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Biosensors for Biomedical, Environmental and Food Applications
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Biosensors for Biomedical, Environmental and Food Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: 25 July 2026 | Viewed by 11966

Special Issue Editor

Dr. Sebania Libertino

E-Mail Website
Guest Editor
Istituto per la Microelettronica e Microsistemi, National Research Council of Italy, 95121 Catania, Italy
Interests: design and fabrication of Si-based microelectronic and optoelectronic devices; integration of biological molecules in Si to fabricate biosensors; design and characterization of sensing systems for environmental and precision agriculture applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to collect the latest advancements in biosensor technologies across the biomedical, environmental, and food sectors. As the demand for rapid, accurate, and portable detection systems grows, biosensors have emerged as transformative tools for real-time monitoring, diagnostics, and quality control.

This Special Issue seeks to bring together cutting-edge research that explores novel biosensor designs, innovative materials, and signal transduction mechanisms.

In the biomedical domain, we welcome studies that focus on point-of-care diagnostics, disease biomarker detection, and personalized health monitoring. For environmental applications, submissions addressing pollution detection, water quality assessment, and ecological monitoring are encouraged. In the food industry, we aim to feature research on contamination detection, freshness assessment, and food authentication.

This interdisciplinary Special Issue will serve as a platform for scientists, engineers, and technologists to share breakthroughs and foster collaboration. By showcasing the versatility and impact of biosensors across diverse fields, we hope to inspire new approaches that address global health, environmental, and safety challenges.

Dr. Sebania Libertino
Guest Editor

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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • biosensors
  • point-of-care diagnostics
  • environmental monitoring
  • food safety
  • electrochemical sensing
  • optical biosensors
  • wearable sensors
  • nanomaterials
  • lab-on-a-chip
  • real-time detection

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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21 pages, 4786 KB  
Article
A Single Polyoxometalate Nanozyme for Cross-Reactive Thiol Array Sensing via pKa-Driven and Enrichment-Synergistic Strategy
by Baohong Sun, Ying Liu, Xinxin Tian, Yu Fang, Jinpei Mei, Yang Chen and Tao Ma
Sensors 2026, 26(10), 3175; https://doi.org/10.3390/s26103175 - 17 May 2026
Viewed by 314
Abstract
Glutathione (GSH), cysteine (Cys), and homocysteine (Hcy) are essential biothiols involved in redox homeostasis and cell signaling. Yet, their structural similarity poses a significant challenge for accurate discrimination in complex biological samples. Herein, we report a polyoxometalate nanozyme (Fe4P2W [...] Read more.
Glutathione (GSH), cysteine (Cys), and homocysteine (Hcy) are essential biothiols involved in redox homeostasis and cell signaling. Yet, their structural similarity poses a significant challenge for accurate discrimination in complex biological samples. Herein, we report a polyoxometalate nanozyme (Fe4P2W18) with an atomically precise structure synthesized via a mild one-step method. Benefiting from its negatively charged surface and multi-electron reduction centers, the nanozyme effectively enriches biothiols under acidic conditions and exhibits excellent peroxidase-like activity. By leveraging its stepped catalytic response across pH 3.5, 4.0, and 4.5, which amplifies the pKa-driven differences in the overall molecular charge and electrostatic properties of biothiols, we constructed a single-material three-channel colorimetric array sensor that generates cross-reactive fingerprints. This sensor achieves 100% discrimination accuracy for GSH, Cys, and Hcy within 5 min, with a detection limit of 0.1 μM. It enables quantitative detection of thiol concentrations between 1 and 50 μM and accurately identifies binary and ternary thiol mixtures. Furthermore, the sensor successfully distinguishes cell types (HUVEC, HeLa, A549) and discriminates serum samples from cardiovascular disease patients. This strategy eliminates the complexity of multi-material arrays while leveraging the well-defined structure of Fe4P2W18 to provide mechanistic clarity, offering a simple, rapid, and reliable tool for biothiol analysis and early disease diagnosis. Full article
(This article belongs to the Special Issue Biosensors for Biomedical, Environmental and Food Applications)
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20 pages, 528 KB  
Article
Dynamic Sleep-Derived Heart Rate and Heart Rate Variability Features Associated with Glucose Metabolism Status: An Exploratory Feature-Selection Study Using Consumer Wearables
by Li Li, Syarifah Nabilah Syed Taha, Yoshiyuki Nishinaka, Yufeng Tan, Hajime Ohtsu, Sinyoung Lee and Ken Kiyono
Sensors 2026, 26(4), 1118; https://doi.org/10.3390/s26041118 - 9 Feb 2026
Viewed by 1219
Abstract
Impaired glucose metabolism, a known precursor to type 2 diabetes, is associated with dysregulation of the autonomic nervous system. To assess such autonomic states, consumer wearable devices provide continuous, non-invasive physiological monitoring and may capture autonomic signatures related to metabolic status. This exploratory [...] Read more.
Impaired glucose metabolism, a known precursor to type 2 diabetes, is associated with dysregulation of the autonomic nervous system. To assess such autonomic states, consumer wearable devices provide continuous, non-invasive physiological monitoring and may capture autonomic signatures related to metabolic status. This exploratory study examined whether dynamic features of heart rate (HR) and heart rate variability (HRV) during sleep—derived from a consumer wrist-worn device (Fitbit)—are associated with glucose metabolism status in free-living adults. We analyzed 189 nights from 18 participants (7 participants in the higher-glycemic-risk group, estimated glycated hemoglobin (HbA1c) ≥ 5.5%; 11 participants in the lower-glycemic-risk group, estimated HbA1c < 5.5%). From 28 candidate HR/HRV variables, Elastic Net regression (α=0.5) was applied to identify features associated with nocturnal mean glucose. Fourteen features retained non-zero coefficients; notably, dynamic features capturing overnight trends and variability patterns showed stronger associations than conventional static mean values. The nocturnal trends of within-window standard deviation and variance of ln(RMSSD) (root mean square of successive differences between consecutive RR intervals, estimated here from PPG-derived inter-beat intervals; RMSSD) emerged as prominent candidates, alongside HR variability indices. Independent between-group comparisons further confirmed that two dynamic HRV features differed significantly between the lower- and higher-glycemic-risk groups (both p<0.05; Cohen’s |d|>1.1). Specifically, the lower-glycemic-risk group exhibited decreasing overnight trends in HRV variability, consistent with progressive autonomic stabilization during sleep. In contrast, the higher-glycemic-risk group showed increasing variability trends, suggestive of persistent autonomic instability. These directional patterns are consistent with prior evidence linking autonomic dysfunction to impaired glucose metabolism. We characterize these findings as hypothesis-generating. The identified dynamic HR/HRV features represent physiologically plausible candidate correlates of glycemic status and warrant confirmatory investigation in larger, independent cohorts with laboratory-measured HbA1c. More broadly, this work highlights the potential of widely available, consumer-grade wearable devices to move beyond activity tracking and support continuous, real-world assessment of cardiometabolic health, thereby expanding their utility in everyday health monitoring and preventive medicine. Full article
(This article belongs to the Special Issue Biosensors for Biomedical, Environmental and Food Applications)
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Review

