Biosensors

12 pages, 10370 KB

Open AccessArticle

Transient Potential Profiling for Rapid Calcium Ion Quantification: Eliminating Conditioning Time in Solid-Contact Ion-Selective Electrodes

by Kaijie Zheng, Chenjie Yan, Mengwei Jiang, Jing Lei, Chengcheng Wang, Kai Zhao, Dajing Chen and Min Guo

Biosensors 2026, 16(6), 335; https://doi.org/10.3390/bios16060335 (registering DOI) - 12 Jun 2026

Abstract

Traditional solid-contact ion-selective electrodes (SC-ISEs) are severely constrained by a long-standing thermodynamic bottleneck, which requires hours of pre-conditioning and stabilization to establish a stable phase-boundary potential. To fundamentally bypass this limitation, we present a paradigm shift in electrochemical ion sensing that exploits dynamic [...] Read more.

Traditional solid-contact ion-selective electrodes (SC-ISEs) are severely constrained by a long-standing thermodynamic bottleneck, which requires hours of pre-conditioning and stabilization to establish a stable phase-boundary potential. To fundamentally bypass this limitation, we present a paradigm shift in electrochemical ion sensing that exploits dynamic kinetics rather than waiting for thermodynamic equilibrium. In this paper, we report a transient potential profiling method that eliminates the need for equilibration by analyzing the open-circuit voltage decay during the first 60 s of polarization. A discharge step on indicator electrode returns the membrane to a reproducible initial state, allowing for the extraction of a concentration correlated coefficient. Using a calcium ISE with an optimized membrane, the early-stage polarization dynamics were fitted to a single exponential saturation model, predicting the steady state response with an average error of 1.6%. The method achieved high repeatability (intra-day RSD 3.22%), batch to batch reproducibility (4.57%), and recovery rates from 90.7% to 115.0% in real water samples. Validation against ion chromatography showed high agreement (R² = 0.997). This strategy enabled conditioning free, disposable ISEs for point of care and environmental monitoring. Full article

(This article belongs to the Section Nano- and Micro-Technologies in Biosensors)

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15 pages, 2984 KB

Open AccessArticle

Fiber-Optic Raman Sensor for Early Dental Caries Detection: Performance Evaluation and Robustness to Probe Positioning

by Sofia Pessanha, João Miguel Silveira, Paulo Ribeiro, António Mata, Valentina Vassilenko and Sofia Barbosa

Biosensors 2026, 16(6), 334; https://doi.org/10.3390/bios16060334 - 11 Jun 2026

Abstract

Early detection of dental caries remains a significant clinical challenge, as conventional diagnostic methods lack sensitivity for incipient lesions. Raman spectroscopy offers high chemical specificity for enamel characterization; however, clinical translation is hindered by the complexity of conventional polarized confocal systems. In this [...] Read more.

Early detection of dental caries remains a significant clinical challenge, as conventional diagnostic methods lack sensitivity for incipient lesions. Raman spectroscopy offers high chemical specificity for enamel characterization; however, clinical translation is hindered by the complexity of conventional polarized confocal systems. In this work, we present a Raman-based fiber-optic sensing approach for the detection and classification of dental enamel conditions, including sound, affected, and carious tissues. A custom fiber-optic probe was developed for remote measurements and evaluated against a reference polarized confocal Raman system. In addition to spectral discrimination, key factors affecting sensing performance were investigated, including spatial variability across enamel surfaces and angular sensitivity due to probe misalignment. Raman-derived features (carbonate-to-phosphate ratio, phosphate peak intensity, position, and bandwidth) were analyzed using a multinomial logistic regression classifier. The fiber-optic sensor achieved an overall classification accuracy of 73% (F1-scores: 0.55 sound, 0.63 affected, 0.9 carious), confirmed by leave-one-tooth-out cross-validation. Probe misalignment studies revealed robustness up to 10° angular deviation. These results demonstrate that a simplified non-polarized fiber-optic Raman system provides competitive diagnostic performance and clinically relevant robustness, supporting its development as a point-of-care sensing platform for early dental caries detection. Full article

(This article belongs to the Special Issue Photonics for Bioapplications: Sensors and Technology—2nd Edition)

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Graphical abstract

20 pages, 6724 KB

Open AccessArticle

A Fluorescence Imaging-Based 3D Analysis Pipeline for Mouse Trigeminal Ganglion Neurons

by Jiajia Wang, Xinyu Yuan, Jianchao Zhang, Jingyi Che and Xiaojun Wang

Biosensors 2026, 16(6), 333; https://doi.org/10.3390/bios16060333 - 11 Jun 2026

Abstract

As the primary peripheral relay station for vibrissal tactile information, the trigeminal ganglion (TG) features heterogeneous three-dimensional (3D) cytoarchitecture that eludes full characterization using conventional two-dimensional methodologies. A high-resolution 3D imaging and reconstruction pipeline is thus required to unveil TG structural organization and [...] Read more.

