Nanobodies are promising recognition elements for food safety biosensors, yet the relationship between their conformational dynamics and ligand binding remains poorly understood. This study presents an integrated computational-experimental framework to elucidate conformational dynamics-function relationships and guide the engineering of nanobody-based detection systems for ochratoxin A (OTA), a prevalent mycotoxin in agricultural commodities. Using the anti-OTA nanobody NB28, we employed molecular dynamics simulations, ion mobility-mass spectrometry, and collision-induced unfolding assays to investigate the ligand recognition mechanisms. NB28 binds OTA through a tunnel-like mechanism, inducing pronounced conformational shifts toward extended states, validated experimentally through collision cross-sectional measurements and unfolding profiles. Leveraging these dynamic insights, we engineered a T80C variant exhibiting ∼1.8-fold enhanced detection sensitivity with reduced IC50 values while preserving specificity. T80C demonstrated robust performance across cereal matrices, achieving detection limits well below the EU regulatory threshold of 5 μg/kg. This dynamics-driven approach provides a generalizable strategy for food safety biosensor development.

FFF as a microfluidic platform for the streamlined optimization of ready-to-use nanozyme-labelled probes to enable robust and ultra-sensitive chemiluminescent bioassays.

Electrochemical and spectrophotometric investigation of DNA interactions with TURKOVAC and Pfizer-BioNTech vaccines: Implications for biosensor sensitivity.

Use of Prussian Blue pseudocapacitive properties to amplify the pulsed amperometric readout of biosensors.

Antibody orientation drives sensitivity in SARS-CoV-2 detection using dynamic light scattering biosensors.

Stimuli-responsive logical gate biosensor based on integrated DNAzyme probe for the discrimination of cancer cells.

Liquid crystal-based biosensors for clinical diagnostics.

Human carboxylesterase 2 (hCES2) has emerged as a protein of significant interest in obesity research. However, whether its activity is increased or decreased in the plasma of children with obesity remains a subject of debate. This study aimed to develop a novel Pepper-based biosensor for the in situ detection and imaging of hCES2 activity and to investigate the relationship between hCES2 activity and adipocyte differentiation. Leveraging the specific catalytic properties of hCES2, we designed and synthesized four probes based on the high-performance Pepper aptamer. Among these, BBC-HBC530 demonstrated superior selectivity and sensitivity for hCES2 compared to the other three candidates. Molecular docking studies revealed the molecular interactions between the four synthetic probes and hCES2/Pepper and explained the reasons for the high selectivity and high sensitivity of BBC-HBC530 for hCES2 detection. Subsequent experiments also confirmed that BBC-HBC530 could be applied to effectively quantify and visualize endogenous hCES2 in living cells. Furthermore, analysis of clinical samples using BBC-HBC530 revealed that the activity of hCES2 in the plasma of obese children was significantly increased. In conclusion, the aptamer-based biosensor BBC-HBC530 represents a promising molecular tool for investigating the biological functions of endogenous hCES2 in living systems and provides an important reference for the development of biosensors for other hydrolases.

Constrained bicyclic peptides (Bicycle molecules) with high affinity for biological targets have emerged as potentially powerful therapeutic agents, particularly for the in vivo targeting of cancer receptors. However, their antibody-mimetic properties have yet to be explored for use in diagnostic immunoassays. These synthetically derived compounds serve as biorecognition scaffolds that allow for facile site-selective modification and large-scale production. A phage display screen against various constructs of the SARS-CoV-2 nucleocapsid (N) protein identified several Bicycle molecules with binding affinities ranging from the micromolar to the low nanomolar range. These Bicycle molecules were validated in the development of enzyme- and nanozyme-linked immunosorbent assays, as well as enzymatic and colorimetric nanoparticle-based lateral flow immunoassays (LFIA) for the detection of ultralow concentrations of the SARS-CoV-2 N protein. We envision that these moieties enable robust, cost-effective, and large-scale development of ultrasensitive biosensors for a diverse range of biomarkers by leveraging their high binding affinity, minimalistic scaffold, and synthetic accessibility.

