Biosensors

17 pages, 4097 KB

Open AccessArticle

Morphological and Thermographic Factors of the Lower Limbs Before Competition and Their Impact on Performance at the Spanish National Cross Country Championships

by Alessio Cabizosu, Victor Ruiz-Angui, Carmen Carazo-Díaz, Francisco Javier Martínez-Noguera and Pedro E. Alcaraz

Biosensors 2026, 16(7), 369; https://doi.org/10.3390/bios16070369 - 7 Jul 2026

Abstract

Introduction: Cross-country running performance is influenced by a complex interaction of physiological, biomechanical, and morphological factors. Recently, infrared thermography (IRT) has emerged as a non-invasive method to assess skin temperature (TSK) and detect potential asymmetries associated with neuromuscular status, fatigue, and injury risk. [...] Read more.

Introduction: Cross-country running performance is influenced by a complex interaction of physiological, biomechanical, and morphological factors. Recently, infrared thermography (IRT) has emerged as a non-invasive method to assess skin temperature (TSK) and detect potential asymmetries associated with neuromuscular status, fatigue, and injury risk. However, limited evidence exists regarding its relationship with competitive performance in endurance athletes. Methods: An observational study, conducted with STROBE guidelines, included 24 national-level cross-country athletes competing in the 2026 Spanish National Championships. Pre-competition assessments comprised bilateral thermographic analysis of the anterior and posterior thigh and leg regions, alongside some anthropometric measurements (thigh and leg circumferences) following ISAK standards. Performance was evaluated using official race times. Independent t-tests and linear regression models were applied to assess sex differences and associations between variables. Results: No significant sex differences were observed in thigh circumference, whereas males presented significantly greater leg volume (right p = 0.020; left p = 0.042). Thermographic analysis showed no differences in bilateral thermal asymmetry (ΔTSK) between sex quadriceps (p = 0.077), hamstrings (p = 0.695), shins (p = 0.510), and calves (p = 0.194); however, higher absolute temperatures were observed in males in specific thigh regions (right anterior p = 0.039, right posterior p = 0.015, left posterior p = 0.020). Males achieved significantly faster race times during the first four laps, t1 (p ≤ 0.001), t2 (p = 0.002), t3 (p = 0.002), and t4 (p = 0.008), but there was no difference in the fifth lap, t5 (p = 0.179). Statistically significant correlations were observed between temperature differences in the various anatomical regions and competition results during the first four laps, in three of the four regions analyzed (anterior thigh p = 0.035, posterior thigh p = 0.010, anterior leg p ≤ 0.001). Conclusions: Pre-competition thermal asymmetry of the lower limbs appears to be negatively associated with endurance performance, potentially reflecting suboptimal neuromuscular status or incomplete recovery. IRT represents a practical and sensitive tool for monitoring athletes’ physiological readiness. Full article

(This article belongs to the Section Biosensor and Bioelectronic Devices)

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32 pages, 1903 KB

Open AccessReview

Research Advances in Diagnostic Methods for Prevalent Neurological Diseases

by Mengli Lv, Xiaojie Sun and Xinpeng Wang

Biosensors 2026, 16(7), 368; https://doi.org/10.3390/bios16070368 - 6 Jul 2026

Abstract

Global population aging has emerged as a major driver of the growing burden of neurological diseases, highlighting the urgent demand for advances in early diagnosis, prevention, and rehabilitation. These conditions are typically characterized by insidious onset and irreversible progression, yet their clinical management [...] Read more.

Global population aging has emerged as a major driver of the growing burden of neurological diseases, highlighting the urgent demand for advances in early diagnosis, prevention, and rehabilitation. These conditions are typically characterized by insidious onset and irreversible progression, yet their clinical management remains critically compromised by substantial diagnostic delays, representing an intractable bottleneck for existing detection technologies. Therefore, the development of precise, early-stage detection technologies is crucial for expanding the therapeutic window and improving long-term clinical outcomes, addressing a critical unmet clinical need. Herein, we review and compare precision detection strategies for neurological diseases, focusing on the types and mechanisms of mainstream biosensing platforms. Based on the classification of detection substrates and signal transduction mechanisms, four major bio-detection branches are analyzed, including liquid, exosomal, imaging, and digital biomarker detection, with representative studies demonstrating detection limits reaching femtomolar concentrations, clinical diagnostic sensitivities exceeding 90%, and classification accuracies comparable to or surpassing conventional imaging modalities. The inherent advantages and limitations of each biosensing technology are also comprehensively discussed. This review underscores that future research on neurological biomarker sensing is trending toward multimodal integration, which enables the construction of more robust early warning and prognostic assessment systems. This work aims to provide valuable theoretical insights for clinical translation of relevant sensing technologies and integrated diagnostic and treatment strategies, thereby facilitating the progress of early intervention and rehabilitation for common neurological diseases. Full article

(This article belongs to the Special Issue Biosensors for Monitoring and Diagnostics, 2nd Edition)

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35 pages, 2633 KB

Open AccessReview

Advances in Optical Fiber Sensors for Multi-Analyte Biochemical Detection

by Jianwei Huang, Fan Jia, Shaoxiang Duan and Bo Liu

Biosensors 2026, 16(7), 367; https://doi.org/10.3390/bios16070367 - 6 Jul 2026

Abstract

Optical fiber multi-analyte biosensors have become an important cutting-edge technology for the simultaneous detection of multiple biochemical substances in complex samples due to their unique advantages such as small size, anti-interference capability, and remote and label-free detection. This paper systematically reviews the recent [...] Read more.