As the primary peripheral relay station for vibrissal tactile information, the trigeminal ganglion (TG) features heterogeneous three-dimensional (3D) cytoarchitecture that eludes full characterization using conventional two-dimensional methodologies. A high-resolution 3D imaging and reconstruction pipeline is thus required to unveil TG structural organization and define the spatial framework of target-related sensory neurons. Herein, we established a fluorescence micro-optical sectioning tomography (fMOST)-based workflow for 3D cytoarchitectural mapping of TG anatomy and validated its utility for profiling the distributions of TG neurons innervating vibrissae via single-axon tracing. fMOST imaging coupled with propidium iodide (PI) staining was applied to acquire whole-head anatomical data encompassing the vibrissae and the TG at cellular resolution. Based on clearly resolved cellular morphology and the spatial distribution of neuronal somata, we delineated the soma distribution of TG neurons and revealed a spatially heterogeneous 3D organization pattern, from which we operationally defined two anatomically distinct subdomains: the neuronal soma-rich region (NSRR) and the fiber-rich region (FRR). Furthermore, with retrograde viral/genetic labeling combined with neuronal tracing, TG neurons innervating the C2, D3, and δ vibrissae were observed in both NSRR and FRR, showing partially overlapping yet spatially biased distributions consistent with previous population-level observations of vibrissa-row-dependent topography. Notably, TG neurons innervating the δ vibrissa occupied a comparatively broader spatial extent along the anteroposterior plane in our dataset. Overall, this study facilitates an in-depth mechanistic and anatomical understanding of TG cytoarchitectural organization and underlying functional mechanisms. Full article

(This article belongs to the Special Issue Fluorescent Materials with Excellent Biocompatibility and Their Application in Bio-Sensing, Bio-Imaging (3rd Edition))

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19 pages, 2604 KB

Open AccessReview

SPR Sensing: From Biomolecular Interactions to Cell-Based Analysis

by Petia Genova-Kalou, Evdokiya O. Hikova, Todor Kereziev, Petar T. Kolev, Vihar Mankov, Hristo Kisov, Anna Atanasova and Georgi L. Dyankov

Biosensors 2026, 16(6), 332; https://doi.org/10.3390/bios16060332 - 10 Jun 2026

Abstract

Surface plasmon resonance (SPR) is a key tool for quantifying biomolecular interactions, and its use in studying interacting components outside cellular systems is well-established. Over the past 20–25 years, cell-based SPR techniques have emerged, with the promise of precise detection of molecular interactions [...] Read more.

Surface plasmon resonance (SPR) is a key tool for quantifying biomolecular interactions, and its use in studying interacting components outside cellular systems is well-established. Over the past 20–25 years, cell-based SPR techniques have emerged, with the promise of precise detection of molecular interactions within their normal physiological environment. Research on a wide variety of biological samples, which requires the detection of numerous parameters, has led to the development of a broad range of SPR techniques. This review aims to trace the chronological development of these techniques and the factors that have driven them. In this context, particular focus is given to grating-coupled SPR applied to cell assays. Its specific capabilities are examined, and the respective advantages and disadvantages of other SPR techniques are discussed based on the results obtained from studying specific biological objects. Finally, we venture to predict the promising SPR techniques, as well as the areas of application in which significant results can be expected. Full article

(This article belongs to the Special Issue Surface Plasmon Resonance-Based Biosensors and Their Applications)

20 pages, 2227 KB

Open AccessArticle

A Standardized Prism-Based TIRF Platform for Quantitative Single-Molecule Fluorescence Studies of Biomolecular Dynamics

by Arijit Patra, Lunden Melton, Lenwood S. Sawyer, Tate King and Sujay Ray

Biosensors 2026, 16(6), 331; https://doi.org/10.3390/bios16060331 - 10 Jun 2026

Abstract

Single-molecule Förster resonance energy transfer (smFRET) enables direct measurement of nanoscale conformational dynamics and heterogeneity in biomolecules, but quantitative interpretation of smFRET data critically depends on well-controlled excitation geometry, low background fluorescence, robust calibration, and reproducible data-analysis workflows. Prism-based total internal reflection fluorescence [...] Read more.

