A microfluidic-based SERS biosensor with multifunctional nanosurface immobilized nanoparticles for sensitive detection of MicroRNA

Finger-actuated microfluidic chip integrated with visual immunoassay for ultrasensitive detection of PSA in whole blood

Cumbersome preprocessing and specialized manual operations in clinical blood samples remain a significant challenge for achieving high sensitivity and accurate quantification in point-of-care testing. In this paper, a finger-driven integrated microfluidic chip based on visualization of single nanoparticle scattering was proposed for the detection of prostate-specific antigen (PSA) in the whole blood. To control on-chip fluid, a finger-driven module based on a Tesla valve was designed to unidirectionally regulate fluid mixing and separation in the microchannel. In addition, a membrane separation unit was designed to efficiently separate blood cells and serum, reducing interference from blood cells in the detection process. For quantitative PSA concentration detection, a Multi-functional core-satellite magnetic probe was constructed by using the principle of complementary base pairing of ligands on the surface of gold nanoparticles and magnetic beads. In the presence of target PSA, the constructed core-satellite nanostructure was decomposed, producing a characteristic fluorescence signal and releasing gold nanoparticles with green scattering spots under dark-field microscopy. By correlating the concentration with the number of green scattering spots, cancer risk levels were displayed intuitively using a traffic light system. This biosensor achieves an ultra-low detection limit of 0.5 pg/mL for PSA. Due to the ultra-sensitive ability in detection, the monitoring of PSA concentrations for patients during treatment was also demonstrated. Compared with other methods, this proposed microfluidic assay technology has the advantages of small sample volume, minimal operation, high sensitivity and accuracy. Overall, this biosensor provides a new approach for cancer recurrence monitoring and early diagnosis.

Synergizing microfluidics and plasmonics: advances, applications, and future directions

In the past decade, interest in nanoplasmonic structures has experienced significant growth, owing to rapid advancements in materials science and the evolution of novel nanofabrication techniques. The activities in the area are not only leading to remarkable progress in specific applications in photonics, but also permeating to and synergizing with other fields. This review delves into the symbiosis between nanoplasmonics and microfluidics, elucidating fundamental principles on nanophotonics centered on surface plasmon-polaritons, and key achievements arising from the intricate interplay between light and fluids at small scales. This review underscores the unparalleled capabilities of subwavelength plasmonic structures to manipulate light beyond the diffraction limit, concurrently serving as fluidic entities or synergistically combining with micro- and nanofluidic structures. Noteworthy phenomena, techniques and applications arising from this synergy are explored, including the manipulation of fluids at nanoscopic dimensions, the trapping of individual nanoscopic entities like molecules or nanoparticles, and the harnessing of light within a fluidic environment. Additionally, it discusses light-driven fabrication methodologies for microfluidic platforms and, contrariwise, the use of microfluidics in the fabrication of plasmonic nanostructures. Pondering future prospects, this review offers insights into potential future developments, particularly focusing on the integration of two-dimensional materials endowed with exceptional optical, structural and electrical properties, such as goldene and borophene, which enable higher carrier densities and higher plasmonic frequencies. Such advancements could catalyze innovations in diverse applications, including energy harvesting, advanced photothermal cancer therapies, and catalytic processes for hydrogen generation and CO2 conversion.

Application of Surface-Enhanced Raman Spectroscopy in Head and Neck Cancer Diagnosis

