Search Results (1,019)

The ultrasensitive detection of microRNA-17 (miRNA-107) is required for clinical diagnosis. In this work, an aggregation-induced electrochemiluminescence (AIECL) sensor was developed for the quantification of miRNA-107, in which AIECL-active polymer dots (Pdots) were characterized by transmission electron microscopy, ultraviolet–visible spectroscopy, and cyclic voltammetry and used as ECL emitters. Black hole quencher-labeled hairpin DNA (HP-BHQ) was modified on the Pdot surfaces, resulting in the ECL signal of the Pdots being in the “off” state due to the resonant energy transfer (RET) between the BHQ and Pdots. In the presence of miRNA-107, HP-BHQ opened through RNA-DNA hybridization. Subsequently, the introduced duplex-specific nuclease (DSN) facilitated the cleavage of DNA in the RNA–DNA hybrid chain and led to the detachment of HP-BHQ from the electrode surface. The ECL signal of the Pdots recovered, i.e., to the “on” state. The variation in the ECL signal was related to the concentration of the target miRNA-107. As a result, the AIECL biosensor exhibited a wide linear response to miRNA-107 concentrations ranging from 1.0 fM to 10.0 pM, and a low detection limit of 0.82 fM. This work provides a novel platform for the sensitive analysis of miRNA. Full article

The demand for rapid and highly sensitive sensing technologies is increasing across diverse fields, including precise disease diagnosis, early-stage screening, and real-time environmental monitoring. Field-effect transistor (FET)-based sensing platforms have shown tremendous potential for detecting target molecules at extremely low concentrations, owing to their ultrahigh sensitivity, label-free and amplification-free operation, and rapid response. In recent years, the rapid advancement of nucleic acid probe design and interfacial engineering has markedly accelerated the development of FET sensors, leading to the emergence of nucleic acid-based FET (NA-FET) biosensors. Beyond their fundamental role in nucleic acid detection, the integration of nucleic acid aptamers and framework nucleic acids has greatly expanded NA-FET biosensors’ applicability to a wide range of analytes and multiplexed detection. At the same time, advances in semiconductor materials have endowed the NA-FET biosensor with highly efficient signal transduction and diverse device architectures, enabling successful proof-of-concept demonstrations for various clinically and environmentally relevant molecular biomarkers. Furthermore, the integration into portable, wearable, and implantable devices has laid a solid foundation for their future development into real-world applications. This review summarizes recent cutting-edge progress in NA-FET biosensors, highlights key design strategies and performance improvements, and discusses current challenges, future development directions, and their prospects for practical applications. Full article

Background: Non-small cell lung carcinoma (NSCLC) is the most prevalent form of lung cancer, and its progression is closely associated with constitutive activation of signal transducer and activator of transcription 3 (STAT3). This study used surface plasmon resonance (SPR) technology to develop a STAT3-targeting recognition system and identify natural STAT3-targeting compounds from the traditional Chinese medicine Psoralea corylifolia and to evaluate their anti-NSCLC activities, with particular attention to reactive oxygen species (ROS) regulation. Methods: The SPR biosensor immobilized with STAT3 was used to screen and enrich STAT3-binding constituents of Psoralea corylifolia, and to determine ligand-STAT3 affinities. Molecular docking was performed to characterize interactions within the STAT3 SH2 domain. Functional effects were assessed in A549 cells using proliferation and scratch migration assays. Antioxidant capacity was evaluated via hydroxyl radical and superoxide anion scavenging assays, and intracellular ROS levels were measured in hydrogen peroxide (H₂O₂)-induced oxidative stress models in human umbilical vein endothelial cells (HUVECs) and A549 cells. Results: SPR analysis showed that psoralen and isopsoralen bind to STAT3, with equilibrium dissociation constants (KD) of 80.92 µM and 28.11 µM, respectively. Molecular docking further confirmed their interaction with the STAT3 SH2 domain. Both compounds inhibited A549 proliferation and reduced migration. Beyond direct STAT3 inhibition, both compounds demonstrated notable free radical scavenging activity. In a H₂O₂-induced oxidative stress model, pretreatment with psoralen or isopsoralen significantly reduced ROS levels in HUVECs, while increasing ROS accumulation in A549 lung cancer cells. Conclusions: This work identifies psoralen and isopsoralen as novel dual-function STAT3 inhibitors that exert anti-NSCLC effects through combined STAT3 suppression and context-dependent ROS modulation, and demonstrates the utility of SPR for screening bioactive natural products. Full article

