Recent development of surface-enhanced Raman scattering for biosensing

Prediction of cardiac differentiation in human induced pluripotent stem cell-derived cardiomyocyte supernatant using surface-enhanced Raman spectroscopy and machine learning

The efficient manufacturing of cardiomyocytes from human-induced pluripotent stem cells (hiPSCs) is essential for advancing regenerative therapies for myocardial injuries. However, ensuring cell quality during production is challenging since traditional methods are invasive, destructive, and time-consuming. In this study, we monitored cardiomyocyte differentiation of WTC11 hiPSCs by analyzing conditioned media collected at various stages using Raman spectroscopy, multivariate analysis, and machine learning. Differentiation efficiency was confirmed via flow cytometry and immunostaining. Raman spectra were processed using standard normal variate and second derivative transformations before performing a principal component analysis (PCA) and machine learning (Random Forest, K-Nearest Neighbors, and Deep Neural Networks [DNN]). Results show that PCA was unable to distinguish cells based on differentiation stages, while machine learning could reliably predict cell differentiation early in the cardiac cell manufacturing process. DNN models achieved accuracies exceeding 82 % in predicting differentiation, highlighting their potential as quality control tools. These findings underscore the potential of Raman spectroscopy coupled with machine learning as a tool for real-time monitoring of cardiomyocyte production.

Femtosecond-laser enabled hybrid manufacturing of scalable and disposable high-performance SERS substrates

Surface-enhanced Raman spectroscopy (SERS) is a well-known label-free analytical technique for chemical and biological detection. Electromagnetic enhancement near the nanostructured surfaces contributes to the SERS performance. However, the substrate-based nanostructured SERS surfaces are conventionally fabricated using time- and resource-intensive techniques. A cost-effective and scalable process chain to fabricate disposable thermoplastic SERS substrates is investigated herewith. The surface design includes a multiscale topography that consists of single-tier laser-induced periodic surface structures (LIPSSs) encircled by two-tier hierarchical structures (HSs). Different types of LIPSS were investigated, generated by linear and circular polarisation of the laser. The process chain employed to produce high-performance SERS substrates includes, first, ultrashort laser-enabled fabrication of a textured metallic master and then replication of functional topographies on cyclic olefin copolymer (COC) using hot embossing and finally mask-coating the LIPSS 'hot spot' with gold for an electromagnetic enhancement. The HS topographies facilitated the superhydrophobic evaporation of samples to enrich the analytes onto the SERS 'hot spot' on the COC substrates. This multiscale design achieved a detection limit of up to 10-7M for methylene blue and 4-MBA analytes. Highly regular linear LIPSS produced consistent Raman signals with a relative standard deviation (RSD) of 6.7%, ensuring reproducibility. In contrast quasi-regular triangular LIPSS exhibited enhanced signal intensity but with a relatively higher RSD of 10.2%. This scalable and cost-efficient approach has potential for widespread use in food and agricultural sectors, advancing the practical applications of SERS technology.

Synergistic Defect and Heterojunction Engineering for Significantly Increased Raman Enhancement on Monolayer Metallic Transition Metal Chalcogenide Nanosheets

2D transition metal chalcogenide nanosheets (TMC NSs) have been recognized as ideal platforms for surface-enhanced Raman spectroscopy (SERS). Nevertheless, the unsatisfying Raman enhancement exerts a substantial restriction on their practical applications. Herein, a strategy is demonstrated simultaneously integrating defect and heterojunction engineering within metallic TMC NSs for highly sensitive SERS detection of analytes. Particularly, metallic FeSe-CoSex/Cu monolayers with finely controlled Cu ion doping ratios and rich FeSe-CoSex/Cu heterojunctions are synthesized. The metallic property endows abundant electronic density of states (DOS) near the fermi level for increasing electron transition probability. The heterojunctions enable the delivery of electrons from FeSe to CoSex/Cu, contributing to charge transfer (CT) from CoSex/Cu to probe molecules. Moreover, Cu ions doping can well modulate the electronic structure of CoSex/Cu, further facilitating the CT between substrates and molecules. Benefiting from the rational engineering of defects and heterojunctions, an ultrasensitive molecular sensing performance is obtained on the FeSe-CoSex/Cu30% NSs. The practical application of the FeSe-CoSex/Cu30% NSs in trace and quantitative SERS detection of metamitron herbicide in water samples is successfully achieved with the limit of detection (LOD) of 1.3 × 10-8 M.

Functionalized Single Crystal Perovskite Materials for SERS and Their Potential Detection Applications

Recent advances in detection and diagnostic tools have improved understanding and identification of plant physiological and biochemical processes. Effective and safe Surface Enhanced Raman Spectroscopy (SERS) can find objects quickly and accurately. Raman enhancement amplifies the signal by 1014-1015 to accurately quantify plant metabolites at the molecular level. This paper shows how to use functionalized perovskite substrates for SERS. These perovskite substrates have lots of surface area, intense Raman scattering, and high sensitivity and specificity. These properties eliminate sample matrix component interference. This study identified research gaps on perovskite substrates' effectiveness, precision, and efficiency in biological metabolite detection compared to conventional substrates. This article details the synthesis and use of functionalized perovskites for plant metabolites measurement. It analyzes their pros and cons in this context. The manuscript analyzes perovskite-based SERS substrates, including single-crystalline perovskites with enhanced optoelectronic properties. This manuscript aims to identify this study gap by comprehensively reviewing the literature and using it to investigate plant metabolite detection in future studies.