Monitoring cytokines, such as interferon-alpha (IFN-α), is essential for assessing immune responses during viral infections and in immunotherapies. Here, we report the development of a microneedle-based electrochemical biosensor for detecting IFN-α in interstitial fluid (ISF), which combines minimally invasive sampling with label-free, offline analysis. The device comprises polycaprolactone (PCL) microneedles fabricated via 3D-printed molds and thermocompression, coated with polypyrrole (PPy) to enable conductivity and biomolecule immobilization. A range of PPy concentrations (10-200 mmol·L-1) was evaluated to optimize performance. Structural and physicochemical analyses revealed that intermediate PPy content (50 mmol·L-1) ensured optimal surface roughness, porosity (29.7%), and electroactive area, while preserving mechanical integrity and biocompatibility. Electrochemical impedance spectroscopy and cyclic voltammetry demonstrated a sensitive and specific response to IFN-α, with a limit of detection of 8.6 pg/mL and a linear range of up to 1000 pg/mL. Selectivity studies in gelatin matrices and cytotoxicity assays confirmed the robust performance and safety of the system. The biosensor operates via skin insertion, immunocapture, and analyte quantification after removal, enabling offline detection without complex instrumentation. These results demonstrate the potential of PPy-coated microneedles as cost-effective, scalable, and minimally invasive platforms for cytokine monitoring in point-of-care diagnostics.

MicroRNA-155 (miR-155) is a clinically important biomarker involved in cancer progression, immune regulation, and inflammatory diseases, highlighting the need for sensitive and reliable detection methods. Conventional biosensor fabrication often relies on labor-intensive trial-and-error optimization, which delays the development of practical diagnostic tools. In contrast to most previous studies that focus on predicting analyte concentration from biosensor signals, this work develops a data-driven framework for modeling the nonlinear relationships between fabrication parameters and biosensor output. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were proposed to model a voltammetric biosensor for plasma miR-155 detection. A dataset containing the biosensor output current and six fabrication parameters was used. The optimal parameter values were determined using a genetic algorithm (GA). The results show that the ANN approach outperforms ANFIS, achieving an [Formula: see text] value of 0.9845. The optimal fabrication parameters were 7.12 nM, 85.22 min, 6.54 min, 118.02 min, 0.12 mM, and 93.39 min for detection probe concentration, detection probe incubation time, MCH incubation time, hybridization time, OB concentration, and OB incubation time, respectively, resulting in an output current of 223 nA. The ANN-GA framework offers a practical and efficient strategy for biosensor development by reducing experimental iterations, thereby lowering material consumption and enabling rapid parameter optimization. These findings demonstrate that ANN-assisted optimization can accelerate the development of cost-effective, high-performance biosensors, supporting their translation into clinical diagnostics for early and accurate miR-155 detection.

Abstract The rapid and efficient detection of pathogenic bacteria is crucial for ensuring food safety and minimizing public health risks. In this study, the optical detection of Salmonella typhimurium was achieved using ZnO nanoplatforms biofunctionalized with antibodies as a bioreceptor. The ZnO nanowires were grown using a vapor–liquid–solid metal-catalyzed method, with a preferential orientation along the (002) plane as determined by x-ray diffraction, yielding homogeneous structures with a high surface-to-volume ratio. The synthesized nanostructures exhibit a strong 529 nm peak, attributed to deep-level emission, as confirmed by photoluminescence measurements. The presence of defect-related sites contributing to biofunctionalization was confirmed by Fourier transform infrared (FTIR) spectroscopy, where we also monitored surface modification and antibody immobilization. Bacterial cells produced discernible optical responses in FTIR spectra over the concentration range of 1 × 10 1 –1 × 10⁸ CFU ml −1 after 60 min of interaction with the biosensing nanoplatforms. Our results, along with scanning electron microscopy observations, provide spectral and morphological evidence of antigen–antibody binding and membrane attachment, confirming effective detection across different bacterial concentrations. This work highlights the potential of ZnO nanowires as a platform for the further development of low-cost, rapid, and sensitive biosensors for S. typhimurium detection, providing a reference for the appropriate management of biofunctionalized nanoplatforms and their preservation under buffer conditions, with promising applications across different sectors.