Single-molecule Förster resonance energy transfer (smFRET) enables direct measurement of nanoscale conformational dynamics and heterogeneity in biomolecules, but quantitative interpretation of smFRET data critically depends on well-controlled excitation geometry, low background fluorescence, robust calibration, and reproducible data-analysis workflows. Prism-based total internal reflection fluorescence (pTIRF) microscopy provides important advantages for such measurements by physically separating excitation and emission paths and generating a highly confined evanescent field, yet practical guidance for implementing reproducible, quantitative pTIRF systems remains fragmented. Here we present a comprehensive, standardized framework for the design, alignment, calibration, validation, and operation of a prism-based TIRF microscope optimized for single-molecule fluorescence measurements. We describe the complete optical architecture for dual-color excitation and detection, establish alignment invariants that ensure reproducible evanescent excitation and stable donor–acceptor channel registration, and detail surface preparation, flow control, and photostabilization strategies required for reliable long-term imaging. Quantitative benchmarking protocols are introduced to evaluate signal-to-noise ratio, photobleaching kinetics, and spectral crosstalk, providing objective criteria for defining optimal operating conditions and instrument performance limits. Finally, we integrate these experimental procedures with an end-to-end single-molecule data-analysis workflow encompassing channel registration, automated and manual trajectory selection, FRET calculation, and kinetic analysis using hidden Markov modeling. The utility of the platform is demonstrated through smFRET measurements of conformational dynamics in a model nucleic acid system. Together, this work provides a reproducible and accessible methodology for implementing prism-based TIRF microscopy as a robust quantitative platform for single-molecule fluorescence studies across a wide range of biomolecular systems. Full article

(This article belongs to the Special Issue Single-Molecule Biosensors: Recent Advances and Future Challenges)

24 pages, 5812 KB

Open AccessArticle

Sequential CRISPR-EspCas9-Mediated Wild-Type Depletion Enhances the Detection Sensitivity of Rare Mutations for Canine Liquid Biopsy Application

by Sumin Hong, Chul-Sung Park, Kyung Wook Been, Seunghun Kang, Jaewoo Hong, Jung-whan Kim and Junho K. Hur

Biosensors 2026, 16(6), 330; https://doi.org/10.3390/bios16060330 - 10 Jun 2026

Abstract

One of the major obstacles in early cancer detection in dogs is the limited sensitivity in detecting circulating tumor DNAs (ctDNAs) with low abundances. Standard next-generation sequencing (NGS) without error correction typically achieves detection limits around ~1% mutant allele frequency (MAF). We sought [...] Read more.

One of the major obstacles in early cancer detection in dogs is the limited sensitivity in detecting circulating tumor DNAs (ctDNAs) with low abundances. Standard next-generation sequencing (NGS) without error correction typically achieves detection limits around ~1% mutant allele frequency (MAF). We sought to improve the detection sensitivity using a sequential CRISPR-EspCas9 enrichment strategy in which iterative in vitro cleavage (IVC) was combined with PCR amplification to selectively deplete wild-type DNA and enrich rare tumor mutations. Applying the strategy to genomic DNA and cell-free DNA mimics from canine mammary gland tumor cell lines demonstrated that IVC enrichment enabled the detection of cancer-associated PIK3CA H1047R mutations that were undetectable by conventional Sanger sequencing. To evaluate detection sensitivity, we characterized enrichment using synthetic templates for PIK3CA H1047R and other cancer-related mutations, BRAF V596E, and KRAS G12C. We observed that three iterations of sequential IVC achieved ~160, ~15, and ~2.2-fold enrichment for PIK3CA H1047R, BRAF V596E, and KRAS G12C, respectively. Under the present synthetic-template conditions, the analytical LOD reached 0.001% MAF for PIK3CA and 0.01% MAF for BRAF, whereas KRAS showed only modest enrichment and remained practically limited under the current guide design. Together, the results show that the CRISPR-EspCas9 IVC strategy enables selective enrichment of low-frequency single-nucleotide mutant alleles. We anticipate that the finding could be utilized to develop a highly sensitive veterinary liquid biopsy application with further optimization and validation using canine plasma cfDNA. Full article

(This article belongs to the Section Biosensor Materials)

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35 pages, 17323 KB

Open AccessReview

Application of Metal–Organic Framework-Based Electrochemiluminescence Sensors for Mycotoxin Detection in Food

by Tong Zhang, Xinyu Chen, Qiangqiang Wang, Shuyue Xing and Dan Wu

Biosensors 2026, 16(6), 329; https://doi.org/10.3390/bios16060329 - 9 Jun 2026

Abstract

Mycotoxins are toxic secondary metabolites produced by filamentous fungi, which extensively contaminate agricultural products such as grains and nuts. Common mycotoxins, including aflatoxin B1, ochratoxin A, and deoxynivalenol, can induce liver cancer, kidney damage, neural tube defects, and immune suppression, necessitating highly sensitive [...] Read more.

