Biosensors

21 pages, 2828 KB

Open AccessArticle

Entropy-Based Analysis of Olfactory EEG as a Candidate Biomarker for Early Mild Cognitive Impairment Detection: A Proof-of-Concept Study

by Sabatina Criscuolo, Andrea De Maria, Annarita Tedesco, Pasquale Arpaia and Egidio De Benedetto

Biosensors 2026, 16(9), 504; https://doi.org/10.3390/bios16090504 - 8 Sep 2026

Abstract

A decline in olfactory ability represents one of the earliest signs of Alzheimer’s disease (AD) and can be valuable information for early diagnosis at the stage of mild cognitive impairment (MCI). Nevertheless, the underlying neurophysiological mechanisms of olfactory impairment have not been systematically [...] Read more.

A decline in olfactory ability represents one of the earliest signs of Alzheimer’s disease (AD) and can be valuable information for early diagnosis at the stage of mild cognitive impairment (MCI). Nevertheless, the underlying neurophysiological mechanisms of olfactory impairment have not been systematically studied and, so far, have not been applied to make objective diagnoses using electroencephalography (EEG). To fill this gap, this proof-of-concept study investigates the possibility of using olfactory-evoked EEG complexity to discriminate between healthy subjects (HSs) and MCI patients. To this purpose, a publicly available olfactory oddball EEG-recording dataset was considered. First, a strategy for cleaning the EEG signals was implemented and applied, including exclusion of participants, channels, and epochs affected by substantial artifacts and noise. Then, a dedicated preprocessing pipeline was implemented: in particular, the cleaned signals were partitioned into three temporal intervals according to the stimulus onsets (i.e., pre-stimulus, early post-stimulus, and late post-stimulus periods). For each window of interest, a novel metric—namely, the Multivariate Multiscale Multi-Frequency Entropy (M3FrEn)—was computed across 10 temporal scales. The obtained results showed significant main effects of group and stimulus, as well as a significant group-by-stimulus interaction across all scales, as assessed by linear mixed-effects models. Post hoc analysis revealed a significantly reduced stimulus-related entropy modulation in MCI subjects compared to healthy controls across several early post-stimulus scales, with the strongest effect at scale 6 (adjusted

p = 0.0189

,

H e d g e s ’ g = - 2.88

). An exploratory, fully nested subject-level classification analysis, in which feature selection was performed independently within each cross-validation fold, achieved an accuracy of approximately 92% with all classifiers, consistently relying on the early post-stimulus feature. These preliminary findings suggest that M3FrEn captures olfactory-related EEG alterations in MCI, providing proof-of-concept evidence for its potential as a candidate biomarker. Full article

(This article belongs to the Special Issue AI-Based Biosensors and Biomedical Imaging)

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25 pages, 7849 KB

Open AccessArticle

Rapid Bacterial Detection on Surfaces by Field-Deployable Respirometric Sensor Sachets

by Valeria Ferraro, Loris Pinto, Liang Li, Federico Baruzzi, Dmitri B. Papkovsky and Elisa Santovito

Biosensors 2026, 16(9), 503; https://doi.org/10.3390/bios16090503 - 8 Sep 2026

Abstract

Monitoring bacterial contamination on surfaces is critical for hygiene and safety assurance in food, healthcare, and pharmaceutical settings, although routine methods still remain slow and laboratory dependent. Here, we report a portable respirometric platform based on sealed sensor sachets incorporating optical oxygen sensors [...] Read more.

Monitoring bacterial contamination on surfaces is critical for hygiene and safety assurance in food, healthcare, and pharmaceutical settings, although routine methods still remain slow and laboratory dependent. Here, we report a portable respirometric platform based on sealed sensor sachets incorporating optical oxygen sensors to rapidly detect and quantify total aerobic viable counts (TVC) from swabbed surfaces. Following standardized surface swabbing, samples were incubated in the sachets and oxygen depletion kinetics were recorded with a handheld reader and microbial activity was inferred from oxygen consumption. Reference quantification was obtained by serial dilution and aerobic plate counting, enabling direct benchmarking of the respirometric readout against an industry-accepted culture method such as ISO 4833:2013. The platform demonstrated strong agreement with plate counts (R² > 0.94), achieving a median detection limit of 2.69 log₁₀ CFU/cm² and a dynamic range of 0–6 log₁₀ CFU/cm² for surface-associated microbial loads. The sensor system was also applied in a semi-industrial setting in a meat processing plant. Across replicate measurements, the assay provided consistent kinetic signatures and quantitative outputs, suitable for rapid and practical decision-making. Compared with traditional culture-based approaches (requiring up to 72 h), the respirometric sachets delivered actionable results within 10 h using a portable, low-infrastructure workflow, supporting rapid on-site hygiene verification and sanitation control. Full article

(This article belongs to the Special Issue Advanced Biosensors for Food Safety)

