Biosensors

21 pages, 2765 KB

Open AccessArticle

Feasibility of IMU-Based Wearable Sonification: Toward Personalized, Real-Time Gait Monitoring and Rehabilitation

by Toh Yen Pang, Chi-Tsun Cheng, Frank Feltham, Azizur Rahman, Luke McCarney and Carolina Quintero Rodriguez

Biosensors 2025, 15(10), 698; https://doi.org/10.3390/bios15100698 - 15 Oct 2025

Abstract

Wearable auditory feedback systems have demonstrated potential to support gait rehabilitation, yet user experience and engagement remain underexplored. This feasibility study investigated the usability and perceptions of an IMU-based (WT901BLECL, WitMotion) sonification system designed to deliver real-time gait feedback. Twenty healthy participants walked [...] Read more.

Wearable auditory feedback systems have demonstrated potential to support gait rehabilitation, yet user experience and engagement remain underexplored. This feasibility study investigated the usability and perceptions of an IMU-based (WT901BLECL, WitMotion) sonification system designed to deliver real-time gait feedback. Twenty healthy participants walked on a treadmill at two speeds under three conditions: no feedback, discrete bass tones, and continuous whoosh tones. The proposed system, with an IMU sensor embedded in a flexible garment, combined real-time gait analysis with auditory cues. Participants reported high levels of comfort, with most (90%) indicating that they had a positive overall experience. Discrete bass tones enhanced awareness of specific gait phases, particularly heel strike and initial contact, whereas continuous whoosh sounds extended awareness to the trunk and hips but were occasionally perceived as distracting. Motivation effects were mixed, and no significant correlations were found between subjective ratings and biomechanical measures, reflecting individual variability in auditory cue interpretation. These results emphasized the role of sound modality in influencing gait perception and highlighted the importance of user-centered design in wearable rehabilitation technologies. The study provides foundational evidence for refining personalized auditory feedback systems and supports future investigations with clinical populations, such as stroke survivors and individuals with Parkinson’s Disease. Full article

(This article belongs to the Special Issue Biomarkers of Disability and Movement Disorders: Insights from Wearable Devices)

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13 pages, 1212 KB

Open AccessArticle

Direct ECL Detection of Fentanyl Drug with Bare Screen-Printed Electrodes

by David Ibáñez, María Begoña González-García, David Hernández-Santos and Pablo Fanjul-Bolado

Biosensors 2025, 15(10), 697; https://doi.org/10.3390/bios15100697 - 15 Oct 2025

Abstract

Electrogenerated chemiluminescence (ECL) is a powerful analytical technique that combines the best features of both electrochemical and photoluminescence methods. In this work, we present a direct ECL-based method for the detection of fentanyl using unmodified screen-printed electrodes. The analysed system consists of tris(2,2′-bipyridyl)ruthenium(II) [...] Read more.

Electrogenerated chemiluminescence (ECL) is a powerful analytical technique that combines the best features of both electrochemical and photoluminescence methods. In this work, we present a direct ECL-based method for the detection of fentanyl using unmodified screen-printed electrodes. The analysed system consists of tris(2,2′-bipyridyl)ruthenium(II) (Ru(bpy)₃²⁺) as the luminophore and fentanyl as the co-reactant. A comprehensive optimization of the experimental parameters, such as buffer pH, luminophore concentration and working electrode material, was performed in order to maximize the ECL response. The optimal conditions are identified as PBS buffer pH 6, 2.5 × 10⁻³ M Ru(bpy)₃²⁺ and bare gold screen-printed electrodes. Under these conditions, the system exhibited a strong and reproducible ECL signal, with a linear response to fentanyl concentration from 1 × 10⁻⁷ to 1 × 10⁻⁵ M and a limit of detection of 6.7 × 10⁻⁸ M. Notably, the proposed method does not require electrode surface modification, sample pretreatment or complex instrumentation, offering a rapid, sensitive, and cost-effective alternative for fentanyl detection. Furthermore, the storage of bare SPEs at room temperature in a dry place ensures their stability over months or even years, overcoming the limitations offered by ECL systems based on modifications of the working electrode with different nanomaterials. These findings highlight the potential of the proposed ECL approach as a robust and sensitive tool for the detection of synthetic opioids. Its simplicity, portability, and analytical performance make it particularly attractive for forensic and clinical applications where rapid and accurate opioid screening is essential. Full article

(This article belongs to the Special Issue Recent Developments in Micro/Nano Sensors for Biomedical Applications)

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Graphical abstract

50 pages, 3979 KB

Open AccessReview

Single-Molecule Detection Technologies: Advances in Devices, Transduction Mechanisms, and Functional Materials for Real-World Biomedical and Environmental Applications

by Sampa Manoranjan Barman, Arpita Parakh, A. Anny Leema, P. Balakrishnan, Ankita Avthankar, Dhiraj P. Tulaskar, Purshottam J. Assudani, Shon Nemane, Prakash Rewatkar, Madhusudan B. Kulkarni and Manish Bhaiyya

Biosensors 2025, 15(10), 696; https://doi.org/10.3390/bios15100696 - 14 Oct 2025

Abstract

Single-molecule detection (SMD) has reformed analytical science by enabling the direct observation of individual molecular events, thus overcoming the limitations of ensemble-averaged measurements. This review presents a comprehensive analysis of the principles, devices, and emerging materials that have shaped the current landscape of [...] Read more.

