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Biosensors: Emerging Technologies and Real-Time Monitoring

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Biochemistry".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 5220

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Guest Editor
Pediatric Infectious Diseases Lab, Department of Pediatrics, University of Oklahoma Health Campus, Oklahoma City, OK 73104, USA
Interests: VOC; real-time breath diagnostics; batteries; nanorods; biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biosensors stand at the intersection of molecular science and modern diagnostics, translating biochemical recognition at the molecular level into quantifiable signals for real-time decision-making. Advances in biomolecular engineering, nanomaterial functionalization, and molecular transduction mechanisms now enable the precise detection of metabolites, nucleic acids, proteins, and other disease-relevant analytes directly at their source. The growing need for accurate and continuous monitoring—spanning medical diagnostics, environmental analysis, and industrial bioprocess control—has accelerated innovation in molecular sensing platforms. However, challenges remain in achieving high selectivity, reproducibility, and molecular-level understanding of the recognition and signal-generation events that underpin sensor performance.

This Special Issue focuses on molecularly driven biosensor technologies designed for real-time monitoring and quantitative molecular analysis. We invite original research articles, reviews, and communications that emphasize the following:

  • Molecular design of recognition elements (e.g., enzymes, antibodies, aptamers, molecularly imprinted polymers);
  • Nanoscale or supramolecular materials that enhance molecular specificity and transduction;
  • Mechanistic studies that elucidate molecular interactions and signal pathways;
  • Integration of molecular biosensors with analytical platforms, such as AI-assisted molecular signal processing, microfluidics, or wearable interfaces.

Submissions may address electrochemical, optical, or mass-sensitive biosensing mechanisms, including those applied in clinical diagnostics, environmental pollutant detection, or non-invasive health monitoring (e.g., breath, sweat, saliva). Through this collection, we aim to bridge molecular insight with device innovation—advancing biosensors from empirical prototypes toward molecularly informed, mechanistically grounded sensing systems.

Dr. Velmurugan Thavasi
Guest Editor

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Keywords

  • biosensors
  • real-time monitoring
  • wearable sensors
  • electrochemical detection
  • optical biosensors
  • point-of-care (POC) diagnostics
  • biomarker identification and analysis
  • wireless technologies

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Published Papers (3 papers)