Innovative applications of SERS in precision medicine: In situ and real-time live imaging

Surface-enhanced Raman scattering (SERS), a molecular spectroscopic technique with high sensitivity and specificity, has demonstrated groundbreaking potential in precision medicine in recent years. This review systematically summarizes recent advancements in SERS technology for in situ and real-time live imaging, focusing on its core value in early tumor diagnosis, intraoperative navigation, drug delivery monitoring, and dynamic pathological analysis. By optimizing nanoscale probe design-including targeted functionalization, enhanced biocompatibility, and integration with imaging systems-SERS overcomes the sensitivity and spatiotemporal resolution limitations of traditional imaging techniques, enabling precise capture and dynamic tracking of molecular events in live biological environments. The article further analyzes challenges in clinical translation, such as signal stability in complex biological environments, multimodal imaging coordination, and standardized data processing methods. Future directions for personalized therapy and intelligent integrated diagnostics are also discussed.

Ultra-sensitive surface plasmon resonance sensor integrating MXene (Ti3C2TX) and graphene for advanced carcinoembryonic antigen detection

Carcinoembryonic antigen (CEA) is a critical biomarker for diagnosing and monitoring cancers such as liver, colon, and breast cancer. This study presents a highly sensitive surface plasmon resonance (SPR) sensor incorporating 2D materials-graphene and MXene (Ti3C2TX)- in a Kretschmann configuration. The sensor, comprising a BK7 prism, gold (Au), graphene, aluminum oxide (Al₂O₃), and MXene, is optimized for detecting CEA in aqueous solutions with high precision. The performance of the proposed sensor was evaluated using the finite difference time domain (FDTD) numerical method, focusing on key parameters such as sensitivity and figure of merit (FOM). Operating at a wavelength of 633 nm, the sensor achieved an exceptional sensitivity of 163.63 deg/RIU and an FOM of 17.52 RIU⁻¹, marking a significant improvement over previously reported SPR biosensors. Comparative analysis further underscores the superior performance of this design, establishing it as a cutting-edge tool for applications in biosensing, medical diagnostics, food safety, and environmental monitoring. The proposed sensor offers significant potential for real-world applications, including clinical diagnostics for early cancer detection, food safety monitoring, and environmental sensing.

Raman spectroscopy for cell analysis: Retrospect and prospect

Cell analysis is crucial to contemporary biomedical research, as it plays a pivotal role in elucidating life processes and advancing disease diagnosis and treatment. Raman spectroscopy, harnessing distinctive molecular vibrational data, provides a non-destructive method for cell analysis. This review surveys the progress of Raman spectroscopy in cellular analysis, emphasizing its utility in identifying individual cells, monitoring biomolecules, and assessing intracellular environments. A significant focus is placed on the novel application of triple-bond molecules as Raman tags, which enhance imaging capabilities by creating a distinctive signature with minimal background noise. The summary of Raman spectroscopy studies provides a forward-looking perspective on its applications.

Exploring the applications for Abscissic acid (ABA) detection using perovskite derived opto-electronic sensors

The hormone abscisic acid (ABA) is crucial in the regulation of many physiological processes in plants, particularly in stress response and developmental control. Recent developments in detection methods utilizing opto-electronic sensors have enabled a more profound comprehension of the processes linked to plant hormones, namely ABA. The present work investigates the potential uses of opto-electronic sensors produced from tailored perovskite materials for the targeted detection of ABA. Modified perovskite substrates, which are characterized by their large surface area, intense Raman scattering, and great sensitivity, provide a distinct advantage in differentiating ABA from other interfering substances present in intricate plant media. Notwithstanding the advancements in these sophisticated detection methods, there is still a significant lack of knowledge on how the distinct opto-electronic characteristics of high-purity perovskite crystals impact their ability to detect ABA. This work aims to close this gap by a thorough investigation of the production, modification, and use of sensors based on perovskite materials. This study also intends to give a thorough analysis comparing the performance of perovskite substrates with traditional substrates, with a specific focus on important characteristics including efficiency, specificity, and sensitivity. Furthermore, the objective of this study is to evaluate the capacity of perovskite substrates to surpass the constraints of conventional detection techniques, namely in terms of sensitivity and interference from competing matrix components. The objective of this work is to make novel contributions to the design and optimization of opto-electronic sensors based on perovskite materials, with the goal of achieving more accurate and dependable detection of ABA. Consequently, this could facilitate the advancement of specialized diagnostic instruments for monitoring plant hormones, so enabling the use of enhanced agricultural techniques and effective stress management in plants.

Current trends and future potential in the detection of avian coronaviruses: An emphasis on sensors-based technologies

Infectious bronchitis virus (IBV), an avian coronavirus, member of the genus Gammacoronavirus, poses significant threats to poultry health, causing severe respiratory, reproductive, and renal infections. The genetic diversity of IBV, driven by mutations, recombination and deletions, has led to the emergence of numerous serotypes and genotypes, complicating both diagnosis and control measures. Rapid and accurate diagnostic tools are essential for effective disease management and minimizing economic losses. Conventional diagnostic methods, such as PCR, virus isolation, and serological assays, are hindered by limitations in sensitivity, specificity, and turnaround time. In contrast, innovative biosensor platforms employing advanced detection mechanisms-including electrochemical, optical, and piezoelectric sensors-offer a transformative solution. These technologies provide portable, highly sensitive, and rapid diagnostic platforms for IBV detection. Beyond addressing the challenges of conventional methods, these biosensor-based approaches facilitate real-time monitoring and enhance disease surveillance. This review highlights the transformative potential of biosensors and their integration into diagnostic strategies for avian coronavirus infections, presenting them as a promising alternative for precise and efficient IBV detection.

Innovative Applications and Perspectives of Surface-Enhanced Raman Spectroscopy Technology in Biomedicine

Surface-enhanced Raman spectroscopy (SERS) has become a revolutionary technique in the biomedical field, providing unparalleled sensitivity for the detection and characterization of biological samples. In this review, recent SERS innovations are comprehensively discussed, including advanced substrate materials, different SERS detection strategies, and multimodal approaches that combine SERS with other biotechnologies. Among them, the role of SERS in the accurate diagnosis of tumors is highlighted, which has promoted accurate molecular analysis and real-time monitoring of treatment effects. In addition, the growing potential of SERS in the treatment of chronic diseases such as cardiovascular disease, diabetes, and neurodegenerative diseases is discussed. Moreover, the integration with microfluidic chip systems for precise single-cell analysis is presented. To give a forward-looking view, the key challenges faced by SERS technology are also proposed, and possible solutions to overcome these obstacles are provided.