Optical fiber multi-analyte biosensors have become an important cutting-edge technology for the simultaneous detection of multiple biochemical substances in complex samples due to their unique advantages such as small size, anti-interference capability, and remote and label-free detection. This paper systematically reviews the recent research progress of optical fiber multi-analyte biosensors in the field of simultaneous detection of various types of targets. The review is organized by detection target type and elaborates on the simultaneous detection of biomarkers and proteins, viruses and bacteria, biological metabolites and nutrients, heavy metal ions, gases, organic pollutants, cells, and mixed detection of different types of biochemical substances. The advantages and disadvantages of existing optical fiber multi-analyte biosensors are summarized. Key technical challenges are also discussed, including issues of selectivity, long-term stability, real-sample validation, and system integration that currently hinder practical deployment. Finally, the future challenges and development directions of optical fiber multi-analyte biosensors are briefly discussed, providing references for relevant research teams. Full article

(This article belongs to the Special Issue Advanced Optics and Photonics in Biosensing Applications)

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22 pages, 2291 KB

Open AccessReview

Synthetic Microbial Community Biosensors: From Engineered Ecosystems to Modular Detection Platforms with AI-Driven Intelligence

by Liangshu Hu, Yipei Yang, Shiqi Xia, Wenhui Mao, Ying Shang, Yuzhen Wang, Huijuan Yang and Mingzhang Guo

Biosensors 2026, 16(7), 366; https://doi.org/10.3390/bios16070366 - 6 Jul 2026

Abstract

Synthetic microbial community (SynCom) biosensors are emerging from the convergence of whole-cell biosensing, synthetic ecology, and computational design. Conventional whole-cell biosensors (WCBs) use a single microbial chassis to convert analyte recognition into optical, electrochemical, gaseous, or growth-linked outputs. This compact architecture supports low-cost [...] Read more.

Synthetic microbial community (SynCom) biosensors are emerging from the convergence of whole-cell biosensing, synthetic ecology, and computational design. Conventional whole-cell biosensors (WCBs) use a single microbial chassis to convert analyte recognition into optical, electrochemical, gaseous, or growth-linked outputs. This compact architecture supports low-cost and field-oriented detection, but it can be limited by cellular burden, narrow dynamic range, environmental interference, and difficulty in interpreting multicomponent signals. Natural microbial consortia provide an ecological template in which sensing, transformation, stress tolerance, and response are distributed across interacting populations. SynCom biosensors seek to translate this logic into engineered platforms with defined members, assigned functional roles, designed communication, and interpretable readouts. This review traces the transition from WCBs to natural consortia and engineered multicellular biosensors, emphasizing functional partitioning, signal routing, community control, and artificial intelligence (AI)-assisted design. AI is discussed as a practical tool for narrowing design space, predicting interactions, decoding complex biosignals, and supporting adaptive operation. Key challenges remain in community stability, orthogonal communication, data quality, biosafety, standardization, and real-sample validation. Future progress will depend on parsimonious community design, reliable containment, quantitative validation, and computational workflows that connect community composition with sensing performance. Full article

(This article belongs to the Special Issue Advanced Biosensors Based on Molecular Recognition)

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Graphical abstract

37 pages, 14118 KB

Open AccessReview

Research Progress and Screening Strategies of Natural Product-Derived Neuraminidase Inhibitors

by Jun Duan, Xinjie Guo, Pinghua Sun, Haibo Zhou and Xiangjiu He

Biosensors 2026, 16(7), 365; https://doi.org/10.3390/bios16070365 - 3 Jul 2026

Abstract

Seasonal epidemics and high variability of influenza viruses pose a severe threat to global public health security. Neuraminidase, a key functional enzyme in the life cycle of influenza viruses, represents an important target for anti-influenza drug development. Given the continuous emergence of drug-resistant [...] Read more.

Seasonal epidemics and high variability of influenza viruses pose a severe threat to global public health security. Neuraminidase, a key functional enzyme in the life cycle of influenza viruses, represents an important target for anti-influenza drug development. Given the continuous emergence of drug-resistant strains against first-line clinical neuraminidase inhibitors (NAIs) such as oseltamivir, there is an urgent need to develop novel, broad-spectrum, and resistance-overcoming NAIs. Natural products, characterized by structural diversity and a wide range of biological activities, provide abundant resources for the discovery of new NAIs. Recent advances in computer-aided drug design, intelligent analytical platforms, and modern screening technologies have accelerated the identification of natural product-derived NAIs. In particular, biosensor-based strategies, including electrochemical, fluorescence, bioluminescence, and surface-enhanced Raman scattering biosensors, have demonstrated significant advantages in sensitivity, selectivity, rapid response, and high-throughput screening. In combination with computational methods and experimental approaches such as affinity ultrafiltration and activity-guided separation, these technologies have promoted the development of intelligent, precise, and multimodal screening platforms. Looking forward, the integration of biosensor-based high-throughput screening platforms with artificial intelligence algorithms is expected to drive the next generation of natural product screening platforms and facilitate the efficient discovery and clinical translation of novel NAIs. This paper systematically reviews the research progress of screening strategies for natural product-derived NAIs; introduces representative natural active NAIs, including phenols, terpenoids, and alkaloids; and prospects future development directions, aiming to provide a scientific reference for the efficient discovery of NAIs from natural products. Full article

