Biosensors

24 pages, 2360 KB

Open AccessSystematic Review

Biosensor-Integrated Virtual Reality for Cognitive Behavioral Therapy in Psychosis: A Systematic Review of a New Therapeutic Frontier

by Aristomenis G. Alevizopoulos, Georgios G. Anastasiou, Iakovos Kritikos, Maria Alevizopoulou and Georgios A. Alevizopoulos

Biosensors 2026, 16(5), 265; https://doi.org/10.3390/bios16050265 - 3 May 2026

Abstract

Psychosis presents significant treatment challenges, and standard Cognitive Behavioral Therapy for psychosis often faces limitations due to patient engagement issues and reliance on subjective self-reporting. The integration of Virtual Reality (VR), physiological biosensors, and artificial intelligence offers a transformative opportunity to address these [...] Read more.

Psychosis presents significant treatment challenges, and standard Cognitive Behavioral Therapy for psychosis often faces limitations due to patient engagement issues and reliance on subjective self-reporting. The integration of Virtual Reality (VR), physiological biosensors, and artificial intelligence offers a transformative opportunity to address these challenges. A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. A thorough literature search was performed across seven databases. Twelve randomized controlled trials involving 1504 participants were included to assess VR-assisted CBT, VR treatment, and AVATAR therapy. Meta-analyses showed that VR interventions significantly decreased auditory verbal hallucinations (pooled SMD = −0.24, p = 0.0011) and paranoid thoughts (SMD = −0.26, p < 0.0001) compared to control conditions. This review supports integrating multi-modal biosensors to collect real-time, objective physiological data. Such integration enables the development of AI-driven, closed-loop systems that dynamically adjust the virtual environment based on the patient’s physiological state. VR-assisted therapies effectively reduce positive symptoms of psychosis. Incorporating biosensors is a crucial step toward a data-driven approach for personalized, closed-loop psychiatric care. Future efforts should focus on large-scale clinical trials, biomarker validation, and robust ethical frameworks to ensure safe and effective implementation. Full article

(This article belongs to the Section Biosensors and Healthcare)

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15 pages, 3414 KB

Open AccessArticle

Longitudinal Monitoring of Metabolic Gradients in Microreactor Culture Platforms by Raman Spectroscopy

by Maitane Márquez, Javier Plou, Stefan Merkens, Eneko Lopez, Carla Solé, Esther Arnaiz, Mariana Medina-Sánchez, Charles H. Lawrie and Andreas Seifert

Biosensors 2026, 16(5), 266; https://doi.org/10.3390/bios16050266 - 2 May 2026

Abstract

Metabolic heterogeneity within the cell microenvironment is a key driver of cancer progression and resistance to therapy. However, current approaches lack the spatial and temporal resolution required to capture its dynamics in living systems. While recent advances in 3D cell culture models and [...] Read more.

Metabolic heterogeneity within the cell microenvironment is a key driver of cancer progression and resistance to therapy. However, current approaches lack the spatial and temporal resolution required to capture its dynamics in living systems. While recent advances in 3D cell culture models and metabolomic profiling have improved our understanding of the tumor niche, their integration with real-time optical sensing remains underdeveloped. Here, we present an integrated platform combining a 3D-printed microreactor culture chamber with Raman spectroscopy to enable non-invasive, spatially resolved metabolic monitoring of living cell cultures. Our microreactor platform generates controlled oxygen and nutrient cues while simultaneously acquiring label-free Raman spectra, revealing extracellular metabolic fingerprints linked to cell catabolism (e.g., glucose and lactate shifts) and acidification. Analysis across four cell lines uncovered temporal evolution as the dominant source of metabolic variance, while spatial heterogeneity along oxygen gradients is a secondary factor. In particular, diffusion-limited regions exhibited localized acidification and accumulation of stress biomarkers—such as the release of nucleotides—features that cannot be detected using conventional bulk assays. By providing a versatile platform for real-time mapping, this work enables the mechanistic dissection of cell adaptation to microenvironmental stress and supports the prediction of metabolic signatures underlying drug response and treatment outcomes. Full article

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

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17 pages, 1867 KB

Open AccessArticle

Synergistic PdMoCu Trimetallic Metallene-Enhanced Electrochemiluminescence Biosensor for Ultrasensitive Detection of Microcystin-LR

by Xiaochen Yang, Linsheng Wang, Jing Tu, Yanlei Li, Lun Yang and Zhongfeng Gao

Biosensors 2026, 16(5), 264; https://doi.org/10.3390/bios16050264 - 2 May 2026

Abstract

The development of highly sensitive and reliable strategies for microcystin-LR (MC-LR) monitoring remains critical for environmental safety and public health protection. Herein, we report a metallene-enabled electrochemiluminescence (ECL) biosensing platform based on ultrathin PdMoCu trimetallic metallenes for femtogram-level MC-LR detection. The two-dimensional PdMoCu [...] Read more.

