A direct method for detecting proteins in body fluids by Surface-Enhanced Raman Spectroscopy under native conditions

An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning

To overcome the limitations of SERS in food safety monitoring, particularly significant interference from citrate ions, this study introduces an intelligent SERS-based platform for food safety monitoring. The platform utilizes sodium borohydride to activate silver nanoparticles, and calcium ions can facilitate the nanoparticles aggregation to promote self-assembly and the form of "hotspots", but will also amplify citrate ions signal. Iodine ions was introduced to eliminate the interference of citrate signals and background fluorescence interference. The substrate achieved limit of detection of 100 fg/mL. Moreover, the innovative of spectral set "SERSome" enables comprehensive molecular fingerprint recognition, significantly enhancing accuracy. Furthermore, combined with machine learning enhances applicability for rapid and precise detection, and classification in food samples, and successfully applied to the monitoring of illegal additives in food. In summary, this system presents an intelligent, innovative detection platform for food safety, contributing to early prevention of foodborne illnesses.

Raman Peak Features Matching: Enhancing Spectral Analysis through Feature Augmentation

Raman spectroscopy has emerged as a pivotal technology in modern scientific research and industrial applications, offering nondestructive, high-resolution analysis with robust molecular fingerprinting capabilities. The extraction of Raman spectral features is a critical step in spectral data analysis, directly influencing sample identification, classification, and quantitative outcomes. However, integrating important data features from machine learning models with context-specific biosignatures to derive meaningful insights into spectral analysis remains a significant challenge. Herein, the Raman Peak Feature Matching (RPFM) method is proposed, which matches protein peak features with salient breast cell data features extracted from the machine learning models. Feature augmentation is subsequently applied to the matching-retained breast cell features, thereby enhancing spectral analysis capabilities. The RPFM method is applied to breast cell spectra for feature augmentation with a reclassification accuracy of 97.12% using a linear support vector machine model, achieving an 8.34% improvement over the model's performance without feature augmentation. The RPFM method has also been successfully implemented in generalized linear logistic regression and tree-based eXtreme gradient boosting, demonstrating its versatility across diverse machine learning algorithms. The RPFM method leverages data-driven machine learning models while compensating for the inability to take into account specific specialized background knowledge. This methodology significantly advances the accuracy and efficacy of spectral analysis in biological and medical applications, offering a novel framework for machine learning algorithms to perform augmented Raman spectral analysis.

Surface-Enhanced Raman Spectroscopy for Biomedical Applications: Recent Advances and Future Challenges

The year 2024 marks the 50th anniversary of the discovery of surface-enhanced Raman spectroscopy (SERS). Over recent years, SERS has experienced rapid development and became a critical tool in biomedicine with its unparalleled sensitivity and molecular specificity. This review summarizes the advancements and challenges in SERS substrates, nanotags, instrumentation, and spectral analysis for biomedical applications. We highlight the key developments in colloidal and solid SERS substrates, with an emphasis on surface chemistry, hotspot design, and 3D hydrogel plasmonic architectures. Additionally, we introduce recent innovations in SERS nanotags, including those with interior gaps, orthogonal Raman reporters, and near-infrared-II-responsive properties, along with biomimetic coatings. Emerging technologies such as optical tweezers, plasmonic nanopores, and wearable sensors have expanded SERS capabilities for single-cell and single-molecule analysis. Advances in spectral analysis, including signal digitalization, denoising, and deep learning algorithms, have improved the quantification of complex biological data. Finally, this review discusses SERS biomedical applications in nucleic acid detection, protein characterization, metabolite analysis, single-cell monitoring, and in vivo deep Raman spectroscopy, emphasizing its potential for liquid biopsy, metabolic phenotyping, and extracellular vesicle diagnostics. The review concludes with a perspective on clinical translation of SERS, addressing commercialization potentials and the challenges in deep tissue in vivo sensing and imaging.