We report a novel dual-receptor lateral flow biosensor (LFB) for the rapid, sensitive, and visual detection of MCF-7 breast cancer cells as a model for circulating tumor cells (CTCs). The biosensor employs a MUC1-specific aptamer conjugated to colloidal gold nanoparticles as the detection probe and an anti-MUC1 antibody immobilized at the test line as the capture probe, forming a unique “aptamer–cell–antibody” sandwich complex upon target recognition. This design enables instrument-free, visual readout within minutes, achieving a detection limit of 675 cells. The assay also demonstrates robust performance in spiked human blood samples, highlighting its potential as a simple, cost-effective dual-mode point-of-care testing (POCT) platform. This platform supports both rapid visual screening and optional strip-reader-based quantification, making it suitable for early detection and monitoring of breast cancer CTCs. Full article

Duck plague virus (DPV), a highly contagious α-herpesvirus in the livestock and poultry environment, poses a significant threat to the healthy growth of ducks, potentially causing substantial economic losses. Effective control of DPV requires the development of specific diagnostic tools. A new fluorescent biosensor (R-C-CHA) was developed to detect virulent strains of DPV. It combined recombinase polymerase amplification (RPA), a CRISPR/Cas12a system, and catalytic hairpin assembly (CHA) for signal enhancement. The RPA primers were specifically designed to target the conserved DPV-CHv UL2 gene region, allowing for the rapid, efficient amplification of the target nucleic acids in isothermal conditions. The CRISPR/Cas12a system was used for sequence-specific recognition, activating its lateral cleavage activity. Furthermore, the CHA cascade reaction was utilized for enzyme-free fluorescent signal amplification. The results showed that the R-C-CHA biosensor completed the detection process in 40 min with a detection limit of 0.02 fg/μL, which was an approximate five-fold improvement compared to traditional RPA-CRISPR/Cas12a biosensors. The R-C-CHA biosensor also demonstrated perfect consistency with clinical detection and polymerase chain reaction (PCR) diagnosis, highlighting its strong potential for rapid detection in livestock and poultry farming settings. Full article

Split G-quadruplex DNAzymes offer unique opportunities for building gated biosensors with a wide range of applications. Splitting G4 DNAzymes involves separating guanine tracts in the G-quadruplex DNA sequence into two non-functional sequences that reconstitute into a functional G-quadruplex with peroxidase activity upon hybridisation of the aptamer probe region within the split system with the target molecule. Several studies have demonstrated the reassembly of split G4 DNAzymes and their applications in the detection of various analytes. This approach offers unique opportunities for modular biosensor construction, target-dependent activation, lack of requirement for labelling, amplification-free high sensitivity, and specificity over traditional G4 sensing. In this review, we explore the strategies of splitting G-quadruplex and their applications in biomedical diagnosis, environmental sensing, food safety monitoring, cell detection, and the integration of the technology with nanomaterials for enhanced stability and sensitivity. We considered the classical intermolecular split strategies that utilise binary probes and intramolecular split systems, which integrate the spacer DNA that allow for single probes as the model G4 sequence. Finally, we explore the current challenges required to develop split G-quadruplex DNAzymes into tools for routine practical applications. Full article

Field-effect transistor (FET) biosensors enable label-free and real-time electrical transduction; however, their practical deployment is often constrained by the need for bulky benchtop instrumentation to provide stable biasing, low-noise readout, and data processing. Here, we report a portable extended-gate FET (EG-FET) integrated sensing system that consolidates the sensing interface, analog front-end conditioning, embedded acquisition/control, and user-side visualization into an end-to-end prototype suitable for on-site operation. The system couples a screen-printed Au extended-gate electrode to a MOSFET and employs a low-noise signal-conditioning chain with microcontroller-based digitization and real-time data streaming to a host graphical interface. As a proof-of-concept, enterohemorrhagic Escherichia coli O157:H7 was selected as the target. A bacteria-specific immunosensing interface was constructed on the Au extended gate via covalent immobilization of monoclonal antibodies. Measurements in buffered samples produced concentration-dependent current responses, and a linear calibration was experimentally validated over 10⁴–10¹⁰ CFU/mL. In specificity evaluation against three common foodborne pathogens (Staphylococcus aureus, Salmonella typhimurium, and Listeria monocytogenes), the sensor showed a maximum interference response of only 13% relative to the target signal (ΔI/ΔImax) with statistical significance (p < 0.001). Our work establishes a practical hardware–software architecture that mitigates reliance on benchtop instruments and provides a scalable route toward portable EG-FET sensing for rapid, point-of-need detection of foodborne pathogens and other biomarkers. Full article