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26 pages, 17499 KB

Open AccessArticle

Detection of Polysaccharide Markers of Fungal Infections by Surface-Enhanced Raman Scattering and Machine Learning Methods

by Julia Yu. Zvyagina, Robert R. Safiullin, Andrey S. Naboko, Victor I. Polozov, Irina A. Boginskaya, Marina V. Sedova, Vadim B. Krylov, Dmitry V. Yashunsky, Dmitry A. Argunov, Nikolay E. Nifantiev, Ilya A. Ryzhikov, Alexander M. Merzlikin and Andrey N. Lagarkov

Biosensors 2026, 16(9), 502; https://doi.org/10.3390/bios16090502 - 8 Sep 2026

Abstract

In this study, we used the SERS method for the first time to measure the spectra of four polysaccharide markers of fungal infections: linear β-(1→3)- and β-(1→6)-linked D-glucans, branched mannan of Candida albicans and galactomannan of Aspergillus fumigatus. Aqueous solutions of the [...] Read more.

In this study, we used the SERS method for the first time to measure the spectra of four polysaccharide markers of fungal infections: linear β-(1→3)- and β-(1→6)-linked D-glucans, branched mannan of Candida albicans and galactomannan of Aspergillus fumigatus. Aqueous solutions of the polysaccharides were studied in concentrations from 10 pg/mL to 100 μg/mL. The spectra were analyzed using machine learning methods: principal component analysis for data visualization and partial least squares with a ridge regularizer, which were used to construct metrics reflecting the accuracy of substance recognition relative to each other. The spectral changes with varying analyte concentration were observed and stable calibration has been achieved. Subsequent measurements of fungal polysaccharides in the presence of a physiological concentration of human serum albumin (45 mg/mL), used to model blood serum, enabled accurate analyte detection in a clinically relevant concentration range of 10 pg/mL to 100 ng/mL. In this case, the calibration dependence was calculated using the partial least squares method with the L1-regularizer. Blind testing was evaluated using a train-derived applicability-domain criterion based on the disagreement between the model prediction and an independent concentration estimate. Full article

(This article belongs to the Special Issue Optical Biosensors for Healthcare: An Artificial Intelligence Approach)

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15 pages, 2715 KB

Open AccessArticle

Explainable AI-Assisted Label-Free Raman Biosensing Reveals Therapy-Associated Spectral Signatures in Melanoma Tumors

by Muhammad Nouman Khan, Qingsong Zhou, Jiaqing Guo, Asif Khalid and Rui Hu

Biosensors 2026, 16(9), 501; https://doi.org/10.3390/bios16090501 - 8 Sep 2026

Abstract

Sensitive detection of treatment-associated Raman spectral alterations in tumor tissues remains challenging, particularly when such changes are not readily apparent from conventional morphological evaluation. Here, we developed a label-free Raman biosensing strategy combined with explainable machine learning to characterise treatment-associated spectral signatures in [...] Read more.

Sensitive detection of treatment-associated Raman spectral alterations in tumor tissues remains challenging, particularly when such changes are not readily apparent from conventional morphological evaluation. Here, we developed a label-free Raman biosensing strategy combined with explainable machine learning to characterise treatment-associated spectral signatures in melanoma tumours. A B16-F10 melanoma-bearing mouse model was used to compare untreated and PBS-treated controls with cohorts receiving immune checkpoint blockade, anti-angiogenic intervention, or combination therapy. Raman spectra were acquired from multiple spatial regions of melanoma tissues and analyzed using nonlinear dimensionality reduction, supervised classification, and SHAP-based feature interpretation. Although cohort-averaged spectra showed substantial overlap, multivariate analysis revealed treatment-dependent spectral organization, with the combination-treatment cohort showing the most compact and distinguishable spectral profile. Supervised models, including convolutional neural networks, support vector machines, and k-nearest neighbors, further supported the reproducibility of treatment-associated Raman signatures when evaluated using mouse-level validation strategies. SHAP analysis identified discriminative Raman features mainly located within lipid, phospholipid, ester, protein, and collagen-associated vibrational domains, suggesting potential contributions from metabolic- and extracellular-matrix-related biochemical components to treatment-associated spectral discrimination. These findings indicate that Raman spectroscopy integrated with explainable machine learning provides a sensitive, label-free method for distinguishing treatment-associated spectral differences among melanoma tissues. The proposed approach may serve as a complementary spectroscopic tool alongside conventional histological and molecular analyses for investigating treatment-associated tissue-state alterations. Full article

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

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15 pages, 5812 KB

Open AccessArticle

Microfluidic Light-Scattering Imaging Coupled with Deep Learning for Label-Free Single-Cell Classification of Lymphoma Cells

by Linyan Xie, Mengfei Wang, Xijia Luo, Shuoxian Xia, Qiongqiong Ren and Xuezhi Zhou

Biosensors 2026, 16(9), 500; https://doi.org/10.3390/bios16090500 - 7 Sep 2026

Abstract

Accurate classification of lymphoma cell subtypes is essential for disease diagnosis and therapeutic decision-making, yet conventional approaches often rely on fluorescence labeling, labor-intensive sample preparation, and specialized instrumentation, limiting their applicability for rapid, label-free single-cell analysis. Here, we present an AI-assisted microfluidic light-scattering [...] Read more.