Mycotoxins are toxic secondary metabolites produced by filamentous fungi, which extensively contaminate agricultural products such as grains and nuts. Common mycotoxins, including aflatoxin B1, ochratoxin A, and deoxynivalenol, can induce liver cancer, kidney damage, neural tube defects, and immune suppression, necessitating highly sensitive detection methods to ensure food safety. Conventional techniques are limited by complex procedures and insufficient sensitivity. Electrochemiluminescence (ECL), owing to its high sensitivity, low background signal, and rapid response, has emerged as a promising strategy for mycotoxin analysis. In this context, metal–organic frameworks (MOFs), with their high surface area and tunable structures, have been widely employed in ECL sensors to improve sensing performance. This review summarizes the construction strategies of MOF-based ECL sensors, the diverse functional roles of MOFs in ECL sensing, the associated sensing mechanisms, and the applications of these sensors for the detection of mycotoxins in food. Current challenges, including material stability, sensor reproducibility, and practical applicability, are discussed, and future directions are outlined. Particular emphasis is placed on the development of stable MOF materials, their integration into portable and intelligent ECL sensing platforms, and the establishment of standardized and scalable production methods to enable practical food safety monitoring. Full article

(This article belongs to the Special Issue Advanced Electrochemical Biosensing: Materials, Mechanisms, and Applications)

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5 pages, 162 KB

Open AccessEditorial

State-of-the-Art Biosensors in China

by Nan Xiang and Chun-Yang Zhang

Biosensors 2026, 16(6), 328; https://doi.org/10.3390/bios16060328 - 9 Jun 2026

Abstract

Biosensors are analytical devices that integrate a biological or synthetic recognition element (e [...] Full article

(This article belongs to the Special Issue State-of-the-Art Biosensors in China (2nd Edition))

32 pages, 9897 KB

Open AccessReview

Advancements in Nanomaterial-Based Biosensors for Neuropsychiatric and Neurodegenerative Diagnostics: From Biomarker Discovery to Clinical Translation

by Xinyue Li, Xiaopeng Han, Qing Han, Xuan He, Yixin Huang and Aimei Liu

Biosensors 2026, 16(6), 327; https://doi.org/10.3390/bios16060327 - 5 Jun 2026

Abstract

Nanobiosensors, with their unique physicochemical properties, are transformative tools for diagnosing and monitoring neurodegenerative diseases and mental disorders. This article systematically reviews the latest progress of nanomaterial systems and integrated sensing modalities in neurological disease diagnosis. First, we clarify the multiple functional roles [...] Read more.

Nanobiosensors, with their unique physicochemical properties, are transformative tools for diagnosing and monitoring neurodegenerative diseases and mental disorders. This article systematically reviews the latest progress of nanomaterial systems and integrated sensing modalities in neurological disease diagnosis. First, we clarify the multiple functional roles of nanomaterials in biosensors, including signal amplification, interface optimization, and spatial positioning, and compare the applicable scenarios of various sensing principles based on different nanomaterials. Second, we evaluate the design and integration strategies of molecular recognition elements (antibodies, nucleic acid aptamers, molecularly imprinted polymers, and CRISPR-Cas systems) and discuss their synergistic integration mechanisms for improving detection performance. In terms of detection targets, we focus on three applications: high-sensitivity quantification of established protein biomarkers, real-time monitoring of dynamic neurochemicals (dopamine, serotonin, glutamate), and emerging liquid biopsy targets such as exosomal cargo and circulating microRNAs. Finally, to address the core challenges of biofouling, sensitivity–selectivity trade-offs, and multiplex detection in complex matrices, we propose three breakthrough directions for next-generation diagnostics: deep integration of multimodal and multiplexing platforms, closed-loop chemical brain–computer interfaces (cBCIs), and AI-driven predictive diagnostic models, collectively enabling a transition from passive detection to active sensing and intervention for precise, rapid, and non-invasive neurological disease management. Full article

(This article belongs to the Special Issue Advanced Biosensors for Disease Screening, Monitoring, Diagnosis, and Treatment—2nd Edition)

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33 pages, 5647 KB

Open AccessArticle

Integration of Machine Learning Techniques in ECG-Based Multiclass Arrhythmia Classification with Explainability Analysis

by Abdullah, Zulaikha Fatima, Abdollah Abadian, Carlos Guzmán Sánchez Mejorada, Miguel Jesús Torres Ruiz and Rolando Quintero Téllez

Biosensors 2026, 16(6), 326; https://doi.org/10.3390/bios16060326 - 3 Jun 2026

Abstract

Electrocardiogram (ECG) analysis is a cornerstone non-invasive diagnostic technique for detecting cardiac arrhythmias, which remain a leading cause of mortality worldwide. While recent advances in deep learning have significantly improved automated arrhythmia classification, the current literature lacks systematic, fair comparisons of fundamental neural [...] Read more.