(This article belongs to the Special Issue Advanced Biosensors for Screening Medicinal Natural Products)

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30 pages, 17878 KB

Open AccessReview

Advances in Detecting Viable/Dead Foodborne Microorganisms Using Diverse Functional Nucleic Acid-Based Molecular Recognition

by Yanger Liu, Huifu Yuan, Juan Zhang, Xiaoyun Sun, Peili Wang, Pazilaiti Yiming, Ailiang Chen and Yanyang Xu

Biosensors 2026, 16(7), 364; https://doi.org/10.3390/bios16070364 - 3 Jul 2026

Abstract

Accurately detecting viable foodborne pathogenic bacteria is essential for food safety risk assessments and public health interventions. Traditional plate counting is time-consuming and operationally cumbersome. Immunological assays are unable to distinguish viable from dead cells, whereas conventional nucleic acid amplification is often affected [...] Read more.

Accurately detecting viable foodborne pathogenic bacteria is essential for food safety risk assessments and public health interventions. Traditional plate counting is time-consuming and operationally cumbersome. Immunological assays are unable to distinguish viable from dead cells, whereas conventional nucleic acid amplification is often affected by residual DNA originating from dead bacteria. These limitations render conventional approaches inadequate for rapid and precise field detection. Functional nucleic acids (FNAs) offer a promising alternative for viability detection because of their high sensitivity, specificity, target diversity, and programmable integrability. This review provides a systematic overview of molecular recognition strategies and FNA-based detection technologies for identifying viable foodborne microorganisms. We categorize the biomarkers targeted by FNAs into nucleic acids, surface structures, and metabolic activities. Building on this categorization, we examine the core principles and technological evolution of primers, aptamers, DNAzymes, guide nucleic acids, and oligonucleotide probes in viability discrimination. We then outline the practical applications of these technologies across the food supply chain and discuss the remaining challenges and future directions in the field. Ultimately, this work provides a theoretical reference and practical guidance for ensuring food safety and advancing precise microbial risk management. Full article

(This article belongs to the Special Issue Advanced Biosensors Based on Molecular Recognition)

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11 pages, 1651 KB

Open AccessArticle

Electrochemical Aptasensor Based on rGO@gold Nanoparticles for Neuropeptide Y Detection

by Bin Gu, Weilong Tu, Biao Zou, Yuxian Chen, Qiaolin Fan, Cong Zhang, Xiao Li and Tao Hu

Biosensors 2026, 16(7), 363; https://doi.org/10.3390/bios16070363 - 2 Jul 2026

Abstract

Neuropeptide Y (NPY) is a stress-modulating neuropeptide and a promising biomarker for non-invasive assessment. Herein, a sensitive electrochemical aptasensor was developed on reduced graphene oxide/gold nanoparticle (rGO/AuNP)-modified screen-printed electrodes for selective NPY detection. A methylene blue (MB)-labeled NPY-specific aptamer was immobilized on the [...] Read more.

Neuropeptide Y (NPY) is a stress-modulating neuropeptide and a promising biomarker for non-invasive assessment. Herein, a sensitive electrochemical aptasensor was developed on reduced graphene oxide/gold nanoparticle (rGO/AuNP)-modified screen-printed electrodes for selective NPY detection. A methylene blue (MB)-labeled NPY-specific aptamer was immobilized on the electrode surface through Au–S chemistry, and square-wave voltammetry (SWV) was used for signal readout. The rGO/AuNP-modified interface provided high conductivity and a large effective surface area, facilitating electron transfer and probe immobilization. Under optimized conditions, the aptasensor exhibited a linear detection range of 10–10,000 pg mL⁻¹ in PBS with a low detection limit of 1.17 pg mL⁻¹ and good linearity (R² = 0.991). In addition, the sensor showed satisfactory selectivity, reproducibility, and mechanical stability. Recovery tests in artificial sweat yielded recoveries of 91.8–107.8% with relative standard deviations below 5%, demonstrating good analytical accuracy in complex matrices. Combined with an agarose-hydrogel-assisted sampling interface and a reverse-iontophoresis-compatible wearable platform, this low-cost and facile sensing strategy provides a portable proof-of-concept approach for NPY analysis in artificial sweat and shows potential for future wearable-oriented biofluid monitoring. Full article

(This article belongs to the Special Issue Recent Advances in Hydrogels-Based Biosensors for Point-of-Care Testing—2nd Edition)

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18 pages, 8744 KB

Open AccessArticle

Wearable Wireless EMG Sensors for Monitoring Post-Error Neuromuscular Responses During a Sport-Specific Inhibitory Control Task

by Mauricio Barramuño-Medina, Pablo Valdés-Badilla, Pablo Aravena-Sagardia, Jordan Hernandez-Martínez, Edgar Vásquez-Carrasco, Tatiana Romero-Arias, Claudio Bascour-Sandoval and Germán Gálvez-García

Biosensors 2026, 16(7), 362; https://doi.org/10.3390/bios16070362 - 1 Jul 2026

Abstract

Post-error slowing (PES) is commonly considered a behavioral marker of post-error adaptation. However, adaptive processes may also emerge through subtle modifications of motor preparation, particularly in combat sports such as taekwondo (TKD), where maintaining rapid motor execution is essential. This study examined post-error [...] Read more.