The development of highly sensitive and reliable strategies for microcystin-LR (MC-LR) monitoring remains critical for environmental safety and public health protection. Herein, we report a metallene-enabled electrochemiluminescence (ECL) biosensing platform based on ultrathin PdMoCu trimetallic metallenes for femtogram-level MC-LR detection. The two-dimensional PdMoCu metallenes provide abundant active sites and accelerated interfacial charge-transfer kinetics through synergistic electronic modulation among Pd, Mo, and Cu atoms, significantly enhancing the Ru(bpy)₃²⁺/TPrA ECL efficiency. By integrating a programmable H1–aptamer duplex interface, electrostatic enrichment of Ru(bpy)₃²⁺ was achieved, enabling target-responsive luminophore release via aptamer-triggered structural switching. This cooperative amplification mechanism, combining catalytic acceleration and DNA-mediated signal modulation, results in a sensitive signal-off detection mode. Under optimized conditions, the biosensor exhibited a wide linear response from 0.1 pg mL⁻¹ to 50 ng mL⁻¹ with a detection limit as low as 37 fg mL⁻¹. The platform demonstrated excellent selectivity against structural analogues, high reproducibility, and satisfactory recovery (99.3–102.0%) in real tap water samples. This work not only highlights the catalytic potential of trimetallic metallenes in ECL systems but also establishes a generalizable interfacial engineering strategy for ultrasensitive detection of trace environmental contaminants. Full article

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

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17 pages, 2887 KB

Open AccessArticle

Wearable Dual-Mode Biosensing System for Dynamic Light Dosimetry in Tissues

by Jun Wei, Lansixu Ma, Wenxuan Li, Peng Xu, Yizhen Wang, Feifan Zhou and Fuhong Cai

Biosensors 2026, 16(5), 263; https://doi.org/10.3390/bios16050263 - 2 May 2026

Abstract

Phototherapy is a physical treatment modality that utilizes natural or artificial light sources and harnesses radiant energy to treat diseases. Dynamic monitoring of the actual light dose received by tissues is crucial to the success of phototherapy. However, most current phototherapy devices feature [...] Read more.

Phototherapy is a physical treatment modality that utilizes natural or artificial light sources and harnesses radiant energy to treat diseases. Dynamic monitoring of the actual light dose received by tissues is crucial to the success of phototherapy. However, most current phototherapy devices feature bulky and complex hardware and depend on fixed parameters or surface measurements for dose estimation, failing to provide precise, real-time monitoring of light dose distribution that is tailored to individual users, specific treatment sessions, and different body regions. Furthermore, most of these devices are incapable of generating tunable and stable LED light. This study presents a preliminary diffusion equation-based proof-of-concept for a wearable, integrated dual-mode sensing system for real-time dynamic monitoring of tissue light dose and temperature change. The system, controlled by a single-chip microcontroller, rapidly extracts key tissue optical parameters via a custom multi-wavelength LED optical probe and provides real-time feedback on light dose distribution through a dynamic tissue optical simulation model. To expand the monitoring dimensions, the system innovatively integrates a thermal sensor. This sensor enables synchronous monitoring of the temperature field in the treatment area, thereby allowing for an estimation of the combined photothermal effect. The system features a compact design, user-friendly operation, fast and stable communication, and repeatable and reliable detection. With promising clinical application prospects, it holds the potential to evolve into a portable, home-use, safe, effective, wearable, and cost-effective phototherapy device. Full article

(This article belongs to the Special Issue Portable, Wearable and Wireless Biosensing Technologies)

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25 pages, 10374 KB

Open AccessArticle

Multi-Feature Adaptive Variational Mode Decomposition for Wearable ECG Devices

by Zixin Chen, Di Wu, Yuanlin Nie, Junwei Zhang, Guanzhou Liu, Feng He, Long Mo, Liming Peng, Chang Zeng and Zhengchun Liu

Biosensors 2026, 16(5), 262; https://doi.org/10.3390/bios16050262 - 1 May 2026

Abstract

To address the issue of motion artifact interference faced by wearable ECG monitoring devices in dynamic environments, this paper proposes an adaptive motion artifact removal framework based on improved Variational Mode Decomposition (VMD). By designing a parameter self-adjustment mechanism and a multi-feature fusion [...] Read more.

To address the issue of motion artifact interference faced by wearable ECG monitoring devices in dynamic environments, this paper proposes an adaptive motion artifact removal framework based on improved Variational Mode Decomposition (VMD). By designing a parameter self-adjustment mechanism and a multi-feature fusion mode selection strategy, the algorithm’s adaptability to non-stationary ECG signals and noise separation accuracy are enhanced. Experiments on the MIT-BIH Arrhythmia Database demonstrate that the improved VMD algorithm outperforms traditional wavelet transform, Recursive Least Squares (RLS), and conventional VMD methods in multiple performance metrics. Specifically, the signal-to-noise ratio (SNR) is improved by 5.17 dB, the Percentage Root Mean Squared Difference (PRD) is reduced to 49.13%, the correlation coefficient is increased to 0.88, and high real-time processing capability (Real-Time Processing Ratio, RTR = 22.5) is maintained, meeting the low-latency requirements of wearable devices. Moreover, case studies on pathological recordings (e.g., Wolff–Parkinson–White syndrome and third-degree atrioventricular block) reveal that the improved VMD better preserves clinically significant features such as delta waves and dissociated P waves. Furthermore, a downstream arrhythmia classification task using a CWT-CNN classifier achieves 91.67% accuracy on denoised heartbeats, which is 2.67 percentage points higher than that on raw noisy signals (89.00%), confirming the practical benefit of the proposed preprocessing for AI-based diagnosis. This study provides an effective processing solution for improving the signal quality of wearable ECG monitoring. Full article