Electrocardiogram (ECG) analysis is a cornerstone non-invasive diagnostic technique for detecting cardiac arrhythmias, which remain a leading cause of mortality worldwide. While recent advances in deep learning have significantly improved automated arrhythmia classification, the current literature lacks systematic, fair comparisons of fundamental neural architectures under unified experimental conditions, and very few studies provide model interpretability. This study addresses these gaps by first providing a rigorous comparative analysis of three representative architectures—Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Residual Network (ResNet)—on the MIT-BIH Arrhythmia Database under identical preprocessing, training, and evaluation protocols. We then propose an efficient Fine-Tuned CNN (FT-CNN) optimized for ECG signal characteristics through adaptive kernel sizing for P-QRS-T morphological extraction, multi-faceted regularization including L2, dropout, and batch normalization, cosine annealing learning rate, and a custom loss function combining weighted categorical cross-entropy with focal loss with gamma equal to 2.0 to address severe class imbalance. The FT-CNN achieves an accuracy of 98.51%, outperforming fourteen benchmark models, including standard CNN with an accuracy of 97.20%, ResNet with 96.88%, LSTM with 96.50%, GRU with 96.30%, and traditional classifiers. Comprehensive ablation studies confirm an improvement of 6.17% over the baseline. Class-wise analysis reveals excellent performance for normal beats with an F1-score of 0.99, ventricular ectopic beats with 0.95, and unknown beats with 0.98, while supraventricular ectopic beats with an F1-score of 0.79 and fusion beats with 0.70 remain challenging. Unlike most prior works, we integrate Grad-CAM and Integrated Gradients for explainability, quantitatively evaluating attribution faithfulness, sanity checks, and noise robustness. Full article

(This article belongs to the Special Issue Biosensors for Physiological Signal Monitoring)

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21 pages, 2765 KB

Open AccessReview

A Review of the Activity Regulation of Au and Pt Bimetallic Nanozymes and Their Application in Food Safety Analysis

by Zhengxin Zhou, Muci Wu, Rui Zhang, Wangting Zhou, Jiaojiao Zhou and Jingren He

Biosensors 2026, 16(6), 325; https://doi.org/10.3390/bios16060325 - 3 Jun 2026

Abstract

Food safety problems caused by pesticide residues, heavy metals, foodborne pathogens, mycotoxins and other hazards seriously threaten public health. Traditional detection methods have the limitations of cumbersome operation, high cost and poor stability, which make it difficult to meet the needs of rapid [...] Read more.

Food safety problems caused by pesticide residues, heavy metals, foodborne pathogens, mycotoxins and other hazards seriously threaten public health. Traditional detection methods have the limitations of cumbersome operation, high cost and poor stability, which make it difficult to meet the needs of rapid and sensitive detection on site. As a new material, nanozymes have the advantages of high stability, low cost and high catalytic activity, showing great application potential in food safety analysis. Among them, gold–platinum (AuPt) bimetallic nanozymes have attracted much attention due to their synergistic catalytic effect, good biocompatibility and modifiability. In this paper, the synthesis methods of AuPt bimetallic nanozymes were systematically reviewed, including chemical reduction, sol–gel, microemulsion, electrochemical deposition, and so on. The control effect of AuPt bimetallic nanozymes on catalytic activity was discussed from the aspects of composition, morphology, structure, external environment and composites with other nanomaterials. The research progress of AuPt bimetallic nanozymes in the detection of pesticide and veterinary drug residues, heavy metal ions, mycotoxins, foodborne pathogens, food additives and food freshness was introduced. Finally, the challenges and future development of AuPt bimetallic nanozymes in food safety analysis were prospected, aiming to provide theoretical reference and design ideas for the construction of a high-performance food safety rapid detection platform. Full article

(This article belongs to the Special Issue Advances in Nanozyme-Based Biosensors)

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14 pages, 3385 KB

Open AccessArticle

Aminated PET Thin Film as a Functionalized Insulating Layer for Capacitive Gliadin Aptasensor Construction

by Po-Chung Chen and Po-Chuan Hsieh

Biosensors 2026, 16(6), 324; https://doi.org/10.3390/bios16060324 - 3 Jun 2026

Abstract

Celiac patients require strict avoidance of gliadin, the primary immunotoxic component of gluten, making sensitive detection essential for food safety. A label-free and reagentless capacitive aptasensor for gliadin detection was developed using an aminated polyethylene terephthalate (PET) thin film as both an insulating [...] Read more.

Celiac patients require strict avoidance of gliadin, the primary immunotoxic component of gluten, making sensitive detection essential for food safety. A label-free and reagentless capacitive aptasensor for gliadin detection was developed using an aminated polyethylene terephthalate (PET) thin film as both an insulating layer and functionalization platform. The PET surface was modified via ethylenediamine-mediated aminolysis, enabling covalent immobilization of 5′-NH₂-modified gliadin aptamers through glutaraldehyde crosslinking. Under optimized conditions (23 µm initial PET thickness and 10 µM aptamer), the sensor showed a linear response from 10 to 500 µg/mL gliadin (R² = 0.9792), with a detection limit of 6.0 µg/mL, equivalent to 12 ppm gluten, which is well below the regulatory threshold of 20 ppm for gluten-free labeling. The aptasensor showed excellent correlation with commercial ELISA for 20 gluten-containing soy sauce samples (R² = 0.926) and spike recoveries of 91.7–105.7% in two gluten-free products. Efficient regeneration was achieved with 25 mM arginine (pH 9.0), retaining >80% activity after six cycles. This simple, low-cost, and reusable platform relies solely on a single PET thin film as consumable in a custom-built system with lab-friendly aminolysis conditions. It substantially lowers barriers to functionalized insulating layer fabrication, the primary challenge in capacitive aptasensor development, providing a promising method for on-site gliadin monitoring in gluten-free food safety applications. Full article