Post-error slowing (PES) is commonly considered a behavioral marker of post-error adaptation. However, adaptive processes may also emerge through subtle modifications of motor preparation, particularly in combat sports such as taekwondo (TKD), where maintaining rapid motor execution is essential. This study examined post-error neuromuscular adjustments during a TKD-specific kicking task by comparing standard Go and post-error Go trials for changes in muscle onset latency, peak electromyographic amplitude, and co-contraction indices. Twenty-eight TKD athletes (14 novice and 14 advanced) performed a sport-specific Go/No-Go task while wearable wireless surface electromyography sensors recorded lower-limb neuromuscular activity from eight lower-limb muscles. Muscle onset latency, peak electromyographic amplitude, co-contraction indices, and reaction time were analyzed using linear mixed-effects models. Post-error Go trials showed significant alterations in muscle onset latency in posterior lower-limb muscles involved in propulsion and movement preparation (semitendinosus, biceps femoris, lateral gastrocnemius, and soleus), with muscle activation occurring closer to the foot take-off. No significant differences were observed in reaction time, peak electromyographic amplitude, or co-contraction indices, and expertise and age did not modulate these effects. These findings suggest that error-related motor adjustments may be expressed through changes in muscle activation timing rather than overt behavioral slowing. Full article

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

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12 pages, 763 KB

Open AccessArticle

Agreement and Reliability of a Digital Incentive Spirometer Compared with a Volume-Oriented Incentive Spirometry Device Across Different Age Groups

by Kornanong Yuenyongchaiwat, Lucksanaporn Mahawong, Chaopraya Nenmanee, Sasipa Buranapuntalug and Chusak Thanawattano

Biosensors 2026, 16(7), 361; https://doi.org/10.3390/bios16070361 - 29 Jun 2026

Abstract

Incentive spirometry is widely used in respiratory rehabilitation to enhance lung expansion and prevent postoperative pulmonary complications. However, conventional devices, including volume-oriented and flow-oriented incentive spirometers, rely on subjective visual interpretation, which may limit measurement accuracy and clinical utility. A digital incentive spirometer [...] Read more.

Incentive spirometry is widely used in respiratory rehabilitation to enhance lung expansion and prevent postoperative pulmonary complications. However, conventional devices, including volume-oriented and flow-oriented incentive spirometers, rely on subjective visual interpretation, which may limit measurement accuracy and clinical utility. A digital incentive spirometer (DIS) has been developed to provide objective, real-time measurements of inspiratory volume. This study aimed to evaluate the agreement and reliability between the DIS and a volume-oriented incentive spirometer (VIS) across different age groups. A cross-sectional study was conducted in 150 participants aged 7–80 years, stratified into five age groups with equal sex distribution. Inspiratory volume was measured simultaneously using both devices. Agreement was assessed using Bland–Altman analysis, and reliability was evaluated using intraclass correlation coefficients (ICC). The DIS demonstrated good overall reliability (ICC = 0.868, 95% CI: 0.821–0.903). The mean difference was 48.69 mL, indicating slight overestimation by the DIS. However, the limits of agreement were wide (−469.24 to 566.63 mL), suggesting limited interchangeability. Reliability varied across age groups, with the highest ICC in older adults and the lowest in adolescents. The DIS showed good reliability but limited agreement with the VIS. Full article

(This article belongs to the Section Biosensors and Healthcare)

23 pages, 2537 KB

Open AccessArticle

Exploring Tetrazolium Salt Reduction by Mono- and Bimetallic Nanoparticles as an Alternative Signal-Generation Strategy for Point-of-Care Diagnostics

by Paweł Stańczak, Maciej Trzaskowski and Mariusz Pietrzak

Biosensors 2026, 16(7), 360; https://doi.org/10.3390/bios16070360 - 29 Jun 2026

Abstract

Nanozymes, nanomaterials that mimic enzymatic activity, offer superior stability, tunability, and lower production costs compared to natural enzymes. To date, most nanozyme-based point-of-care (PoC) diagnostic systems have relied on oxidation reactions, such as oxidation of 3,3′,5,5′-tetramethylbenzidine, which often suffer from limited substrate stability [...] Read more.