A Surface-Enhanced Raman Spectroscopy Platform Integrating Dual Signal Enhancement and Machine Learning for Rapid Detection of Veterinary Drug Residues in Meat Products

The detection and quantification of veterinary drug residues in meat remain a significant challenge due to the complex background interference inherent to the meat matrix, which compromises the stability and accuracy of spectroscopic analysis. This study introduces an advanced label-free surface-enhanced Raman spectroscopy (SERS) platform for the precise identification and quantification of veterinary drugs. By employing a dual enhancement strategy involving sodium borohydride activation and calcium ion-deuterium oxide guidance, this platform achieves the efficient capture and signal amplification of drug molecules on highly active nanoparticles. High-quality SERS spectra were obtained for carprofen, doxycycline hydrochloride, chloramphenicol, and penicillin G sodium salt, enabling accurate classification and interference suppression. In addition, the application of machine learning algorithms, including PCA-LDA, heatmap, and decision tree modeling, allows for accurate differentiation of mixed drug samples. Quantitative analyses in meat samples were achieved through Raman intensity ratios and multivariate curve resolution-alternate least-squares (MCR-ALS) analysis, with results showing high consistency with high-performance liquid chromatography (HPLC) measurements. These findings highlight the potential of this SERS-based platform for accurate and rapid detection of multicomponent veterinary drug residues in complex food matrices.

Design and Engineering of Silver Nanomushroom Arrays as a Universal Solid-State SERS Platform for the Label-Free, Sensitive, and Quantitative Detection of Trace Proteins

Surface-enhanced Raman scattering (SERS) is an ultrasensitive optical technique that is critical for protein detection and essential for identifying protein structure and concentrations in various biomedical and diagnostic applications. However, achieving highly sensitive and reproducible SERS signals for label-free proteins remains challenging due to their weak Raman signals and structural complexity. In this study, silver nanomushroom arrays (Ag NMAs) as SERS substrates were readily prepared and surface-engineered using a facile template-assisted micro- and nanofabrication approach. The surface of the substrate exhibits nanoscale roughness, long-range order, and hydrophilicity, enabling rapid and uniform dispersion of protein molecules. These molecules are anchored through Ag-S bonds, resulting in ultrasensitive Raman signals driven by strong electromagnetic enhancement effects. The highly ordered array structure improves signal repeatability, achieving a relative standard deviation of as low as 4.32%. Additionally, utilizing the silicon characteristic peak of the SERS substrate as an internal standard significantly reduces measurement errors, allowing for reliable and precise quantitative detection of protein molecules, with a linear correlation coefficient (R2) exceeding 0.96. Ultrasensitive SERS detection and effective protein discrimination via principal component analysis further validate the Ag NMA substrate's potential for universal trace protein detection. This study presents an advanced SERS platform for the sensitive and rapid detection of trace proteins, showcasing significant potential in pharmaceutical research, metabolic studies, diagnostic medicine, and protein engineering.

Advancing Protein Detection and Analysis Based on Ag/Au PHCN for Enhanced SERS Sensitivity and Specificity in Biomolecular Diagnostics

In the realm of disease diagnostics, particularly for conditions such as proteinuria and hemoglobinuria, the quest for a method that combines accurate, label-free detection of protein compositions and their conformational changes remains a formidable challenge. In this study, we introduce an innovative Ag/Au plasmonic hybrid coupling nanoarray (Ag/Au PHCN) architecture marked by sub-10 nm interparticle gaps. These nanoarrays, leveraging plasmonic hybrid coupling and synergistic enhancement mechanisms, create a plethora of uniform surface-enhanced Raman spectroscopy (SERS) hotspots. The Ag/Au PHCN substrates demonstrated unparalleled sensitivity in the unmarked detection of hemoglobin (HGB), bovine serum albumin (BSA), and cytochrome C (Cyt.C) in bodily fluids, incorporating the advantages of high sensitivity, high reproducibility, durability, recyclability, and biocompatibility. Notably, the detection limits for BSA and HGB are unprecedented at 0.5 and 5 ng/mL, respectively. This achievement sets a new benchmark for label-free protein detection using two-dimensional nanostructures. Crucially, the Ag/Au PHCNs possess the novel capability to discern protein conformational changes post denaturation, underscoring their potential in probing protein functionalities. Most importantly, these nanoarrays can differentiate between normal and proteinuria-affected urine samples and monitor protein content variations over time, heralding a new era in clinical diagnostics with particular relevance to proteinuria and hemoglobinuria detection.