Surface-enhanced Raman spectroscopy (SERS) has emerged as a crucial analytical tool in the field of oncology, particularly presenting significant challenges for the diagnosis and treatment of head and neck cancer. This Review provides an overview of the current status and prospects of SERS applications, highlighting their profound impact on molecular biology-level diagnosis, tissue-level identification, HNC therapeutic monitoring, and integration with emerging technologies. The application of SERS for single-molecule assays such as epidermal growth factor receptors and PD-1/PD-L1, gene expression analysis, and tumor microenvironment characterization is also explored. This Review showcases the innovative applications of SERS in liquid biopsies such as high-throughput lateral flow analysis for ctDNA quantification and salivary diagnostics, which can offer rapid and highly sensitive assays suitable for immediate detection. At the tissue level, SERS enables cancer cell visualization and intraoperative tumor margin identification, enhancing surgical precision and decision-making. The role of SERS in radiotherapy, chemotherapy, and targeted therapy is examined along with its use in real-time pharmacokinetic studies to monitor treatment response. Furthermore, this Review delves into the synergistic relationship between SERS and artificial intelligence, encompassing machine learning and deep learning algorithms, marking the dawn of a new era in precision oncology. The integration of SERS with genomics, metabolomics, transcriptomics, proteomics, and single-cell omics at the multiomics level will revolutionize our comprehension and management of HNC. This Review offers an overview of the transformative impacts of SERS and examines future directions as well as challenges in this dynamic research field.

Sensitive detection of miR-21 and miR-25 in gastric adenocarcinoma patient serum using a SERS sensor based on AuNT and enzyme cleavage strategy

MicroRNA (miRNA) detection has significant application value for early cancer diagnosis. In this study, a surface-enhanced Raman scattering (SERS) sensor was developed for detecting miR-21 and miR-25 in the serum of Gastric adenocarcinoma (GAC) patients. The sensor was constructed using arrays of Au trioctahedral nanoparticles (AuNT) and enzyme cleavage techniques. The AuNT was obtained by self-assembly at the oil-water interface, and the Cy5-labeled miR-21 and 5-FAM-labeled miR-25 complementary single-stranded ssDNA-21 and ssDNA-25 were connected with the AuNT to form the SERS sensor. When miR-21 and miR-25 were present, ssDNA-21 and ssDNA-25 were paired and hybridized to form miR-21-ssDNA-21 and miR-25-ssDNA-25 double strands. Duplex-specific nuclease (DSN) could act on the DNA phosphodiester bond in the double strand, causing Cy5 and 5-FAM to be far away from the AuNT, which resulted in a reduction of the SERS signal. In the range of 10 aM to 1 pM, the logarithm of miR-25 concentration was linearly related to the intensity of the characteristic peak of 5-FAM at 1178 cm-1, and the limit of detection (LOD) was determined to be 8.12 aM. The logarithm of miR-21 concentration was linearly related to the characteristic peak intensity of Cy5 at 1367 cm-1, and the LOD was determined to be 4.29 aM. Furthermore, the accuracy of the SERS sensor for the detection of miR-21 and miR-25 in clinical serum samples was evaluated using real-time quantitative polynucleotide chain reaction (qRT-PCR) technology as the gold standard. The relative errors of the two methods miR-21 in healthy people and gastric adenocarcinoma patients were 1.71% and -2.40%. The relative errors of miR-25 were 2.74% and -2.67%. There was no significant difference between the two methods, and the expression levels of miR-21 and miR-25 in the serum of GAC patients were found to be higher than those in healthy individuals. Consequently, this method offers a reliable solution for the early diagnosis of gastric cancer.

Advances and Future Trends in Nanozyme-Based SERS Sensors for Food Safety, Environmental and Biomedical Applications

Nanozymes, a kind of nanoparticles with enzyme-mimicking activities, have attracted considerable attention due to their robust catalytic properties, ease of preparation, and resistance to harsh conditions. By combining nanozymes with surface-enhanced Raman spectroscopy (SERS) technology, highly sensitive and selective sensors have been developed. These sensors are capable of detecting a wide range of analytes, such as foodborne toxins, environmental pollutants, and biomedical markers. This review provides an overview of recent advancements in the synthesis and surface modification of nanozymes, highlighting their ability to mimic multiple enzymes and enhance catalytic performance. In addition, we explore the development and applications of nanozyme-based SERS sensors in food contaminants, environmental pollutants, and biomedical markers. The review concludes with perspectives and challenges facing the field, involving the need for deeper understanding of nanozyme principles and mechanisms, development of standardized systems for characterization, and the engineering of nanozymes with tailored properties for specific applications. Finally, we discuss the potential for integrating various techniques with nanozymes to create multi-modal detection platforms, paving the way for the next generation of analytical tools in the fields of food safety, environmental monitoring, and biomedical diagnostics.

