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Biosensors
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Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition
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Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensors and Healthcare".

Deadline for manuscript submissions: 31 January 2027 | Viewed by 6382

Special Issue Editors

Dr. Nina Dimcheva

E-Mail Website
Guest Editor
Department of Physical Chemistry, Plovdiv University, 4000 Plovdiv, Bulgaria
Interests: sensor design; sensor architecture; immobilization; bioreceptor; biomimics; advanced materials; disease diagnosis; pharmaceutical analysis; forensic sciences; pathogens
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sergey Shleev

E-Mail Website
Guest Editor
Department of Biomedical Science, Faculty of Health and Society and Biofilms, Research Center for Biointerfaces, Malmo University, 205 06 Malmö, Sweden
Interests: bioelectronics; biosensors; biological power sources; biofuel cells; biosupercapacitor; physiological sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

After the success of the second volume of this Special Issue, ‘Electrochemical (Bio-)Sensors in Biological Applications’, the Journal’s Editorial Board, in collaboration with the Guest Editors Dr. Nina Dimcheva (assoc. prof.) and Prof. Dr. Sergey Shleev, is launching a third edition under the same title. This Special Issue is dedicated to electrochemical sensors and biosensors that are applicable in diseases diagnosis; clinical, pharmaceutical, agricultural, food, and forensic analyses; and any other area of biological interest.

In addition to those already announced in the second edition, the following topics may be addressed:

  • Sensor design: The application of nanomaterials and bio-nanomaterials, hybrid materials, composites and bio-composites, biomimics or bio-inspired materials in sensor architecture, and the immobilization of bio-receptors (proteins, nucleic acids, tissues, microorganisms, etc.) as a tool for their stabilization.
  • Areas of application: Sensors/biosensors for disease diagnosis; clinical analysis, drug discovery, and pharmacy; forensic science and food analyses; and any of other field of biological analyses.
  • Sensor’s analytical performance: The selectivity of analysis in complex matrices, low detection limits, etc.

This third edition will focus also on cutting-edge sensing technologies, including the following:

- Wearables, electronic textiles, and point-of-care (POC) devices;

- Implantable biodegradable sensors and biosensors for disease monitoring and treatment;

- (Bio-)sensors equipped with advanced signal processing techniques, incorporating machine learning and artificial intelligence for data analysis.

Both critical reviews and original research articles that address analytical aspects (selectivity, validation, etc.), the design of sensing devices and/or platforms (bioreceptor immobilization, use of bio-mimics, bio-inspired catalysts), or sensing principles will be considered for publication.

Dr. Nina Dimcheva
Prof. Dr. Sergey Shleev
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor design
  • sensor architecture
  • immobilization
  • bio-receptor
  • bio-mimics
  • advanced materials
  • disease diagnosis
  • pharmaceutical analysis
  • forensic sciences
  • pathogens

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Related Special Issues

Published Papers (4 papers)