This review aims to provide a broad, multidisciplinary perspective on how dynamic genomics and systems biology are transforming modern healthcare, with a focus on cancer especially liver cancer (HCC). It explains how integrating multi-omics technologies such as genomics, transcriptomics, proteomics, interactomics, metabolomics, and spatial transcriptomics deepens our understanding of the complex tumor environment. These innovations enable precise patient stratification based on molecular, spatial, and functional tumor characteristics, allowing for personalized treatment plans. Emphasizing the role of regulatory networks and cell-specific pathways, the review shows how mapping these networks using multi-omics data can predict resistance, identify therapeutic targets, and aid in the development of targeted therapies. The approach shifts from standard, uniform treatments to flexible, real-time strategies guided by technologies such as liquid biopsies and wearable biosensors. A case study showcases the benefits of personalized therapy, which integrates epigenetic modifications, checkpoint inhibitors, and ongoing multi-omics monitoring in a patient with HCC. Future innovations, such as cloud-based genomic ecosystems, federated learning for privacy, and AI-driven data analysis, are also discussed to enhance decision-making and outcomes. The review underscores a move toward predictive and preventive healthcare by integrating layered data into clinical workflows. It reviews ongoing clinical trials using advanced molecular and immunological techniques for HCC. Overall, it promotes a systemic, technological, and spatial approach to cancer treatment, emphasizing the importance of experimental, biochemical–functional, and biophysical data-driven insights in personalizing medicine. Full article

Yeast biosensors represent a promising biotechnological innovation for ensuring the safety and quality of fermented beverages such as beer, wine, and kombucha. These biosensors employ genetically engineered yeast strains to detect specific contaminants, spoilage organisms, or hazardous compounds during fermentation or the final product. By integrating synthetic biology tools, researchers have developed yeast strains that can sense and respond to the presence of heavy metals (e.g., lead or arsenic), mycotoxins, ethanol levels, or unwanted microbial metabolites. When a target compound is detected, the biosensor yeast activates a reporter system, such as fluorescence, color change, or electrical signal, providing a rapid, visible, and cost-effective means of monitoring safety parameters. These biosensors offer several advantages: they can operate in real time, are relatively low-cost compared to conventional chemical analysis methods, and can be integrated directly into the fermentation system. Furthermore, as Saccharomyces cerevisiae is generally recognized as safe (GRAS), its use as a sensing platform aligns well with existing practices in beverage production. Yeast biosensors are being investigated for the early detection of contamination by spoilage microbes, such as Brettanomyces and lactic acid bacteria. These contaminants can alter the flavor profile and shorten the product’s shelf life. By providing timely feedback, these biosensor systems allow producers to intervene early, thereby reducing waste and enhancing consumer safety. In this work, we review the development and application of yeast-based biosensors as potential safeguards in fermented beverage production, with the overarching goal of contributing to the manufacture of safer and higher-quality products. Nevertheless, despite their substantial conceptual promise and encouraging experimental results, yeast biosensors remain confined mainly to laboratory-scale studies. A clear gap persists between their demonstrated potential and widespread industrial implementation, underscoring the need for further research focused on robustness, scalability, and regulatory integration. Full article

Microparticle detection technology uses materials that can specifically recognize complex biostructures, such as antibodies and aptamers, as trapping agents. The development of antibody production technology and simplification of sensing signal output methods have facilitated commercialization of disposable biosensors, making rapid diagnosis possible. Although this contributed to the early resolution of pandemics, traditional biosensors face issues with sensitivity, durability, and rapid response times. We aimed to fabricate microspaces using metallic materials to further enhance durability of mold fabrication technologies, such as molecular imprinting. Low-damage metal deposition was performed on target protozoa and Norovirus-like particles (NoV-LPs) to produce thin metallic films that adhere to the material. The procedure for fitting the object into the bio structured space formed on the thin metal film took less than a minute, and sensitivity was 10 fg/mL for NoV-LPs. Furthermore, because it was a metal film, no decrease in reactivity was observed even when the same substrate was stored at room temperature and reused repeatedly after fabrication. These findings underscore the potential of integrating stable metallic structures with bio-recognition elements to significantly enhance robustness and reliability of environmental monitoring. This contributes to public health strategies aimed at early detection and containment of infectious diseases. Full article

Paper-based rapid tests are widely used in point-of-care diagnostics due to their simplicity and low cost. However, their application in quantitative analysis remains limited. In this work, a nucleic acid lateral flow assay (NALFA) was integrated with an automated image acquisition system built on a Raspberry Pi platform for the quantitative detection of SARS-CoV-2 virus, increasing the accuracy of the test compared to subjective visual interpretation. The assay employed blue polystyrene microspheres as reporters, while automated image capturing, image processing and quantification were performed using custom Python software (version 3.12). Signal quantification was achieved by comparing the grayscale intensity of the test line with that of a simultaneously captured negative control strip, allowing correction for illumination and background variability. Calibration curves were used for the training of the algorithm. The system was applied for the analysis of a series of samples with varying DNA concentrations, yielding recoveries between 84 and 108%. The proposed approach integrates a simple biosensor with an accessible computational platform to achieve full low-cost automation. This work introduces the first Raspberry Pi-driven image processing approach for accurate quantification of NALFAs and establishes a foundation for future low-cost, portable diagnostic systems targeting diverse nucleic acids, proteins, and biomarkers. Full article