Single-molecule detection (SMD) has reformed analytical science by enabling the direct observation of individual molecular events, thus overcoming the limitations of ensemble-averaged measurements. This review presents a comprehensive analysis of the principles, devices, and emerging materials that have shaped the current landscape of SMD. We explore a wide range of sensing mechanisms, including surface plasmon resonance, mechanochemical transduction, transistor-based sensing, optical microfiber platforms, fluorescence-based techniques, Raman scattering, and recognition tunneling, which offer distinct advantages in terms of label-free operation, ultrasensitivity, and real-time responsiveness. Each technique is critically examined through representative case studies, revealing how innovations in device architecture and signal amplification strategies have collectively pushed the detection limits into the femtomolar to attomolar range. Beyond the sensing principles, this review highlights the transformative role of advanced nanomaterials such as graphene, carbon nanotubes, quantum dots, MnO₂ nanosheets, upconversion nanocrystals, and magnetic nanoparticles. These materials enable new transduction pathways and augment the signal strength, specificity, and integration into compact and wearable biosensing platforms. We also detail the multifaceted applications of SMD across biomedical diagnostics, environmental monitoring, food safety, neuroscience, materials science, and quantum technologies, underscoring its relevance to global health, safety, and sustainability. Despite significant progress, the field faces several critical challenges, including signal reproducibility, biocompatibility, fabrication scalability, and data interpretation complexity. To address these barriers, we propose future research directions involving multimodal transduction, AI-assisted signal analytics, surface passivation techniques, and modular system design for field-deployable diagnostics. By providing a cross-disciplinary synthesis of device physics, materials science, and real-world applications, this review offers a comprehensive roadmap for the next generation of SMD technologies, poised to impact both fundamental research and translational healthcare. Full article

(This article belongs to the Special Issue Polymers-Based Biosensors and Bioelectronics: Designs and Applications)

14 pages, 2162 KB

Open AccessArticle

Sensing Cellular Damages Induced by Food Safety Hazards Using Bacterial Stress-Responsive Biosensors

by Ruiqi Li, Manzhuan Lou, Wei He and Shu Quan

Biosensors 2025, 15(10), 695; https://doi.org/10.3390/bios15100695 - 14 Oct 2025

Abstract

Food safety hazards induce diverse cellular damages including DNA damage, oxidative stress, proteotoxic stress, and membrane disruption, ultimately contributing to various human diseases. Conventional toxicity assays, while effective, are often resource-intensive and lack the capacity to distinguish among these different damage types, thereby [...] Read more.

Food safety hazards induce diverse cellular damages including DNA damage, oxidative stress, proteotoxic stress, and membrane disruption, ultimately contributing to various human diseases. Conventional toxicity assays, while effective, are often resource-intensive and lack the capacity to distinguish among these different damage types, thereby limiting insight into toxic responses and the development of effective strategies for targeted risk mitigation. Here, we constructed a panel of Escherichia coli whole-cell biosensors capable of distinguishing distinct categories of cellular damage. Specifically, an optimized RecA-LexA-based DNA damage biosensor that precisely controls the exogenous expression of the transcriptional repressor LexA achieved a 35.5% reduction in baseline signal and a 36.6-fold induction of fluorescence. In parallel, systematic promoter screening identified P_fpr, P_katG, P_grpE, and P_fabA as effective modules for constructing oxidative, proteotoxic, and membrane stress biosensors. These biosensors exhibited high specificity and sensitivity, generating dose-dependent responses to model toxicants and enabling discrimination of cellular damage induced by typical hazards such as norfloxacin and ciprofloxacin. Notably, the DNA damage biosensor detected norfloxacin with a limit of detection (LOD) of 1.3 ng/mL in standard solution and 3.0 ng/mL in milk, comparable to that of high-performance liquid chromatography (HPLC). Together, our work not only provides a versatile, cost-effective, and sensitive tool for assessing diverse cellular damages induced by food safety hazards, but also demonstrates potential utility for practical food safety monitoring. Full article

(This article belongs to the Special Issue Advanced Cell-Analyzing Technologies and Their Biosensing Applications)

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15 pages, 2027 KB

Open AccessArticle

Exosome Biomarker Profiling Using a Paper-Based Vertical Flow Assay

by Arnau Pallarès-Rusiñol, Jennifer Marfà, Rosanna Rossi, Mercè Martí and María Isabel Pividori

Biosensors 2025, 15(10), 694; https://doi.org/10.3390/bios15100694 - 14 Oct 2025

Abstract

Exosomes are nanoscale extracellular vesicles that carry valuable biomolecular information. However, their characterization still depends on complex and costly techniques such as flow cytometry. In this study, a paper-based Vertical Flow Assay (VFA) specifically designed for the detection and profiling of exosomes derived [...] Read more.