(This article belongs to the Special Issue Advanced Electrochemical Biosensors and Their Applications)

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22 pages, 16698 KB

Open AccessArticle

Wearable-Derived Axis-Specific Motor Signatures of ADHD Symptoms in Children and Adolescents

by Siyu Zhang, Jingsong Liu and Shoujiang Wu

Biosensors 2026, 16(6), 323; https://doi.org/10.3390/bios16060323 - 2 Jun 2026

Abstract

ADHD is typically assessed through reports from parents, teachers, or clinicians, but these reports may not fully capture how motor behavior is organized at the signal level. This cross-sectional study examined whether X-axis acceleration features derived from a wearable device could provide preliminary [...] Read more.

ADHD is typically assessed through reports from parents, teachers, or clinicians, but these reports may not fully capture how motor behavior is organized at the signal level. This cross-sectional study examined whether X-axis acceleration features derived from a wearable device could provide preliminary evidence of ADHD symptom-related motor-pattern differences in children and adolescents. Primary school children aged 6–13 years wore an Apple Watch Series 7, and X-axis accelerometer signals were used to extract features reflecting waveform distribution, zero-crossing rate, micro-motion, and local movement fragmentation. ADHD symptoms and broader emotional and behavioral difficulties were assessed using the SNAP-IV and SDQ. The results showed that the X-axis zero-crossing rate was the most robust feature differentiating the High ADHD and Low ADHD groups across the T-task and F-task recordings. X-axis zero-crossing rate reached statistical significance (p = 0.029), indicating more frequent short-interval switching between positive and negative acceleration directions in children with higher ADHD symptom levels. This finding suggests that directional switching or local movement fragmentation in X-axis acceleration may be a sensitive movement characteristic associated with ADHD symptoms. In addition, X-axis skewness showed a consistent directional tendency, with higher values in the High ADHD group; this effect was marginal in the T-task recording (p = 0.065), suggesting a possible tendency toward waveform asymmetry or distributional imbalance during longer movement recording. Overall, these findings provide preliminary evidence that ADHD symptom-related motor differences may be reflected in the organization of X-axis acceleration signals, particularly in directional switching indexed by zero-crossing rate and, to a lesser extent, waveform asymmetry indexed by skewness. Given the cross-sectional design, symptom-based grouping, modest sample size, and incomplete recording-context control, these results should be interpreted cautiously and require confirmation in larger, diagnostically characterized samples with standardized wearable-recording protocols. Full article

(This article belongs to the Special Issue Advances in Flexible Bioelectronics and Intelligent Biosensing Systems—2nd Edition)

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47 pages, 34960 KB

Open AccessReview

Ultraviolet Sensing-Guided Biomedical Systems: From Label-Free Imaging to Dosimetry and Therapy Feedback

by Haosong Du, Yunxin Wang, Ruochong Zhang, Malini Olivo and Renzhe Bi

Biosensors 2026, 16(6), 322; https://doi.org/10.3390/bios16060322 - 2 Jun 2026

Abstract

Ultraviolet (UV) light is emerging as an important tool for biosensing, biomedical signal readout, and dose monitoring because of its strong and selective interactions with nucleic acids, proteins, and other biological components. This review summarizes recent progress in UV sensing-guided biomedical systems, with [...] Read more.

Ultraviolet (UV) light is emerging as an important tool for biosensing, biomedical signal readout, and dose monitoring because of its strong and selective interactions with nucleic acids, proteins, and other biological components. This review summarizes recent progress in UV sensing-guided biomedical systems, with emphasis on three interconnected directions: label-free and surface-weighted imaging, wearable and embedded UV dosimetry, and sensor-assisted therapeutic guidance. Representative examples include ultraviolet photoacoustic microscopy (UV-PAM) for label-free nuclear imaging, microscopy with ultraviolet surface excitation (MUSE) for rapid slide-free histology-like readout, epidermal and flexible UV dosimeters for skin-level exposure quantification, and UV therapeutic platforms that are increasingly supported by sensing, dosimetry, and feedback for safer dose delivery. Across these applications, we emphasize the shared biosensing principles of signal generation, optical or acoustic transduction, quantitative readout, calibration, and feedback-informed decision support. We also discuss the role of artificial intelligence in virtual staining, image enhancement, domain correction, dose prediction, and decision support. The review concludes with key translational challenges in standardization, uncertainty quantification, multimodal integration, and feedback-driven system design. Overall, this sensing-centered perspective helps define the role of UV technologies more clearly within biosensors-oriented biomedical engineering. Full article