(This article belongs to the Special Issue Wearable Biosensors and Health Monitoring)

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18 pages, 21989 KB

Open AccessArticle

Imaging Study of MnO₂-Based Nanomotors Modulating HIF-1α/Lipid Droplet Biogenesis and Activating the cGAS-STING Pathway

by Ziyi Li, Yingxin Tian, Gefei Ren and Yingshu Guo

Biosensors 2026, 16(5), 261; https://doi.org/10.3390/bios16050261 - 1 May 2026

Abstract

The overexpression of hypoxia-inducible factor-1α (HIF-1α) suppresses STING signaling and modulates lipid metabolism in tumor cells, leading to abnormal lipid droplet (LD) accumulation. Herein, we constructed a manganese dioxide (MnO₂)-based nanomotor (HMIP@A). HMIP@A depletes intracellular hydrogen peroxide (H₂O₂ [...] Read more.

The overexpression of hypoxia-inducible factor-1α (HIF-1α) suppresses STING signaling and modulates lipid metabolism in tumor cells, leading to abnormal lipid droplet (LD) accumulation. Herein, we constructed a manganese dioxide (MnO₂)-based nanomotor (HMIP@A). HMIP@A depletes intracellular hydrogen peroxide (H₂O₂) and glutathione (GSH) to generate oxygen (O₂), reactive oxygen species (ROS), and manganese (Mn²⁺). A dual strategy of “oxygen supplementation” and “small-molecule inhibition” synergistically downregulates HIF-1α, thereby suppressing LD biogenesis. This process sensitizes tumor cells to ROS, leading to severe DNA damage. Released Mn²⁺ and damaged DNA synergistically activate the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. In vitro, HMIP@A markedly increases ROS production, lipid peroxidation (LPO), and DNA damage, thereby inducing tumor cell death, immunogenic cell death (ICD), and dendritic cell (DC) maturation. Furthermore, HMIP@A exhibits excellent penetration in tumor spheroids. Overall, this study provides a theoretical basis for the design of nanomedicines through a strategy integrating metabolic intervention, oxidative damage sensitization, and immune activation. Full article

(This article belongs to the Special Issue Biosensing Technologies in Medical Diagnosis—2nd Edition)

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17 pages, 5747 KB

Open AccessArticle

A Flexible Triboelectric-Based Sensor for Seismocardiography Monitoring

by Changke Wang, Yingjie He, Haojie Peng, Haijun Luo and Xue Wang

Biosensors 2026, 16(5), 260; https://doi.org/10.3390/bios16050260 - 1 May 2026

Abstract

Seismocardiography (SCG) is a promising noninvasive modality for cardiovascular monitoring. By capturing subtle chest wall vibrations induced by the mechanical pumping activity of the heart at the body surface, SCG is of considerable value for blood pressure-related cardiovascular risk assessment and cardiac function [...] Read more.

Seismocardiography (SCG) is a promising noninvasive modality for cardiovascular monitoring. By capturing subtle chest wall vibrations induced by the mechanical pumping activity of the heart at the body surface, SCG is of considerable value for blood pressure-related cardiovascular risk assessment and cardiac function monitoring. However, continuous SCG monitoring in daily life settings still relies predominantly on rigid accelerometers, and reports on flexible acquisition systems remain scarce. This is mainly because SCG signals are characterized by low frequency, low amplitude, and high sensitivity to the sensor-skin interface, requiring the sensor to achieve stable, high-fidelity acquisition of weak chest wall mechanical vibrations while maintaining conformal contact and wearing comfort. To address this challenge, this study proposes a flexible pressure sensor based on the triboelectric effect. The sensor adopts a single-electrode contact-separation structure and is composed of a polymer material capable of achieving a high negative charge density and a nickel foil electrode. The sensor exhibits a sensitivity of 3.76 V/N within a small force range of 0–200 mN, shows good frequency response over the 0.5–25 Hz band, and maintains stable output after approximately 5300 cycles. The sensor was attached to the lower-middle segment of the sternum to capture weak vibration signals generated by cardiac mechanical activity and transmitted through the chest wall, thereby enabling continuous SCG monitoring. This study presents a feasible approach for flexible SCG acquisition in daily life scenarios and provides experimental evidence supporting the application of flexible sensors in home-based health monitoring. Full article

(This article belongs to the Section Biosensors and Healthcare)

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18 pages, 815 KB

Open AccessArticle

GA-SVR Optimized Surface-Enhanced Raman Spectroscopy for Rapid Detection of Ciprofloxacin Residues in Chicken Blood

by Gaoliang Zhang, Zihan Ma, Chao Yang, Yang Liu, Tianyan You and Jinhui Zhao

Biosensors 2026, 16(5), 259; https://doi.org/10.3390/bios16050259 - 1 May 2026

Abstract

Ciprofloxacin residues in chicken blood pose a potential food safety risk; however, rapid detection methods for complex chicken blood matrices are lacking. This study aimed to establish a surface-enhanced Raman spectroscopy (SERS) method for the rapid detection of ciprofloxacin in chicken blood using [...] Read more.