Exosomes are nanoscale extracellular vesicles that carry valuable biomolecular information. However, their characterization still depends on complex and costly techniques such as flow cytometry. In this study, a paper-based Vertical Flow Assay (VFA) specifically designed for the detection and profiling of exosomes derived from metastatic breast cancer cell lines is presented. The assay operates in an ELISA-like format, targeting exosomal surface proteins (CD9, CD63, CD81, and EGFR1) with specific antibodies and a secondary antibody conjugated to alkaline phosphatase. Upon reaction with the NBT/BCIP substrate, an insoluble indigo precipitate forms on the nitrocellulose membrane, generating a visual signal that can be further quantified by smartphone imaging. The VFA was optimized for membrane type, pore size, and blocking agents, reaching a detection limit of ~6 × 10⁷ exosomes µL⁻¹ in less than 20 min. Comparative studies with bead-based flow cytometry confirmed consistent biomarker expression profiles, demonstrating the reliability of the method. By enabling exosome biomarker profiling in a simplified and low-cost format, this approach provides a promising alternative to flow cytometry and other applications required for exosome characterization. Full article

(This article belongs to the Section Biosensors and Healthcare)

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24 pages, 3722 KB

Open AccessArticle

Automated T-Cell Proliferation in Lab-on-Chip Devices Integrating Microfluidics and Deep Learning-Based Image Analysis for Long-Term Experiments

by María Fernanda Cadena Vizuete, Martin Condor, Dennis Raith, Avani Sapre, Marie Follo, Gina Layedra, Roland Mertelsmann, Maximiliano Perez and Betiana Lerner

Biosensors 2025, 15(10), 693; https://doi.org/10.3390/bios15100693 - 13 Oct 2025

Abstract

T cells play a pivotal role in cancer research, particularly in immunotherapy, which harnesses the immune system to target malignancies. However, conventional expansion methods face limitations such as high reagent consumption, contamination risks, and difficulties in maintaining suspension cells in dynamic culture environments. [...] Read more.

T cells play a pivotal role in cancer research, particularly in immunotherapy, which harnesses the immune system to target malignancies. However, conventional expansion methods face limitations such as high reagent consumption, contamination risks, and difficulties in maintaining suspension cells in dynamic culture environments. This study presents a microfluidic system for long-term culture of non-adherent cells, featuring automated perfusion and image acquisition. The system integrates deep learning-based image analysis, which quantifies cell coverage and estimates cell numbers, and efficiently processes large volumes of data. The performance of this deep learning approach was benchmarked against the widely used Trainable Weka Segmentation (TWS) plugin for Fiji. Additionally, two distinct lab-on-a-chip (LOC) devices were evaluated independently: the commercial ibidi^® LOC and a custom-made PDMS LOC. The setup supported the proliferation of Jurkat cells and primary human T cells without significant loss during medium exchange. Each platform proved suitable for long-term expansion while offering distinct advantages in terms of design, cell seeding and recovery, and reusability. This integrated approach enables extended experiments with minimal manual intervention, stable perfusion, and supports multi-reagent administration, offering a powerful platform for advancing suspension cell research in immunotherapy. Full article

(This article belongs to the Special Issue Microfluidics and Organ-on-a-Chip for Disease Modeling and Drug Screening (2nd Edition))

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33 pages, 3983 KB

Open AccessArticle

Real-Time EEG Decoding of Motor Imagery via Nonlinear Dimensionality Reduction (Manifold Learning) and Shallow Classifiers

by Hezzal Kucukselbes and Ebru Sayilgan

Biosensors 2025, 15(10), 692; https://doi.org/10.3390/bios15100692 - 13 Oct 2025

Abstract

This study introduces a real-time processing framework for decoding motor imagery EEG signals by integrating manifold learning techniques with shallow classifiers. EEG recordings were obtained from six healthy participants performing five distinct wrist and hand motor imagery tasks. To address the challenges of [...] Read more.

This study introduces a real-time processing framework for decoding motor imagery EEG signals by integrating manifold learning techniques with shallow classifiers. EEG recordings were obtained from six healthy participants performing five distinct wrist and hand motor imagery tasks. To address the challenges of high dimensionality and inherent nonlinearity in EEG data, five nonlinear dimensionality reduction methods, t-SNE, ISOMAP, LLE, Spectral Embedding, and MDS, were comparatively evaluated. Each method was combined with three shallow classifiers (k-NN, Naive Bayes, and SVM) to investigate performance across binary, ternary, and five-class classification settings. Among all tested configurations, the t-SNE + k-NN pairing achieved the highest accuracies, reaching 99.7% (two-class), 99.3% (three-class), and 89.0% (five-class). ISOMAP and MDS also delivered competitive results, particularly in multi-class scenarios. The presented approach builds upon our previous work involving EEG datasets from individuals with spinal cord injury (SCI), where the same manifold techniques were examined extensively. Comparative findings between healthy and SCI groups reveal consistent advantages of t-SNE and ISOMAP in preserving class separability, despite higher overall accuracies in healthy subjects due to improved signal quality. The proposed pipeline demonstrates low-latency performance, completing signal processing and classification in approximately 150 ms per trial, thereby meeting real-time requirements for responsive BCI applications. These results highlight the potential of nonlinear dimensionality reduction to enhance real-time EEG decoding, offering a low-complexity yet high-accuracy solution applicable to both healthy users and neurologically impaired individuals in neurorehabilitation and assistive technology contexts. Full article