(This article belongs to the Special Issue Advanced Optical Imaging Biosensors: Technologies and Biomedical Applications)

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20 pages, 2228 KB

Open AccessArticle

A Centrifugal Microfluidic Platform Integrating Immunomagnetic Separation and Isothermal Amplification for Rapid and High-Sensitivity Detection of Foodborne Pathogens

by Qingfeng Zheng, Zhun Zhuang, Hua Lei, Jianhan Lin, Hua Yang and Ruibin Hu

Biosensors 2026, 16(6), 321; https://doi.org/10.3390/bios16060321 - 2 Jun 2026

Abstract

The contamination by foodborne pathogens posed a significant health threat and huge economic burden. Traditional detection methods were limited by cumbersome and time-consuming procedures, low automation, and reliance on expensive instrumentation, making them inadequate for on-site detection. This paper presented a centrifugal microfluidic [...] Read more.

The contamination by foodborne pathogens posed a significant health threat and huge economic burden. Traditional detection methods were limited by cumbersome and time-consuming procedures, low automation, and reliance on expensive instrumentation, making them inadequate for on-site detection. This paper presented a centrifugal microfluidic chip that integrated sample pretreatment, nucleic acid extraction, amplification reaction, and signal detection. The chip featured an innovative design that combined a bursting valve with the siphon channel and employed a dual-channel configuration for splitting and directing the flow of different reagents, thereby overcoming the instability issue of unintended pre-activation or interruption that often occurred in the cascade design of multilevel siphon channels. Moreover, by synergistically combining with immunomagnetic separation as well as multi-enzyme isothermal rapid amplification, a portable, easy, rapid, high-sensitivity, and low-cost point-of-care testing (POCT) system for foodborne pathogens was developed. Under optimized conditions, the system enabled detection of Salmonella in spiked milk samples at 10 CFU/mL in 1 h. The recoveries ranged from 83.22% to 127.60%, with relative standard deviations of ≤13.7%, indicating that this system had great potential for rapid and high-sensitivity detection of foodborne pathogens in resource-limited settings. Full article

(This article belongs to the Special Issue Sensors for Environmental Monitoring and Food Safety—2nd Edition)

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24 pages, 3413 KB

Open AccessArticle

CNN-Based Classification of Ziziphus Seeds with Focal Loss for Overcoming Size-Based Shortcut Learning

by Yea-Jin Park and Dae-Hyun Jung

Biosensors 2026, 16(6), 320; https://doi.org/10.3390/bios16060320 - 2 Jun 2026

Abstract

Herbal medicines represent a significant global market, yet food safety remains threatened by counterfeit products morphologically resembling authentic samples. Models trained on limited datasets are prone to shortcut learning, relying on superficial features rather than intrinsic morphological characteristics. This study identified size-based shortcut [...] Read more.

Herbal medicines represent a significant global market, yet food safety remains threatened by counterfeit products morphologically resembling authentic samples. Models trained on limited datasets are prone to shortcut learning, relying on superficial features rather than intrinsic morphological characteristics. This study identified size-based shortcut learning as a critical factor degrading the classification of Ziziphus jujuba Mill. var. spinosa and its counterfeit Ziziphus mauritiana Lam., and demonstrated that focal loss alone can effectively mitigate this issue. Models trained on the internal dataset were evaluated on an external dataset acquired with the Herb-X. On the internal test set, all configurations achieved high classification accuracies (≥98%), thereby obscuring meaningful differences in external generalization. However, consistent performance degradation was observed on the external dataset. The cross-entropy model trained on background-removed data dropped to 82.08 ± 10.97%, while size-normalized models recovered to 84.17 ± 10.15% (upsizing) and 88.94 ± 6.76% (downsizing), confirming that suppressing size shortcuts improves external generalization. The focal loss model, without any preprocessing, achieved 90.88 ± 2.71%, reducing the internal–external generalization gap from 16.18 to 8.11 percentage points. Grad-CAM++ and loss analyses confirmed that the focal loss model attended to intrinsic morphological features rather than object size. This study provides a practical, preprocessing-free approach for reliable herbal-medicine authentication in field conditions. Full article

(This article belongs to the Special Issue Machine Learning-Assisted Biosensing in Agriculture, Food, and Environmental Applications)

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23 pages, 4447 KB

Open AccessReview

Opto-Electrochemical Probes for In Vitro/In Vivo Analysis: Principles, Designs, and Applications

by Alexander N. Vaneev, Petr V. Gorelkin, Natalia L. Klyachko and Alexander S. Erofeev

Biosensors 2026, 16(6), 319; https://doi.org/10.3390/bios16060319 - 2 Jun 2026

Abstract

This review examines recent advances in multifunctional probes that integrate optical and electrochemical channels for in vitro/in vivo studies. Integration of electrodes with optical fibers provides a powerful platform for localized light delivery and simultaneous electrochemical detection of cellular metabolites both within and [...] Read more.