Nanozymes, nanomaterials that mimic enzymatic activity, offer superior stability, tunability, and lower production costs compared to natural enzymes. To date, most nanozyme-based point-of-care (PoC) diagnostic systems have relied on oxidation reactions, such as oxidation of 3,3′,5,5′-tetramethylbenzidine, which often suffer from limited substrate stability and high background signal. This study investigates reduction reactions, particularly those involving tetrazolium salts, as an alternative route for signal generation in PoC devices. For this purpose, monometallic and bimetallic gold, palladium, and platinum nanoparticles were synthesized via chemical reduction using poly(vinyl alcohol) as a stabilizing agent. The resulting nanoparticles were uniform in size and morphology. Their catalytic performance was confirmed through the reduction of 4-nitrophenol. The tetrazole salts were selected as promising substrates for application in PoC settings and further explored by examining the nanozyme-based reduction of 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT). The nanozymes catalyzed the reduction of MTT in the presence of sodium borohydride, producing a distinct colorimetric signal under selected conditions. The effects of reducing agent concentration, buffer pH, and potential interferents were evaluated, with performance suitable for PoC devices achieved at basic pH and low borohydride concentration. Interference studies showed negligible MTT reduction in the presence of physiological levels of ascorbic acid, human serum albumin, and 10% concentration of human serum. Finally, a proof-of-concept lateral flow assay demonstrated successful signal generation through nanozyme-catalyzed MTT reduction. Results establish tetrazolium salts as suitable substrates for nanozyme-enhanced PoC diagnostics and highlight reduction-based chromogenic systems as a viable alternative to traditional oxidation-based assays. Full article

(This article belongs to the Special Issue Advances in Nanozyme-Based Biosensors)

37 pages, 38138 KB

Open AccessReview

Electrochemical (Bio)Sensors for Antibiotic Residue Detection in Aquatic Animal Products: A Review

by Meiqing Yang, Qiuhe Hu, Suiping Wang, Haozi Lu and Song Liu

Biosensors 2026, 16(7), 359; https://doi.org/10.3390/bios16070359 - 28 Jun 2026

Abstract

The rapid and sensitive quantification of antibiotic residues in aquatic animals is crucial for ensuring food safety and protecting public health. Electrochemical (bio)sensors show great potential in this field due to their quick response time, low cost, and ease of miniaturization. This paper [...] Read more.

The rapid and sensitive quantification of antibiotic residues in aquatic animals is crucial for ensuring food safety and protecting public health. Electrochemical (bio)sensors show great potential in this field due to their quick response time, low cost, and ease of miniaturization. This paper presents a systematic review of advances in the electrochemical detection of eight classes of antibiotics: fluoroquinolones, sulfonamides, amphenicols, tetracyclines, nitrofurans, macrolides, aminoglycosides, and β-lactams in aquatic animal samples. It covers four types of sensors: direct electrochemical sensors, immunosensors, aptasensors, and molecularly imprinted sensors. The review emphasizes the electrochemical behavior of the targets, interface design, recognition elements, signal amplification strategies, and validation using real samples. It also summarizes the sample pretreatment methods for different classes of antibiotics. Finally, the paper analyzes key challenges related to adaptability to complex matrices, consistency in sample preparation, and validation with real-world samples. Additionally, it proposes future directions for development in this field. Full article

(This article belongs to the Special Issue Electrochemical Biosensors for Food Analysis)

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30 pages, 7358 KB

Open AccessArticle

MalariaNet: A Microcontroller-Deployable Malaria-Microscopy Detector for Point-of-Care Biosensing Under Leakage-Free Evaluation

by Mengdi Hou, Gaoming He, Zongchang Liu, Jianbo Huang and Heliang Zou

Biosensors 2026, 16(7), 358; https://doi.org/10.3390/bios16070358 - 28 Jun 2026

Abstract

Compact malaria detectors for microcontrollers are almost always benchmarked on the NIH Malaria dataset with a per-cell random split. This leaks slide identity because the cells come from only about 200 slides and a random split mixes same-slide cells across training and testing. [...] Read more.

Compact malaria detectors for microcontrollers are almost always benchmarked on the NIH Malaria dataset with a per-cell random split. This leaks slide identity because the cells come from only about 200 slides and a random split mixes same-slide cells across training and testing. The leakage also distorts architectural conclusions: under a leakage-free slide-disjoint protocol, per-module ablation gains collapse to seed noise and an apparent cross-site robustness variant loses most of its advantage. Headline accuracy falls from 97.1% to 95.6%, a gap that sits within the cross-seed noise, and all eight tested architectures move the same way. The evidence is this unanimous direction, not the size of any single gap. This benchmarking finding is our main contribution. Two results survive. First, MalariaNet, our 21 K-parameter detector, reaches about 95.6% accuracy at 23.5 KB of INT8 weights, with a numerically faithful on-chip forward on an STM32H743 at a 1.2 FPS triage rate. Second, it is among the most interference-robust of the eight networks and the most robust microcontroller-deployable model. Scope is limited to single P. falciparum thin-smear cells. Slide-disjoint evaluation should become standard, and we provide MalariaNet as the first leakage-free, on-device-validated point-of-care malaria reference. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Machine Learning (ML) in Biosensors: Innovation, Application, and Challenge)

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16 pages, 6499 KB

Open AccessArticle

Manganese-Doped Carbon Dots for Sensitive Fluorescence Detection of Ciprofloxacin in Environmental and Pharmaceutical Samples

by Jian Xue, Wenli Fu, Luhang Liu, Qizhong Qin, Jieying Gao, Yingli Li and Anyi Chen

Biosensors 2026, 16(7), 357; https://doi.org/10.3390/bios16070357 - 26 Jun 2026

Abstract

A simple and sensitive fluorescence sensing method was developed for ciprofloxacin (CIP) determination based on manganese-doped carbon dots (Mn-CDs). The Mn-CDs were synthesized through a one-step hydrothermal method using anhydrous citric acid and manganese chloride tetrahydrate as precursors. The prepared Mn-CDs exhibited good [...] Read more.