Direct comparison of different protocols to obtain surface enhanced Raman spectra of human serum

Label-free Surface Enhanced Raman Spectroscopy (SERS) is a rapid technique that has been extensively applied in clinical diagnosis and biomedicine for the analysis of biofluids. The purpose of this approach relies on the ability to detect specific "metabolic fingerprints" of complex biological samples, but the full potential of this technique in diagnostics is yet to be exploited, mainly because of the lack of common analytical protocols for sample preparation and analysis. Variation of experimental parameters, such as substrate type, laser wavelength and sample processing can greatly influence spectral patterns, making results from different research groups difficult to compare. This study aims at making a step toward a standardization of the protocols in the analysis of human serum samples with Ag nanoparticles, by directly comparing the SERS spectra obtained from five different methods in which parameters like laser power, nanoparticle concentration, incubation/deproteinization steps and type of substrate used vary. Two protocols are the most used in the literature, and the other three are "in-house" protocols proposed by our group; all of them are employed to analyze the same human serum sample. The experimental results show that all protocols yield spectra that share the same overall spectral pattern, conveying the same biochemical information, but they significantly differ in terms of overall spectral intensity, repeatability, and preparation steps of the sample. A Principal Component Analysis (PCA) was performed revealing that protocol 3 and protocol 1 have the least variability in the dataset, while protocol 2 and 4 are the least repeatable.

Advances in Label-Free Glucose Detection Using Self-Assembled Nanoparticles and Surface-Enhanced Raman Spectroscopy

In the landscape of biomolecular detection, surface-enhanced Raman spectroscopy (SERS) confronts notable obstacles, particularly in the label-free detection of biomolecules, with glucose and other sugars presenting a quintessential challenge. This study heralds the development of a pioneering SERS substrate, ingeniously engineered through the self-assembly of nanoparticles of diverse sizes (Ag1@Ag2NPs). This configuration strategically induces 'hot spots' within the interstices of nanoparticles, markedly amplifying the detection signal. Rigorous experimental investigations affirm the platform's rapidity, precision, and reproducibility, and the detection limit of this detection method is calculated to be 6.62 pM. Crucially, this methodology facilitates nondestructive glucose detection in simulated samples, including phosphate-buffered saline and urine. Integrating machine learning algorithms with simulated serum samples, the approach adeptly discriminates between hypoglycemic, normoglycemic, and hyperglycemic states. Moreover, the platform's versatility extends to the detection and differentiation of monosaccharides, disaccharides, and methylated glycosides, underscoring its universality and specificity. Comparative Raman spectroscopic analysis of various carbohydrate structures elucidates the unique SERS characteristics pertinent to these molecules. This research signifies a major advance in nonchemical, label-free glucose determination with enhanced sensitivity via SERS, laying a new foundation for its application in precision medicine and advancing structural analysis in the sugar domain.

Reliable biological and multi-omics research through biometrology

Metrology is the science of measurement and its applications, whereas biometrology is the science of biological measurement and its applications. Biometrology aims to achieve accuracy and consistency of biological measurements by focusing on the development of metrological traceability, biological reference measurement procedures, and reference materials. Irreproducibility of biological and multi-omics research results from different laboratories, platforms, and analysis methods is hampering the translation of research into clinical uses and can often be attributed to the lack of biologists' attention to the general principles of metrology. In this paper, the progresses of biometrology including metrology on nucleic acid, protein, and cell measurements and its impacts on the improvement of reliability and comparability in biological research are reviewed. Challenges in obtaining more reliable biological and multi-omics measurements due to the lack of primary reference measurement procedures and new standards for biological reference materials faced by biometrology are discussed. In the future, in addition to establishing reliable reference measurement procedures, developing reference materials from single or multiple parameters to multi-omics scale should be emphasized. Thinking in way of biometrology is warranted for facilitating the translation of high-throughput omics research into clinical practices.