Development of user-friendly biosensors for bacterial detection remains a critical concern in public health. The bipolar electrode-based electrochemiluminescence (BPE-ECL) systems are distinguished by their inherent spatial separation of sensing and reporting functions, representing a promising approach for biosensor development. This work innovatively presents a parallel BPE-ECL biosensor, wherein the cathodes are interdigitally inserted and the anodes are functionalized with vertically ordered mesoporous silica films (VMSFs) bearing negative and positive charges, to achieve dual-channel ratiometric ECL detection. The infection of Escherichia coli (E. coli) by T4 phage induces host cell lysis, resulting in a significant increase in the surrounding conductivity. This conductivity alteration within the sensing cell of VMSFs/pBPE-ECL leads to a decrease in the ECL signal of Ru(bpy)32+/TPrA in detection channel 1 and an increase in the ECL signal of Luminol/H2O2 in detection channel 2 independently, due to the enhanced polarization of the BPEs and the nanoconfinement effects of hetero-charged silica nanochannels on the ECL luminophors. By using the ratio of ECL intensities (ILu/IRu) from the two detection channels, E. coli can be detected with improved accuracy and resistance to interference. This biosensing approach is operationally straightforward, avoiding complicated probe immobilization or modification, rendering it a user-friendly platform for bacterial detection. Moreover, by replacing the specific phage-bacteria lysis bioreaction, this biosensing platform could be used for various bacterial detections, highlighting its promising applications.

PEGDA hydrogel-based biosensor for continuous salivary cortisol monitoring without pre-treatment.

In-situ fabrication of BiOI-based single transducer enabling dual photoelectrochemical/colorimetric biosensing.

Enhancing creatinine detection: Innovative biosensors for monitoring kidney function.

Development of a whole-cell biosensor for the detection of low concentrations of tetracycline.

Wearable alcohol biosensors offer an innovative solution for real-time alcohol monitoring, yet concerns about comfort, privacy, and social acceptability have limited their adoption. This study presents the largest real-world evaluation to date of a new-generation wrist-worn alcohol biosensor. In this study, 150 healthy adults (ages 21-54) wore the BACtrack Skyn sensor continuously for 14 days. Using a mixed methods design, we assessed pre- and poststudy feasibility and acceptability through structured surveys and open-ended responses, applying innovative machine learning techniques, including Term Frequency-Inverse Document Frequency and sentiment analysis, to capture nuanced user experiences at scale. Participants showed high compliance (median wear time: 94.66%), and 77% expressed willingness to extend device use. The device's discreet, smartwatchlike appearance supported high social acceptability, with most users reporting easy integration into daily life even if no significant changes in alcohol consumption were observed. While some discomfort-particularly itching and sleep interference-was reported, overall comfort and usability ratings were favorable. Findings indicate that the new-generation wrist-worn alcohol biosensor is a feasible and well-accepted tool for alcohol monitoring. High compliance and positive user reception highlight its potential for real-world applications. While sensor comfort was generally positively rated, refining the device's fit and materials could enhance wearability over extended periods. These insights contribute to the ongoing development of wearable alcohol biosensors that balance usability, functionality, and user experience. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Regeneration of tethered bilayer lipid membrane biosensors for repetitive use in toxin detection.

Development of electrochemical biosensor utilizing Fe3O4@Au and DNAzyme-mediated polymerase strand displacement amplification for the detection of nickel ions