A simple and sensitive fluorescence sensing method was developed for ciprofloxacin (CIP) determination based on manganese-doped carbon dots (Mn-CDs). The Mn-CDs were synthesized through a one-step hydrothermal method using anhydrous citric acid and manganese chloride tetrahydrate as precursors. The prepared Mn-CDs exhibited good dispersibility, uniform nanoscale morphology, abundant surface functional groups and favorable fluorescence properties. The incorporation of Mn was designed to introduce coordination-related binding sites for CIP, thereby enhancing the interaction between Mn-CDs and CIP. Under excitation at 330 nm, the Mn-CDs showed a pronounced fluorescence enhancement response toward CIP, enabling their use as fluorescent probes for quantitative detection. Under the optimized conditions, the fluorescence intensity increased linearly with CIP concentration over the range of 20 nM–10 μM, with a detection limit of 1.12 nM. The proposed sensing system exhibited satisfactory selectivity toward CIP over various potentially interfering substances and good storage stability. The practicality of the method was further verified by analysis of pond water samples, affording recoveries of 86–118% with relative standard deviations below 5%. In addition, the method showed acceptable applicability for CIP determination in different pharmaceutical formulations. These results indicate that the Mn-CD-based fluorescent probe provides a convenient, sensitive and promising platform for CIP determination in environmental and pharmaceutical samples. Full article

(This article belongs to the Special Issue Applications of Nanomaterials in Optical and Photonic Biosensors)

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49 pages, 7837 KB

Open AccessReview

Green Synthesis of Fluorescent Carbon Dots and AI-Driven New Paradigms: A Comprehensive Review

by Qian Wang, Huiyao Liang, Xiaofeng Chang, Huili He, Rong Li, Jian Mao, Weiwei Han, Ying Tang, Yongfei Li, Maogang Li and Qunzheng Zhang

Biosensors 2026, 16(7), 356; https://doi.org/10.3390/bios16070356 - 26 Jun 2026

Abstract

Carbon dots (CDs) have been widely employed in diverse fields by virtue of their excellent water solubility, low toxicity, high fluorescence stability, and favorable biocompatibility. Nevertheless, traditional preparation methods for CDs generally suffer from drawbacks that run counter to the concept of green [...] Read more.

Carbon dots (CDs) have been widely employed in diverse fields by virtue of their excellent water solubility, low toxicity, high fluorescence stability, and favorable biocompatibility. Nevertheless, traditional preparation methods for CDs generally suffer from drawbacks that run counter to the concept of green chemistry. This review comprehensively summarizes the green synthesis technologies, machine learning (ML)-assisted synthesis strategies, and diversified application fields of fluorescent CDs. Specifically, it discusses the characteristics of synthetic organic molecular/polymeric materials and natural sources (e.g., plants and fruit peels, etc.) and elaborates on the top-down and bottom-up green synthesis methods, analyzing their advantages. It also focuses on ML’s core role in precisely regulating CD emission wavelengths, enhancing and predicting fluorescence quantum yields to optimize synthesis processes. Additionally, this review highlights the representative biological applications of CDs, including biosensing and biomedicine (e.g., bioimaging, drug delivery, and photodynamic therapy), while briefly covering their applications in other fields. Finally, the review points out current challenges in green synthesis, ML-assisted applications and industrial translation, and puts forward future research directions, aiming to promote the greenization, intellectualization and large-scale development of CDs. Full article

(This article belongs to the Section Biosensor Materials)

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23 pages, 3639 KB

Open AccessArticle

A Label-Free Cell-Based Biosensor Method for Ethanol Quantification Using Temperature-Induced Spontaneous Cell Detachment

by Derick Yongabi, Alex Krane, Heloisa Espreafico Guelerman Ramos, Sofia Xavier Bustia, Jonas Gruber, Michael J. Schöning, Frank Delvigne and Patrick Wagner

Biosensors 2026, 16(7), 355; https://doi.org/10.3390/bios16070355 - 25 Jun 2026

Abstract

Rapid, low-cost ethanol quantification is vital for beverage quality control, biofuel production, and pharmaceutical applications, yet current approaches are costly, reagent- or label-dependent, or rely on spectroscopy with substantial sample preparation. We introduce a purely cell-based, label-free biosensor that exploits temperature-gradient-induced spontaneous detachment [...] Read more.