Accurate classification of lymphoma cell subtypes is essential for disease diagnosis and therapeutic decision-making, yet conventional approaches often rely on fluorescence labeling, labor-intensive sample preparation, and specialized instrumentation, limiting their applicability for rapid, label-free single-cell analysis. Here, we present an AI-assisted microfluidic light-scattering imaging platform for label-free classification of lymphoma cells. The platform integrates hydrodynamic focusing within a microfluidic chip, continuous acquisition of two-dimensional (2D) light-scattering patterns, automated image preprocessing, and transfer learning based on a pretrained ResNet50 network for intelligent optical feature extraction and classification. Human B lymphoma (Daudi) and T lymphoblastic lymphoma (SUP-T1) cells were used to evaluate the proposed framework. The optical imaging system was first validated using standard microspheres, demonstrating reliable acquisition of light-scattering patterns under continuous-flow conditions. A dataset comprising 800 single-cell scattering patterns was subsequently established and evaluated using stratified five-fold cross-validation. The proposed framework achieved an average classification accuracy of 94.75% with an average area under the receiver operating characteristic (ROC) curve of 0.986. By integrating microfluidic optical biosensing with deep learning, this work enables automated interpretation of intrinsic optical scattering signatures and provides a promising AI-enabled strategy for rapid, label-free lymphoma screening and intelligent healthcare applications. Full article

(This article belongs to the Special Issue Optical Biosensors for Healthcare: An Artificial Intelligence Approach)

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44 pages, 16238 KB

Open AccessReview

Rapid Diagnostics for Distinguishing Bacterial and Viral Infections: A Review of Technologies, Clinical Utility, and Stewardship Implications

by Mohammad Javanmard, Rohan Vellanki, Ali Fardoost and Mehdi Javanmard

Biosensors 2026, 16(9), 499; https://doi.org/10.3390/bios16090499 - 6 Sep 2026

Abstract

Antimicrobial resistance (AMR) is a growing global health threat driven in part by inappropriate and unnecessary antibiotic use resulting from diagnostic uncertainty at the point of care. In outpatient and acute-care settings, clinicians are often unable to rapidly distinguish between viral and bacterial [...] Read more.

Antimicrobial resistance (AMR) is a growing global health threat driven in part by inappropriate and unnecessary antibiotic use resulting from diagnostic uncertainty at the point of care. In outpatient and acute-care settings, clinicians are often unable to rapidly distinguish between viral and bacterial infections, leading to empiric antibiotic prescribing that contributes to the emergence and spread of resistant pathogens. This review examines current and emerging rapid diagnostic technologies for differentiating bacterial and viral infections, including molecular assays, rapid antigen tests, biomarker-based diagnostics, host-response platforms, hematologic methods, and artificial intelligence-based decision-support systems. These technologies are evaluated based on diagnostic accuracy, turnaround time, cost, accessibility, and clinical actionability within real-world healthcare settings. Although several emerging and point-of-care (POC) technologies can provide results within approximately 6–15 min, their ability to consistently align with the timing, workflow, and clinical decision-making requirements of frontline outpatient and emergency-care settings remains variable and incompletely established. Future progress in antimicrobial stewardship will depend on developing rapid, clinically actionable diagnostic systems that integrate seamlessly into patient care and reduce unnecessary antibiotic use. Full article

(This article belongs to the Special Issue Interdisciplinary Advances: Lab-on-a-Chip Biosensors Shaping Precision Diagnosis)

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31 pages, 4794 KB

Open AccessReview

Optical and Electrochemical Biosensors Using Electrochemically Etched Porous Silicon

by Teodora Despotovski Kiš, Marko Radović, Brankica Kartalović and Nikola Knežević

Biosensors 2026, 16(9), 498; https://doi.org/10.3390/bios16090498 - 6 Sep 2026

Abstract

Versatile nanostructured materials based on electrochemically etched porous silicon (pSi) are being developed, which have tuneable pore morphology and unique optical and electrochemical properties that enable their effective biosensing applications. It has been shown that fabrication parameters critically influence pore formation and sensor [...] Read more.

Versatile nanostructured materials based on electrochemically etched porous silicon (pSi) are being developed, which have tuneable pore morphology and unique optical and electrochemical properties that enable their effective biosensing applications. It has been shown that fabrication parameters critically influence pore formation and sensor performance, yet challenges remain in reproducible synthesis, structural stability and device integration. Here we review the electrochemical etching synthesis of pSi and recent advances in pSi-based optical and electrochemical biosensors for detecting bacteria, biomolecules, and viruses. We highlight strategies such as surface functionalisation, incorporation of nanomaterials, and integration with microfluidic and lab-on-a-chip technologies that enhance sensitivity and response times by addressing mass transfer limitations. These developments highlight pSi’s potential as a low-cost, adaptable biosensing material with applications in clinical diagnostics and environmental monitoring, while mapping future directions to overcome current fabrication and stability challenges. Full article

(This article belongs to the Special Issue Development and Application of Functional Nanomaterial-Based Biosensors)

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27 pages, 2570 KB

Open AccessReview

Photoacoustic Imaging for Liver Disease: The Systems and the Molecules

by Bowen Jiang, Zhixian Lin and Xiaoquan Yang

Biosensors 2026, 16(9), 497; https://doi.org/10.3390/bios16090497 - 5 Sep 2026

Abstract

Liver disease represents a significant global health burden, and its effective management relies on early, accurate diagnosis. Established assessments for liver diseases, ranging from invasive biopsies to conventional noninvasive imaging (e.g., ultrasound, MRI, and CT), are often limited by inadequate specificity, potential safety [...] Read more.