(This article belongs to the Section Wearable Biosensors)

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12 pages, 1755 KB

Open AccessArticle

A Highly Sensitive Fluorescent Sensor Based on Carbon Dots and Gold Nanoparticles for Carbaryl Through the Inner Filter Effect

by Yan Lu, Chengqi Bao and Minghui Yang

Biosensors 2025, 15(10), 691; https://doi.org/10.3390/bios15100691 - 13 Oct 2025

Abstract

A highly sensitive fluorescent sensing platform was successfully constructed through carbon dots (CDs) and gold nanoparticles (AuNPs) for the specific detection of carbaryl pesticide. Because of the overlap between the fluorescence emission spectrum of CDs and the ultraviolet (UV) absorption spectrum of AuNPs, [...] Read more.

A highly sensitive fluorescent sensing platform was successfully constructed through carbon dots (CDs) and gold nanoparticles (AuNPs) for the specific detection of carbaryl pesticide. Because of the overlap between the fluorescence emission spectrum of CDs and the ultraviolet (UV) absorption spectrum of AuNPs, the fluorescence intensity of CDs exhibited a remarkable decrease in the presence of AuNPs, which was primarily attributed to the inner filter effect (IFE). Acetylcholinesterase (AChE), as a crucial hydrolase in the cholinergic system, can efficiently catalyze the substrate acetylthiocholine iodide (ATChI), leading to the formation of thiocholine. Due to the fact that thiocholine exhibited a positive charge and contained a thiol (-SH), the introduction of thiocholine resulted in the aggregation of AuNPs via gold–thiol bonding and electrostatic interactions. Subsequently, the fluorescence of CDs was restored as the inner filter effect between CDs and AuNPs was alleviated. In addition, carbaryl exerted a significant inhibitory effect on the activity of AChE, impeding the generation of thiocholine and the aggregation of AuNPs, thereby maintaining the fluorescence of CDs quenched. Under the optimal analytical conditions, the detection range of carbaryl is from 0.1 to 200 ng/mL with a detection limit (LOD) of 0.05 ng/mL (S/N = 3). The proposed fluorescent sensor was successfully employed for the detection of carbaryl in strawberry samples with recoveries in the range of 97.5%–101.1%, with the relative standard deviation (RSD) less than 5%. Full article

(This article belongs to the Special Issue Feature Paper in Biosensor and Bioelectronic Devices 2025)

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38 pages, 4151 KB

Open AccessReview

Integration of Artificial Intelligence in Biosensors for Enhanced Detection of Foodborne Pathogens

by Riza Jane S. Banicod, Nazia Tabassum, Du-Min Jo, Aqib Javaid, Young-Mog Kim and Fazlurrahman Khan

Biosensors 2025, 15(10), 690; https://doi.org/10.3390/bios15100690 - 12 Oct 2025

Abstract

Foodborne pathogens remain a significant public health concern, necessitating the development of rapid, sensitive, and reliable detection methods for various food matrices. Traditional biosensors, while effective in many contexts, often face limitations related to complex sample environments, signal interpretation, and on-site usability. The [...] Read more.

Foodborne pathogens remain a significant public health concern, necessitating the development of rapid, sensitive, and reliable detection methods for various food matrices. Traditional biosensors, while effective in many contexts, often face limitations related to complex sample environments, signal interpretation, and on-site usability. The integration of artificial intelligence (AI) into biosensing platforms offers a transformative approach to address these challenges. This review critically examines recent advancements in AI-assisted biosensors for detecting foodborne pathogens in various food samples, including meat, dairy products, fresh produce, and ready-to-eat foods. Emphasis is placed on the application of machine learning and deep learning to improve biosensor accuracy, reduce detection time, and automate data interpretation. AI models have demonstrated capabilities in enhancing sensitivity, minimizing false results, and enabling real-time, on-site analysis through innovative interfaces. Additionally, the review highlights the types of biosensing mechanisms employed, such as electrochemical, optical, and piezoelectric, and how AI optimizes their performance. While these developments show promising outcomes, challenges remain in terms of data quality, algorithm transparency, and regulatory acceptance. The future integration of standardized datasets, explainable AI models, and robust validation protocols will be essential to fully harness the potential of AI-enhanced biosensors for next-generation food safety monitoring. Full article

(This article belongs to the Special Issue Biosensors for Environmental Monitoring and Food Safety)

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14 pages, 2514 KB

Open AccessArticle

Ultrasensitive Electrochemical Immunoassays of IgG and CA125 Based on Glucose Oxidase-Catalyzed Signal Amplification with Gold Staining

by Long Chao, Zhisong Wu, Shiqiang Qi, Aigui Xu, Zhao Huang and Dexuan Yan

Biosensors 2025, 15(10), 689; https://doi.org/10.3390/bios15100689 - 11 Oct 2025

Abstract

Herein, we propose an ultrasensitive electrochemical immunosensor based on glucose oxidase labeling and enzyme-catalyzed Au staining. In brief, the primary antibody (Ab₁), bovine serum albumin, an antigen and then a bionanocomposite that contains a second antibody (Ab₂), poly(3-anilineboronic acid) [...] Read more.