Rapid, low-cost ethanol quantification is vital for beverage quality control, biofuel production, and pharmaceutical applications, yet current approaches are costly, reagent- or label-dependent, or rely on spectroscopy with substantial sample preparation. We introduce a purely cell-based, label-free biosensor that exploits temperature-gradient-induced spontaneous detachment of Saccharomyces cerevisiae from a chip surface. The readout is the detachment half-time, t_d₅₀, derived from time-resolved changes in interfacial thermal resistance, R_th, at the solid–liquid interface. Cells were pre-exposed to ethanol (0–70% v/v) and the detachment kinetics monitored using the heat transfer method (HTM). Under these conditions, cells display a pronounced non-monotonic t_d₅₀ response with a peak around 20% v/v ethanol. Overall, the t_d₅₀ rises from ~45 min (0% ethanol) to ≳10 h (20%) and then decreases, with no detachment at 60% and beyond. Critically, cell quality gates the detachment window. Fresh yeast responds up to ~50%, whereas aged yeast ceases to detach above ~8%, demonstrating a dual-function assay. Complementary measurements show that ethanol decreases surface tension monotonically, as expected, while optical/SEM imaging reveals aggregation above the detachment window. Requiring only a heater and a temperature probe, this platform offers a compact and low-cost strategy for ethanol sensing. Its applicability in a complex matrix is further demonstrated using whiskey diluted to selected alcohol concentrations, which produced responses consistent with the ethanol calibration trend. Potentially, it also offers a thermal assay for real-time monitoring of microbial cell quality across biotechnology and bioengineering applications. Considering ethanol as a proxy for drugs, the strategy may also support label-free drug screening on cells. At a fundamental level, the non-monotonic effect of ethanol, and especially the sharp maximum at 20%, remains unresolved and invites further studies. Full article

(This article belongs to the Section Biosensors and Healthcare)

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27 pages, 1221 KB

Open AccessArticle

Digital and Remote Interventions for Musculoskeletal Aging: Real-Time Muscle Strain Severity Detection Using Artificial Intelligence

by Zulaikha Fatima, Abdullah, Nida Hafeez, Rolando Quintero Téllez, Miguel Jesús Torres Ruiz, Carlos Guzmán Sánchez Mejorada, Miguel Félix Mata-Rivera and Roberto Zagal-Flores

Biosensors 2026, 16(7), 354; https://doi.org/10.3390/bios16070354 - 25 Jun 2026

Abstract

As global populations grow and technology advances, daily life is increasingly shaped by digital systems such as computers and smart devices. However, prolonged device use has contributed to increasing physical and mental health concerns, particularly those associated with poor sitting posture. Posture-related strain [...] Read more.

As global populations grow and technology advances, daily life is increasingly shaped by digital systems such as computers and smart devices. However, prolonged device use has contributed to increasing physical and mental health concerns, particularly those associated with poor sitting posture. Posture-related strain is frequently overlooked and contributes to musculoskeletal discomfort, including back, neck, shoulder, and wrist pain, and may also be associated with sleep disturbances and elevated stress levels. To the best of our knowledge and based on the existing literature, this is the first study to introduce a machine learning-based framework for advanced muscle strain severity classification using Internet of Things (IoT) devices that integrates posture monitoring and muscle strain detection into a unified low-cost framework ($23 hardware cost). The primary objective of this work is accurate classification of muscle strain severity, while real-time alerts serve as a secondary ergonomic feedback mechanism. Specifically, this study makes four major contributions. First, we created a novel dataset through real-time acquisition of electromyography (EMG) and posture signals from participants in hospital and industrial environments, capturing diverse muscle strain patterns validated against clinical assessment procedures. Second, we designed a two-part hardware architecture consisting of posture detection (PD) and strain detection (SD) modules using a NodeMCU ESP8266, HC-SR04 ultrasonic sensor, EMG sensor, and buzzer for real-time physiological monitoring, incorporating EMG-specific preprocessing including band-pass filtering, rectification, and RMS smoothing. Third, we proposed and evaluated a hybrid machine learning framework integrating Vision Transformer (ViT) and XGBoost to classify strain severity into three study-specific categories: baseline (EMG RMS < 40 µV), compensatory strain (40–59 µV), and overload (≥60 µV). These categories were used as reproducible severity proxies for machine learning annotation and should not be interpreted as universal biomarkers of structural tissue damage. Finally, the proposed framework achieved a classification accuracy of 99.0% (95% CI: 98.5–99.5%) with an inference latency of 15.2 ms. Full article

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

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16 pages, 1663 KB

Open AccessArticle

Application of Aptamer–Carbon Surfaces for Electrochemical Label-Free Detection of Vancomycin

by Izabela Zaras, Piotr Pieta and Marta Jarczewska

Biosensors 2026, 16(7), 353; https://doi.org/10.3390/bios16070353 - 24 Jun 2026

Abstract

Gold is considered the most widely used surface for the development of aptamer-based layers. However, its high cost, laborious surface-cleaning protocols, and susceptibility of receptor layers to degradation in complex samples, including biological fluids, enforce the search for alternative transducers. One solution is [...] Read more.