Ciprofloxacin residues in chicken blood pose a potential food safety risk; however, rapid detection methods for complex chicken blood matrices are lacking. This study aimed to establish a surface-enhanced Raman spectroscopy (SERS) method for the rapid detection of ciprofloxacin in chicken blood using gold colloid as the SERS substrate. Gold colloid was synthesized via the Frens method with slight modification, and key SERS detection conditions were systematically optimized to maximize SERS intensities at 1265 cm⁻¹, including the amount of trisodium citrate solution, the electrolyte type, the amount of gold colloid, the amount of NaCl solution, and the adsorption time. Raw SERS spectra were pretreated with adaptive iteratively reweighted penalized least squares (air-PLS) combined with Savitzky–Golay (SG) smoothing. A genetic algorithm (GA) was used to extract characteristic Raman shifts, and a GA-SVR prediction model with radial basis function (RBF) as the kernel was constructed, with its performance compared with multivariate linear regression (MLR) and partial least squares regression (PLSR) models. The GA-SVR model exhibited the best performance, with a coefficient of determination for the calibration set (

R_{c}^{2}

) value of 0.9893 and for the prediction set (

R_{p}^{2}

) value of 0.9874. The root mean square error of calibration (RMSEC) and prediction (RMSEP) were 1.2953 and 1.8617, respectively, outperforming the MLR and PLSR models. These results demonstrate that the SERS method combined with GA-SVR enables rapid quantitative detection of ciprofloxacin residues in chicken blood, providing a technical reference for monitoring veterinary drug residues in livestock and poultry products. Full article

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

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24 pages, 2535 KB

Open AccessArticle

A Two-Stage EEG Microstate Fusion Framework for Dementia Screening and Alzheimer’s Disease/Frontotemporal Dementia Differentiation

by Lei Jiang, Yingna Chen, Yan He, Jiarui Liang, Xuan Zhao and Xiuyan Guo

Biosensors 2026, 16(5), 258; https://doi.org/10.3390/bios16050258 - 1 May 2026

Abstract

Differentiating Alzheimer’s disease (AD) from frontotemporal dementia (FTD) using resting-state electroencephalography (EEG) remains clinically challenging because of their overlapping electrophysiological characteristics. Although EEG suits large-scale dementia screening, current method often overestimates performance because of epoch-level data leakage and multiclass feature competition in unified [...] Read more.

Differentiating Alzheimer’s disease (AD) from frontotemporal dementia (FTD) using resting-state electroencephalography (EEG) remains clinically challenging because of their overlapping electrophysiological characteristics. Although EEG suits large-scale dementia screening, current method often overestimates performance because of epoch-level data leakage and multiclass feature competition in unified models. We propose a task-decoupled, two-stage hierarchical deep learning framework utilizing multiband EEG microstate dynamics. Continuous microstate sequences, modeled via Hungarian matching to preserve fine-grained temporal information, are processed using a normalizer-free 1D convolutional neural network (1D-CNN-NFNet) integrated with multi-head attention. By decoupling the workflow, Stage 1 performs generalized dementia screening using alpha and delta microstates, achieving an area under the curve (AUC) of 0.851. Stage 2 disentangles AD from FTD using delta and theta dynamics, yielding an AD-locking specificity of 86.1%. Evaluated under a strict subject-level leave-one-subject-out (LOSO) cross-validation protocol, the two-stage framework achieved 63.9% balanced accuracy, outperforming the single-stage baseline (55.4%) with a negligible inference latency of 0.733 ms. Furthermore, attention-based interpretability analysis links frequency-specific microstate alterations to underlying cortical disconnection syndromes. These results demonstrate that the framework provides a reproducible and interpretable auxiliary reference for dementia screening and subtyping in clinical neurology. Full article

(This article belongs to the Special Issue Applications of AI in Non-Invasive Biosensing Technologies)

31 pages, 29254 KB

Open AccessReview

Advanced Strategies and Mechanisms of Nanomaterial–Molecularly Imprinted Polymer Synergistically Functionalized Biosensors for Biomarker Detection

by Yaru Zhang, Tao Zhao, Chaoyun Li and Yong Huang

Biosensors 2026, 16(5), 257; https://doi.org/10.3390/bios16050257 - 1 May 2026

Abstract

Biomarker detection demands low cost, rapid turnaround, interference resistance, and wide dynamic range. However, traditional immunoassays and nucleic acid amplification methods remain constrained by complex matrices, batch stability, and portability limitations. Molecularly imprinted polymers (MIPs) exhibit “artificial antibody”-like specific recognition and high stability, [...] Read more.