Candida albicans poses significant health risks through its virulent peptide toxin Candidalysin. As no existing therapeutics specifically target this toxin, developing high-affinity aptamers for its efficient and safe removal is urgently needed. In response, we developed a dual-mode biosensor based on gold nanoparticles (AuNPs) and aptamers for screening high-affinity aptamers for Candidalysin. This biosensor leverages the localized surface plasmon resonance (LSPR) phenomenon and surface-enhanced Raman scattering (SERS) of AuNPs to detect changes in color and Raman signals, respectively, indicative of high-affinity aptamer for Candidalysin presence. This dual-mode capability reduces false-negative signals and enhances detection accuracy. Our findings reveal a specific aptamer with high affinity for Candidalysin, presenting a significant advancement in candidiasis treatment. This work sets the stage for the development of effective therapeutic strategies against Candida infections. Full article

Microfluidics has emerged as a powerful enabling technology in plant science, offering unprecedented control over microscale environments for the cultivation, manipulation, and analysis of plant cells, tissues, and organs. This review provides a comprehensive overview of the development and application of microfluidic systems in plant physiology and development studies. We categorize the platforms based on their structural designs and biological targets—from single-cell trapping devices and droplet-based screening systems to organ-on-a-chip and root–microbe interaction modules. Key applications include live-cell imaging, real-time monitoring of stress responses, microenvironment simulation, and high-throughput phenotyping. Particular attention is given to microfluidic investigations of plant mechanobiology, chemotropism, and cell-to-cell communication, as well as their integration with biosensors, electrophysiological tools, and environmental control systems. We also examine current limitations related to material compatibility, device scalability, and biological complexity, and highlight emerging solutions such as modular design, interdisciplinary integration, and soil-on-a-chip systems. By addressing both fundamental research needs and practical agricultural challenges, microfluidic technologies offer a transformative path toward precision plant science and sustainable crop innovation. Full article

Optical fibers are gaining increasing attention in biomedical applications due to their unique advantages, including flexibility, biocompatibility, immunity to electromagnetic interference, potential for miniaturization, and the ability to perform remote, real-time, and in situ sensing. Label-free optical fiber biosensors represent a promising alternative to conventional cancer diagnostics, offering comparable sensitivity and specificity while enabling real-time detection at ultra-low concentrations without the need for complex labeling procedures. However, the sensing performance of biosensors is fundamentally governed by surface modification. The choice of optimal functionalization strategy is dictated by the sensor type, target biomarker, and detection environment. This review paper presents a comprehensive and expanded overview of various surface functionalization methods specifically designed for cancer biomarker detection using optical fiber biosensors, including silanization, self-assembled monolayers, polymer-based coatings, and different dimensional nanomaterials (0D, 1D, and 2D). Furthermore, the emerging integration of computational methods and machine learning in optimizing functionalized optical sensing has been discussed. To the best of our knowledge, this is the first work that consolidates existing surface modification approaches into a single, cohesive resource, providing valuable insights for researchers developing next-generation fiber optic biosensors for cancer diagnostics. Moreover, the paper points out the current technical challenges and outlines the future perspectives of optical fiber-based biosensors. Full article

G-quadruplex (G4) DNAzymes, guanine-rich sequences that fold into four-stranded structures and bind hemin to mimic peroxidase activity, are widely used in biosensing. Split G4 DNAzymes offer conditional activation upon target recognition, enabling high specificity and modularity. However, achieving low OFF-state leakage remains a major challenge. Here, we systematically characterized four representative G4 scaffolds, C-myc, Bcl2, PS5.M, and C-kit, under standardized ABTS/H₂O₂ conditions to assess their kinetic properties and suitability for split designs. C-myc exhibited the highest sustained activity and near-linear concentration dependence, making it ideal for quantitative sensing, while Bcl2 showed durable catalysis suited for extended read windows. C-kit produced rapid bursts with early plateaus, favoring binary outputs, and PS5.M initiated quickly but inactivated rapidly, suggesting potential application of systems requiring fast response. Split-mode analysis revealed that symmetric 2:2 partitions often retained significant activity, whereas asymmetric 3:1 splits reduced but did not eliminate leakage. Among the four G4 DNAzymes, PS5.M demonstrated the most promising OFF-state suppression. Design strategies to minimize leakage including non-classical splits, loop/flank edits, and template-assisted assembly could be used to optimize biosensor functionalities. These findings identify essential factors critical for designing robust split DNAzyme biosensors, advancing applications in diagnostics and molecular logic gates. Full article