Surface-Enhanced Raman Spectroscopy-Based Detection of EMT-Related Targets in Endometrial Cancer: Potential for Diagnosis and Prognostic Prediction

Epithelial-mesenchymal transformation (EMT) is one of the important mechanisms of malignancy in endometrial cancer, and detection of EMT targets is a key challenge to explore the mechanism of endometrial carcinoma (EC) malignancy and discover novel therapeutic targets. This study attempts to use surface-enhanced Raman spectroscopy (SERS), a highly sensitive, ultrafast, and highly specific analytical technology, to rapidly detect microRNA-200a-3p and ZEB1 in endometrial cancer cell lines. The silver nanoparticles were decorated with iodine and calcium ions, can capture the SERS fingerprints of microRNA-200a-3p and ZEB1 protein, and effectively avoid the interference of impurity signals. At the same time, the method has high sensitivity for the detection of the above EMT targets, and the lowest detection limits for microRNA-200a-3p and ZEB1 are 4.5 pmol/mL and 10 ng/mL, respectively. At the lowest detection concentration, the method still has high stability. In addition, principal component analysis can not only identify microRNA-200a-3p and ZEB1 protein from a variety of EMT-associated microRNA and proteins but also identify them in the total RNA and total protein of endometrial cancer cell lines and normal endometrial epithelial cell lines. This study modified silver nanoparticles with iodine and calcium ions and for the first time captured the fingerprints of EMT-related targets microRNA-200a-3p and ZEB1 at the same time without label, and the method has high sensitivity and stability. This SERS-based method has immense potential for elucidating the molecular mechanisms of EMT-related EC, as well as identifying biomarkers for malignant degree and prognosis prediction.

Three-dimensional hotspot structures constructed from nanoporous gold with a V-cavity and gold nanoparticles for surface-enhanced Raman scattering

The intensity and sensitivity of surface-enhanced Raman scattering (SERS) spectra are highly dependent on the consistency and homogeneity of the nanomaterials. In this study, we developed a large-area three-dimensional (3D) hotspot substrate with good homogeneity and reproducibility in SERS signals. The substrate is based on the synergistic structures of nanoporous gold (NPG) and gold nanoparticles (AuNPs). NPG was combined with a periodic V-shaped nanocavity array to create nanoporous gold with a V-cavity (NPGVC) array featuring uniform hotspots. A nanoporous gold V-shaped resonant cavity (NPGVRC) structure was developed by incorporating AuNPs into the NPGVC array. The coupling action between the AuNPs and NPGVC resulted in a SERS-enhanced electromagnetic field with 3D hotspot distribution. The strategic incorporation of NPG and V-cavity array significantly expanded the surface area available for analyte adsorption and interaction with AuNPs. Using rhodamine 6G (R6G) and malachite green (MG) as probe molecules, the SERS performance was investigated, and the NPGVRC substrate not only showed excellent enhancement with the limit of detection as low as 10-11 M, but also presented good homogeneity. NPGVRC was then used for biological detection of the influenza A virus, where we acquired and examined the characteristic SERS spectra of two spike proteins. It is demonstrated that there is significant potential for our proposed SERS platform to be used in biosensors.