Liver disease represents a significant global health burden, and its effective management relies on early, accurate diagnosis. Established assessments for liver diseases, ranging from invasive biopsies to conventional noninvasive imaging (e.g., ultrasound, MRI, and CT), are often limited by inadequate specificity, potential safety risks, or unsuitability for dynamic tracking. Photoacoustic imaging (PAI), a hybrid modality that combines optical absorption contrast with deep ultrasonic detection, offers an attractive solution for noninvasive, high-sensitivity, and high-specificity imaging in deep organs such as the liver. This review summarizes recent advances in photoacoustic imaging for liver pathophysiology, beginning with the evolution of imaging systems and extending to the diverse molecules employed for preclinical studies and early clinical trials. Specifically, novel reconstruction algorithms improved the spatial resolution and acquisition speed by up to threefold, Monte Carlo-based fluence compensation increased the deep-tissue signal-to-background ratio by approximately 50%, and a 7-azaindole-modified probe exhibited one-magnitude-higher superoxide-triggered activation than conventional hemicyanine dyes. Furthermore, we discuss key challenges and future perspectives, highlighting the translational potential of PAI as an emerging liver imaging modality. Full article

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

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21 pages, 4557 KB

Open AccessFeature PaperArticle

Wearable Inertial Sensor-Based Detection of Exercise-Induced Mobility Adaptations in Older Women: A Randomized Controlled Trial

by Mauricio Barramuño-Medina, Pablo Valdés-Badilla, Pablo Aravena-Sagardia, Jordan Hernandez-Martínez, Edgar Vásquez-Carrasco, Wilson Pastén-Hidalgo, Cristian Sandoval-Vásquez and Germán Gálvez-García

Biosensors 2026, 16(9), 496; https://doi.org/10.3390/bios16090496 - 5 Sep 2026

Abstract

Wearable inertial sensors have become tools for objectively assessing mobility in older people. This study analyzed whether wearable inertial sensors could detect exercise-induced mobility changes and compared the effects of multicomponent training (MCT) and elastic band training (EBT) on mobility and physical function [...] Read more.

Wearable inertial sensors have become tools for objectively assessing mobility in older people. This study analyzed whether wearable inertial sensors could detect exercise-induced mobility changes and compared the effects of multicomponent training (MCT) and elastic band training (EBT) on mobility and physical function in older women. Forty-two participants were randomly allocated to either the MCT (n = 21) or EBT (n = 21) group, where 38 (EBT: n = 19; MCT: n = 19) completed the 16-week intervention. Outcomes included instrumented Timed Up-and-Go (iTUG) assessed with a wearable inertial sensor, the Senior Fitness Test, maximal isometric handgrip strength, conventional TUG, anthropometric measurements, health-related quality of life, and blood biomarkers. Data were analyzed using age-adjusted linear mixed-effects models. The iTUG showed shorter completion time (p < 0.001), reduced middle-turn duration (p = 0.004), and increased cadence (p = 0.007). Significant time effects were also observed for chair stand (p = 0.011), arm curl (p < 0.001), and conventional TUG (p = 0.009). No significant group × time interactions were detected. After adjustment for multiple comparisons, no significant changes were observed in anthropometric measures, health-related quality of life, or blood biomarkers. Wearable inertial sensors detected training-related mobility changes, and both exercise programs improved physical function and mobility without between-group differences. Full article

(This article belongs to the Special Issue Advances and Challenges in Wearable Biosensors for Human Activity Monitoring)

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20 pages, 16343 KB

Open AccessArticle

Geometry-Tunable Nanoneedle Arrays Reveal Membrane Penetration Mechanics for Intracellular Delivery

by Xuanhe Zhang, Zheng Wang, Yiqing Chen, Lele Song, Yuan Ma and Jiadao Wang

Biosensors 2026, 16(9), 495; https://doi.org/10.3390/bios16090495 - 4 Sep 2026

Abstract

Nanoneedle arrays provide a promising interface for intracellular delivery, yet scalable control of array geometry and membrane penetration mechanics remains insufficiently understood. Here, we developed a rapid and scalable strategy for fabricating geometry-tunable silicon nanoneedle arrays. One-step SF₆/O₂ etching produced [...] Read more.