Biomarker detection demands low cost, rapid turnaround, interference resistance, and wide dynamic range. However, traditional immunoassays and nucleic acid amplification methods remain constrained by complex matrices, batch stability, and portability limitations. Molecularly imprinted polymers (MIPs) exhibit “artificial antibody”-like specific recognition and high stability, while nanomaterials (NMs), depending on their composition, structure, and interfacial organization, can provide conductive pathways, catalytic activity, high-density loading sites, or mass-transfer-favorable architectures. Electrochemical biosensors synergistically constructed from these two components achieve complementary functions in recognition, mass transfer, and signal transduction. This paper systematically reviews key strategies and mechanisms for NM–MIP synergistic construction, focusing on six synergistic strategies that target key bottlenecks in mass transfer, signal generation, and interfacial stability: dynamic response regulation, hierarchical structural engineering, anti-fouling interfaces, multi-signal cross-validation, catalytic–recognition integration, and interfacial binding regulation. Representative biomarker cases are analyzed to illustrate how functional modules can coordinate across sample processing, signal generation, and recognition confirmation to improve analytical reliability and overall sensing performance. Finally, the review discusses challenges in clinical translation, including consistent manufacturing, matrix interference, long-term stability, and standardized validation, while outlining future directions toward mechanism-guided imprint design, intelligent data-assisted optimization, and integration with microfluidic and wearable platforms for multiplexed biomarker detection. Full article

(This article belongs to the Section Biosensor Materials)

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15 pages, 1694 KB

Open AccessArticle

Assessment of Respiratory Rate and Simulated Apnea Utilizing the PneumoWave Biosensor: In Vitro and In Vivo Validation

by Burcu Kolukisa Birgec, Beyza Toprak and Alexander Balfour Mullen

Biosensors 2026, 16(5), 256; https://doi.org/10.3390/bios16050256 - 1 May 2026

Abstract

Accurate monitoring of respiratory rates is critical for early detection of a range of clinical conditions. However, standard manual counting or inadequate clinical monitoring often fails to provide reliable measurements. This study evaluated and validated the PneumoWave biosensor for respiratory rate measurement across [...] Read more.

Accurate monitoring of respiratory rates is critical for early detection of a range of clinical conditions. However, standard manual counting or inadequate clinical monitoring often fails to provide reliable measurements. This study evaluated and validated the PneumoWave biosensor for respiratory rate measurement across a broad physiological range and different body postures (45°, 90°, and 180°) in both in vitro and in vivo settings. In vitro validation was performed using a SimMan ALS manikin operated at respiratory settings of 6–30 breaths per minute, with 10 s periods of simulated apnea. In vivo validation involved 20 healthy volunteers performing metronome-guided breathing while wearing bilateral PneumoWave biosensors. In vitro results demonstrated an excellent correlation between biosensors and manikin respiratory settings and captured all apnea events (r = 0.99, ICC = 0.99). In vivo findings showed good agreement with direct observational count (r = 0.99, R² = 0.99, ICC = 0.99), with 97% of apnea events captured by both devices in all positions. Body postures had no significant impact on biosensor accuracy. These findings demonstrate that the PneumoWave biosensor provides accurate and reliable respiratory monitoring and supports its potential as a robust, non-invasive tool for continuous clinical and remote patient monitoring. Full article

(This article belongs to the Section Biosensors and Healthcare)

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17 pages, 1771 KB

Open AccessArticle

Ultrasensitive Dopamine Detection in Undiluted Serum with a Disposable Electrochemical Sensor Employing MOF-Derived Gold Nanocomposites

by Rohan Sagar, Hsiao-Wei Wen, Ching-Chou Wu and M. S. Gaur

Biosensors 2026, 16(5), 255; https://doi.org/10.3390/bios16050255 - 30 Apr 2026

Abstract

Dopamine (DA) is essential for motor control, motivation, and cognition, and its dysregulation is associated with neurological and psychiatric disorders such as Parkinson’s disease, schizophrenia, and addiction. Accurate and selective DA quantification in complex biological matrices is important, but remains challenging because of [...] Read more.

Dopamine (DA) is essential for motor control, motivation, and cognition, and its dysregulation is associated with neurological and psychiatric disorders such as Parkinson’s disease, schizophrenia, and addiction. Accurate and selective DA quantification in complex biological matrices is important, but remains challenging because of coexisting interferents and the low physiological concentration of DA. Here, we report a disposable electrochemical DA sensor based on screen-printed carbon electrodes (SPCEs) modified with metal–organic framework-derived gold nanocomposites (MOFD-AuNCs). The optimal material, synthesized with a 60 min NaBH₄ reduction step (MOFD-AuNC-60), exhibited superior electron-transfer kinetics compared with materials prepared at other reduction times. A single coating of MOFD-AuNC-60 on SPCEs enabled DA oxidation at a low potential (~0.05 V) with high selectivity in the presence of ascorbic acid and uric acid. In undiluted porcine serum, the sensor exhibited a dynamic range of 2.5–500 nM with a calculated detection limit of 0.5 nM. In undiluted human serum, it exhibited a dynamic range of 5–100 nM with a calculated detection limit of 4.4 nM. The MOFD-AuNC-60/SPCEs further demonstrated excellent reproducibility (relative standard deviation, 3%) and stability (7.5% current loss over 7 days). These results demonstrate that the proposed sensor provides a disposable, robust, and reliable sensing platform for direct DA detection in undiluted serum, showing promise for practical applications. Full article