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Research

21 pages, 1864 KB  
Article
Rapid Electrochemical Profiling of Fecal Short-Chain Fatty Acids Using Esterification/Dissociation Fingerprints and Artificial Neural Networks
by Bing-Chen Gu, Guan-Ying Jiang, Ching-Hung Tseng, Yi-Ju Chen, Chun-Ying Wu, Zhi-Xuan Lin, Zhung-Wen Yeh and Chia-Che Wu
Biosensors 2026, 16(4), 223; https://doi.org/10.3390/bios16040223 - 17 Apr 2026
Viewed by 634
Abstract
Short-chain fatty acids (SCFAs) are key biomarkers of gut microbiota activity; however, routine quantification in fecal samples relies largely on chromatography, which is instrument-intensive and throughput-limited chromatography techniques. Herein, we present a rapid machine-learning-assisted electroanalysis platform for SCFAs profiling that integrates a disposable [...] Read more.
Short-chain fatty acids (SCFAs) are key biomarkers of gut microbiota activity; however, routine quantification in fecal samples relies largely on chromatography, which is instrument-intensive and throughput-limited chromatography techniques. Herein, we present a rapid machine-learning-assisted electroanalysis platform for SCFAs profiling that integrates a disposable three-electrode planar gold chip with voltammetric fingerprinting and artificial neural network (ANN)-based signal decoupling. To generate orthogonal chemical information and improve the discrimination of structurally similar species, a dual pretreatment strategy combining acid-catalyzed esterification and alkaline dissociation was employed prior to electrochemical analyses. Differential pulse voltammetry (DPV) and cyclic voltammetry (CV) were employed to acquire high-dimensional fingerprints, from which current-, potential-, and area-based descriptors were extracted using a cross-information feature strategy. A hierarchical modeling framework improved total SCFAs prediction by incorporating ANN-predicted propionate and butyrate concentrations as auxiliary inputs. While linear calibration was achievable in standard mixtures, direct linear models performed poorly in real fecal matrices due to strong sample-dependent matrix interference. In contrast, the ANN captured nonlinear relationships among multifeature inputs and suppressed matrix effects. Validation against gas chromatography–mass spectrometry in an independent fecal test cohort (n = 30) demonstrated excellent agreement and low prediction errors, with mean absolute error/root mean square error values of 0.063/0.072 mM (propionic acid), 0.029/0.034 mM (butyric acid), and 0.135/0.202 mM (total SCFAs). The DPV/CV acquisition requires only minutes per sample, whereas pretreatment takes 1~3 h depending on the target route but can be performed in parallel for batch processing; thus, overall throughput is determined mainly by batch pretreatment rather than per-sample instrument time. This electrochemical–ANN workflow provides a portable, high-throughput alternative to chromatography for fecal SCFAs profiling in clinical screening and microbiome research. Full article
(This article belongs to the Special Issue Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition)
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20 pages, 2593 KB  
Article
Electrochemical Detection of Neuronal Injury in Cell Culture Samples: A Cost-Effective Biosensor for Neurofilament Light Sensing
by Anna Panteleeva, Sujey Palma-Florez, Ashlyne M. Smith, Sara Palma-Tortosa, Zaal Kokaia, Josep Samitier and Mònica Mir
Biosensors 2026, 16(4), 212; https://doi.org/10.3390/bios16040212 - 9 Apr 2026
Viewed by 796
Abstract
Neurofilament light chain (NfL) is a promising biomarker of axonal injury across acute and chronic neurodegeneration, which can improve drug discovery and disease monitoring models. Traditional in vivo animal models cannot fully mimic human pathophysiology of neurodegenerative diseases (NDDs), but in vitro models [...] Read more.
Neurofilament light chain (NfL) is a promising biomarker of axonal injury across acute and chronic neurodegeneration, which can improve drug discovery and disease monitoring models. Traditional in vivo animal models cannot fully mimic human pathophysiology of neurodegenerative diseases (NDDs), but in vitro models based on human cells solve this problem, reducing the time and cost of drug testing. We developed an electrochemical immunosensor for NfL detection in cell culture media to monitor acute neuronal injury in in vitro models. The biosensor was designed in two configurations: the label-free system, which directly detects NfL in the sample via the antibody–antigen interaction, and the sandwich configuration, which incorporates two additional antibodies. Detection was examined using electrochemical techniques, including cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and chronoamperometry (CA). The sensor demonstrated a detection limit of 3–9 pg mL−1, and a dynamic working range spanning from 10 up to 107 pg mL−1. Importantly, NfL was successfully detected in physiological media collected from cultured neurons that were differentiated from the long-term human neuroepithelial-like stem cells. This discovery highlights the platform’s applicability for in vitro neurodegenerative models. The immunosensor offers a sensitive, scalable, and cost-effective alternative for neurodegeneration detection in drug testing applications. Full article
