Sensing gastric cancer exosomes with MoS2-based SERS aptasensor

"Partner" cellulose gel with "dialysis" function: Achieve the integration of filtration-enrichment-SERS detection

Hydrogel and aerogel materials have garnered significant attention in constructing effective surface-enhanced Raman spectroscopy (SERS) substrates due to their excellent adsorption capabilities, high specific surface area, and abundant chemical groups. However, in liquids with complex compositions, non-specific adsorption of macromolecules can lead to surface scaling and pore clogging of the substrate material, limiting the selective enrichment and SERS detection of target molecules. To address this, an innovative aerogel-chimeric hydrogel material (CH@S-CNF/SA/Ag NPs) was developed. The aerogel component, with its high specific surface area and electronegative properties, functions as a SERS "chip" for adsorption and detection of target molecules. Simultaneously, the mesoporous structure of the hydrogel "shell" effectively filters macromolecules from the solution. These CH@S-CNF/SA/Ag NPs were utilized as SERS substrate materials for detecting urine from healthy individuals and patients with chronic kidney disease stage 5 (CKD5). When combined with machine learning algorithms, the detection accuracy reached 99.50%. This work represents a significant advancement in the specific adsorption and SERS detection of small molecules in complex biological samples such as urine and blood.

Radial SERS acquisition on coffee ring for Serum-based breast cancer diagnosis through Multilayer Perceptron

The coffee-ring effect, involving spontaneous solute separation, has demonstrated promising potential in the context of patient serum analysis. In this study, an approach leveraging the coffee-ring-based analyte redistribution was developed for spectral analysis of surface-enhanced Raman scattering (SERS). By performing radical SERS scanning through the coffee-ring area and sampling across the coffee ring, complicated chemical information was spatially gathered for further spectra analysis. The corresponding application in classification of serum samples from breast cancer patients was also proposed. A simulated serum environment was constructed by mixing phenylalanine, hypoxanthine, and bovine serum albumin (BSA), yielding the coffee-ring patterns along with gold nanoparticles. Distinct divergence in the distributions between hypoxanthine and phenylalanine within the rings were characterized, which is attributed to the inherent electrostatic properties of the noble metal colloid and the interactions among different solvents. Subsequently, this method was applied to serum samples from patients diagnosed with the four breast cancer subtypes. By preparing serum with SERS substrates and forming the coffee-ring patterns, radial SERS scanning was conducted across the rings. The acquired spectra were spatially segmented and processed by employing a multilayer perceptron for learning and prediction. The classification results demonstrated a predictive accuracy of 85.7% in distinguishing among the four breast cancer subtypes, highlighting the feasibility and effectiveness of the coffee-ring assisted radial SERS analysis.

Advances in exosome plasmonic sensing: Device integration strategies and AI-aided diagnosis

Exosomes, as next-generation biomarkers, has great potential in tracking cancer progression. They face many detection limitations in cancer diagnosis. Plasmonic biosensors have attracted considerable attention at the forefront of exosome detection, due to their label-free, real-time, and high-sensitivity features. Their advantages in multiplex immunoassays of minimal liquid samples establish the leading position in various diagnostic studies. This review delineates the application principles of plasmonic sensing technologies, highlighting the importance of exosomes-based spectrum and image signals in disease diagnostics. It also introduces advancements in miniaturizing plasmonic biosensing platforms of exosomes, which can facilitate point-of-care testing for future healthcare. Nowadays, inspired by the surge of artificial intelligence (AI) for science and technology, more and more AI algorithms are being adopted to process the exosome spectrum and image data from plasmonic detection. Using representative algorithms of machine learning has become a mainstream trend in plasmonic biosensing research for exosome liquid biopsy. Typically, these algorithms process complex exosome datasets efficiently and establish powerful predictive models for precise diagnosis. This review further discusses critical strategies of AI algorithm selection in exosome-based diagnosis. Particularly, we categorize the AI algorithms into the interpretable and uninterpretable groups for exosome plasmonic detection applications. The interpretable AI enhances the transparency and reliability of diagnosis by elucidating the decision-making process, while the uninterpretable AI provides high diagnostic accuracy with robust data processing by a "black-box" working mode. We believe that AI will continue to promote significant progress of exosome plasmonic detection and mobile healthcare in the near future.