A Self-Adhesive Flexible and Stretchable Compliant Surface Sensor for Real-Time Monitoring of Starch-Based Food Processing

Flexible sensors have attracted great attention because of their important applications in many areas. It is important to monitor the surface of starch-based food during food processing because it can provide key information related to the appearance, texture level, and chewiness of the food. However, there is no report on real-time monitoring of the surface of steamed bread in the literature. Here, we report a self-adhesive and stretchable compliant sensor that can be mounted to the surface of starch-based food and provides real-time signals for the steaming process. The sensors consisting of biocompatible poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), tannic acid (TA), and glycerol can be fabricated by solution processing. Because it is stretchable and self-adhesive to the dough surface, it is compliant with the expansion or contraction of the dough during food processing. Its resistance varies with the shape and volume of the dough and thus can be monitored in a real-time manner. This is the first report of a surface sensor that can monitor the steaming process of starch-based food.

A novel controllable nanocyclic plasma coupled array in SERS trace detection of multi-component pollutants

The development and design of a novel, uniform and highly active local electromagnetic field enhanced structure is crucial for expanding Surface-enhanced Raman Scattering (SERS) applications. In this study, we developed Ag ring-coupled nanoarrays (Ag RCNAs) with controllable nanogaps using a substrate rotary evaporation coating technique with self-assembled polystyrene (PS) microspheres as templates. This straightforward and cost-effective method efficiently prepares plasma-coupled nanoarrays. Ag RCNAs demonstrated high sensitivity in detecting organic dyes, our prepared Ag RCNAs showed high sensitivity (with the limit of detection of 10-8 M), high signal reproducibility (with the relative standard deviation of 6.73 %). Furthermore, Ag RCNAs showed remarkable sensitivity to a broad spectrum of dyes in river water, indicating the large-area uniform and highly active circular-ring-shaped nanogaps can realize highly sensitive detection of various pollutants. This approach offers advantages in electromagnetic field enhancement, tunable nanogaps, uniformity, reproducibility, and recyclability, making it promising for applications in environmental monitoring, bioassays, food safety, and medical diagnostics.

SERS-Based Local Field Enhancement in Biosensing Applications

Surface-enhanced Raman scattering (SERS) stands out as a highly effective molecular identification technique, renowned for its exceptional sensitivity, specificity, and non-destructive nature. It has become a main technology in various sectors, including biological detection and imaging, environmental monitoring, and food safety. With the development of material science and the expansion of application fields, SERS substrate materials have also undergone significant changes: from precious metals to semiconductors, from single crystals to composite particles, from rigid to flexible substrates, and from two-dimensional to three-dimensional structures. This report delves into the advancements of the three latest types of SERS substrates: colloidal, chip-based, and tip-enhanced Raman spectroscopy. It explores the design principles, distinctive functionalities, and factors that influence SERS signal enhancement within various SERS-active nanomaterials. Furthermore, it provides an outlook on the future challenges and trends in the field. The insights presented are expected to aid researchers in the development and fabrication of SERS substrates that are not only more efficient but also more cost-effective. This progress is crucial for the multifunctionalization of SERS substrates and for their successful implementation in real-world applications.

Unraveling the Nanomechanical and Vibrational Properties of the Mayaro Virus

Mayaro virus (MAYV) is an emerging mosquito-borne viral pathogen whose infection results in arthritogenic disease. Despite ongoing research efforts, MAYV biology is largely unknown. Physical virology can assess MAYV nanoparticle metastability, assembly/disassembly, and polymorphism, allowing us to understand virion architecture and dynamics. Here, we employ atomic force microscopy (AFM) and surface enhancement Raman spectroscopy (SERS) to assess MAYV nanomechanical properties, including maps of adhesion force and Young's modulus on individual viral particles. We established topographic maps of MAYV in two and three dimensions, revealing the three-dimensional arrangement and distribution of charges on viral spikes at the virus surface. Furthermore, the organization of the densely packaged RNA, which affords the viral particle exceptional mechanical resistance compared to chikungunya (CHIKV), was observed using MAYV adsorption patterns. The vibrational signature of MAYV particles differs from CHIKV, with more intense protein modes matching the distribution of E1/E2 dimers and the nucleocapsid, which are well structured and suggestive of mechanical strength.

Carbon nanomaterial-based aptasensors for rapid detection of foodborne pathogenic bacteria

Each year, millions of people suffer from foodborne illness due to the consumption of food contaminated with pathogenic bacteria, which severely challenges global health. Therefore, it is essential to recognize foodborne pathogens swiftly and correctly. However, conventional detection techniques for bacterial pathogens are labor-intensive, low selectivity, and time-consuming, highlighting a notable knowledge gap. A novel approach, aptamer-based biosensors (aptasensors) linked to carbon nanomaterials (CNs), has shown the potential to overcome these limitations and provide a more reliable method for detecting bacterial pathogens. Aptamers, short single-stranded DNA (ssDNA)/RNA molecules, serve as bio-recognition elements (BRE) due to their exceptionally high affinity and specificity in identifying foodborne pathogens such as Salmonella spp., Escherichia coli (E. coli), Listeria monocytogenes, Campylobacter jejuni, and other relevant pathogens commonly associated with foodborne illnesses. Carbon nanomaterials' high surface area-to-volume ratio contributes unique characteristics crucial for bacterial sensing, as it improves the binding capacity and signal amplification in the design of aptasensors. Furthermore, aptamers can bind to CNs and create aptasensors with improved signal specificity and sensitivity. Hence, this review intends to critically review the current literature on developing aptamer functionalized CN-based biosensors by transducer optical and electrochemical for detecting foodborne pathogens and explore the advantages and challenges associated with these biosensors. Aptasensors conjugated with CNs offers an efficient tool for identifying foodborne pathogenic bacteria that is both precise and sensitive to potentially replacing complex current techniques that are time-consuming.