Deciphering biomolecular complexities: the indispensable role of surface-enhanced Raman spectroscopy in modern bioanalytical research

Surface-enhanced Raman spectroscopy (SERS) has emerged as an indispensable analytical tool in biomolecular research, providing unmatched sensitivity critical for the elucidation of biomolecular structures. This review presents a thorough examination of SERS, outlining its fundamental principles, cataloging its varied applications within the biomolecular sphere, and contemplating its future developmental trajectories. We begin with a detailed analysis of SERS's mechanistic principles, emphasizing both the phenomena of surface enhancement and the complexities inherent in Raman scattering spectroscopy. Subsequently, we delve into the pivotal role of SERS in the structural analysis of diverse biomolecules, including proteins, nucleic acids, lipids, carbohydrates, and biochromes. The remarkable capabilities of SERS extend beyond mere detection, offering profound insights into biomolecular configurations and interactions, thereby enriching our comprehension of intricate biological processes. This review also sheds light on the application of SERS in real-time monitoring of various bio-relevant compounds, from enzymes and coenzymes to metal ion-chelate complexes and cellular organelles, thereby providing a holistic view and empowering researchers to unravel the complexities of biological systems. We also address the current challenges faced by SERS, such as enhancing sensitivity and resolution, developing stable and reproducible substrates, and conducting thorough analyses in complex biological matrices. Nonetheless, the continual advancements in nanotechnology and spectroscopy solidify the standing of SERS as a formidable force in biomolecular research. In conclusion, the versatility and robustness of SERS not only deepen our understanding of biomolecular intricacies but also pave the way for significant developments in medical research, therapeutic innovation, and diagnostic approaches.

A breakthrough in phytochemical profiling: ultra-sensitive surface-enhanced Raman spectroscopy platform for detecting bioactive components in medicinal and edible plants

A perennial challenge in harnessing the rich biological activity of medicinal and edible plants is the accurate identification and sensitive detection of their active compounds. In this study, an innovative, ultra-sensitive detection platform for plant chemical profiling is created using surface-enhanced Raman spectroscopy (SERS) technology. The platform uses silver nanoparticles as the enhancing substrate, excess sodium borohydride prevents substrate oxidation, and methanol enables the tested molecules to be better adsorbed onto the silver nanoparticles. Subsequently, nanoparticle aggregation to form stable "hot spots" is induced by Ca2+, and the Raman signal of the target molecule is strongly enhanced. At the same time, deuterated methanol was used as the internal standard for quantitative determination. The method has excellent reproducibility, RSD ≤ 1.79%, and the enhancement factor of this method for the detection of active ingredients in the medicinal plant Coptis chinensis was 1.24 × 109, with detection limits as low as 3 fM. The platform successfully compared the alkaloid distribution in different parts of Coptis chinensis: root > leaf > stem, and the difference in content between different batches of Coptis chinensis decoction was successfully evaluated. The analytical technology adopted by the platform can speed up the determination of Coptis chinensis and reduce the cost of analysis, not only making better use of these valuable resources but also promoting development and innovation in the food and pharmaceutical industries. This study provides a new method for the development, evaluation, and comprehensive utilization of both medicinal and edible plants. It is expected that this method will be extended to the modern rapid detection of other medicinal and edible plants and will provide technical support for the vigorous development of the medicinal and edible plants industry.

ZIF-8 encapsulated-enzymes integrated nanozyme cascade biocatalysis platform for the colorimetric sensing of glucose and lactose in milk

Cascade biocatalytic reactions have a wide range of applications, especially in the filed of food analysis. Herein, a multi-enzyme composite (ZGGPC) was prepared by in-situ synthesis of Zeolite imidazole framework-8 (ZIF-8) on Prussian blue (PB) modified carbon cloth (CC). The composite encapsulated both glucose oxidase and β-galactosidase simultaneously during the synthesis process. CC and ZIF-8 showed high loading capacity for PB and natural enzymes, respectively. And ZIF-8 also displayed excellent tolerance in protecting enzyme activity under extreme conditions. Based on the cascade biocatalysis, ZGGPC was used to detect glucose and lactose by colorimetric method with detection limits of 1.2 μM and 1.7 mM, respectively. Benefiting from the merits of low cost, easy preparation, and good stability, the sensing system was used to successfully determine glucose and lactose in different milk samples. The present cascade biocatalysis system is hopeful to develop simple and efficient sensing platforms for food analysis.