Point-of-care testing for early-stage liver cancer diagnosis and personalized medicine: Biomarkers, current technologies and perspectives

Liver cancer is a highly prevalent and lethal form of cancer worldwide. In the absence of early diagnosis, treatment options for this disease are severely restricted. Recent advancements in genomics and bioinformatics have facilitated the discovery of a multitude of novel biomarkers that accurately depict an individual's disease diagnosis, progression, and treatment response. Leveraging these breakthroughs, personalized medicine employs an individual's biomarker profile to enable early detection of liver cancer and inform decisions regarding treatment selection, dosage determination, and prognosis assessment. The current lack of readily applicable, timely, and economically viable tools for biomarker analysis has hindered the incorporation of personalized medicine into regular clinical procedures. Over the past decade, significant advancements have been achieved in the field of molecular point-of-care testing (POCT) and amplification techniques, leading to substantial improvements in the diagnosis of liver cancer and the implementation of precision medicine. Instrument-free PCR technology or plasma PCR technology can shorten the complex procedure of in vitro detection of nucleic acid-based biomarkers. Also, compared to traditional ELISA, various nanomaterials modified with monoclonal antibodies to target proteins for recognition, capture, and detection have improved the efficiency of protein-based biomarker detection. These advances have reduced the time and cost of clinical detection of early-stage hepatocellular carcinoma and improved the efficiency of timely diagnosis and survival of suspected patients while reducing unnecessary testing costs and procedures. This review aims to provide a comprehensive overview of the current and emerging biomarkers employed in the early detection of liver cancer, as well as the advancements in point-of-care molecular testing technology and platforms. The primary objective is to assess their potential in facilitating the implementation of personalized medicine. This review ultimately revealed that the diagnosis of early-stage hepatocellular carcinoma not only requires sensitive biomarkers, but its various modifications and changes during the progression of cirrhosis to early-stage hepatocellular carcinoma will be a greater focus of our attention in the future. The rapid development of POCT has facilitated the opportunity to readily detect liver cancer in the general population in the future, and the integration of multi-pathway multiplexing and intelligent algorithms has improved the sensitivity and accuracy of early liver cancer biomarker detection. It is expected that the integration of point-of-care technology will be instrumental in the widespread adoption of personalized medicine in the foreseeable future.

Machine Learning-Assisted Light Management and Electromagnetic Field Modulation of Large-Area Plasmonic Coaxial Cylindrical Pillar/Ring Nanoarray Patterns

Hexagonal coaxial cylindrical gold pillar/ring nanoarray patterns can be fabricated with an anodic aluminum oxide (AAO) template or nanosphere lithography. It is time-consuming and expensive for experimental work solely to tune and optimize geometrical parameters for achieving desirable optical properties. Herein, finite-difference time-domain (FDTD) simulation has been performed to investigate how the key geometrical parameters govern optical properties such as plasmonic resonance band, local electric field enhancement, and quality factor (Q-factor). FDTD simulation results reveal that these three important optical properties can be modulated by coupling localized surface plasmon resonance (LSPR) and charge distributions on the metal-dielectric interface to suppress its radiative damping, concentrate the electric field, and tune a spectral resonance. The impact of specific geometric parameters on optical properties was further analyzed via machine learning for visualization. For the gold pillar/ring nanoarrays, the local electric field enhancement can occur at the gap between two adjacent nanostructures or at the gap between pillar and ring. Adjusting the height and gap width proves to be the most effective to optimize both the Q-factor and electric field enhancement. These machine learning-assisted studies will provide a theoretical framework for tailoring the geometrical parameters of the coaxial cylindrical pillar/ring nanoarray patterns toward desirable optical properties.