Nanoneedle arrays provide a promising interface for intracellular delivery, yet scalable control of array geometry and membrane penetration mechanics remains insufficiently understood. Here, we developed a rapid and scalable strategy for fabricating geometry-tunable silicon nanoneedle arrays. One-step SF₆/O₂ etching produced ordered arrays with center-to-center spacing of 1–5 μm, whereas pseudo-Bosch etching produced high-aspect-ratio (HAR) nanoneedles. Using a microwell-assisted cell-on-probe atomic force microscopy platform, we quantified the first penetration force, penetration probability, and number of penetration events at the single-cell level. For one-step-etching arrays, increasing spacing from 1 to 5 μm reduced the first penetration force from 34.87 ± 2.90 to 4.05 ± 0.30 nN and increased the penetration probability from 0.21 ± 0.03 to 0.87 ± 0.04. A phenomenological inverse-square model captured the force–spacing relationship, supporting an array-level load-sharing mechanism. Under identical vibration-assisted microfluidic conditions, the FITC-dextran-positive fraction increased from 22.8% for 1 μm arrays to 77.1% for 5 μm arrays, whereas 1 μm HAR arrays achieved 28.8%. These results identify array spacing as a key factor governing single-cell penetration and delivery and provide a mechanistic basis for nanoneedle-based biosensor and cell-interface design. Full article

(This article belongs to the Collection Microfluidic Sensing for Biomedical Applications)

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24 pages, 4435 KB

Open AccessArticle

Design and Performance Analysis of an SPR Sensor for Milk Adulteration Monitoring

by John Germán Vera Luzuriaga, Marco Guevara, Diana Coello-Fiallos and Cristian Vacacela Gomez

Biosensors 2026, 16(9), 494; https://doi.org/10.3390/bios16090494 - 4 Sep 2026

Abstract

Hydrogen peroxide (H₂O₂) may be illegally added to milk to delay visible spoilage, producing concentration-dependent changes in its refractive index. This study numerically evaluates the optical response of a B-sil/Al/Al₂O₃/WS₂ surface plasmon resonance (SPR) [...] Read more.

Hydrogen peroxide (H₂O₂) may be illegally added to milk to delay visible spoilage, producing concentration-dependent changes in its refractive index. This study numerically evaluates the optical response of a B-sil/Al/Al₂O₃/WS₂ surface plasmon resonance (SPR) configuration to these refractive-index variations. The angular SPR response was calculated at λ = 633 nm using the transfer matrix method under TM-polarized illumination. The B-sil/Al/Al₂O₃/WS₂ architecture was established through sequential evaluation of prism material, Al thickness, Al₂O₃ thickness, and 2D interfacial material, followed by assessment of its response to H₂O₂-associated refractive-index changes in milk. The final structure consisted of 70 nm Al, 25 nm Al₂O₃, and 0.80 nm WS₂. Across the simulated H₂O₂ conditions, the resonance angle shifted from 85.65° to 86.11°, while the angular sensitivity ranged from 383.82 to 406.45°/RIU. The best balance among the evaluated metrics was obtained for H₂O₂-C2, with a sensitivity of 406.45°/RIU, QF of 4.65 RIU⁻¹, FoM of 436.48 RIU⁻¹, LoD of 1.23 × 10⁻⁵, and CSF of 436.56. The WS₂-containing interface produced calculated angular shifts for small refractive-index variations in the milk sensing medium. Comparison with reported SPR systems for milk-related sensing showed a comparable angular sensitivity range, while QF and detection accuracy were limited by the broad resonance profile. These results characterize the theoretical optical response of the B-sil/Al/Al₂O₃/WS₂ multilayer under H₂O₂-associated refractive-index changes but do not establish chemical selectivity toward H₂O₂. Experimental implementation would require an appropriate selective filtering or recognition strategy, together with validation of matrix effects and practical sensing performance. Full article

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

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12 pages, 2379 KB

Open AccessArticle

Two Signals from One Event: Exploiting Intrinsic Dual-Functional Selenium Nanomaterials for Signal-On Chiroptical and Colorimetric Sensing of Free Thiols

by Jiayang Gao and Xinling Liu

Biosensors 2026, 16(9), 493; https://doi.org/10.3390/bios16090493 - 3 Sep 2026

Abstract

Rapid identification of free thiols is essential in pharmaceutical quality control and food safety. Herein, we demonstrate the sensing concept of “two signals from one event” by exploiting the intrinsic dual functionality of selenium (Se) nanomaterials to construct a signal-on, dual-mode sensing platform [...] Read more.

Rapid identification of free thiols is essential in pharmaceutical quality control and food safety. Herein, we demonstrate the sensing concept of “two signals from one event” by exploiting the intrinsic dual functionality of selenium (Se) nanomaterials to construct a signal-on, dual-mode sensing platform for free thiols. The single event is thiol-triggered seeded growth: free thiols interact with L-cysteine-modified Se seeds, driving seed fusion and crystallization into chiral trigonal Se structures. This same event yields two readouts simultaneously: a colorimetric response arising from particle size enlargement (UV-Vis red-shift) and a turn-on circular dichroism (CD) signal from long-range chiral ordering. The method achieves a detection threshold of 10 μmol/L for various free thiols and can be completed within 60 min from seed preparation to signal readout without complex instrumentation. It serves as a general indicator of total free thiols rather than distinguishing individual thiol species. Above the threshold, concentration-dependent color deepening and spectral redshifts provide semi-quantitative estimation of the concentration range. Its practicality was validated by detecting D-penicillamine in commercial tablets. This strategy offers an approach for on-site free thiol screening and highlights the potential of chiral inorganic nanomaterials in multi-mode sensing via chiral transfer and amplification. Full article

