-sensing.