Handcrafted silver substrates boost surface plasmon resonance for ultra-sensitive lipid analysis

Lipid monitoring plays a crucial role in biomedical research, particularly in the areas of cardiovascular health, metabolic disorders and nutrition. However, direct and highly sensitive detection of lipids poses significant challenges due to the interference of high SERS background noise in lipid samples. In this study, we present a SERS platform for the quantitative analysis of lipids. By harnessing the Surface Plasmon Resonance (SPR) effect of nanostructured grooves and leveraging deuterium oxide, a remarkable enhancement of in-situ Raman signals originating from cholesterol is achieved. This approach yielded an impressive average enhancement factor of 7.3 × 105 and a detection limit of 1.9 × 10-4 mg/mL, highlighting the exceptional sensitivity and precision of our method. We have obtained high quality, in-situ SERS signals for six distinct lipid molecules. Rapid identification of lipid samples in mixed systems has been achieved through the combination of characteristic peak analysis and PCA-LDA, including the detection of SERS signals from lipids in milk. Notably, univariate monitoring of in-situ cholesterol in human serum was successfully achieved for the first time using deuterium water as an internal standard. In addition, silver substrate demonstrated outstanding reproducibility, maintaining consistent SERS activity even after more than 10 repetitions. Therefore, this platform offers the distinct advantages of high sensitivity, specificity and cost-effectiveness for lipid detection. These findings enable dietary management and blood lipid monitoring, and therefore hold crucial implications for the early prevention of lipid-related disorders and diseases.

DNA induced CTAB-caped gold bipyramidal nanoparticles self-assembly using for Raman detection of DNA molecules

DNA is an indispensable part of metabolism, which affects many important processes in the body, including gene expression, protein synthesis, and drug delivery. Surface-enhanced Raman spectroscopy (SERS) is one of the most important methods used to study the structure and function of DNA and can obtain rich DNA molecular fingerprints. However, it is still a great challenge to use SERS to directly analyze the characteristic Raman signals of the DNA molecule and achieve rapid and simple detection. Hence, a detection platform based on gold bipyramidal nanoparticles (AuNBs) self-assembly that can be directly used for the detection of DNA molecules without the need for additional aggregators and cleaning agents was designed in this study. The original hexadecyltrimethylammonium bromide (CTAB) of AuNBs can be used as the internal standard for DNA quantification without an additional standard. This is the first time that the Raman signals of the analyte molecule can be obtained directly without labels by using the interaction between the molecule and the enhanced substrate. We used this method to capture the original DNA molecules in methylated DNA, serum, and cell metabolites and obtained spectral data processing results using linear discriminant analysis (LDA). This provides new ideas for the digitization of disease treatment and the study of the metabolic processes of life.

Colloidal SERS measurement of enrofloxacin with petaloid nanostructure clusters formed by terminal deoxynucleotidyl transferase catalyzed cytosine-constituted ssDNA

We developed petal-like plasmonic nanoparticle (PLNP) clusters-based colloidal SERS method for enrofloxacin (EnFX) detection. PLNPs were synthesized by the regulation of single-stranded DNA composed of homo-cytosine deoxynucleotides (hC) catalyzed by terminal deoxynucleotidyl transferase. SERS hot spots were created via the agglomeration process of PLNPs by adding an inorganic salt potassium iodide solution, in which EnFX molecules were attached to the negatively charged PLNPs surface by electrostatic interactions. This approach enabled direct in situ detection of antibiotic residues, achieving a limit of detection (LOD) of 1.15 μg/kg for EnFX. The spiked recoveries of the SERS method were approximately 92.7% to 107.2% and the RSDs ranged from 1.05% to 7.8%, indicating that the method can be applied to actual sample detection. This colloidal SERS measurement platform would be very promising in various applications, especially in real-time and on-site food safety screening owing to its rapidness, simplicity, and sensitivity.