Dual function of magnetic nanocomposites-based SERS lateral flow strip for simultaneous detection of aflatoxin B1 and zearalenone

Aflatoxin B1 (AFB1) and zearalenone (ZEN) are two mycotoxins that often co-occur in corn. A surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-LFIA) that can simultaneously detect AFB1 and ZEN in corn samples was developed employing the core-interlayer-satellite magnetic nanocomposites (Fe3O4@PEI/AuMBA@AgMBA) as dual-functional SERS tags. Under the optimal conditions, the detection ranges of AFB1 and ZEN in corn samples were 0.1-10 μg/kg and 4-400 μg/kg, respectively. Moreover, the test results for two mycotoxins in contaminated corn samples employing the suggested SERS-LFIA was in line with those of the HPLC technique. In view of its satisfactory sensitivity, accuracy, precision and short testing time (20 min), the developed system has a promising application prospect in the on-site simultaneous detection of AFB1 and ZEN.

Microfluidic-based cardiovascular systems for advanced study of atherosclerosis

Atherosclerosis (AS) is a significant global health concern due to its high morbidity and mortality rates. Extensive efforts have been made to replicate the cardiovascular system and explore the pathogenesis, diagnosis, and treatment of AS. Microfluidics has emerged as a valuable technology for modeling the cardiovascular system and studying AS. Here a brief review of the advances of microfluidic-based cardiovascular systems for AS research is presented. The critical pathogenetic mechanisms of AS investigated by microfluidic-based cardiovascular systems are categorized and reviewed, with a detailed summary of accurate diagnostic methods for detecting biomarkers using microfluidics represented. Furthermore, the review covers the evaluation and screening of AS drugs assisted by microfluidic systems, along with the fabrication of novel drug delivery carriers. Finally, the challenges and future prospects for advancing microfluidic-based cardiovascular systems in AS research are discussed and proposed, particularly regarding new opportunities in multi-disciplinary fundamental research and therapeutic applications for a broader range of disease treatments.

Application of Biosensors and Biomimetic Sensors in Dairy Products Testing

This article summarizes the applications of biosensors and biomimetic sensors in the detection of residues in dairy products. Biosensors utilize biological molecules such as enzymes or antibodies to detect residual substances in dairy products, demonstrating high specificity and sensitivity. Biomimetic sensors, inspired by biosensors, use synthetic materials to mimic biological sensing mechanisms, enhancing stability and reproducibility. Both sensor types have achieved significant success in detecting pesticide residues, veterinary drugs, bacteria, and other contaminants in dairy products. The applications of biological and biomimetic sensors not only improve the efficiency of residue detection in dairy products but also have the potential to reduce the time and cost of traditional methods. Their specificity and high sensitivity make them powerful tools in the dairy industry, thus contributing to ensuring the quality and safety of dairy products and meeting the growing consumer demands for health and food safety.

SERS biosensors for liquid biopsy towards cancer diagnosis by detection of various circulating biomarkers: current progress and perspectives

Liquid biopsy has emerged as a promising non-invasive strategy for cancer diagnosis, enabling the detection of various circulating biomarkers, including circulating tumor cells (CTCs), circulating tumor nucleic acids (ctNAs), circulating tumor-derived small extracellular vesicles (sEVs), and circulating proteins. Surface-enhanced Raman scattering (SERS) biosensors have revolutionized liquid biopsy by offering sensitive and specific detection methodologies for these biomarkers. This review comprehensively examines the application of SERS-based biosensors for identification and analysis of various circulating biomarkers including CTCs, ctNAs, sEVs and proteins in liquid biopsy for cancer diagnosis. The discussion encompasses a diverse range of SERS biosensor platforms, including label-free SERS assay, magnetic bead-based SERS assay, microfluidic device-based SERS system, and paper-based SERS assay, each demonstrating unique capabilities in enhancing the sensitivity and specificity for detection of liquid biopsy cancer biomarkers. This review critically assesses the strengths, limitations, and future directions of SERS biosensors in liquid biopsy for cancer diagnosis.