Utilization of microdroplets as optical lenses for surface-enhanced Raman spectroscopy (SERS) enhancement on localized silver nanoparticle-decorated porous silicon substrates

Surface-enhanced Raman spectroscopy (SERS) is a widely used analytical technique known for its high sensitivity and broad applicability. Despite its potential, SERS faces challenges related to detection sensitivity and reproducibility. This study proposes an innovative method to enhance SERS performance by employing water microdroplets as optical lenses on localized silver nanoparticle-decorated porous silicon (LocAg-PS) substrates. The hydrophobic nature of the LocAg-PS substrate not only ensures precise positioning of the microdroplet lenses on the silver nanoparticle grafted pad (AgNP pad) but also forms a plano-convex-like microdroplet lens for the focusing of the excitation laser and the collection of scattered light. Experimental results demonstrate that using microdroplet lenses enhances the SERS signal intensity and reproducibility, providing a rapid and cost-effective solution for advanced SERS analysis.

Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system

Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated needle-based surface-enhanced Raman scattering (SERS) sensor, integrated with endoscopy, for direct mucus sampling and label-free detection of CRC. The thin and flexible stainless-steel needle is coated with polymerized dopamine, which serves as an adhesive layer and simultaneously initiates the nucleation of gold nanoparticle (AuNP) seeds on the needle surface. The AuNP seeds are further grown through a surface-directed reduction using Au ions-hydroxylamine hydrochloride solution, resulting in the formation of dense AuNHs. The formation mechanism of AuNHs and the layered structure of the plasmonic needle-based SERS (PNS) sensor are thoroughly analyzed. Furthermore, a strong field enhancement of the PNS sensor is observed, amplified around the edges of the polyhedral shapes and at nanogap sites between AuNHs. The feasibility of the PNS sensor combined with endoscopy system is further investigated using mouse models for direct colonic mucus sampling and verifying noninvasive label-free classification of CRC from normal controls. A logistic regression-based machine learning method is employed and successfully differentiates CRC and normal mice, achieving 100% sensitivity, 93.33% specificity, and 96.67% accuracy. Moreover, Raman profiling of metabolites and their correlations with Raman signals of mucus samples are analyzed using the Pearson correlation coefficient, offering insights for identifying potential cancer biomarkers. The developed PNS-assisted endoscopy technology is expected to advance the early screening and diagnosis approach of CRC in the future.

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced Raman scattering (SERS) technology. In this study, gold@silver-porous silicon (Au@Ag-PSi) composite substrates were synthesized by electrochemical etching and in-situ reduction methods, which showed excellent sensitivity and accuracy in the detection of rhodamine 6G (R6G) and serum from SLE patients. SERS technology was combined with deep learning algorithms to model serum features using selected CNN, AlexNet, and RF models. 92 % accuracy was achieved in classifying SLE patients by CNN models, and the reliability of these models in accurately identifying sera was verified by ROC curve analysis. This study highlights the great potential of Au@Ag-PSi substrate in SERS detection and introduces a novel deep learning approach for SERS for accurate screening of SLE. The proposed method and composite substrate provide significant value for rapid, accurate, and noninvasive SLE screening and provide insights into SERS-based diagnostic techniques.

A paradigm shift in the detection of bloodborne pathogens: conventional approaches to recent detection techniques

Bloodborne pathogens (BBPs) pose formidable challenges in the realm of infectious diseases, representing significant risks to both human and animal health worldwide. The review paper provides a thorough examination of bloodborne pathogens, highlighting the serious worldwide threat they pose and the effects they have on animal and human health. It addresses the potential dangers of exposure that healthcare workers confront, which have affected 3 million people annually, and investigates the many pathways by which these viruses can spread. The limitations of traditional detection techniques like PCR and ELISA have been criticized, which has led to the investigation of new detection methods driven by advances in sensor technology. The objective is to increase the amount of knowledge that is available regarding bloodborne infections as well as effective strategies for their management and detection. This review provides a thorough overview of common bloodborne infections, including their patterns of transmission, and detection techniques.

Real-time monitoring of single dendritic cell maturation using deep learning-assisted surface-enhanced Raman spectroscopy

Background: Dynamic real-time detection of dendritic cell (DC) maturation is pivotal for accurately predicting immune system activation, assessing vaccine efficacy, and determining the effectiveness of immunotherapy. The heterogeneity of cells underscores the significance of assessing the maturation status of each individual cell, while achieving real-time monitoring of DC maturation at the single-cell level poses significant challenges. Surface-enhanced Raman spectroscopy (SERS) holds great potential for providing specific fingerprinting information of DCs to detect biochemical alterations and evaluate their maturation status. Methods: We developed Au@CpG@PEG nanoparticle as a self-reporting nanovaccine for DC activation and maturation state assessment, utilizing a label-free SERS strategy. Fingerprint vibrational spectra of the biological components in different states of DCs were collected and analyzed using deep learning Convolutional Neural Networks (CNN) algorithms, aiding in the rapid and efficient identification of DC maturation. Results: This approach enables dynamic real-time detection of DC maturation, maintaining accuracy levels above 98.92%. Conclusion: By employing molecular profiling, we revealed that the signal ratio of tryptophan-to-carbohydrate holds potential as a prospective marker for distinguishing the maturation status of DCs.