Utilizing DNA Logic Device for Precise Detection of Circulating Tumor Cells via High Catalytic Activity Au Nanoparticle Anchoring

As medical advancements turn most cancers into manageable chronic diseases, new challenges arise in cancer recurrence monitoring. Detecting circulating tumor cells (CTCs) is crucial for monitoring cancer recurrence, but the current methods are cumbersome and costly. This study developed a new CTC detection system combining DNA aptamer recognition, hybridization chain reaction (HCR) technology, and DNA logic devices, enabling the one-step recognition of CTCs by identifying multiple membrane proteins. After catalytically active Au nanoparticles were attached through reduction synthesis in situ onto the DNA hybridization strands of the CTCs surface, a 3,3',5,5'-tetramethylbenzidine (TMB) colorimetric reaction was used to detect CTCs concentration via peroxidase-like catalysis. With this CTCs detection reporting system, we achieved an LOD of 4 cells/mL using an ultraviolet-visible (UV-vis) spectrophotometer. At certain concentrations, CTCs could even be detected visually without the need for an instrument. The development of this CTCs detection reporting system provided a convenient, reliable, and cost-effective detection strategy for widespread CTCs-based cancer recurrence monitoring.

Surface-enhanced Raman scattering-based strategies for tumor markers detection: A review

The presence of malignant tumors poses a significant threat to people's life and well-being. As biochemical parameters indicate the occurrence and development of tumors, tumor markers play a pivotal role in early cancer detection, treatment, prognosis, efficient monitoring, and other aspects. Surface-enhanced Raman scattering (SERS) is considered a potent tool for the detection of tumor markers owing to its exceptional advantages encompassing high sensitivity, superior selectivity, rapid analysis speed, and photobleaching resistance nature. This review aims to provide a comprehensive understanding of SERS applications in the detection of tumor markers. Firstly, we introduce the SERS enhancement mechanism, classification of active substrates, and SERS detection techniques. Secondly, the latest research progress of in vitro SERS detection of different types of tumor markers in body fluids and the application of SERS imaging in biomedical imaging are highlighted in sections of the review. Finally, according to the current status of SERS detection of tumor markers, the challenges and problems of SERS in biomedical detection are discussed, and insights into future developments in SERS are offered.

The Design of WTe2/Graphene/Ag NPs Heterostructure for the Improvement of the Chemical Enhancement in SERS

Combining the advantages of metal and two-dimensional (2D) nanomaterials, various 2D/metal composite structures are proposed as surface-enhanced Raman spectroscopy (SERS) substrates. However, the chemical enhancement in the composite structure is usually less responsible for the total enhancement. In this work, we proposed a heterostructure including WTe2/graphene/Ag nanoparticles (WTe2/Gr/Ag) as an effective platform for SERS. The matching of energy levels facilitates charge transfer (CT) within the composite structure, which in turn significantly improves the chemical enhancement of SERS. Compared with WTe2/Ag or Gr/Ag substrate, the SERS signals can be amplified up to 18-fold, and the detection limit could further reduce 3 orders of magnitude. Furthermore, the CT process in the SERS test can be further promoted after introducing the pyroelectric field based on the ferro-electricity of WTe2. The enhancement factor of the WTe2/Gr/Ag substrate finally reached 1.34 × 1012. This work proposes a new idea for the design of highly sensitive SERS sensors.

Development and Biomedical Application of Non-Noble Metal Nanomaterials in SERS

Surface-enhanced Raman scattering (SERS) is vital in many fields because of its high sensitivity, fast response, and fingerprint effect. The surface-enhanced Raman mechanisms are generally electromagnetic enhancement (EM), which is mainly based on noble metals (Au, Ag, etc.), and chemical enhancement (CM). With more and more studies on CM mechanism in recent years, non-noble metal nanomaterial SERS substrates gradually became widely researched and applied due to their superior economy, stability, selectivity, and biocompatibility compared to noble metal. In addition, non-noble metal substrates also provide an ideal new platform for SERS technology to probe the mechanism of biomolecules. In this paper, we review the applications of non-noble metal nanomaterials in SERS detection for biomedical engineering in recent years. Firstly, we introduce the development of some more common non-noble metal SERS substrates and discuss their properties and enhancement mechanisms. Subsequently, we focus on the progress of the application of SERS detection of non-noble metal nanomaterials, such as analysis of biomarkers and the detection of some contaminants. Finally, we look forward to the future research process of non-noble metal substrate nanomaterials for biomedicine, which may draw more attention to the biosensor applications of non-noble metal nanomaterial-based SERS substrates.