Gold is considered the most widely used surface for the development of aptamer-based layers. However, its high cost, laborious surface-cleaning protocols, and susceptibility of receptor layers to degradation in complex samples, including biological fluids, enforce the search for alternative transducers. One solution is the application of carbon materials, which are inexpensive and allow for the use of a wide potential range when electrochemical measurements are performed. Herein, we present studies on the elaboration of aptamer receptor layers formed on carbon macroelectrodes. To achieve this, a one-step procedure for aptamer molecules containing a pyrene or anthracene group at the 5′ end was used, with immobilization via adsorption facilitated by Π–Π interactions between the anchor group and the carbon surface. It was evidenced that using anthracene-modified aptamer and sodium anthraquinone-2-sulfonic acid (AQMS) redox indicator enabled the detection of a model analyte–vancomycin below the millimolar concentration range. It was also revealed that vancomycin can be successfully detected in serum samples, and the aptasensor exhibits good selectivity towards vancomycin. The latter was observed by comparison of responses in PBS containing solely vancomycin and a solution spiked with vancomycin and a mixture of antibiotics. Full article

(This article belongs to the Special Issue Advanced Biosensors for Disease Screening, Monitoring, Diagnosis, and Treatment—2nd Edition)

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16 pages, 2008 KB

Open AccessArticle

AI-Assisted Electrochemical Immunosensing for Matrix-Aware Detection of Aflatoxin M1 and Atrazine in Food Matrices

by Kundan Kumar Mishra, Shanmathi Venkatesan, Sriram Muthukumar and Shalini Prasad

Biosensors 2026, 16(7), 352; https://doi.org/10.3390/bios16070352 - 23 Jun 2026

Abstract

Food contamination by Aflatoxin M1 and Atrazine remains a critical food-safety concern, requiring sensitive detection methods that can operate reliably in complex matrices. Here, we report an AI-assisted antibody-functionalized electrochemical sensing platform for the detection and classification of Aflatoxin M1 and Atrazine across [...] Read more.

Food contamination by Aflatoxin M1 and Atrazine remains a critical food-safety concern, requiring sensitive detection methods that can operate reliably in complex matrices. Here, we report an AI-assisted antibody-functionalized electrochemical sensing platform for the detection and classification of Aflatoxin M1 and Atrazine across corn, corn flour, and protein matrices. The sensor used analyte-specific antibodies immobilized on an electrochemical electrode surface, where target binding produced measurable changes in the interfacial electrochemical response. Sensor performance was evaluated using cyclic voltammetry, coulometry, and electrochemical impedance spectroscopy (EIS), with EIS providing strong frequency-dependent signatures for concentration-dependent analysis. Spike-and-recovery studies further demonstrated the applicability of the platform in food-matrix conditions. To improve interpretation of complex electrochemical signals, full-spectrum EIS features were integrated with machine learning models for concentration-level classification into low, mid, and high groups. The AI workflow achieved an overall classification accuracy of 93.33%, with 96.67% specificity, 93.44% PPV, 96.66% NPV, and 0.982 AUC for Atrazine, and 96.70% specificity, 93.38% PPV, 96.67% NPV, and 0.987 AUC for Aflatoxin M1. In addition, analyte classification between Aflatoxin M1 and Atrazine reached 97.4% accuracy and 0.994 ROC-AUC. Overall, this work demonstrates a matrix-aware electrochemical immunosensing strategy enhanced by AI-based signal interpretation for food contaminant detection. Full article

(This article belongs to the Special Issue Nanobiosensors Based on Electrochemical Principles)

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17 pages, 3843 KB

Open AccessArticle

A Coumarin-Based Probe for Sequential ON–OFF–ON Detection of Cu²⁺ and Biothiols: Naked-Eye Detection, Smartphone RGB Readout and In Vivo Imaging

by Mingjie Wei, Linxin Zheng, Weilong Tian, Xingfeng Wang, Rong Liu, Lijuan Chen and Li Niu

Biosensors 2026, 16(6), 351; https://doi.org/10.3390/bios16060351 - 22 Jun 2026

Abstract

Copper ions (Cu²⁺) and intracellular biothiols are tightly coupled in cellular redox regulation, where copper–thiol coordination governs oxidative stress and metal homeostasis. However, analytical platforms capable of sequentially monitoring Cu²⁺ and biothiols within a single molecular system remain scarce. Herein, [...] Read more.

Copper ions (Cu²⁺) and intracellular biothiols are tightly coupled in cellular redox regulation, where copper–thiol coordination governs oxidative stress and metal homeostasis. However, analytical platforms capable of sequentially monitoring Cu²⁺ and biothiols within a single molecular system remain scarce. Herein, we report a coumarin-based fluorescent probe XDP that enables sequential ON–OFF–ON sensing of Cu²⁺ and biothiols through a coordination–competition mechanism. The imine (C=N) site of XDP selectively coordinates Cu²⁺, leading to fluorescence quenching arising from coordination-induced electronic perturbation and enhanced nonradiative decay. The probe exhibits a linear response toward Cu²⁺ over 1–80 μM with a detection limit of 0.108 μM. Subsequent competitive binding of biothiols (GSH, Cys, and Hcy) releases Cu²⁺ from the complex, thereby restoring fluorescence and enabling detection within 1–30 μM with submicromolar sensitivity. XDP also displays a large Stokes shift (135 nm), which minimizes spectral overlap and improves signal reliability. Notably, Cu²⁺ binding triggers a distinct color change that supports naked-eye detection and smartphone-based RGB quantification. The probe further enables visualization of Cu²⁺ and thiol-triggered signal recovery in living cells and zebrafish. This work establishes a versatile analytical platform for probing copper–thiol interactions in environmental and biological systems. Full article

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

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