Herein, we propose an ultrasensitive electrochemical immunosensor based on glucose oxidase labeling and enzyme-catalyzed Au staining. In brief, the primary antibody (Ab₁), bovine serum albumin, an antigen and then a bionanocomposite that contains a second antibody (Ab₂), poly(3-anilineboronic acid) (PABA), Au nanoparticles (AuNPs) and glucose oxidase (GOx) are modified on a glassy carbon electrode coated with multiwalled carbon nanotubes, yielding a corresponding sandwich-type immunoelectrode. In the presence of glucose, a chemical reduction of NaAuCl₄ by enzymatically generated H₂O₂ can precipitate a lot of gold on the Ab₂-PABA-AuNPs-GOx immobilized immunoelectrode. In situ anodic stripping voltammetry (ASV) detection of gold in 8 μL 1.0 M aqueous HBr-Br₂ is conducted for the antigen assay, and the ASV detection process takes approximately 6 min. This method is employed for the assay of human immunoglobulin G (IgG) and human carbohydrate antigen 125 (CA125), which demonstrates exceptional sensitivity, high selectivity and fewer required reagents/samples. The achieved limits of detection (S/N = 3) by the method are 0.25 fg mL⁻¹ for IgG (approximately equivalent to containing 1 IgG molecule in the 1 microlitre of the analytical solution) and 0.1 nU mL⁻¹ for CA125, which outperforms many previously reported results. Full article

(This article belongs to the Special Issue Materials and Techniques for Bioanalysis and Biosensing—2nd Edition)

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19 pages, 5197 KB

Open AccessArticle

Nanoliter-Fabricated Paper-Based Colorimetric Lateral Flow Strip for Urea Detection

by Supatinee Kongkaew, Suparat Cotchim and Warakorn Limbut

Biosensors 2025, 15(10), 688; https://doi.org/10.3390/bios15100688 - 11 Oct 2025

Abstract

A nanoliter-scale fabrication method was applied to construct a colorimetric lateral flow strip for urea detection (Urea-CLFS). The device involves two main papers: a nitrocellulose membrane (NC-Mb) for urease enzyme immobilization and chromatography paper (CH-PP) containing a phenol red indicator. Urea-CLFS is a [...] Read more.

A nanoliter-scale fabrication method was applied to construct a colorimetric lateral flow strip for urea detection (Urea-CLFS). The device involves two main papers: a nitrocellulose membrane (NC-Mb) for urease enzyme immobilization and chromatography paper (CH-PP) containing a phenol red indicator. Urea-CLFS is a tool for detecting urea that is based on enzyme catalysis and the change in color of phenol red when urea is present. The Urea-CLFS fabrication was made possible by the minimal amount of nanoliters used in reagent consumption. The use of small arrays of phenol red dots provides a higher response result compared to single dots applied on CH-PP. To find the most effective design, it analyzed how urease was aligned on NC-Mb horizontally and vertically. According to our findings, the vertical alignment of the urease enzyme on NC-Mb leads to a prolonged reaction time, which leads to higher product production. The optimization process included optimizing various parameters, including the layer number of phenol red on CH-PP, phenol red concentration, urease concentration, reaction time, and sample volume. Under optimal conditions, the Urea-CLFS provided a linear range of 0.25–8.0 mmol L⁻¹ with an LOD of 0.34 mmol L⁻¹, which is sufficient for human health diagnostics. The accuracy of the Urea-CLFS was demonstrated by the recovery of the human urine sample between 95 ± 3% and 103 ± 3% (n = 3). Full article

(This article belongs to the Special Issue Paper-Based Biosensing Technologies: From Design to Application)

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19 pages, 2480 KB

Open AccessArticle

Matrix Optical Biosensor for Determining YKL-40/CHI3L1—A Biomarker Potentially Associated with Alzheimer’s Disease

by Zuzanna Zielinska, Abdulelah Ba Tarfi and Ewa Gorodkiewicz

Biosensors 2025, 15(10), 687; https://doi.org/10.3390/bios15100687 - 10 Oct 2025

Abstract

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon [...] Read more.

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon Resonance imaging (SPRi) detection, sensitive to YKL-40, was constructed for the detection of this analyte in the blood plasma of AD patients. Extensive validation of the biosensor was performed. This included the determination of analytical parameters such as the biosensor’s response characteristics, detection and quantification limits, precision, accuracy, repeatability, selectivity, stability, and performance in natural samples. Validation parameters were primarily tested using standard solutions, while natural samples were employed to evaluate repeatability, stability, and assay accuracy in three groups of samples from different patients. A YKL-40-specific antibody was used as the receptor layer, immobilized on a gold plate using the EDC/NHS protocol on thiol 11-MUA. The biosensor exhibited a wide operating range (1–200 ng/mL), a low detection limit (LOD) of 2 pg/mL, and a quantification limit (LOQ) of 7 pg/mL. High precision and accuracy were confirmed by the calculated standard deviations (SD) and coefficients of variation (CV), which ranged from 0.0009 to 7.02 ng/mL and from 0.12% to 9.24%, respectively. The sensor also demonstrated good repeatability (CV = 4.995%) and was capable of detecting the analyte of interest in complex biological matrices. Its applicability was confirmed in a study using plasma from AD patients and two selected control groups: plasma from smokers and patients with prostatitis. This allowed the assessment of YKL-40 levels across different groups. The results were consistent with literature values, and statistical analysis confirmed the significance of concentration differences between groups. Furthermore, ROC curve analysis confirmed the diagnostic usefulness of the constructed YKL-40 test in the context of Alzheimer’s disease. Full article