Detection of simple proteins by direct surface-enhanced Raman scattering based on the Hofmeister ion-specific effect

Surface-enhanced Raman scattering (SERS) spectroscopy has unique advantages in detecting biomolecules, but label-free determination of proteins with low scattering cross-sections remains challenging. In this study, such proteins' SERS signals have been optimized using the Hofmeister effect between protein molecules and CsI solution at physiological concentrations (A 100 mmol/L Cesium iodide, CsI). Cs⁺ as chaotro cation ion has a complex interaction mechanism with protein, can not only deprive hydrated water molecules on the surface of protein but also penetrate into the hydrophobic interior of protein. In addition to the above advantages, I^- in excess CsI solution with appropriate concentration can removes the interference of citric acid-based impurities on the surface of silver nanoparticles, and Cs⁺ in excess CsI solution attracts the aggregation of negatively charged silver nanoparticles and cause local electromagnetic field enhancement to achieve high sensitivity in protein detection. This has been combined with principal component analysis to perform a comprehensive analysis of several proteins. Molecular dynamics simulations have been performed to study the mechanism of interaction between CsI and proteins. In addition, the vibrational peak of water has been used as an internal standard to quantify the protein content, and a good linear relationship between peak intensity and concentration was obtained.

Universal Method for Label-Free Detection of Pathogens and Biomolecules by Surface-Enhanced Raman Spectroscopy Based on Gold Nanoparticles

The detection of biomolecules is the key to basic molecular research, diagnostics, drug screening, and other biomedical applications. However, the existing detection techniques can only detect single classes of biomolecules, which warrant the development of a versatile biomolecule detection platform. Here, we developed a universal method for label-free detection of biomolecules via surface-enhanced Raman spectroscopy (SERS) by using sulfhydryl-modified gold nanoparticles as the substrate. The biomolecules can be adsorbed on the surface of gold nanoparticles cleaned by bromide ions to obtain initially enhanced Raman signals, and the aggregator (calcium ion) was further added to form a "hot spot", which enhanced the biomolecular signal again. Through the "two-step enhancement method", we were able to obtain fingerprints of DNA, RNA, amino acids, peptides, proteins, viruses, bacteria, and lipid molecules. This low-toxic, highly sensitive, and widely applicable technique has potential applications in biomedical research, clinical testing, and disease diagnosis and lays the foundation for the development of SERS technology in various fields.

Electrochemical Synthesis, Magnetic and Optical Characterisation of FePd Dense and Mesoporous Nanowires

Dense and mesoporous FePd nanowires (NWs) with 45 to 60 at.% Pd content were successfully fabricated by template- and micelle-assisted pulsed potentiostatic electrodeposition using nanoporous anodic alumina and polycarbonate templates of varying pore sizes. An FePd electrolyte was utilized for obtaining dense NWs while a block copolymer, P-123, was added to this electrolyte as the micelle-forming surfactant to produce mesoporous NWs. The structural and magnetic properties of the NWs were investigated by electron microscopy, X-ray diffraction, and vibrating sample magnetometry. The as-prepared NWs were single phase with a face-centered cubic structure exhibiting 3.1 µm to 7.1 µm of length. Mesoporous NWs revealed a core-shell structure where the porosity was only witnessed in the internal volume of the NW while the outer surface remained non-porous. Magnetic measurements revealed that the samples displayed a soft ferromagnetic behavior that depended on the shape anisotropy and the interwire dipolar interactions. The mesoporous core and dense shell structure of the NWs were seen to be slightly affecting the magnetic properties. Moreover, mesoporous NWs performed excellently as SERS substrates for the detection of 4,4'-bipyridine, showing a low detection limit of 10^-12 M. The signal enhancement can be attributed to the mesoporous morphology as well as the close proximity of the embedded NWs being conducive to localized surface plasmon resonance.