(This article belongs to the Special Issue Multidimensional Nanomaterial-Based Biosensors for Environmental and Healthcare Monitoring)

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Graphical abstract

24 pages, 1056 KB

Open AccessReview

Cell-Based Biosensors in Oral Health: Emerging Tools for Rapid Detection and Monitoring of Oral Diseases

by Florinel Cosmin Bida, Ionut Luchian, Dana Gabriela Budala, Dragos Ioan Virvescu, Costin Iulian Lupu, Oana Maria Butnaru, Teona Tudorici, Florin Razvan Curca, Ovidiu Aungurencei and Andrei Georgescu

Biosensors 2026, 16(5), 254; https://doi.org/10.3390/bios16050254 - 30 Apr 2026

Abstract

Oral diseases remain highly prevalent worldwide and require early diagnosis and continuous monitoring to improve clinical outcomes. Conventional diagnostic methods are often invasive, time-consuming, and limited in their capacity for real-time assessment, which has driven the development of biosensor technologies for point-of-care applications. [...] Read more.

Oral diseases remain highly prevalent worldwide and require early diagnosis and continuous monitoring to improve clinical outcomes. Conventional diagnostic methods are often invasive, time-consuming, and limited in their capacity for real-time assessment, which has driven the development of biosensor technologies for point-of-care applications. Among these, cell-based biosensors utilize living cells as sensing elements capable of responding to inflammatory mediators, bacterial toxins, metabolic products, and tumor-associated biomarkers. This narrative review summarizes the principles, cell types, detection mechanisms, and applications of cell-based biosensors in oral health. The literature was identified through a structured search of PubMed, Scopus, Web of Science, and Google Scholar using keywords related to cell-based biosensors, oral diagnostics, salivary biomarkers, periodontal disease, oral cancer, and lab-on-chip technologies. Due to the heterogeneity of biosensor designs and detection methods, the selected studies were analyzed qualitatively. Cell-based biosensors have demonstrated applications in periodontal disease detection, cariogenic biofilm monitoring, oral cancer diagnostics, cytotoxicity testing of dental materials, and salivary biomarker analysis. The integration of microfluidic and lab-on-chip systems enables real-time and multiplex detection, supporting the development of chairside diagnostic platforms in dentistry. However, challenges related to standardization, reproducibility, and clinical validation remain and must be addressed to facilitate broader implementation in routine practice. Full article

(This article belongs to the Special Issue Cell-Based Biosensors for Rapid Detection and Monitoring (3rd Edition))

18 pages, 1868 KB

Open AccessArticle

Cell-Based Luciferase Assay for Testing SARS-CoV-2 3CL Protease Inhibitors

by Dmitry N. Shcherbakov, Ekaterina D. Mordvinova, Vadim O. Trufanov, Natalia V. Volkova, Yulia V. Meshkova, Maria K. Marenina, Anna V. Zaykovskaya, Ekaterina A. Volosnikova, Sophia S. Borisevich and Svetlana V. Belenkaya

Biosensors 2026, 16(5), 253; https://doi.org/10.3390/bios16050253 - 30 Apr 2026

Abstract

A cell-based screening system for viral protease inhibitors was developed using firefly luciferase fragment complementation and validated on the SARS-CoV-2 3CLpro model. The optimal luciferase variant incorporating the VLQSGF proteolytic site (Luc III) retained 88% of its native activity. A critical requirement for [...] Read more.

A cell-based screening system for viral protease inhibitors was developed using firefly luciferase fragment complementation and validated on the SARS-CoV-2 3CLpro model. The optimal luciferase variant incorporating the VLQSGF proteolytic site (Luc III) retained 88% of its native activity. A critical requirement for system performance was the use of an extended nsp4–nsp6 fragment of the viral polyprotein rather than the mature protease, underscoring the importance of the native context for 3CLpro activity. The bicistronic construct pCAG-Luc-III-IRES-nsp4-6 enables coordinated expression of the reporter and protease, thereby increasing assay reproducibility. IC₅₀ values obtained in this system for nirmatrelvir and GC376 correlated with live-virus assay data but differed significantly from those of a cell-free FRET assay, reflecting the impact of cellular barriers. This approach combines simplicity, a standard substrate, and high reproducibility, making it promising for high-throughput screening in basic laboratory settings and adaptable to other viral proteases. Full article

(This article belongs to the Special Issue Cell-Based Biosensors for Rapid Detection and Monitoring (3rd Edition))

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15 pages, 15395 KB

Open AccessArticle

Development of a Sandwich-Type sxtA4 Electrochemical Biosensor for Proactive Environmental Monitoring of STX-Producing Microalgae

by Hyunjun Park, Seohee Kim, Minyoung Ju, Yunseon Han, Yoseph Seo, Junhong Min, Hyeon-Yeol Cho and Taek Lee

Biosensors 2026, 16(5), 252; https://doi.org/10.3390/bios16050252 - 30 Apr 2026

Abstract

Saxitoxin (STX), produced by certain harmful algal bloom (HAB) species, bioaccumulates through the food chain and can cause paralytic toxicity in humans, potentially resulting in fatal outcomes. To date, STX detection has primarily been conducted under laboratory-controlled conditions, and the availability of a [...] Read more.