The new advance of exosome-based liquid biopsy for cancer diagnosis

Liquid biopsy is a minimally invasive method that uses biofluid samples instead of tissue samples for cancer diagnosis. Exosomes are small extracellular vesicles secreted by donor cells and act as mediators of intercellular communication in human health and disease. Due to their important roles, exosomes have been considered as promising biomarkers for liquid biopsy. However, traditional methods for exosome isolation and cargo detection methods are time-consuming and inefficient, limiting their practical application. In the past decades, many new strategies, such as microfluidic chips, nanowire arrays and electrochemical biosensors, have been proposed to achieve rapid, accurate and high-throughput detection and analysis of exosomes. In this review, we discussed about the new advance in exosome-based liquid biopsy technology, including isolation, enrichment, cargo detection and analysis approaches. The comparison of currently available methods is also included. Finally, we summarized the advantages and limitations of the present strategies and further gave a perspective to their future translational use.

Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers

Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors' role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensor-based lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.

Surface-enhanced Raman scattering-based identification of breast cancer progression using extracellular vesicles-derived integrin α6β4

Detection of progression is of great importance to breast cancer treatment and can benefit patients. Limited by current detection technologies and biomarkers, early breast cancer progression diagnosis remains challenging. Researchers have found blood extracellular vesicles (EVs)-derived integrin α6β4 directly facilitate progression in breast cancer, enabling cancer detection. However, EVs size and heterogeneity hinder protein detection, masked by abundant background EVs. Hence, novel tools for efficient detection of EVs with high selectivity and low interference are significantly desired. Here, a new silver-coated gold nanorods SERS probe, termed as Au@Ag@IDA-B/4MSTP, based on DNA aptamer was established for the detection of integrin α6β4 derived from EVs. Validation of the Au@Ag@IDA-B/4MSTP probes using cell-culture-derived EVs revealed a LOD of 23 particles/μL for EVs detection. This tool was further confirmed to mimic the real state of cancer with subcutaneous tumor model and lung metastasis model in mice. With 10 μL of blood plasma and simple Raman analysis process, the test achieved 85.7 % sensitivity and 83.3 % specificity. Moreover, our method achieves a simplified approach that expedites the detection process. These results demonstrate the good detection performance of Au@Ag@IDA-B/4MSTP probes for EVs integrin α6β4, and suggest that this non-invasive approach could be a promising tool for early detection of breast cancer progression.

A simple chemiluminescent method for the quantification of exosomes based on horseradish peroxidase adsorbed on two-dimensional nanomaterials

The development of simple methods for the isolation and quantification of exosomes in biological samples is important. By using the typical two-dimensional (2D) nanomaterials, graphene oxide (GO), the present work first studied the interaction of liposomes with the nanocomposites formed by adsorbing HRP on the GO surface and found the presence of liposomes led to the release of HRP from the GO surface to the solution phase triggering the luminol-H2O2 chemiluminescence (CL) reaction to emit light. Benefiting from the similarity of exosomes to liposomes in both composition and morphology aspects, the GO-HRP nanocomposites with a mass ratio of 120:1 and 160:1 were employed for the quantitative detection of exosomes in 100-fold diluted serum samples. The whole detection process took about 15 min and as low as 3.2 × 102 particles μL-1 of exosomes could be sensitively detected. In addition to GO-HRP nanocomposites, the CL responses of other nanocomposites obtained from adsorbing HRP on other 2D nanomaterials such as layered MoS2 for exosomes were also tested. MoS2-HRP exhibited similar behavior and the LODs for the detection of exosomes were 5.8 × 102 particles μL-1. The proposed assays were a biomarker-independent quantitative method that achieved the quantification of exosomes in serum samples directly without an isolation process.