A direct approach toward investigating DNA-ligand interactions via surface-enhanced Raman spectroscopy combined with molecular dynamics simulations

Small molecules that interfere with DNA replication can trigger genomic instability, which makes these molecules valuable in the search for anticancer drugs. Thus, interactions between DNA and its ligands at the molecular level are of great significance. In the present study, a new method based on surface-enhanced Raman spectroscopy (SERS) combined with molecular dynamics simulations has been proposed for analyzing the interactions between DNA and its ligands. The SERS signals of DNA hairpins (ST: d(CGACCAACGTGTCGCCTGGTCG), AP1: d(CGCACAACGTGTCGCCTGTGCG)), pure argininamide, and their complexes, were obtained, and the characteristic peak sites of the DNA secondary structure and argininamide ligand-binding region were analyzed. Molecular dynamics calculations predicted that argininamide binds to the 8C and 9G bases of AP1 via hydrogen bonding. Our method successfully detected the changes of SERS fingerprint peaks of hydrogen bonds and bases between argininamide and DNA hairpin bases, and their binding sites and action modes were consistent with the predicted results of the molecular dynamics simulations. This SERS technology combined with the molecular dynamics simulation detection platform provides a general analysis tool, with the advantage of effective, rapid, and sensitive detection. This platform can obtain sufficient molecular level conformational information to provide avenues for rapid drug screening and promote progress in several fields, including targeted drug design.

Rapid Detection of SARS-CoV-2 Spike RBD Protein in Body Fluid: Based on Special Calcium Ion-Mediated Gold Nanoparticles Modified by Bromide Ions

The receptor-binding domain of the SARS-CoV-2 spike mediates the key to binding the virus to the host receptor, but capturing the molecular signal of this spike RBD remains a formidable challenge. Here, we report a new surface-enhanced Raman spectroscopy (SERS) approach, which used gold nanoparticles prepared by low-speed constant-temperature centrifugation by bromine and calcium ions in two cleaning steps as the enhanced substrate to rapidly and accurately detect spike RBD large protein molecules in body fluids. The detection signal was extremely stable, and the orientation of the spike RBD on the enhanced substrate surface was also determined. This approach was specific in distinguishing different SARS-CoV-2 variants of spike RBD, including Delta, Beta, Gamma, and Omicron. Additionally, the enhanced substrate can identify biologically active or inactive spike RBD. This two-step cleaning enhanced substrate opens up opportunities not only for early diagnostics of SARS-CoV-2 virus but also for developing targeted drugs against viruses.

Correlation coefficient-directed label-free characterization of native proteins by surface-enhanced Raman spectroscopy

Investigation of proteins in their native state is the core of proteomics towards better understanding of their structures and functions. Surface-enhanced Raman spectroscopy (SERS) has shown its unique advantages in protein characterization with fingerprint information and high sensitivity, which makes it a promising tool for proteomics. It is still challenging to obtain SERS spectra of proteins in the native state and evaluate the native degree. Here, we constructed 3D physiological hotspots for a label-free dynamic SERS characterization of a native protein with iodide-modified 140 nm Au nanoparticles. We further introduced the correlation coefficient to quantitatively evaluate the variation of the native degree, whose quantitative nature allows us to explicitly investigate the Hofmeister effect on the protein structure. We realized the classification of a protein of SARS-CoV-2 variants in 15 min, which has not been achieved before. This study offers an effective tool for tracking the dynamic structure of proteins and biomedical research.

How Surface-Enhanced Raman Spectroscopy Could Contribute to Medical Diagnoses

In the last decade, there has been a rapid increase in the number of surface-enhanced Raman scattering (SERS) spectroscopy applications in medical research. In this article we review some recent, and in our opinion, most interesting and promising applications of SERS spectroscopy in medical diagnostics, including those that permit multiplexing within the range important for clinical samples. We focus on the SERS-based detection of markers of various diseases (or those whose presence significantly increases the chance of developing a given disease), and on drug monitoring. We present selected examples of the SERS detection of particular fragments of DNA or RNA, or of bacteria, viruses, and disease-related proteins. We also describe a very promising and elegant ‘lab-on-chip’ approach used to carry out practical SERS measurements via a pad whose action is similar to that of a pregnancy test. The fundamental theoretical background of SERS spectroscopy, which should allow a better understanding of the operation of the sensors described, is also briefly outlined. We hope that this review article will be useful for researchers planning to enter this fascinating field.