(This article belongs to the Special Issue Fundamental Innovation and Device Engineering of Biosensors Driven by Advanced Functional Materials)

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44 pages, 6288 KB

Open AccessArticle

Modeling and Experimental Validation for Detecting Indoor Respiratory Droplet

by Fuqiang Hu, Pengfei Zhang, Yusheng Sun, Xiaofang Wang and Pengfei Lu

Biosensors 2026, 16(9), 492; https://doi.org/10.3390/bios16090492 - 3 Sep 2026

Abstract

Precise quantification of respiratory pathogen transmission is urgently needed to underpin disease surveillance and support diagnostic decision-making in indoor healthcare settings. Although numerical simulations are widely used to study macro-scale transmission, the key physical parameters governing droplet dynamics remain insufficiently understood. This study [...] Read more.

Precise quantification of respiratory pathogen transmission is urgently needed to underpin disease surveillance and support diagnostic decision-making in indoor healthcare settings. Although numerical simulations are widely used to study macro-scale transmission, the key physical parameters governing droplet dynamics remain insufficiently understood. This study develops a multi-scale transmission model to evaluate the effects of droplet evaporation, sedimentation, and ventilation on viral transmission. Based on the Wells evaporation–sedimentation theory, a time-varying model is formulated incorporating droplet size distribution, environmental humidity, and ventilation conditions, with analytical expressions derived for concentration distributions across different respiratory activities (breathing, speaking, coughing, and sneezing). Results show that droplet size is decisive for transmission distance and lower relative humidity significantly extends sedimentation range. Small coughing droplets can travel up to 2.5 m, while the bimodal sneezing distribution (1.5 µm and 74 µm) generates high-concentration zones up to 2 m. To validate the model, a molecular communication testbed is developed as a biosensing-oriented platform integrating transmitters, receivers, and configurable ventilation modules with real-time sensing capabilities, enabling systematic verification under varied breathing modes, humidity, and ventilation conditions. Experimental results show strong agreement with theoretical predictions. This framework provides a quantitative basis for biosensing-enabled environmental monitoring and diagnostic-oriented risk assessment, informing ventilation optimization and infection control measures in indoor environments. Full article

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

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18 pages, 4489 KB

Open AccessArticle

Periodontal Disease Diagnosis by a Chemically Etched Single-Mode Fiber-Optic Biosensor for Label-Free Detection of Matrix Metalloproteinase-8 (MMP-8)

by Rigoberto Tovar, Jr., Sarkis Sozkes and Marzhan Sypabekova

Biosensors 2026, 16(9), 491; https://doi.org/10.3390/bios16090491 - 3 Sep 2026

Abstract

A miniature label-free biosensor based on a chemically etched single-mode optical fiber (SMF) is reported for the detection of matrix metalloproteinase-8 (MMP-8), a salivary biomarker of active periodontitis with a clinical decision threshold of 20 ng/mL. Fibers etched in 48% hydrofluoric acid to [...] Read more.

A miniature label-free biosensor based on a chemically etched single-mode optical fiber (SMF) is reported for the detection of matrix metalloproteinase-8 (MMP-8), a salivary biomarker of active periodontitis with a clinical decision threshold of 20 ng/mL. Fibers etched in 48% hydrofluoric acid to a waist diameter of 16.0 ± 1.4 µm gave a mean refractive index (RI) sensitivity of 376.8%/RIU and an RI limit of detection (LOD) of 5.9 × 10⁻⁴ RIU. Fibers were tested with MMP-8 spiked into phosphate-buffered saline (PBS) and into saliva over 0–200 ng/mL using a post-rinse protocol with per-fiber matrix subtraction. Dose–responses followed a Langmuir isotherm (Kd = 7.1 ng/mL in PBS, 12.7 ng/mL in saliva), with cohort LODs of 0.043 and 0.52 ng/mL, both well below the threshold. MMP-9 (100 ng/mL) and human serum albumin (1 mg/mL) gave negligible responses (≤2.7%, versus 68.2% for MMP-8 at 100 ng/mL); antibody immobilization was confirmed by confocal immunofluorescence. A commercial sandwich ELISA on the same spike series gave a matched-matrix LOD of 41.1 ng/mL, nearly two orders of magnitude higher. This performance requires no metal coating, nanostructuring, label, or signal amplification, only a single wet-etching step on stock telecommunications fiber. Full article

(This article belongs to the Special Issue Emerging Trends in Optical Fiber Biosensing Based on Micro- and Nanostructures and Materials)

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16 pages, 15459 KB

Open AccessArticle

Portable Paper-Based Colorimetric Biosensor for Rapid Screening of Organophosphate Exposure via Acetylcholinesterase Activity and RGB Image Analysis

by Carlos E. Zambra, Jorge Morales-Ferreiro, Francisca Herrera Vielma and Jessica Zúñiga-Hernández

Biosensors 2026, 16(9), 490; https://doi.org/10.3390/bios16090490 - 3 Sep 2026

Abstract

Background: Rapid screening of acetylcholinesterase (AChE) inhibition is essential for monitoring exposure to organophosphate compounds, particularly in field settings where access to laboratory infrastructure is limited. This study aimed to develop a portable paper-based colorimetric biosensor for the semi-quantitative detection of AChE activity [...] Read more.