Advances in Nanoplasmonic Biosensors: Optimizing Performance for Exosome Detection Applications

The development of sensitive and specific exosome detection tools is essential because they are believed to provide specific information that is important for early detection, screening, diagnosis, and monitoring of cancer. Among the many detection tools, surface-plasmon resonance (SPR) biosensors are analytical devices that offer advantages in sensitivity and detection speed, thereby making the sample-analysis process faster and more accurate. In addition, the penetration depth of the SPR biosensor, which is <300 nm, is comparable to the size of the exosome, making the SPR biosensor ideal for use in exosome research. On the other hand, another type of nanoplasmonic sensor, namely a localized surface-plasmon resonance (LSPR) biosensor, has a shorter penetration depth of around 6 nm. Structural optimization through the addition of supporting layers and gap control between particles is needed to strengthen the surface-plasmon field. This paper summarizes the progress of the development of SPR and LSPR biosensors for detecting exosomes. Techniques in signal amplification from two sensors will be discussed. There are three main parts to this paper. The first two parts will focus on reviewing the working principles of each sensor and introducing several methods that can be used to isolate exosomes. This article will close by explaining the various sensor systems that have been developed and the optimizations carried out to obtain sensors with better performance. To illustrate the performance improvements in each sensor system discussed, the parameters highlighted include the detection limit, dynamic range, and sensitivity.

Advances of machine learning-assisted small extracellular vesicles detection strategy

Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great significance in exploring their physiological characteristics and clinical applications. The heterogeneity of sEVs plays a crucial role in distinguishing different types of cells and diseases. Machine learning, with its exceptional data processing capabilities, offers a solution to overcome the limitations of conventional detection methods for accurately classifying sEV subtypes and sources. Principal component analysis, linear discriminant analysis, partial least squares discriminant analysis, XGBoost, support vector machine, k-nearest neighbor, and deep learning, along with some combined methods such as principal component-linear discriminant analysis, have been successfully applied in the detection and identification of sEVs. This review focuses on machine learning-assisted detection strategies for cell identification and disease prediction via sEVs, and summarizes the integration of these strategies with surface-enhanced Raman scattering, electrochemistry, inductively coupled plasma mass spectrometry and fluorescence. The performance of different machine learning-based detection strategies is compared, and the advantages and limitations of various machine learning models are also evaluated. Finally, we discuss the merits and limitations of the current approaches and briefly outline the perspective of potential research directions in the field of sEV analysis based on machine learning.

Design superhydrophobic no-noble metal substrates for highly sensitive and signal stable SERS sensing

Surface-enhanced Raman spectroscopy (SERS) is an analytical technique with a broad range of potential applications in fields such as biomedicine, electrochemistry, and hazardous chemicals. However, it is challenging to develop SERS substrates that are both good sensitive and signal stable. Here we designed a superhydrophobic Nd doped MoS2 uniformly assembled on the activated carbon fiber cloth (CFC) to avoid the coffee ring effect and enrich the analyte, improving the enhancement factor (EF) to 3.9 × 109 and pesticide endosulfan (<10-10) analyte detection. We demonstrate our strategy by density-functional theory (DFT) calculations confirming that both adsorption energy and density of states are enhanced after doping Nd leading to SERS enhancement. Beside DFT calculations, our experiments also provide an effective means to demonstrate that the high SERS sensitivity is based on multiple charge transfer processes combined with the activated carbon cloth. Our results address the limitations of low sensitivity and limit of detection (LOD) of semiconductor SERS substrates for trace analysis and are a step towards practical applications.