(This article belongs to the Special Issue Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition)
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16 pages, 1219 KB  
Article
Flexible Inkjet-Printed pH Sensors for Application in Organ-on-a-Chip Biomedical Testing
by Željka Boček, Donna Danijela Dragun, Laeticia Offner, Sara Krivačić, Ernest Meštrović and Petar Kassal
Biosensors 2026, 16(1), 38; https://doi.org/10.3390/bios16010038 - 3 Jan 2026
Cited by 1 | Viewed by 1367
Abstract
Reliable models of the lung environment are important for research on inhalation products, drug delivery, and how aerosols interact with tissue. pH fluctuations frequently accompany real physiological processes in pulmonary environments, so monitoring pH changes in lung-on-a-chip devices is of considerable relevance. Presented [...] Read more.
Reliable models of the lung environment are important for research on inhalation products, drug delivery, and how aerosols interact with tissue. pH fluctuations frequently accompany real physiological processes in pulmonary environments, so monitoring pH changes in lung-on-a-chip devices is of considerable relevance. Presented here are flexible, miniaturized, inkjet-printed pH sensors that have been developed with the aim of integration into lung-on-a-chip systems. Different types of functional pH-sensitive materials were tested: hydrogen-selective plasticized PVC membranes and polyaniline (both electrodeposited and dropcast). Their deposition and performance were evaluated on different flexible conducting substrates, including screen-printed carbon electrodes (SPE) and inkjet-printed graphene electrodes (IJP-Gr). Finally, a biocompatible dropcast polyaniline-modified IJP was selected and paired with an inkjet-printed Ag/AgCl quasireference electrode. The printed potentiometric device showed Nernstian sensitivity (58.8 mV/pH) with good reproducibility, reversibility, and potential stability. The optimized system was integrated with a developed lung-on-a-chip model with an electrospun polycaprolactone membrane and alginate, simulating the alveolar barrier and the natural mucosal environment, respectively. The permeability of the system was studied by monitoring the pH changes upon the introduction of a 10 wt.% acetic acid aerosol. Overall, the presented approach shows that electrospun-hydrogel materials together with integrated microsensors can help create improved models for studying aerosol transport, diffusion, and chemically changing environments that are relevant for inhalation therapy and respiratory research. These results show that our system can combine mechanical behavior with chemical sensing in one platform, which may be useful for future development of lung-on-a-chip technologies. Full article
(This article belongs to the Special Issue Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition)
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17 pages, 5908 KB  
Article
Analysis of Olfactive Prints from Artificial Lung Cancer Volatolome with Nanocomposite-Based vQRS Arrays for Healthcare
by Abhishek Sachan, Mickaël Castro and Jean-François Feller
Biosensors 2025, 15(11), 742; https://doi.org/10.3390/bios15110742 - 4 Nov 2025
Cited by 1 | Viewed by 1031
Abstract
Exhaled breath analysis is emerging as one of the most promising non-invasive strategies for the early detection of life-threatening diseases, especially lung cancer, where rapid and reliable diagnosis remains a major clinical challenge. In this study, we designed and optimized an electronic nose [...] Read more.
Exhaled breath analysis is emerging as one of the most promising non-invasive strategies for the early detection of life-threatening diseases, especially lung cancer, where rapid and reliable diagnosis remains a major clinical challenge. In this study, we designed and optimized an electronic nose (e-nose) platform composed of quantum resistive vapor sensors (vQRSs) engineered by polymer-carbon nanotube nanocomposites via spray layer-by-layer assembly. Each sensor was tailored through specific polymer functionalization to tune selectivity and enhance sensitivity toward volatile organic compounds (VOCs) of medical relevance. The sensor array, combined with linear discriminant analysis (LDA), demonstrated the ability to accurately discriminate between cancer-related biomarkers in synthetic blends, even when present at trace concentrations within complex volatile backgrounds. Beyond artificial mixtures, the system successfully distinguished real exhaled breath samples collected under challenging conditions, including before and after smoking and alcohol consumption. These results not only validate the robustness and reproducibility of the vQRS-based array but also highlight its potential as a versatile diagnostic tool. Overall, this work underscores the relevance of nanocomposite chemo-resistive arrays for breathomics and paves the way for their integration into future portable e-nose devices dedicated to telemedicine, continuous monitoring, and early-stage disease diagnosis. Full article
(This article belongs to the Special Issue Electrochemical (Bio-)Sensors in Biological Applications—3rd Edition)
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