Innovative and versatile surface-enhanced Raman spectroscopy-inspired approaches for viral detection leading to clinical applications: A review

The evolution of analytical techniques has opened the possibilities of accurate analyte detection through a straightforward method and short acquisition time, leading towards their applicability to identify medical conditions. Surface-enhanced Raman spectroscopy (SERS) has long been proven effective for rapid detection and relies on SERS spectra that are unique to each specific analyte. However, the complexity of viruses poses challenges to SERS and hinders further progress in its practical applications. The principle of SERS revolves around the interaction among substrate, analyte, and Raman laser, but most studies only emphasize the substrate, especially label-free methods, and the synergy among these factors is often ignored. Therefore, issues related to reproducibility and consistency of results, which are crucial for medical diagnosis and are the main highlights of this review, can be understood and largely addressed when considering these interactions. Viruses are composed of multiple surface components and can be detected by label-free SERS, but the presence of non-target molecules in clinical samples interferes with the detection process. Appropriate spectral data processing workflow also plays an important role in the interpretation of results. Furthermore, integrating machine learning into data processing can account for changes brought about by the presence of non-target molecules when analyzing spectral features to accurately group the data, for example, whether the sample corresponds to a positive or negative patient, and whether a virus variant or multiple viruses are present in the sample. Subsequently, advances in interdisciplinary fields can bring SERS closer to practical applications.

Principles and Applications of ZnO Nanomaterials in Optical Biosensors and ZnO Nanomaterial-Enhanced Biodetection

Significant research accomplishments have been made so far for the development and application of ZnO nanomaterials in enhanced optical biodetection. The unparalleled optical properties of ZnO nanomaterials and their reduced dimensionality have been successfully exploited to push the limits of conventional optical biosensors and optical biodetection platforms for a wide range of bioanalytes. ZnO nanomaterial-enabled advancements in optical biosensors have been demonstrated to improve key sensor performance characteristics such as the limit of detection and dynamic range. In addition, all nanomaterial forms of ZnO, ranging from 0-dimensional (0D) and 1D to 2D nanostructures, have been proven to be useful, ensuring their versatile fabrication into functional biosensors. The employment of ZnO as an essential biosensing element has been assessed not only for ensembles but also for individual nanomaterials, which is advantageous for the realization of high miniaturization and minimal invasiveness in biosensors and biodevices. Moreover, the nanomaterials' incorporations into biosensors have been shown to be useful and functional for a variety of optical detection modes, such as absorption, colorimetry, fluorescence, near-band-edge emission, deep-level emission, chemiluminescence, surface evanescent wave, whispering gallery mode, lossy-mode resonance, surface plasmon resonance, and surface-enhanced Raman scattering. The detection capabilities of these ZnO nanomaterial-based optical biosensors demonstrated so far are highly encouraging and, in some cases, permit quantitative analyses of ultra-trace level bioanalytes that cannot be measured by other means. Hence, steady research endeavors are expected in this burgeoning field, whose scientific and technological impacts will grow immensely in the future. This review provides a timely and much needed review of the research efforts made in the field of ZnO nanomaterial-based optical biosensors in a comprehensive and systematic manner. The topical discussions in this review are organized by the different modes of optical detection listed above and further grouped by the dimensionality of the ZnO nanostructures used in biosensors. Following an overview of a given optical detection mode, the unique properties of ZnO nanomaterials critical to enhanced biodetection are presented in detail. Subsequently, specific biosensing applications of ZnO nanomaterials are discussed for ~40 different bioanalytes, and the important roles that the ZnO nanomaterials play in bioanalyte detection are also identified.

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Recent Progress in the Synthesis of 3D Complex Plasmonic Intragap Nanostructures and Their Applications in Surface-Enhanced Raman Scattering

Plasmonic intragap nanostructures (PINs) have garnered intensive attention in Raman-related analysis due to their exceptional ability to enhance light-matter interactions. Although diverse synthetic strategies have been employed to create these nanostructures, the emphasis has largely been on PINs with simple configurations, which often fall short in achieving effective near-field focusing. Three-dimensional (3D) complex PINs, distinguished by their intricate networks of internal gaps and voids, are emerging as superior structures for effective light trapping. These structures facilitate the generation of hot spots and hot zones that are essential for enhanced near-field focusing. Nevertheless, the synthesis techniques for these complex structures and their specific impacts on near-field focusing are not well-documented. This review discusses the recent advancements in the synthesis of 3D complex PINs and their applications in surface-enhanced Raman scattering (SERS). We begin by describing the foundational methods for fabricating simple PINs, followed by a discussion on the rational design strategies aimed at developing 3D complex PINs with superior near-field focusing capabilities. We also evaluate the SERS performance of various 3D complex PINs, emphasizing their advanced sensing capabilities. Lastly, we explore the future perspective of 3D complex PINs in SERS applications.

Formaldehyde contamination in seafood industry: an update on detection methods and legislations

Seafood is abundant in high-quality protein, healthy fats (n-3 and n-6 PUFAs), minerals (calcium, magnesium, copper, selenium, and so on), and vitamin D. Functional compounds in seafood can protect against lifestyle-related diseases. Having had all the merits mentioned, it is also a highly putrefiable food item. To maintain quality and prolong seafood's shelf life, various chemicals have been added, including nitrite, sulfur dioxide, and formaldehyde. In this review, we summarize the uses, the incidence of added formalin contamination, and the approved limit for seafood products. Additionally, worldwide regulations or standards for the use of formalin in seafood products, as well as recent changes relevant to new methods, are highlighted. Although strict limits and regulations have been placed on the utilization of formaldehyde for seafood preservation, there are few incidences reported of formalin/formaldehyde detection in seafood products around Asian countries. In this context, various qualitative and quantitative detection methods for formaldehyde have been developed to ensure the presence of formaldehyde within acceptable limits. Besides this, different rules and regulations have been forced by each country to control formaldehyde incidence. Although it is not an issue of formaldehyde incidence in European countries, strict regulations are implemented and followed.