Printed Divisional Optical Biochip for Multiplex Visualizable Exosome Analysis at Point-of-Care

Rapid detection of various exosomes is of great significance in early diagnosis and postoperative monitoring of cancers. Here, a divisional optical biochip is reported for multiplex exosome analysis via combining the self-assembly of nanochains and precise surface patterning. Arising from resonance-induced near-field enhancement, the nanochains show distinct color changes after capturing target exosomes for direct visual detection. Then, a series of divisional nanochain-based biochips conjugated with several specific antibodies are fabricated through designed hydrophilic and hydrophobic patterns. Because of the significant wettability difference, one sample droplet is precisely self-splitting into several microdroplets enabling simultaneous identification of multiple target exosomes in 30 min with a sensitivity of 6 × 107 particles mL-1 , which is about two orders lower than enzyme-linked immunosorbent assay. Apart from the trace amount detection, excellent semiquantitative capability is demonstrated to distinguish clinical exosomes from glioblastoma patients and healthy people. This method is simple, versatile, and highly efficient that can be extended as a diagnostic tool for many diseases, promoting the development of liquid biopsy.

Transforming native exosomes to engineered drug vehicles: A smart solution to modern cancer theranostics

Exosomes have been the hidden treasure of the cell in terms of cellular interactions, transportation and therapy. The native exosomes (NEx) secreted by the parent cells hold promising aspects in cancer diagnosis and therapy. NEx has low immunogenicity, high biocompatibility, low toxicity and high stability which enables them to be an ideal prognostic biomarker in cancer diagnosis. However, due to heterogeneity, NEx lacks specificity and accuracy to be used as therapeutic drug delivery vehicle in cancer therapy. Transforming these NEx with their innate structure and multiple receptors to engineered exosomes (EEx) can provide better opportunities in the field of cancer theranostics. The surface of the NEx exhibits numeric receptors which can be modified to pave the direction of its therapeutic drug delivery in cancer therapy. Through surface membrane, EEx can be modified with increased drug loading potentiality and higher target specificity to act as a therapeutic nanocarrier for drug delivery. This review provides insights into promising aspects of NEx as a prognostic biomarker and drug delivery tool along with its need for the transformation to EEx in cancer theranostics. We have also highlighted different methods associated with NEx transformations, their nano-bio interaction with recipient cells and major challenges of EEx for clinical application in cancer theranostics.

An aptamer and Au/Si CCA based SERS sensor for ultra-sensitive detection of Vimentin during EMT in gastric cancer

Introduction: In this study, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized Au/Si cap-cone array (Au/Si CCA) was constructed using the identity-release strategy to detect Vimentin changes during epithelial-mesenchymal transition (EMT) in gastric cancer (GC). Methods: The periodic structure of Au/Si CCA, which can form "hot spots" with high density and regular arrangement, is a substrate with excellent performance. Au/Si CCA was functionalized with aptamers as the capture substrate, and Au nanocubes (AuNCs) were modified with 5-carboxyfluorescein (5-FAM) labelled complementary strand as SERS probe. The capture substrate and SERS probe were assembled by hybridization, and the SERS signal intensity of 5-FAM was greatly enhanced. The binding of Vimentin to the aptamer resulted in a broken connection between the SERS sensor Au/Si CCA array and AuNCs, which resulted in a decrease in the signal intensity of 5-FAM. The identity-release strategy requires only a simple step of reaction to achieve rapid detection of target proteins, which has clinical practicability. Results: Using this protocol, the concentration of Vimentin in GES-1 cells could be successfully detected, and the detection limit was as low as 4.92 pg/mL. Biological experiments of Vincristine, Oncovin (VCR)-treated GES-1 cells effectively mimicked the EMT process, and Vimentin changes during EMT could be accurately detected by this method. Discussion: This study provides a selective, ultra-sensitive and accurate assay for Vimentin detection, which may provide a means for the future detection of EMT process in GC.

Molybdenum Disulfide as Tunable Electrochemical and Optical Biosensing Platforms for Cancer Biomarker Detection: A Review