Background: Rapid screening of acetylcholinesterase (AChE) inhibition is essential for monitoring exposure to organophosphate compounds, particularly in field settings where access to laboratory infrastructure is limited. This study aimed to develop a portable paper-based colorimetric biosensor for the semi-quantitative detection of AChE activity in blood samples. Methods: The biosensor was based on a pH-dependent color change adapted from the modified Edson method. The platform was first optimized using experimental models and then evaluated in human capillary blood samples collected under real field conditions. Reference serum cholinesterase activity was determined by a certified clinical laboratory and used for comparison with the colorimetric response of the biosensor. RGB (red, green, and blue) image analysis was performed in a subset of samples to digitally characterize the chromatic response of the device. Results: Samples with preserved AChE activity showed a visible color shift associated with substrate hydrolysis, whereas samples with reduced or inhibited activity maintained darker blue-dominant tones. RGB analysis of human samples revealed significant associations between AChE activity and the R and G channels, supporting the ability of the platform to distinguish between chromatic patterns associated with different ranges of enzymatic activity. Conclusions: The proposed platform demonstrated the feasibility of translating a pH-based AChE assay into a portable paper-based format for semi-quantitative visual and RGB-assisted screening. Its evaluation in human samples demonstrated the feasibility of its use under field conditions as a proof-of-concept. Further studies are needed to optimize its analytical performance and validate its application in larger and more diverse populations. Full article

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

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15 pages, 12446 KB

Open AccessArticle

A Robust Electrochemical Aptasensor Based on a AuNP/Chitosan Conductive Network for Saxitoxin Detection in Freshwater Samples

by Luyang Zhang, Zongyu Yan, Zaiyu Zhang, Ziran Wang and Guorui Zhao

Biosensors 2026, 16(9), 489; https://doi.org/10.3390/bios16090489 - 3 Sep 2026

Abstract

Saxitoxin (STX) is a highly potent marine biotoxin, and trace contamination in aquatic environments can pose serious risks to human health. Therefore, reliable detection of low-concentration STX is crucial for water safety monitoring. Here, we developed a robust electrochemical aptasensor based on a [...] Read more.

Saxitoxin (STX) is a highly potent marine biotoxin, and trace contamination in aquatic environments can pose serious risks to human health. Therefore, reliable detection of low-concentration STX is crucial for water safety monitoring. Here, we developed a robust electrochemical aptasensor based on a gold nanoparticle/chitosan (AuNP/CS) conductive network for STX detection in freshwater samples. The chitosan matrix provides a three-dimensional scaffold for aptamer immobilization, while interconnected AuNPs create efficient electron-transfer pathways across the sensing interface. This integrated architecture improves interfacial conductivity and supports stable target-induced aptamer recognition. The aptasensor exhibits a linear response from 1 to 1000 nM and a limit of detection of 0.74 nM, with an apparent dissociation constant K_d = 70.29 ± 29.2 nM, together with high batch-to-batch consistency and long-term stability, retaining 93% of its initial response after 25 days. In spiked freshwater samples, the aptasensor achieved recoveries ranging from 99.10% to 111.33%, demonstrating the practical potential of this platform for monitoring STX contamination in aquatic environments. Full article

(This article belongs to the Special Issue Aptamer-Based Biosensing: Innovations in Molecular Recognition, Signal Transduction, and Applications)

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17 pages, 5452 KB

Open AccessArticle

Mechanical Properties and Fabrication of Bioinspired Cactus Spine Microneedles

by Hongru Liu, Xiang Long, Qiumeng Sun, Shixiong Wu and Zhishan Yuan

Biosensors 2026, 16(9), 488; https://doi.org/10.3390/bios16090488 - 3 Sep 2026

Abstract

Microneedle-based transdermal drug delivery enables painless and efficient drug administration but is limited by insufficient mechanical strength and high insertion forces. Inspired by the efficient penetration capability of cactus spines, this study investigated the microstructure and biomechanics of natural cactus spines and bioinspired [...] Read more.