Controlled Spread of a Ag Layer from the Core to the Tip along the Branches of AuAg Nanostars for Improved SERS Detection of Okadaic Acid in Shellfish

Plasmonic Au-Ag nanostars are excellent surface-enhanced Raman scattering (SERS) probes due to bimetallic coupling and the tip effect. However, the existing preparation methods of AuAg nanostars cannot achieve controlled growth of the Ag layer on the branches of nanostars and so cannot display their SERS to the maximum extent, thus limiting its sensitivity in biosensing. Herein, a novel strategy "PEI (polyethylenimine)-guided Ag deposition method" is proposed for synthesizing AuAg core-shell nanostars (AuAg@Ag NS) with a tunable distribution of the Ag layer from the core to the tip, which offers an avenue for investigating the correlation between SERS efficiency and the extent of spread of the Ag layer. It is found that AuAg@Ag NS with a Ag layer coated the whole branch has the strongest SERS performance because the coupling between the tips and Ag layer is maximized. Meanwhile, as a completely closed core-shell structure, AuAg@Ag NS can confine and anchor 4-ATP inside the Ag layer to avoid an unstable SERS signal. By connecting the aptamer, a reliable internal standard nanoprobe with a SERS enhancement factor (EF) up to 1.86 × 108 is prepared. Okada acid is detected through competitive adsorption of this SERS probes, and the detection limit is 36.6 pM. The results gain fundamental insights into tailoring the nanoparticle morphologies and preparation of internal standard nanoprobes and also provide a promising avenue for marine toxin detection in food safety.

Extracellular Vesicle Preparation and Analysis: A State-of-the-Art Review

In recent decades, research on Extracellular Vesicles (EVs) has gained prominence in the life sciences due to their critical roles in both health and disease states, offering promising applications in disease diagnosis, drug delivery, and therapy. However, their inherent heterogeneity and complex origins pose significant challenges to their preparation, analysis, and subsequent clinical application. This review is structured to provide an overview of the biogenesis, composition, and various sources of EVs, thereby laying the groundwork for a detailed discussion of contemporary techniques for their preparation and analysis. Particular focus is given to state-of-the-art technologies that employ both microfluidic and non-microfluidic platforms for EV processing. Furthermore, this discourse extends into innovative approaches that incorporate artificial intelligence and cutting-edge electrochemical sensors, with a particular emphasis on single EV analysis. This review proposes current challenges and outlines prospective avenues for future research. The objective is to motivate researchers to innovate and expand methods for the preparation and analysis of EVs, fully unlocking their biomedical potential.

Evaluating the accuracy of Raman spectroscopy in differentiating leukemia patients from healthy individuals: A systematic review and meta-analysis

PURPOSE

To assess the accuracy of Raman spectroscopy in distinguishing between patients with leukemia and healthy individuals.

METHOD

PubMed, Embase, Web of Science, Cochrane Library, and CNKI databases were searched for relevant articles published from inception of the respective database to November 1, 2023. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), were calculated along with their corresponding 95 % confidence intervals (CI). A summary comprehensive receiver operating characteristic curve (SROC) was constructed and the area under the curve (AUC) was calculated. The degree of heterogeneity was tested and analyzed.

RESULTS

Fifteen groups of original studies from 13 articles were included. The pooled SEN and SPE were 0.93 (95 % CI, [0.92 -0.93]) and 0.91(95 % CI, [0.90-0.92]), respectively. The DOR was 613.01 (95 %CI, [270.79-1387.75]), and the AUC was 0.99. The Deeks' funnel plot asymmetry test indicated no significant publication bias among the included studies (bias coefficient, 40.80; P = 0.13 < 0.10). The meta-regression analysis findings indicated that the observed heterogeneity could be attributed to variations in sample categories and Raman spectroscopy techniques.

CONCLUSION

We confirmed that Raman spectroscopy has good accuracy in differentiating patients with leukemia from healthy individuals, and may become a means of leukemia screening in clinical practice. In the case of analysis based on live cells using surface-enhanced Raman spectroscopy (SERS) improved diagnostic efficacy was observed.

Biosensors for Cancer Biomarkers Based on Mesoporous Silica Nanoparticles

Mesoporous silica nanoparticles (MSNs) exhibit highly beneficial characteristics for devising efficient biosensors for different analytes. Their unique properties, such as capabilities for stable covalent binding to recognition groups (e.g., antibodies or aptamers) and sensing surfaces, open a plethora of opportunities for biosensor construction. In addition, their structured porosity offers capabilities for entrapping signaling molecules (dyes or electroactive species), which could be released efficiently in response to a desired analyte for effective optical or electrochemical detection. This work offers an overview of recent research studies (in the last five years) that contain MSNs in their optical and electrochemical sensing platforms for the detection of cancer biomarkers, classified by cancer type. In addition, this study provides an overview of cancer biomarkers, as well as electrochemical and optical detection methods in general.

Sea hedgehog-inspired surface-enhanced Raman scattering biosensor probe for ultrasensitive determination of Staphylococcus aureus in food supplements

Staphylococcus aureus contamination in food supplements poses substantial challenges to public health and large-scale production but the sensitive detection in a timely manner remains a bottleneck. Drawing inspiration from the sea hedgehog, gold nanostars (AuNSs) were leveraged to design an ultrasensitive surface-enhanced Raman scattering (SERS) biosensor for the determination of Staphylococcus aureus in food supplements. Besides the surface enhancement furnished by the AuNSs, Raman reporter molecules and specific aptamers sequentially self-assembled onto these AuNSs to construct the "three-in-one" SERS biosensor probe for label-based quantitation of Staphylococcus aureus. Following incubation with contaminated health product samples, the gold nanostars@Raman reporter-aptamer specifically recognize and assemble around Staphylococcus aureus cells, forming a distinctive sea hedgehog structure. This unique configuration results in an amplified Raman signal at 1338 cm-1 and an enhancement factor of up to 6.71 × 107. The entire quantitative detection process can be completed within 30 min, boasting an exceptional limit of detection as low as 1.0 CFU mL-1. The method exhibits a broad working range for the determination of Staphylococcus aureus, with concentrations spanning 2.15 CFU mL-1 to 2.15 × 105 CFU mL-1. Furthermore, it demonstrates outstanding precision, with relative standard deviation values consistently below 5.0%. As a showcase to validate the practicality of the SERS method, we conducted tests on determining Staphylococcus aureus in a herbal food supplement, i.e., Ginkgo Biloba extract (GBE); the results align closely with those obtained through the conventional lysogeny broth agar plate method, pointing to the potential applicability in real-world scenarios.