An integrated liposome-based microfluidic strategy for rapid colorimetric analysis: A case study of microRNA-21 detection

In this study, a novel integrated liposome-based microfluidic platform combined with a smartphone was designed for the rapid colorimetric detection of microRNA-21 (miRNA-21) in real samples. The flowing surface-functionalized liposomes were first captured by nucleic acid-functionalized Au nanoparticles in the microfluidic chip. In the presence of miRNA-21, the DNA strand modified on the surface of Au nanoparticles hybridized with the target to form double-stranded products and was cleaved by duplex-specific nuclease (DSN) enzyme, causing the liposomes to be re-released. Then, as the liposomes in the colorimetric module were lysed and the "cellular" contents were released, a step-by-step "glucose-glucose oxidase-3,3',5,5'-tetramethylbenzidine (TMB)" colorimetric reaction process catalyzed by the G-quadruplex/hemin was triggered. The grayscale values were recorded and recognized by the smartphone camera for miRNA-21 analysis. The advantages of the present strategy included the portability of smartphone-based colorimetric assay, the encapsulation and transport of reactants by liposomes and the low solvent usage of microfluidic chip. Under optimal conditions, this assay exhibited a wide linear range from 1 pM to 1 nM (r2 = 0.9981), and the limit of detection of miRNA-21 was as low as 0.27 pM. Moreover, the high specificity of this strategy allowed its successful application to the rapid analysis of miRNA-21 in real blood serum samples of people with type 2 diabetes.

Directly Self-Assembly of Aligned Ag NWs Films at the Air-Water Interface for the Detection of Pathogens in Artificial Breath Aerosols

Exhaled aerosols from humans, containing various pathogens, are crucial for early disease diagnosis. However, the traditional pathogen detection methods, such as polymerase chain reaction, are often slow and cumbersome due to complex sampling and procedures. This study introduces a novel, direct, and label-free detection method for pathogens in respiratory aerosols, utilizing a highly aligned silver nanowire (Ag NW) film combined with a filter membrane (Ag NWs@filter) as a surface-enhanced Raman spectroscopy-active substrate. A large-scale, ordered silver nanowire film was developed through a simplified self-assembly process. This process eliminates the need for an organic phase and complex surface modifications of Ag NWs, which are common in other preparation methods. Subsequently, the fabricated Ag NWs@filter demonstrated its capability to continuously capture and efficiently preconcentrate pathogens from aerosols, achieving a remarkable detection limit of 3 × 103 CFU/mL, demonstrated using Escherichia coli (E. coli) as a model pathogen. Moreover, the classification between E. coli and Pseudomonas aeruginosa achieved an overall accuracy of 96.5% by the principal component analysis with linear discriminant analysis models. The success of this sensing strategy illustrates its potential in detecting and identifying a variety of biomarkers present in respiratory aerosols, marking a significant step forward in the field of pathogen detection.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review

With the continuous discovery and research of predictive cancer-related biomarkers, liquid biopsy shows great potential in cancer diagnosis. Surface-enhanced Raman scattering (SERS) and microfluidic technology have received much attention among the various cancer biomarker detection methods. The former has ultrahigh detection sensitivity and can provide a unique fingerprint. In contrast, the latter has the characteristics of miniaturization and integration, which can realize accurate control of the detection samples and high-throughput detection through design. Both have the potential for point-of-care testing (POCT), and their combination (lab-on-a-chip SERS (LoC-SERS)) shows good compatibility. In this paper, the basic situation of circulating proteins, circulating tumor cells, exosomes, circulating tumor DNA (ctDNA), and microRNA (miRNA) in the diagnosis of various cancers is reviewed, and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail. At the same time, the challenges and future development of the platform are discussed at the end of the review. Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.

Plasmonic Nanopillars-A Brief Investigation of Fabrication Techniques and Biological Applications

Nanopillars (NPs) are submicron-sized pillars composed of dielectrics, semiconductors, or metals. They have been employed to develop advanced optical components such as solar cells, light-emitting diodes, and biophotonic devices. To integrate localized surface plasmon resonance (LSPR) with NPs, plasmonic NPs consisting of dielectric nanoscale pillars with metal capping have been developed and used for plasmonic optical sensing and imaging applications. In this study, we studied plasmonic NPs in terms of their fabrication techniques and applications in biophotonics. We briefly described three methods for fabricating NPs, namely etching, nanoimprinting, and growing NPs on a substrate. Furthermore, we explored the role of metal capping in plasmonic enhancement. Then, we presented the biophotonic applications of high-sensitivity LSPR sensors, enhanced Raman spectroscopy, and high-resolution plasmonic optical imaging. After exploring plasmonic NPs, we determined that they had sufficient potential for advanced biophotonic instruments and biomedical applications.