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

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13 pages, 1932 KB

Open AccessArticle

Universal Platform Based on Carbon Nanotubes Functionalised with Carboxylic Acid Groups for Multi-Analyte Enzymatic Biosensing

by Edmundas Lukoševičius, Julija Kravčenko, Grėta Mikėnaitė, Augustas Markevičius and Gintautas Bagdžiūnas

Biosensors 2025, 15(10), 686; https://doi.org/10.3390/bios15100686 - 10 Oct 2025

Abstract

This work presents the development of carbon nanotubes functionalised with carboxylic acid groups (CNT-COOH) as an oxygen-sensitive electrochemical platform for parallel multi-analyte enzymatic biosensing. The platform was constructed by depositing carboxylic-acid-functionalised single-walled carbon nanotubes covalently onto nanostructured gold electrodes modified with a self-assembled [...] Read more.

This work presents the development of carbon nanotubes functionalised with carboxylic acid groups (CNT-COOH) as an oxygen-sensitive electrochemical platform for parallel multi-analyte enzymatic biosensing. The platform was constructed by depositing carboxylic-acid-functionalised single-walled carbon nanotubes covalently onto nanostructured gold electrodes modified with a self-assembled monolayer of 4-aminothiophenol. Atomic force microscopy characterization revealed that the nanotubes attached via their ends to the surface and had a predominantly horizontal orientation. Glucose oxidase, lactate oxidase, glutamate oxidase, and tyrosinase were immobilised onto the electrodes to create selective biosensor for lactate, glucose, glutamate, and dopamine, respectively. A key finding is that incorporating catalase significantly extends the linear detection range for analytes by mitigating the accumulation of hydrogen peroxide. The resulting multifunctional biosensor demonstrated its capability for the simultaneous and independent measurement of glucose, lactate as the key bioanalytes under uniform conditions in blood plasma samples, highlighting its potential for applications in health and food technologies. Full article

(This article belongs to the Topic Applications of Nanomaterials in Biosensing: Current Trends and Future Prospects)

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15 pages, 2897 KB

Open AccessArticle

A Molecularly Imprinted Membrane for High-Density Lipoprotein Extraction in Point-of-Care Testing

by Gian Luca de Gregorio, Denis Prim, Alberto Zavattoni, Italo Mottini, Daniele Pezzoli, Federico Roveda, Marc E. Pfeifer and Jean-Manuel Segura

Biosensors 2025, 15(10), 685; https://doi.org/10.3390/bios15100685 - 10 Oct 2025

Abstract

Cholesterol blood levels in low-density lipoproteins (LDLs) are a key parameter for assessing the risk of cardiovascular diseases. Direct quantification of LDL cholesterol at the point of care would be possible if all other lipoproteins, particularly the high-density lipoproteins (HDLs), could be removed [...] Read more.

Cholesterol blood levels in low-density lipoproteins (LDLs) are a key parameter for assessing the risk of cardiovascular diseases. Direct quantification of LDL cholesterol at the point of care would be possible if all other lipoproteins, particularly the high-density lipoproteins (HDLs), could be removed prior to measurement. Here, we investigated whether a molecularly imprinted membrane (MIM) could be used for the solid-phase affinity extraction (SPAE) of HDL in a paper-based lateral flow test. Samples traveled by capillarity through the MIM before reaching a detection zone where LDL cholesterol was quantified enzymatically. MIMs were produced by impregnation of the membrane with a dispersion of molecularly imprinted polymers (MIPs) selective for HDL. MIPs were synthesized using precipitation polymerization and exhibited good selectivity for HDL compared with LDL and an uptake capacity of 5.0–7.0 µg of HDL-C/mg of MIP. The MIM enabled the removal of HDL with an efficiency of typically 68%. However, quantification of LDL cholesterol suffered from strong non-specific binding of LDL, likely due to its inherent colloidal instability. Overall, our results highlight the challenges associated with SPAE of colloidal particles. Furthermore, our study demonstrates a novel, efficient, and potentially generic modality to integrate SPAE into paper-based POC diagnostic tests. Full article

(This article belongs to the Special Issue Biosensing and Diagnosis—2nd Edition)

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56 pages, 7355 KB

Open AccessReview

Carbon Nanomaterial-Based Electrochemical Biosensors for Alzheimer’s Disease Biomarkers: Progress, Challenges, and Future Perspectives

by Berfin Şak, Helena B. A. Sousa and João A. V. Prior

Biosensors 2025, 15(10), 684; https://doi.org/10.3390/bios15100684 - 9 Oct 2025

Abstract

Alzheimer’s disease (AD) requires early and accurate identification of affected brain regions, which can be achieved through the detection of specific biomarkers to enable timely intervention. Carbon nanomaterials (CNMs), including graphene derivatives, carbon nanotubes, graphitic carbon nitride, carbon black, fullerenes, and carbon dots, [...] Read more.