This review examines recent advances in multifunctional probes that integrate optical and electrochemical channels for in vitro/in vivo studies. Integration of electrodes with optical fibers provides a powerful platform for localized light delivery and simultaneous electrochemical detection of cellular metabolites both within and at the surface of single living cells. These hybrid devices bridge optical stimulation methods, including optogenetics, and electrochemical monitoring of the cellular response within the same experimental preparation. The review systematically categorizes distinct probe architectures: optical nanoendoscopes for intracellular measurements, probes with a shared opto-electrochemical channel, devices where optical and electrochemical channels are physically separated, and probes engineered for neural interfaces and scanning probe microscopy. For each category, fabrication approaches, surface modification strategies, and representative biological applications are discussed. Particular attention is given to the fundamental tension between optical transparency and electrical conductivity in shared-channel designs, to the mechanical requirements imposed by neural tissue on implantable probes, and to the spatial resolution limits of current scanning probe platforms. The review concludes with a critical assessment of current limitations and future directions, including higher spatial resolution, simultaneous multiplexed analyte detection and broader translation of these technologies toward in vivo experimental models. Full article

(This article belongs to the Section Optical and Photonic Biosensors)

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18 pages, 15061 KB

Open AccessArticle

Development of Laser-Scribed Graphene Electrodes for Label-Free L-Histidine Sensing in Artificial Sweat

by William García-Rodríguez, Karla Echeverría-Altamar, José A. Lasalde-Ramirez and Pedro J. Resto-Irizarry

Biosensors 2026, 16(6), 318; https://doi.org/10.3390/bios16060318 - 2 Jun 2026

Abstract

This study investigates the fabrication of laser-scribed graphene (LSG) electrodes on polyimide substrates using a CO₂ laser cutter for label-free L-Histidine detection in artificial sweat. Two-level full factorial and central composite designs were employed to optimize critical manufacturing parameters, including laser speed, [...] Read more.

This study investigates the fabrication of laser-scribed graphene (LSG) electrodes on polyimide substrates using a CO₂ laser cutter for label-free L-Histidine detection in artificial sweat. Two-level full factorial and central composite designs were employed to optimize critical manufacturing parameters, including laser speed, power, and electrode width. Electrochemical characterization using cyclic voltammetry with K₃Fe[CN]₆ demonstrated superior LSG electrode performance compared to standard glassy carbon electrodes, exhibiting a 702 ± 62% higher oxidation current peak at 0.56 mM K₃Fe[CN]₆ in 0.1 M KCl. We successfully demonstrated the label-free electrochemical detection of L-Histidine in artificial sweat using these LSG electrodes. The results show a linear relationship (R² = 0.987) between current peak and L-Histidine concentration within the 8.3 mM to 50 mM range, demonstrating high sensitivity towards L-Histidine. These findings highlight the potential of this optimized LSG electrode fabrication approach for developing high-performance, user-friendly, and disposable wearable biosensors for real-time and non-invasive health monitoring applications in sweat analysis. Full article

(This article belongs to the Special Issue Wearable Sensors and Systems for Continuous Health Monitoring)

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32 pages, 8493 KB

Open AccessReview

From Single-Ion to Integrated Multi-Ion Platforms: Wearable Sweat Sensors for Electrolyte Monitoring

by Jieru Yang, Junyao Li, Xiao Han, Zewen Wei, Gang Wang and Ting Zou

Biosensors 2026, 16(6), 317; https://doi.org/10.3390/bios16060317 - 1 Jun 2026

Abstract

Sweat contains abundant ions, offering a rich source of physiological information for non-invasive health monitoring. Wearable sweat sensors have become a promising technology due to advances in electrochemical devices, sensing materials and structural design. The current monitoring platforms primarily employ two fundamental sensing [...] Read more.

Sweat contains abundant ions, offering a rich source of physiological information for non-invasive health monitoring. Wearable sweat sensors have become a promising technology due to advances in electrochemical devices, sensing materials and structural design. The current monitoring platforms primarily employ two fundamental sensing modalities to convert sweat chemical information into detectable numerical signals: electrochemical (potentiometric, voltammetric, transistor-based) and optical (colorimetric) transduction mechanisms. The demand for more comprehensive physiological and biochemical data in clinical diagnosis and daily health monitoring is driving sensors towards multi-ion detection. Building on these modalities, researchers have optimized hardware and software algorithms based on the characteristics of different ions, thereby promoting the transition of wearable devices from the laboratory to practical applications. Here, we summarize recent progress in wearable sweat ion sensors, focusing on their mechanisms, advantages, and limitations. Finally, current challenges and future prospects of wearable sweat ion sensors for research applications, clinical use, and market demands are discussed. Full article

(This article belongs to the Special Issue Latest Wearable Biosensors—2nd Edition)

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