Microneedle-based transdermal drug delivery enables painless and efficient drug administration but is limited by insufficient mechanical strength and high insertion forces. Inspired by the efficient penetration capability of cactus spines, this study investigated the microstructure and biomechanics of natural cactus spines and bioinspired microneedles. Finite element analysis showed that a groove width of 50 μm produced the highest stress and strain. Solid bioinspired microneedles were fabricated by 3D printing, while dissolvable hyaluronic acid, chitosan, and gelatin microneedles were prepared using femtosecond laser-fabricated titanium molds and replica molding. Optimized laser parameters generated micropores approximately 500 μm deep. Mechanical tests showed insertion forces of 60–100 mN for solid microneedles, with the 50 μm groove design exhibiting the highest value. Among dissolvable microneedles, gelatin displayed the greatest mechanical strength, whereas hyaluronic acid demonstrated the best overall potential for transdermal drug delivery. Full article

(This article belongs to the Special Issue Recent Advances in Microneedle Array Electrodes in Biomedicine)

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23 pages, 5337 KB

Open AccessReview

Fetal Magnetocardiography Using Optically Pumped Magnetometers: A Literature Review

by Rok Hren, Urban Marhl, Tamás Dóczi, Erika Országh, Vojko Jazbinšek and Tilmann Sander

Biosensors 2026, 16(9), 487; https://doi.org/10.3390/bios16090487 - 2 Sep 2026

Abstract

Fetal magnetocardiography (fMCG) provides direct non-invasive assessment of fetal cardiac electrophysiology, enabling detailed evaluation of cardiac rhythm, conduction, and repolarization. However, the clinical adoption of conventional fMCG has been limited by its reliance on superconducting quantum interference device (SQUID) systems, which require cryogenic [...] Read more.

Fetal magnetocardiography (fMCG) provides direct non-invasive assessment of fetal cardiac electrophysiology, enabling detailed evaluation of cardiac rhythm, conduction, and repolarization. However, the clinical adoption of conventional fMCG has been limited by its reliance on superconducting quantum interference device (SQUID) systems, which require cryogenic cooling and specialized infrastructure. Optically pumped magnetometers (OPMs) have emerged as a promising cryogen-free alternative with the potential to broaden access to fetal electrophysiological assessment. This review summarizes the technological evolution and early clinical evaluation of OPM-based fMCG through an analysis of original in vivo human studies published up to June 2026. Twelve eligible studies were identified and synthesized narratively. Advances in sensor design, magnetic shielding, acquisition strategies, and signal-processing algorithms have enabled SQUID-comparable signal quality and cardiac interval measurements while substantially reducing cryogenic and infrastructure requirements. OPM-fMCG has demonstrated the potential to assess fetal cardiac time intervals, heart rate variability, fetal movement, and clinically important arrhythmias, including congenital long QT syndrome, atrioventricular block, and supraventricular and ventricular tachyarrhythmias. However, the available evidence remains dominated by small, single-centre studies, with relatively few fetuses affected by clinically significant arrhythmias. Prospective multicenter clinical validation, protocol standardization, independent replication, and regulatory evaluation are therefore required before OPM-fMCG can be integrated into routine diagnostic pathways for pregnancies requiring advanced fetal electrophysiological assessment. Full article

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

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25 pages, 4106 KB

Open AccessArticle

Wearable and Invisible ECG Quality and Usability Assessment in Cockpit Monitoring

by Mariangela Pinnelli, Ana Sofia Antunes Calado, Tiago Filipe Rodrigues Fernandes, Paulo Sérgio de Brito André, Emiliano Schena, Carlo Massaroni and Hugo Plácido da Silva

Biosensors 2026, 16(9), 486; https://doi.org/10.3390/bios16090486 - 2 Sep 2026

Abstract

Continuous physiological monitoring can support pilot-state assessment, but routine cockpit use requires sensing approaches that are both unobtrusive and physiologically reliable. Wearable ECG (wECG) provides stable cardiac recordings through skin-contact electrodes, whereas cockpit-integrated invisible ECG (iECG) can reduce user burden by acquiring signals [...] Read more.

Continuous physiological monitoring can support pilot-state assessment, but routine cockpit use requires sensing approaches that are both unobtrusive and physiologically reliable. Wearable ECG (wECG) provides stable cardiac recordings through skin-contact electrodes, whereas cockpit-integrated invisible ECG (iECG) can reduce user burden by acquiring signals through instrumented controls. However, iECG depends on intermittent hand contact and may show incomplete ECG morphology even when cardiac timing information is still preserved. This study proposes a window-based framework to assess the quality and task-specific usability of simultaneous wECG and iECG acquired during simulated flight. ECG data were collected in an Airbus A320 simulator from 14 volunteers, including experienced pilots and novices. The framework combines contact availability, R-peak reliability, PQRST morphology, and complementary signal quality indices into graded usability classes for heart rate (HR)-oriented monitoring. The iECG channel remained accessible for most of the analyzed recording time, with 93.8% of windows showing full or partial contact. Several windows classified as low quality by individual SQIs were retained as HR-usable when contact and R-peak timing remained reliable, indicating that single-metric rejection can be overly conservative for external-contact ECG. HR agreement supported the physiological relevance of the proposed classes: concordant wECG–iECG windows showed a mean absolute error (MAE) of 1.1 bpm, compared with 7.1 bpm for discordant windows. Bland–Altman analysis for iECG windows classified as usable for HR estimation showed a small mean bias of 1.4 bpm. These findings indicate that incomplete ECG morphology does not necessarily imply loss of HR usability, and that contact-aware, task-specific classification can preserve useful physiological information from unobtrusive cockpit interfaces. Full article

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

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