Alzheimer’s disease (AD) requires early and accurate identification of affected brain regions, which can be achieved through the detection of specific biomarkers to enable timely intervention. Carbon nanomaterials (CNMs), including graphene derivatives, carbon nanotubes, graphitic carbon nitride, carbon black, fullerenes, and carbon dots, offer high conductivity, large electroactive surface area, and versatile surface chemistry that enhance biosensor performance. While such properties benefit a wide range of transduction principles (e.g., electrochemical, optical, and plasmonic), this review focuses on their role in electrochemical biosensors. This review summarizes CNM-based electrochemical platforms reported from 2020 to mid-2025, employing aptamers, antibodies, and molecularly imprinted polymers for AD biomarker detection. Covered topics include fabrication strategies, transduction formats, analytical performance in complex matrices, and validation. Reported devices achieve limits of detection from the femtomolar to picogram per milliliter range, with linear ranges typically spanning 2–3 orders of magnitude (e.g., from femtomolar to picomolar, or from picogram to nanogram per milliliter levels). They exhibit high selectivity against common interferents such as BSA, glucose, uric acid, ascorbic acid, dopamine, and non-target peptides, along with growing capabilities for multiplexing and portable operation. Remaining challenges include complex fabrication, limited long-term stability and reproducibility data, scarce clinical cohort testing, and sustainability issues. Opportunities for scalable production and integration into point-of-care workflows are outlined. Full article

(This article belongs to the Special Issue Nano/Micro Biosensors for Biomedical Applications (2nd Edition))

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26 pages, 3265 KB

Open AccessReview

Kinetics and Activation Strategies in Toehold-Mediated and Toehold-Free DNA Strand Displacement

by Yuqin Wu, Mingguang Jin, Cuizheng Peng, Guan Alex Wang and Feng Li

Biosensors 2025, 15(10), 683; https://doi.org/10.3390/bios15100683 - 9 Oct 2025

Abstract

Nucleic acid strand displacement reactions (SDRs) are fundamental building blocks of dynamic DNA nanotechnology. A detailed understanding of their kinetics is crucial for designing efficient sequences and regulating reaction networks with applications in biosensing, synthetic biology, biocomputing, and medical diagnostics. Since the development [...] Read more.

Nucleic acid strand displacement reactions (SDRs) are fundamental building blocks of dynamic DNA nanotechnology. A detailed understanding of their kinetics is crucial for designing efficient sequences and regulating reaction networks with applications in biosensing, synthetic biology, biocomputing, and medical diagnostics. Since the development of toehold-mediated strand displacement, researchers have devised many strategies to adjust reaction kinetics. These efforts have expanded the available tools in DNA nanotechnology. This review summarizes the basic principles and recent advances in activation strategies, emphasizing the role of strand proximity as a central driving force. Proximity-based approaches include toehold docking, associative toeholds, remote toeholds, and allosteric designs, as well as strategies that operate without explicit toehold motifs. These methods enable flexible and scalable construction of DNA reaction networks. We further discuss how combining different activation and kinetic control approaches gives rise to dynamic networks with complex and dissipative behaviors, providing new directions for DNA-based nanotechnology. Full article

(This article belongs to the Special Issue Aptamer-Based Biosensors for Point-of-Care Diagnostics)

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38 pages, 2958 KB

Open AccessReview

Multiplexed Optical Nanobiosensing Technologies for Disease Biomarker Detection

by Pureum Kim, Min Yu Choi, Yubeen Lee, Ki-Bum Lee and Jin-Ha Choi

Biosensors 2025, 15(10), 682; https://doi.org/10.3390/bios15100682 - 9 Oct 2025

Abstract

Most biomarkers exhibit abnormal expression in more than one disease, making conventional single-biomarker detection strategies prone to false-negative results. Detecting multiple biomarkers associated with a single disease can therefore substantially improve diagnostic accuracy. Accordingly, recent research has focused on precise multiplex detection, leading [...] Read more.

Most biomarkers exhibit abnormal expression in more than one disease, making conventional single-biomarker detection strategies prone to false-negative results. Detecting multiple biomarkers associated with a single disease can therefore substantially improve diagnostic accuracy. Accordingly, recent research has focused on precise multiplex detection, leading to the development of sensors employing various readout methods, including electrochemical, fluorescence, Raman, and colorimetric approaches. This review focuses on optical sensing applications, such as fluorescence, Raman spectroscopy, and colorimetry, which offer rapid and straightforward detection and are well suited for point-of-care testing (POCT). These optical sensors exploit nanoscale phenomena derived from the intrinsic properties of nanomaterials, including metal-enhanced fluorescence (MEF), Förster resonance energy transfer (FRET), and surface-enhanced Raman scattering (SERS), which can be tailored through modifications in material type and structure. We summarize the types and properties of commonly used nanomaterials, including plasmonic and carbon-based nanoparticles, and provide a comprehensive overview of recent advances in multiplex biomarker detection. Furthermore, we address the potential of these nanosensors for clinical translation and POCT applications, highlighting their relevance for next-generation disease diagnostic platforms. Full article