Saxitoxin (STX), produced by certain harmful algal bloom (HAB) species, bioaccumulates through the food chain and can cause paralytic toxicity in humans, potentially resulting in fatal outcomes. To date, STX detection has primarily been conducted under laboratory-controlled conditions, and the availability of a gold-standard method for the proactive monitoring and prevention of HAB-induced secondary damage remains limited. Therefore, the present study introduces an electrochemical-based biosensor that is capable of early monitoring of STX in HAB-occurred environments. The conserved region of sxtA4, a nucleic acid precursor that is essential for STX biosynthesis, is immobilized on the sensing membrane surface in a sandwich structure. In this process, target detection is recognized as an electrochemical signal by a methylene blue-labeled detection probe, and the reliability of biosensing is supplemented by an electrochemical trend that is opposite to DNA binding. The application of an alternating current electrochemical flow technique achieves more sensitive detection at attomolar levels and rapid measurement within 10 min than a conventional DNA biosensor based on hybridization. In addition, the designed biosensing structure selectively detects STX-synthesizing and non-synthesizing dinoflagellates significantly. The proposed platform can utilize the identification of STX-induced secondary damage of HAB and provide insight into a field-ready biosensor based on its characterization and detection performance. Full article

(This article belongs to the Special Issue Biosensor-Integrated Drug Delivery Systems)

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21 pages, 7717 KB

Open AccessArticle

Noninvasive Detection of Acute Hyperglycemia Using Signal from Wearable ECG Sensors Considering Individual HRV Response Delays to Glucose

by Jiho Ha, Ho Bin Hwang, Hayoung Kim, Seungyeon Lee, Jeyeon Lee, Jung Hwan Park, Jongshill Lee and In Young Kim

Biosensors 2026, 16(5), 251; https://doi.org/10.3390/bios16050251 - 29 Apr 2026

Abstract

Noninvasive blood glucose monitoring is crucial for detecting early dysglycemia, yet continuous glucose monitors remain invasive and costly. Electrocardiogram (ECG) and its derived heart rate variability (HRV) measure may offer a noninvasive indicator of autonomic and cardiac responses associated with acute changes in [...] Read more.

Noninvasive blood glucose monitoring is crucial for detecting early dysglycemia, yet continuous glucose monitors remain invasive and costly. Electrocardiogram (ECG) and its derived heart rate variability (HRV) measure may offer a noninvasive indicator of autonomic and cardiac responses associated with acute changes in glucose. In this study, 30 adults underwent a 75 g oral glucose tolerance test with concurrent ECG Holter and interstitial glucose monitoring. From these recordings, HRV and ECG features were extracted. A deep learning classifier with HRV and ECG was then trained to detect hyperglycemia (glucose ≥ 180 mg/dL). Cross-correlation analysis confirmed a significant association between HRV and glucose (Pearson r ~0.65, p < 0.05) when aligning each participant’s data according to individual response delays. The model achieved high classification performance under rigorous temporal validation (accuracy ~89%, area under the receiver operating characteristic curve ~0.89). Saliency analyses revealed that the classifier’s decisions focus on distinct ECG waveform transitions and key HRV features linked to glucose-induced autonomic changes. Overall, acute hyperglycemia elicited discernible changes in HRV and cardiac conduction, supporting the feasibility of this physiologically grounded approach for detecting the acute hyperglycemic phase under controlled conditions. This method holds promise for real-time implementation in wearable devices, enabling early diabetes risk screening. Full article

(This article belongs to the Special Issue Recent Advances in Glucose Biosensors—2nd Edition)

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38 pages, 2448 KB

Open AccessReview

Unobtrusive Sensing at Home Towards Healthcare 5.0: Technologies, Applications, and Future Directions

by Regina Oliveira, Joana Simões, Pedro Correia, António Teixeira, Florinda Costa, Cátia Leitão and Ana Luísa Silva

Biosensors 2026, 16(5), 250; https://doi.org/10.3390/bios16050250 - 29 Apr 2026

Abstract

The growing prevalence of chronic diseases, population aging, and the shift toward preventive and personalized care under Healthcare 5.0 have increased the need for continuous health monitoring beyond clinical settings. While wearable devices enable remote monitoring, their long-term use is often limited by [...] Read more.