Advances in uremic toxin detection and monitoring in the management of chronic kidney disease progression to end-stage renal disease

Patients with end-stage kidney disease (ESKD) rely on dialysis to remove toxins and stay alive. However, hemodialysis alone is insufficient to completely remove all/major uremic toxins, resulting in the accumulation of specific toxins over time. The complexity of uremic toxins and their varying clearance rates across different dialysis modalities poses significant challenges, and innovative approaches such as microfluidics, biomarker discovery, and point-of-care testing are being investigated. This review explores recent advances in the qualitative and quantitative analysis of uremic toxins and highlights the use of innovative methods, particularly label-mediated and label-free surface-enhanced Raman spectroscopy, primarily for qualitative detection. The ability to analyze uremic toxins can optimize hemodialysis settings for more efficient toxin removal. Integration of multiple omics disciplines will also help identify biomarkers and understand the pathogenesis of ESKD, provide deeper understanding of uremic toxin profiling, and offer insights for improving hemodialysis programs. This review also highlights the importance of early detection and improved understanding of chronic kidney disease to improve patient outcomes.

Cation Chain Length of Nonhalogenated Ionic Liquids Matters in Enhancing SERS of Cytochrome c on Zr-Al-Co-O Nanotube Arrays

Surface-enhanced Raman scattering (SERS) is a remarkably powerful analytical technique enabling trace-level detection of biological molecules. The interaction of a probe molecule with the SERS substrate shows important distinctions in the SERS spectra, providing inherent fingerprint information on the probe molecule. Herein, nonhalogenated phosphonium-based ionic liquids (ILs) containing cations with varying chain lengths were used as trace additives to amplify the interaction between the cytochrome c (Cyt c) and Zr-Al-Co-O (ZACO) nanotube arrays, strengthening the SERS signals. An increased enhancement factor (EF) by 2.5-41.2 times compared with the system without ILs was achieved. The improvement of the SERS sensitivity with the introduction of these ILs is strongly dependent on the cation chain length, in which the increasing magnitude of EF is more pronounced in the system with a longer alkyl chain length on the cation. Comparing the interaction forces measured by Cyt c-grafted atomic force microscopy (AFM) probes on ZACO substrates with those predicted by the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, the van der Waals forces became increasingly dominant as the chain length of the cations increased, associated with stronger Cyt c-ZACO XDLVO interaction forces. The major contributing component, van der Waals force, stems from the longer cation chains of the IL, which act as a bridge to connect Cyt c and the ZACO substrate, promoting the anchoring of the Cyt c molecules onto the substrate, thereby benefiting SERS enhancement.

Fast Detection and Classification of Microplastics below 10 μm Using CNN with Raman Spectroscopy

In light of the growing awareness regarding the ubiquitous presence of microplastics (MPs) in our environment, recent efforts have been made to integrate Artificial Intelligence (AI) technology into MP detection. Among spectroscopic techniques, Raman spectroscopy is preferred for the detection of MP particles measuring less than 10 μm, as it overcomes the diffraction limitations encountered in Fourier transform infrared (FTIR). However, Raman spectroscopy's inherent limitation is its low scattering cross section, which often results in prolonged data collection times during practical sample measurements. In this study, we implemented a convolutional neural network (CNN) model alongside a tailored data interpolation strategy to expedite data collection for MP particles within the 1-10 μm range. Remarkably, we achieved the classification of plastic types for individual particles with a mere 0.4 s of exposure time, reaching an approximate confidence level of 85.47(±5.00)%. We postulate that the result significantly accelerates the aggregation of microplastic distribution data in diverse scenarios, contributing to the development of a comprehensive global microplastic map.

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.

Electrochemical synthesis of 2D-silver nanodendrites functionalized with cyclodextrin for SERS-based detection of herbicide MCPA

Surface enhanced Raman spectroscopy (SERS) is a powerful analytical technique that has found application in the trace detection of a wide range of contaminants. In this paper, we report on the fabrication of 2D silver nanodendrites, on silicon chips, synthesized by electrochemical reduction of AgNO3at microelectrodes. The formation of nanodendrites is tentatively explained in terms of electromigration and diffusion of silver ions. Electrochemical characterization suggests that the nanodendrites do not stay electrically connected to the microelectrode. The substrates show SERS activity with an enhancement factor on the order of 106. Density functional theory simulations were carried out to investigate the suitability of the fabricated substrate for pesticide monitoring. These substrates can be functionalized with cyclodextrin macro molecules to help with the detection of molecules with low affinity with silver surfaces. A proof of concept is demonstrated with the detection of the herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA).

Rapid Nucleic Acid Diagnostic Technology for Pandemic Diseases

The recent global pandemic of coronavirus disease 2019 (COVID-19) has enormously promoted the development of diagnostic technology. To control the spread of pandemic diseases and achieve rapid screening of the population, ensuring that patients receive timely treatment, rapid diagnosis has become the top priority in the development of clinical technology. This review article aims to summarize the current rapid nucleic acid diagnostic technologies applied to pandemic disease diagnosis, from rapid extraction and rapid amplification to rapid detection. We also discuss future prospects in the development of rapid nucleic acid diagnostic technologies.