(This article belongs to the Special Issue Nanomaterial-Based Biosensors for Point-of-Care Testing)

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12 pages, 1745 KB

Open AccessArticle

Construction and Characterization of a Novel Direct Electron Transfer Type Enzymatic Sensor Using Spermidine Dehydrogenase

by Sheng Tong, Yuki Yaegashi, Mao Fukushi, Takumi Yanase, Junko Okuda-Shimazaki, Ryutaro Asano, Kazunori Ikebukuro, Madoka Nagata, Koji Sode and Wakako Tsugawa

Biosensors 2025, 15(10), 681; https://doi.org/10.3390/bios15100681 - 9 Oct 2025

Abstract

This study reports on the direct electron transfer (DET) ability of the enzyme spermidine dehydrogenase (SpDH) and its use in a DET-type enzymatic sensor for detecting spermine. SpDH was found to exhibit internal electron transfer from its cofactor, flavin adenine dinucleotide (FAD), to [...] Read more.

This study reports on the direct electron transfer (DET) ability of the enzyme spermidine dehydrogenase (SpDH) and its use in a DET-type enzymatic sensor for detecting spermine. SpDH was found to exhibit internal electron transfer from its cofactor, flavin adenine dinucleotide (FAD), to heme b. This was confirmed by observing the heme b-derived reduction peak at 560 nm in the presence of spermine, the substrate. SpDH was immobilized on a gold electrode via a dithiobis (succinimidyl hexanoate) self-assembled monolayer. The cyclic voltammetry analysis of the SpDH-immobilized gold electrode revealed an increased oxidation current in the presence of 0.1 mM spermine with an onset potential of −0.14 V vs. Ag/AgCl in the absence of an additional external electron acceptor. This result confirmed that SpDH is capable of DET. Chronoamperometric analyses were conducted using an SpDH-immobilized gold electrode with spermine as the substrate under a 0 V oxidation potential vs. Ag/AgCl using an artificial saliva matrix containing 10 µM ascorbic acid and 100 µM uric acid. The sensor exhibited good linear correlation between the current increase and spermine concentration from 0.2 to 2.0 µM, with a limit of detection of 0.084 µM, which encompasses the physiologically relevant spermine concentration found in the saliva. Primary structure alignments and 3D structure predictions revealed that all SpDH homologs possess two conserved histidine residues in the same location on the surface as the heme b ligand of SpDH. This indicates their potential for DET-ability with an electrode. Full article

(This article belongs to the Special Issue New Trends in Electrochemical Biosensors for Healthcare and Environmental Monitoring)

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19 pages, 5194 KB

Open AccessArticle

Automatic Removal of Physiological Artifacts in OPM-MEG: A Framework of Channel Attention Mechanism Based on Magnetic Reference Signal

by Yong Li, Dawei Wang, Hao Lu, Yuyu Ma, Chunhui Wang, Binyi Su, Jianzhi Yang, Fuzhi Cao and Xiaolin Ning

Biosensors 2025, 15(10), 680; https://doi.org/10.3390/bios15100680 - 9 Oct 2025

Abstract

The high spatiotemporal resolution of optically pumped magnetometers (OPMs) makes them an essential tool for functional brain imaging, enabling accurate recordings of neuronal activity. However, physiological signals such as eye blinks and cardiac activity overlap with neural magnetic signals in the frequency domain, [...] Read more.

The high spatiotemporal resolution of optically pumped magnetometers (OPMs) makes them an essential tool for functional brain imaging, enabling accurate recordings of neuronal activity. However, physiological signals such as eye blinks and cardiac activity overlap with neural magnetic signals in the frequency domain, resulting in contamination and creating challenges for the observation of brain activity and the study of neurological disorders. To address this problem, an automatic physiological artifact removal method based on OPM magnetic reference signals and a channel attention mechanism is proposed. The randomized dependence coefficient (RDC) is employed to evaluate the correlation between independent components and reference signals, enabling reliable recognition of artifact components and the construction of training and testing datasets. A channel attention mechanism is subsequently introduced, which fuses features from global average pooling (GAP) and global max pooling (GMP) layers through convolution to establish a data-driven automatic recognition model. The backbone network is further optimized to enhance performance. Experimental results demonstrate a strong correlation between the magnetic reference signals and artifact components, confirming the reliability of magnetic signals as artifact references for OPM-MEG. The proposed model achieves an artifact recognition accuracy of 98.52% and a macro-average score of 98.15%. After artifact removal, both the event-related field (ERF) responses and the signal-to-noise ratio (SNR) are significantly improved. Leveraging the flexible and modular characteristics of OPM-MEG, this study introduces an artifact recognition framework that integrates magnetic reference signals with an attention mechanism. This approach enables highly accurate automatic recognition and removal of OPM-MEG artifacts, paving the way for real-time, automated data analysis in both scientific research and clinical applications. Full article

(This article belongs to the Section Wearable Biosensors)

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