The growing prevalence of chronic diseases, population aging, and the shift toward preventive and personalized care under Healthcare 5.0 have increased the need for continuous health monitoring beyond clinical settings. While wearable devices enable remote monitoring, their long-term use is often limited by user compliance, comfort issues, battery dependence, and disruption of daily routines. To address these limitations, unobtrusive home-based health monitoring systems have emerged, integrating sensing technologies into domestic environments and everyday objects. This review provides a system-level analysis of unobtrusive health monitoring technologies for smart homes. It examines seven major sensing approaches, including camera-, laser-, radar-, infrared-, mechanical-, bioelectrical-, and optical-based sensors, and their integration into four home environments: living areas, bathrooms, bedrooms, and home offices. For each sensing modality, the operating principles, monitored physiological parameters, representative applications, and key advantages and limitations are discussed. Overall, existing solutions reveal trade-offs among measurement accuracy, robustness in real home conditions, energy autonomy, privacy preservation, and user acceptance. Heart rate and respiratory rate are the most commonly monitored parameters, while multimodal and clinically validated systems remain limited. Although unobtrusive sensing technologies show strong potential for proactive and personalized healthcare, challenges related to accuracy, interoperability, privacy, and cost continue to hinder large-scale adoption. Full article

(This article belongs to the Special Issue Multimodal Biosensing: From Performance Enhancement to Multiplexed Readouts)

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118 pages, 30318 KB

Open AccessReview

Graphene Quantum Dot-Based Biosensors: Recent Advances in Functionalization Strategies and Biomedical Applications

by Mahnoush Beygisangchin, Jaroon Jakmunee, Nawee Kungwan, Kontad Ounnunkad, Padchanee Sangthong, Amir Hossein Baghdadi and Siti Kartom Kamarudin

Biosensors 2026, 16(5), 249; https://doi.org/10.3390/bios16050249 - 29 Apr 2026

Abstract

Graphene quantum dots (GQDs) have emerged as a promising class of carbon-based nanomaterials owing to their unique optical properties, tunable surface chemistry, excellent biocompatibility, and high physicochemical stability. These features make GQDs particularly attractive for the development of advanced biosensing platforms. This review [...] Read more.

Graphene quantum dots (GQDs) have emerged as a promising class of carbon-based nanomaterials owing to their unique optical properties, tunable surface chemistry, excellent biocompatibility, and high physicochemical stability. These features make GQDs particularly attractive for the development of advanced biosensing platforms. This review provides a comprehensive overview of recent progress in the design, synthesis, and functionalization of GQDs, with a primary focus on their applications in biomedical and biosensors. Various synthesis approaches, including top-down, bottom-up, and chemical methods, are critically discussed in relation to their impact on structural and optical properties. The role of surface engineering and heteroatom doping in modulating sensitivity, selectivity, and signal transduction mechanisms is also highlighted. Furthermore, recent advances in GQD-based biosensors for the detection of clinically relevant biomarkers, environmental analytes, and pathogens are systematically summarized, with emphasis on analytical performance metrics such as sensitivity, selectivity, and limit of detection. In addition, complementary biomedical applications, including bioimaging and therapeutic platforms, are briefly discussed to provide a broader context for the multifunctionality of GQDs. Finally, current challenges and future perspectives toward the rational design of high-performance GQD-based biosensors are outlined. Full article

(This article belongs to the Section Biosensor Materials)

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11 pages, 5345 KB

Open AccessArticle

Establishment of a Rapid Escherichia coli Detection Method Based on MIRA-PfAgo

by Xinjun Chen, Yayun Liu, Jieru Wang, Yin Dai, Xuehuai Shen, Xiaocheng Pan and Dongdong Yin

Biosensors 2026, 16(5), 248; https://doi.org/10.3390/bios16050248 - 29 Apr 2026

Abstract

Conventional Escherichia coli (E. coli) detection methods are often time-consuming, while molecular diagnostics typically rely on expensive thermocycling equipment. To address these limitations, this study developed a rapid nucleic acid detection method for E. coli by integrating multienzyme isothermal rapid amplification [...] Read more.

Conventional Escherichia coli (E. coli) detection methods are often time-consuming, while molecular diagnostics typically rely on expensive thermocycling equipment. To address these limitations, this study developed a rapid nucleic acid detection method for E. coli by integrating multienzyme isothermal rapid amplification (MIRA) with Pyrococcus furiosus Argonaute (PfAgo)-mediated targeted cleavage. The conserved housekeeping gene phoA was selected as the target, and specific MIRA primers and 5′-phosphorylated guide DNAs (gDNAs) were designed accordingly. After exponential amplification at 39 °C, the amplicons were specifically recognized by PfAgo at 95 °C, leading to molecular beacon cleavage and generation of a detectable FAM fluorescence signal. Among the tested guides, gDNA6 showed the highest cleavage efficiency. Optimal performance was achieved with 1 μM PfAgo, 0.5 μM gDNA, and 5 mM MnCl₂. The optimized MIRA-PfAgo assay demonstrated a limit of detection of 10⁰ copies/μL, comparable to qPCR, and exhibited high specificity with no cross-reactivity against common enteric pathogens. In 28 clinical and environmental samples, the assay results were fully consistent with those of qPCR. Overall, the MIRA-PfAgo platform provides a rapid, sensitive, and specific approach for E. coli detection, demonstrating strong potential to reduce reliance on precision thermal cyclers for resource-limited applications. Full article

(This article belongs to the Section Environmental, Agricultural, and Food Biosensors)

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