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32 pages, 2763 KB  
Review
A Review on the Application of Biosensors for Monitoring Emerging Contaminants in the Water Environment
by Yi Xiao, Zhe Du, Yuqian Li, Lijia Cao, Bo Zhu, Tetsuya Kitaguchi and Caihong Huang
Sensors 2025, 25(16), 4945; https://doi.org/10.3390/s25164945 - 10 Aug 2025
Cited by 28 | Viewed by 9918
Abstract
Due to the frequent occurrence and elevated concentrations of emerging contaminants (ECs) in water environments, as well as their high toxicity, these compounds have become a growing concern, threatening water safety, human health, and environmental health. Stricter regulations and routine monitoring are required [...] Read more.
Due to the frequent occurrence and elevated concentrations of emerging contaminants (ECs) in water environments, as well as their high toxicity, these compounds have become a growing concern, threatening water safety, human health, and environmental health. Stricter regulations and routine monitoring are required to control EC pollution in water. Analytical chemistry-based techniques are the most widely used approach for quantifying ECs in environmental samples. However, high costs, complex sample preparation, time-consuming protocols, and labor-intensive processes limit their application for the routine and rapid detection of ECs. Biosensors are a promising biotechnological alternative that has received increased attention in recent years for the quantification of ECs. This review provides a comprehensive overview of the main types of biosensors used for monitoring ECs in aquatic environments, highlighting their underlying detection mechanisms and recent technological advancements. It also discusses key challenges associated with different biosensor platforms, such as stability, sensitivity, and development complexity. Potential future research directions to address these limitations and enhance the performance of biosensors include immobilization on hybrid nanomaterials, and the development of portable and multifunctional biosensors for on-site and real-time monitoring. By summarizing current progress and identifying future directions, this review will broaden the awareness and recognition of biosensors for monitoring ECs in water environments, contributing to water safety, sanitation, and sustainability. Full article
(This article belongs to the Special Issue Biosensors for Biomedical, Environmental and Food Applications)
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