Cancer is a common illness with a high mortality. Compared with traditional technologies, biomarker detection, with its low cost and simple operation, has a higher sensitivity and faster speed in the early screening and prognosis of cancer. Therefore, extensive research has focused on the development of biosensors and the construction of sensing interfaces. Molybdenum disulfide (MoS2) is a promising two-dimensional (2D) nanomaterial, whose unique adjustable bandgap shows excellent electronic and optical properties in the construction of biosensor interfaces. It not only has the advantages of a high catalytic activity and low manufacturing costs, but it can also further expand the application of hybrid structures through different functionalization, and it is widely used in various biosensors fields. Herein, we provide a detailed introduction to the structure and synthesis methods of MoS2, and explore the unique properties and advantages/disadvantages exhibited by different structures. Specifically, we focus on the excellent properties and application performance of MoS2 and its composite structures, and discuss the widespread application of MoS2 in cancer biomarkers detection from both electrochemical and optical dimensions. Additionally, with the cross development of emerging technologies, we have also expanded the application of other emerging sensors based on MoS2 for early cancer diagnosis. Finally, we summarized the challenges and prospects of MoS2 in the synthesis, functionalization of composite groups, and applications, and provided some insights into the potential applications of these emerging nanomaterials in a wider range of fields.

Polyhedral Au Nanoparticle/MoOx Heterojunction-Enhanced Ultrasensitive Dual-Mode Biosensor for miRNA Detection Combined with a Nonenzymatic Cascade DNA Amplification Circuit

A novel homologous surface-enhanced Raman scattering (SERS)-electrochemical (EC) dual-mode biosensor based on a 3D/2D polyhedral Au nanoparticle/MoO_x nanosheet heterojunction (PAMS HJ) and target-triggered nonenzyme cascade autocatalytic DNA amplification (CADA) circuit was constructed for highly sensitive detection of microRNA (miRNA). Mixed-dimensional heterostructures were prepared by in situ growth of polyhedral Au nanoparticles (PANPs) on the surface of MoO_x nanosheets (MoO_x NSs) via a seed-mediated growth method. As a detection substrate, the resulting PAMS HJ shows the synergistic effects of both electromagnetic and chemical enhancements, efficient charge transfer, and robust stability, thus achieving a high SERS enhancement factor (EF) of 4.2 × 10⁹ and strong EC sensing performance. Furthermore, the highly efficient molecular recognition between the target and smart lock probe and the gradually accelerated cascade amplification reaction further improved the selectivity and sensitivity of our sensing platform. The detection limits of miRNA-21 in SERS mode and EC mode were 0.22 and 2.69 aM, respectively. More importantly, the proposed dual-mode detection platform displayed excellent anti-interference and accuracy in the analysis of miRNA-21 in human serum and cell lysates, indicating its potential as a reliable tool in the field of biosensing and clinical analysis.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

MoS2 QDs-MXene heterostructure-based ECL sensor for the detection of miRNA-135b in gastric cancer exosomes

Exosomes play an important role in the proliferation, adhesion and migration of cancer cells. In this study, we have developed a novel electrochemiluminescence (ECL) sensor based on MoS₂ QDs-MXene heterostructure and Au NPs@biomimetic lipid layer to detect exosomal miRNA. MoS₂ QDs-MXene heterostructure had been prepared as the luminescence probe. Ti₃C₂T_x MXene nanosheets possessed the large specific surface area, excellent flexibility and superior conductivity. MoS₂ QDs on the MXene nanosheets worked as the radiation center to generate strong ECL signal. Meanwhile, Au NPs with biomimetic lipid layer have been modified on the electrode, which retained the lipid dynamics and excellent antifouling property. When miRNA-135b was recognized on the Au NPs@biomimetic lipid layer, MoS₂ QDs-MXene heterostructure was linked on the electrode and further extended the outer Helmholtz plane. As a result, the self-luminous Faraday cage-mode sensing system has been used to detect miRNA-135b from 30 fM to 20 nM with a detection limit of 10 fM. Furthermore, gastric cancer exosomal miRNA in the ascites of clinical patients has been detected successfully. The sensing system can be served as a versatile platform with huge application potential in the field of exosome detection.