Investigation of selective SERS enhancement mechanism of Au nanospheres and Au nanorods based on 2T2D-SERS correlation spectroscopy

The selective enhancement mechanism in surface-enhanced Raman scattering (SERS) is demonstrated. Two different types of single nanoparticles (Au nanosphere and Au nanorod) were used to investigate the role of the localized surface plasmon resonance (LSPR) in SERS spectra by using the two-trace two-dimensional (2T2D) correlation spectroscopy. The SERS intensities of three probe molecules, 4-mercaptobenzoic acid (4-MBA), 4-aminothiophenol (4-ATP), and 4-bromobenzenethiol (4-BBT), respectively, were enhanced but slightly different when adsorbed on Au nanospheres and Au nanorods. 2T2D correlation SERS spectra clearly showed that even with the same shape of Au nanoparticles, the main factors influencing the SERS enhancement can vary depending on the specific type of SERS tags used. Such subtle difference could not be clearly identified by the conventional spectral analysis. This result sheds light on potential applications of 2T2D correlation spectroscopy. For 4-MBA molecules, the a1 and b2 modes are mainly affected by the Au nanospheres and Au nanorods. For 4-ATP molecules, the a1 and b2 modes related to C-S stretching combined with C-C stretching band are mainly affected by Au nanorods and Au nanospheres. For 4-BBT molecules, the a1 and b2 modes of C-C (aromatic ring) stretching band are mainly affected by Au nanorods and Au nanospheres. This study offers valuable insights into the relationship between nanoparticle shape and SERS enhancement.

Machine Learning for COVID-19 Determination Using Surface-Enhanced Raman Spectroscopy

The rapid, low cost, and efficient detection of SARS-CoV-2 virus infection, especially in clinical samples, remains a major challenge. A promising solution to this problem is the combination of a spectroscopic technique: surface-enhanced Raman spectroscopy (SERS) with advanced chemometrics based on machine learning (ML) algorithms. In the present study, we conducted SERS investigations of saliva and nasopharyngeal swabs taken from a cohort of patients (saliva: 175; nasopharyngeal swabs: 114). Obtained SERS spectra were analyzed using a range of classifiers in which random forest (RF) achieved the best results, e.g., for saliva, the precision and recall equals 94.0% and 88.9%, respectively. The results demonstrate that even with a relatively small number of clinical samples, the combination of SERS and shallow machine learning can be used to identify SARS-CoV-2 virus in clinical practice.

Research advances of SERS analysis method based on silent region molecules for food safety detection

Food safety is a critical issue that is closely related to people's health and safety. As a simple, rapid, and sensitive detection technique, surface-enhanced Raman scattering (SERS) technology has significant potential for food safety detection. Recently, researchers have shown a growing interest in utilizing silent region molecules for SERS analysis. These molecules exhibit significant Raman scattering peaks in the cellular Raman silent region between 1800 and 2800 cm-1 avoiding overlapping with the SERS spectrum of biological matrices in the range 600-1800 cm-1, which could effectively circumvent matrix effects and improve the SERS accuracy. In this review, the application of silent region molecules-based SERS analytical technique for food safety detection is introduced, detection strategies including label-free detection and labeled detection are discussed, and recent applications of SERS analysis technology based on molecules containing alkyne and nitrile groups, as well as Prussian blue (PB) in the detection of pesticides, mycotoxins, metal ions, and foodborne pathogens are highlighted. This review aims to draw the attention to the silent region molecules-based SERS analytical technique and to provide theoretical support for its further applications in food safety detection.

SERS-Based Optical Nanobiosensors for the Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a leading cause of dementia, impacting millions worldwide. However, its complex neuropathologic features and heterogeneous pathophysiology present significant challenges for diagnosis and treatment. To address the urgent need for early AD diagnosis, this review focuses on surface-enhanced Raman scattering (SERS)-based biosensors, leveraging the excellent optical properties of nanomaterials to enhance detection performance. These highly sensitive and noninvasive biosensors offer opportunities for biomarker-driven clinical diagnostics and precision medicine. The review highlights various types of SERS-based biosensors targeting AD biomarkers, discussing their potential applications and contributions to AD diagnosis. Specific details about nanomaterials and targeted AD biomarkers are provided. Furthermore, the future research directions and challenges for improving AD marker detection using SERS sensors are outlined.

Graphene nanospacer layer modulated multilayer composite structures of precious metals and their SERS performance

Graphene(G)-noble metal-ZnO hybrid systems were developed as highly sensitive and recyclable surface enhanced Raman scattering (SERS) platforms, in which ultrathin graphene of varying thickness was embedded between two metallic layers on top of a ZnO layer. Due to the multi-dimensional plasmonic coupling effect, the Au/G/Ag@ZnO multilayer structure possessed ultrahigh sensitivity with the detection limit of Rhodamine 6 G (R6G) as low as 1.0×10-13 mol/L and a high enhancement factor of 5.68×107. Both experimental and simulation results showed that graphene films could significantly regulate the interlayer plasmon resonance coupling strength, and single-layer graphene had the best interlayer regulation effect. Additionally, the SERS substrate structure prepared through physical methods exhibited high uniformity, the graphene component of the substrate possessed excellent molecular enrichment ability and silver oxidation inhibition characteristics, resulting in a substrate with high stability and exceptional reproducibility. The signal change was less than 15%. Simultaneously, due to the excellent photocatalytic performance of the low-cost and wide-band-gap semiconductor material ZnO, the SERS substrate exhibited exceptional reusability. Even after five cycles of adsorption-desorption, the SERS performance remained stable and maintained a reliable detection limit. The study introduced a novel approach to creating multilayer composite SERS substrates that exhibited exceptional performance, offering a new analytical tool with high sensitivity, stability, and reusability.