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Review

34 pages, 3027 KB  
Review
Real-Time Breath Diagnostics: Linking Molecular Pathways, Measurement Technologies, and Clinical Translation
by Velmurugan Thavasi, Nirmal Choradia, Naoko Takebe, Neal Naito, Susan Yeyeodu, Peter William Sadler, Dean Hougen, Sanchith Velmurugan, Jordan P. Metcalf, Donna L. Tyungu and Thirumalai Venkatesan
Int. J. Mol. Sci. 2026, 27(10), 4276; https://doi.org/10.3390/ijms27104276 - 11 May 2026
Viewed by 958
Abstract
Diagnostic latency limits time-sensitive care and early detection, and exhaled breath provides a rapid, repeatable window into metabolic and inflammatory chemistry. We review real-time breath sampling and analytical technologies and evaluate their readiness for clinical adoption, with emphasis on molecular pathways reflected in [...] Read more.
Diagnostic latency limits time-sensitive care and early detection, and exhaled breath provides a rapid, repeatable window into metabolic and inflammatory chemistry. We review real-time breath sampling and analytical technologies and evaluate their readiness for clinical adoption, with emphasis on molecular pathways reflected in the breath volatilome and in exhaled breath condensate. Real-time mass spectrometry enables kinetic VOC profiling and targeted quantification, while humidity-aware sensors and wearable condensate platforms extend monitoring beyond the laboratory. Pathway-anchored interpretation links breath readouts to ketone handling, isoprenoid metabolism, nitric oxide signaling, lipid peroxidation, uremic nitrogen handling, and microbiome–host co-metabolism, but performance remains vulnerable to confounding, drift, and non-representative comparators. Translation requires standardized breath fraction control, traceable features, robust quality systems, and governed device algorithm stacks so that breath outputs inform decisions and outcomes. Full article
(This article belongs to the Special Issue Biosensors: Emerging Technologies and Real-Time Monitoring)
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30 pages, 8434 KB  
Review
AI-Assisted Molecular Biosensors: Design Strategies for Wearable and Real-Time Monitoring
by Sishi Zhu, Jie Zhang, Xuming He, Lijun Ding, Xiao Luo and Weijia Wen
Int. J. Mol. Sci. 2026, 27(7), 3305; https://doi.org/10.3390/ijms27073305 - 6 Apr 2026
Cited by 9 | Viewed by 1953
Abstract
Artificial intelligence (AI) has become a transformative tool in the field of molecular biosensing, enabling data-driven optimization in sensor design, signal processing, and real-time monitoring. AI promotes the discovery of biomarkers, the design of high-affinity receptors, and the rational engineering of sensing materials, [...] Read more.
Artificial intelligence (AI) has become a transformative tool in the field of molecular biosensing, enabling data-driven optimization in sensor design, signal processing, and real-time monitoring. AI promotes the discovery of biomarkers, the design of high-affinity receptors, and the rational engineering of sensing materials, thereby enhancing sensitivity, specificity, and detection accuracy. In the development of biosensors, AI-assisted strategies have accelerated the identification of novel molecular targets, guided the design of proteins and aptamers with enhanced binding performance, and optimized plasmonic and nanophotonic structures through forward prediction and inverse design frameworks. The integration of artificial intelligence has significantly enhanced the performance of various biosensing platforms, including optical, electrochemical, and microfluidic biosensors. It also enabled automatic feature extraction, noise reduction, dimensionality reduction, and multimodal data fusion, overcoming the challenges posed by complex signals, environmental interference, and device variations. These capabilities are particularly crucial for wearable molecular biosensors, as low signal strength, motion artifacts, and fluctuations in physiological conditions impose strict requirements on robustness and real-time reliability. This review systematically summarizes the latest advancements in AI-assisted molecular biosensors, highlighting representative sensing strategies and algorithms for wearable and real-time monitoring, and discusses the current challenges and future development opportunities of intelligent biosensing technologies. Full article
(This article belongs to the Special Issue Biosensors: Emerging Technologies and Real-Time Monitoring)
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29 pages, 1967 KB  
Review
Small-Molecule Detection in Biological Fluids: The Emerging Role of Potentiometric Biosensors
by Nikola Lenar and Beata Paczosa-Bator
Int. J. Mol. Sci. 2025, 26(23), 11604; https://doi.org/10.3390/ijms262311604 - 29 Nov 2025
Cited by 8 | Viewed by 1515
Abstract
Detecting small molecules in biological fluids is essential for diagnosing diseases, monitoring therapy, and studying how the body works. Traditional biosensing methods—such as amperometric, optical, or piezoelectric systems—offer excellent sensitivity but often rely on complex instruments, additional reagents, or time-consuming sample preparation. Potentiometric [...] Read more.
Detecting small molecules in biological fluids is essential for diagnosing diseases, monitoring therapy, and studying how the body works. Traditional biosensing methods—such as amperometric, optical, or piezoelectric systems—offer excellent sensitivity but often rely on complex instruments, additional reagents, or time-consuming sample preparation. Potentiometric biosensors, by contrast, provide a simpler, low-power, and label-free alternative that can operate directly in biological environments. This review explores the latest progress in potentiometric biosensing for small-molecule detection, focusing on new solid-contact materials and advanced sensing membranes and compact device designs. We also discuss key challenges, including biofouling, matrix effects, and signal drift, together with promising strategies such as antifouling coatings, nanostructured interfaces, and calibration-free operation. Finally, we highlight how combining potentiometric sensors with artificial intelligence, digital data processing, and flexible electronics is shaping the future of personalized and point-of-care diagnostics. By summarizing recent advances and identifying remaining barriers, this review aims to show why potentiometric biosensors are becoming a powerful and versatile platform for next-generation biomedical analysis. Full article
(This article belongs to the Special Issue Biosensors: Emerging Technologies and Real-Time Monitoring)
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