Recent Progress of Surface-Enhanced Raman Spectroscopy for Bacteria Detection

There are various pathogenic bacteria in the surrounding living environment, which not only pose a great threat to human health but also bring huge losses to economic development. Conventional methods for bacteria detection are usually time-consuming, complicated and labor-intensive, and cannot meet the growing demands for on-site and rapid analyses. Sensitive, rapid and effective methods for pathogenic bacteria detection are necessary for environmental monitoring, food safety and infectious bacteria diagnosis. Recently, benefiting from its advantages of rapidity and high sensitivity, surface-enhanced Raman spectroscopy (SERS) has attracted significant attention in the field of bacteria detection and identification as well as drug susceptibility testing. Here, we comprehensively reviewed the latest advances in SERS technology in the field of bacteria analysis. Firstly, the mechanism of SERS detection and the fabrication of the SERS substrate were briefly introduced. Secondly, the label-free SERS applied for the identification of bacteria species was summarized in detail. Thirdly, various SERS tags for the high-sensitivity detection of bacteria were also discussed. Moreover, we emphasized the application prospects of microfluidic SERS chips in antimicrobial susceptibility testing (AST). In the end, we gave an outlook on the future development and trends of SERS in point-of-care diagnoses of bacterial infections.

Microfluidic-based blood immunoassays

Microfluidics enables the integration of whole protocols performed in a laboratory, including sample loading, reaction, extraction, and measurement steps on a single system, which offers significant advantages thanks to small-scale operation combined with precise fluid control. These include providing efficient transportation mechanisms and immobilization, reduced sample and reagent volumes, fast analysis and response times, lower power requirements, lower cost and disposability, improved portability and sensitivity, and greater integration and automation capability. Immunoassay is a specific bioanalytical method based on the interaction of antigens and antibodies, which is utilized to detect bacteria, viruses, proteins, and small molecules in several areas such as biopharmaceutical analysis, environmental analysis, food safety, and clinical diagnostics. Because of the advantages of both techniques, the combination of immunoassays and microfluidic technology is considered one of the most potential biosensor systems for blood samples. This review presents the current progress and important developments in microfluidic-based blood immunoassays. After providing several basic information about blood analysis, immunoassays, and microfluidics, the review points out in-depth information about microfluidic platforms, detection techniques, and commercial microfluidic blood immunoassay platforms. In conclusion, some thoughts and future perspectives are provided.

Selecting optimum miRNA panel for miRNA signature-based companion diagnostic model to predict the response of R-CHOP treatment in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Although the first-line treatment, R-CHOP treatment, shows efficacy in approximately 80% of patients with DLBCL, some patients have refractory disease or relapse after the initial response to therapy, resulting in a significantly poorer prognosis. In this study, we developed a microRNA (miRNA) signature-based companion diagnostic model to predict the response of patients with DLBCL to R-CHOP treatment by integrating two clinical study datasets. To select the optimum miRNA combination as a panel, we examined three feature selection methods (p-value-based ranking, stepwise method, and Boruta), together with 11 types of classifiers systematically. Boruta selection enabled a higher area under the curve (AUC) with a lower number of miRNAs compared with other feature selection methods, leading to an AUC of 0.751 via the random forest classifier using 36 miRNAs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that Boruta avoided multiple selection of miRNAs with similar functions, thereby preventing the decrease in diagnostic ability via collinearity. The AUC value first increased with an increasing number of miRNAs and then became almost constant at approximately 30 miRNAs, suggesting the existence of the optimum number of miRNAs as a panel for future clinical translation of multiple miRNA-based diagnostics.