Nucleic Acid Molecular Systems for In Vitro Detection of Biomolecules

Molecular systems composed of information-rich nucleic acids have emerged as one of the most robust materials due to their programmability, editability, and designability. Among their various applications, the specific and sensitive in vitro detection of biomolecules for the purpose of disease diagnosis has attracted increasing attention from both fundamental and translational researchers. In this perspective, we introduce the basic design principles for nucleic acid molecular systems toward in vitro detection of biomolecules, accompanied by representative examples from reported works. The perspective concludes with perspectives and outlooks to tackle a variety of technical hurdles for the development and practical translation of nucleic acid molecular systems for biomolecule detection.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

Towards hospital-on-chip supported by 2D MXenes-based 5th generation intelligent biosensors

Existing public health emergencies due to fatal/infectious diseases such as coronavirus disease (COVID-19) and monkeypox have raised the paradigm of 5th generation portable intelligent and multifunctional biosensors embedded on a single chip. The state-of-the-art 5th generation biosensors are concerned with integrating advanced functional materials with controllable physicochemical attributes and optimal machine processability. In this direction, 2D metal carbides and nitrides (MXenes), owing to their enhanced effective surface area, tunable physicochemical properties, and rich surface functionalities, have shown promising performances in biosensing flatlands. Moreover, their hybridization with diversified nanomaterials caters to their associated challenges for the commercialization of stability due to restacking and oxidation. MXenes and its hybrid biosensors have demonstrated intelligent and lab-on-chip prospects for determining diverse biomarkers/pathogens related to fatal and infectious diseases. Recently, on-site detection has been clubbed with solution-on-chip MXenes by interfacing biosensors with modern-age technologies, including 5G communication, internet-of-medical-things (IoMT), artificial intelligence (AI), and data clouding to progress toward hospital-on-chip (HOC) modules. This review comprehensively summarizes the state-of-the-art MXene fabrication, advancements in physicochemical properties to architect biosensors, and the progress of MXene-based lab-on-chip biosensors toward HOC solutions. Besides, it discusses sustainable aspects, practical challenges and alternative solutions associated with these modules to develop personalized and remote healthcare solutions for every individual in the world.

Recent developments in isolating methods for exosomes

Exosomes are the smallest extracellular vesicles that can be released by practically all cell types, and range in size from 30 nm to 150 nm. As the major marker of liquid biopsies, exosomes have great potential for disease diagnosis, therapy, and prognosis. However, their inherent heterogeneity, the complexity of biological fluids, and the presence of nanoscale contaminants make the isolation of exosomes a great challenge. Traditional isolation methods of exosomes are cumbersome and challenging with complex and time-consuming operations. In recent years, the emergence of microfluidic chips, nanolithography, electro-deposition, and other technologies has promoted the combination and innovation of the isolation methods. The application of these methods has brought very considerable benefits to the isolation of exosomes such as ultra-fast, portable integration, and low loss. There are significant functional improvements in isolation yield, isolation purity, and clinical applications. In this review, a series of methods for the isolation of exosomes are summarized, with emphasis on the emerging methods, and in-depth comparison and analysis of each method are provided, including their principles, merits, and demerits.

Ultrasensitive Antibiotic Perceiving Based on Aptamer-Functionalized Ultraclean Graphene Field-Effect Transistor Biosensor

Antibiotics are powerful tools to treat bacterial infections, but antibiotic pollution is becoming a severe threat to the effective treatment of human bacterial infections. The detection of antibiotics in water has been a crucial research area for bioassays in recent years. There is still an urgent need for a simple ultrasensitive detection approach to achieve accurate antibiotic detection at low concentrations. Herein, a field-effect transistor (FET)-based biosensor was developed using ultraclean graphene and an aptamer for ultrasensitive tetracycline detection. Using a newly designed camphor-rosin clean transfer (CRCT) scheme to prepare ultraclean graphene, the carrier mobility of the FET is found to be improved by more than 10 times compared with the FET prepared by the conventional PMMA transfer (CPT) method. Based on the FET, aptamer-functionalized transistor antibiotic biosensors were constructed and characterized. A dynamic detection range of 5 orders of magnitude, a sensitivity of 21.7 mV/decade, and a low detection limit of 100 fM are achieved for the CRCT-FET biosensors with good stability, which are much improved compared with the biosensor prepared by the CPT method. The antibiotic sensing and sensing performance enhancement mechanisms for the CRCT-FET biosensor were studied and analyzed based on experimental results and a biosensing model. Finally, the CRCT-FET biosensor was verified by detecting antibiotics in actual samples obtained from the entrances of Bohai Bay.