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Biosensors

Biosensors is an international, peer-reviewed, open access journal on the technology and science of biosensors, published monthly online by MDPI.

Indexed in PubMed | Quartile Ranking JCR - Q1 (Instruments and Instrumentation | Chemistry, Analytical)

All Articles (5,115)

In the modernization of traditional Chinese medicine (TCM), trace detection of pharmacodynamic substances faces a critical challenge: insufficient sensitivity, which significantly hinders accurate quality assessment and standardization. Conventional techniques often fail to measure trace components in complex sample matrices. Therefore, the development of a rapid, effective, sensitive, and reliable analytical method, along with a corresponding quality evaluation system, is of great importance. This study used moth wing (MW) scales as a template to fabricate an Ag/MW SERS substrate via magnetron sputtering. The optimal Ag30/MW SERS substrate (30 min sputtering) achieved an enhancement factor of 6.47 × 106 and good reproducibility (minimum RSD: 7.03%). Principal component analysis (PCA) was integrated with four deep learning algorithms (MLP, Transformer, ResNet, DNN) to detect three typical TCM pharmacodynamic substances in pure standard solutions: atractylon, cimifugin, and timosaponin A-III. The models enabled rapid identification, with the MLP model reaching 95.00% accuracy. This research provides a novel, highly accurate, and efficient detection method with potential for TCM pharmacodynamic substances, demonstrating feasibility for bioactive compound identification in model systems, and shows promising potential for future application in TCM composition analysis and quality control.

27 February 2026

Schematic of the fabrication process for Ag/MW SERS substrates and their application in the Raman spectroscopic detection of pharmacodynamic substances.

New Zealand green-lipped mussel (Perna canaliculus) is a premium seafood product that may be substituted with morphologically similar mussels after shucking and cooking, particularly Asian green mussel (Perna viridis). This study developed a rapid, on-site duplex recombinase-aided amplification–lateral flow dipstick (dRAA–LFD) assay to authenticate P. canaliculus and differentiate it from P. viridis. Species-specific primers were designed from mitochondrial COI alignment and combined in a dRAA reaction. Reaction conditions were optimized at 37–42 °C and 15–60 min. Specificity was assessed against 11 non-target seafood species, and sensitivity was evaluated using 2-fold serial dilutions. The assay was further validated using DNA from boiled (85 °C, 5–15 min), steamed (105 °C, 10–30 min), and fried (185 °C, 30–90 s) mussels, and 15 restaurant products labeled as New Zealand mussel dishes. Optimal performance was achieved at 40 °C for 30 min, with no cross-reactivity. The LFD detection limits were 0.05 ng/reaction for P. viridis and 0.2–0.1 ng/reaction for P. canaliculus. All cooked samples remained identifiable, and commercial testing classified 13/15 products as P. canaliculus and 2/15 as P. viridis. Overall, the dRAA–LFD assay enables rapid, equipment-light authentication of cooked mussel products for routine screening.

27 February 2026

COI marker selection and optimization of the duplex RAA–LFD assay for discriminating Asian green mussel and New Zealand green-lipped mussel. (A) Clustal Omega alignment of mitochondrial COI sequences showing the primer-binding regions used to design species-specific primer sets (PV-F/PV-R and PC-F/PC-R) within the aligned COI fragment. (B) Optimization of RAA reaction temperature (37, 40, and 42 °C) using singleplex PV or PC primer sets. (C) Optimization of RAA reaction time (15, 30, and 60 min) using duplex primer reactions (PV + PC) with either PV or PC genomic DNA as template.

Viruses are an indispensable part of the environment we live in. The occurrence of seasonal and pandemic infections underscores the urgent need to develop new antiviral drugs or repurpose existing ones. Among the methods used in research on new antiviral molecules, surface plasmon resonance (SPR) has a well-established position due to its diverse applications in interaction analysis. It can be used to investigate various molecules (proteins, nucleic acids, small-molecular drugs) in different configurations and in real time. Although it is a gold-standard method for biomolecular interaction analysis, it is not free of constraints. Here, we review research on SPR in antiviral drug discovery. We focus on experimental design and discuss the application of SPR to investigate key stages of viral infection and to characterize antiviral interactions. In addition, we address the main limitations and challenges associated with SPR measurements and consider strategies for adapting the technique to meet the specific needs of antiviral research.

26 February 2026

Schemes for sensor chip surfaces and ligand immobilization strategies in SPR for analysis of putative drugs. (A,B) An example of a sensor chip surface with dextran matrix for (A) amine-coupling immobilization of amine-containing molecule with available COO− grups or (B) with already immobilized strepavidine, NTA-Ni2+ and protein A for immobilization of biotinylated, Hist-tag-containg molecules and antibodies, respectively. (C) Analysis of interaction between the putative drug and lipid monolayer or liposomes immobilized on HPA or L1 sensor chips, respectively. (D) Left panel: host receptor protein (e.g., ACE2) immobilized via amine groups and analysis of surface binding by viral protein alone (e.g., SARS-CoV-2 spike protein). Right panel: analysis of binding immobilized host receptor by viral protein preincubated with the tested inhibitor. An inhibitor that binds to the viral protein at the same interface as the host receptor blocks the receptor’s binding. (E) Left panel: analysis of viral RNA polymerase (RdRp) binding to immobilized RNA molecule alone. Right panel: analysis of viral RdRp binding after the preincubation with the putative inhibitor. (based on [31]). (F,G) Sensorgrams showing the response after injections of the analyte onto the surface with immobilized ligand, followed by injection of the inhibitor (blue) or buffer (green). The increase in signal after inhibitor injection indicates binding to the analyte (blue) (F). The decrease in signal after inhibitor injection, more significant than after buffer injection, indicates removal of the analyte from the complex with the ligand (blue) (G). Not drawn in scale.

Microbial imbalance and the spread of pathogenic microorganisms pose severe threats to human health and ecological security. Traditional microbial detection methods suffer from several drawbacks such as long detection time, low sensitivity, and insufficient specificity. As an emerging fluorescent probe, carbon dots (CDs) offer an innovative direction for microbial labeling and detection due to their ultra-small particle size, unique optical properties, excellent biocompatibility, and facile surface modifiability. Herein, this article reviews the research progress of CDs on microbial labeling and detection. The content covers a brief introduction of CDs and explores the main recognition strategies including non-covalent interactions and biomolecule-mediated targeted binding. It also elaborates on the application status of multi-modal sensing technologies for microbial detection, such as CDs-based fluorescent sensing, electrochemical sensing, and surface-enhanced Raman scattering (SERS) sensing. Additionally, the challenges faced in current research, such as achieving simultaneous detection of multiple pathogens and in vivo dynamic tracking, are analyzed, and the development prospects of CDs in fields like clinical diagnosis and public health monitoring are prospected. This review aims to provide comprehensive references for further research and application of CDs in the field of microbial detection.

26 February 2026

An overview on the binding strategies between fluorescent CDs and microorganisms, as well as CDs-based diverse methods for the detection of microorganisms.

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Editors: Nélia Jordão Alberto, Maria de Fátima Domingues, Nunzio Cennamo, Adriana Borriello

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Biosensors - ISSN 2079-6374