Search Results (718)

Chronic kidney disease (CKD) is a progressive global health burden often diagnosed in late stages due to reliance on invasive and centralized blood and urine tests. Saliva, as a non-invasive diagnostic fluid, has emerged as a promising alternative for assessing renal function. This scoping review aims to evaluate the diagnostic accuracy of salivary biomarkers compared to traditional methods, and to explore the potential of emerging biosensing technologies for CKD detection and monitoring. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, and Cochrane Library up to 1 July 2025, following the PRISMA-ScR guidelines. Studies involving adult CKD patients and healthy controls that assessed the diagnostic performance of salivary biomarkers against validated reference standards (e.g., serum creatinine, eGFR) were included. A total of 29 eligible studies were selected after applying predefined inclusion and exclusion criteria. Results: Salivary creatinine and urea were the most frequently assessed biomarkers and demonstrated strong correlations with serum levels (AUCs up to 1.00; sensitivity and specificity frequently >85%). Several studies reported high diagnostic potential for novel salivary markers such as Trimethylamine N-oxide (TMAO), cystatin C, and amino acids. Technological innovations, including electrochemical biosensors and ATR-FTIR spectroscopy, showed promise for enhancing sensitivity and enabling point-of-care testing. However, heterogeneity in sampling protocols and limited data for early-stage CKD were notable limitations. Conclusions: Salivary diagnostics, supported by biosensor technologies, offer a feasible and non-invasive alternative for CKD screening and monitoring. Standardization, broader clinical validation, and integration into dental workflows are key to clinical implementation. Full article

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti₃C₂T_x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10⁻¹⁷ M and a wide linear range (10⁻¹⁴–10⁻⁸ M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection. Full article

Recent progress in microfluidic technologies has led to the development of compact and highly efficient electrochemical platforms, including lab-on-a-chip (LoC) systems, that integrate multiple testing functions into a single, portable device. Combined with smartphone-based electrochemical devices, these systems enable rapid and accurate on-site detection of food contaminants, including pesticides, heavy metals, pathogens, and chemical additives at farms, markets, and processing facilities, significantly reducing the need for traditional laboratories. Smartphones improve the performance of these platforms by providing computational power, wireless connectivity, and high-resolution imaging, making them ideal for in-field food safety testing with minimal sample and reagent requirements. At the core of these systems are electrochemical biosensors, which convert specific biochemical reactions into electrical signals, ensuring highly sensitive and selective detection. Advanced nanomaterials and integration with Internet of Things (IoT) technologies have further improved performance, delivering cost-effective, user-friendly food monitoring solutions that meet regulatory safety and quality standards. Analytical techniques such as voltammetry, amperometry, and impedance spectroscopy increase accuracy even in complex food samples. Moreover, low-cost engineering, artificial intelligence (AI), and nanotechnology enhance the sensitivity, affordability, and data analysis capabilities of smartphone-integrated electrochemical devices, facilitating their deployment for on-site monitoring of food and agricultural contaminants. This review explains how these technologies address global food safety challenges through rapid, reliable, and portable detection, supporting food quality, sustainability, and public health. Full article

The increasing presence of microplastics (MPs) and nanoplastics (NPs) in environmental matrices presents substantial analytical challenges due to their small size and chemical diversity. This study introduces a novel enzymatic biosensor based on the Surface Plasmon Resonance (SPR) platform for the sensitive detection of MPs and NPs, utilizing laccase as the recognition element. Standard plastic particles, including polystyrene (PS, 0.1 µm), polymethyl methacrylate (PMMA, 1.0 µm and 100 µm), and polyethylene (PE, 34–50 µm), were analyzed using SPR angular interrogation along with a fixed-angle scheme. The angular approach revealed a clear relationship between the resonance angle, particle size, and refractive index, while the fixed-angle method, combined with immobilized laccase, facilitated specific detection through enzyme/substrate interactions. The analytical parameters showed detection limits ranging from 7.5 × 10⁻⁴ µg/mL (PE, 34–50 µm) to 253.2 µg/mL (PMMA, 1 µm), with significant differences based on polymer type and enzymatic affinity. Application of the biosensor to real rainwater samples collected from two regions in Mexico (Tula and Molango) confirmed its functionality, although performance varied depending on matrix composition, exhibiting inhibition in samples with high manganese (Mn²⁺), chromium (Cr²⁺), and zinc (Zn²⁺) content. Despite these limitations, the sensor achieved a 113% recovery rate in Tula rainwater, demonstrating its potential for straightforward in situ environmental monitoring. This study highlights the capabilities of laccase-based SPR biosensors in enhancing microplastic detection and underscores the necessity of considering matrix effects for real-world applications. Full article

Enzyme-based biosensors have emerged as a transformative technology, leveraging the specificity and catalytic efficiency of enzymes across various domains, including medical diagnostics, environmental monitoring, food safety, and industrial processes. These biosensors integrate biological recognition elements with advanced transduction mechanisms to provide highly sensitive, selective, and portable solutions for real-time analysis. This review explores the key components, detection mechanisms, applications, and future trends in enzyme-based biosensors. Artificial enzymes, such as nanozymes, play a crucial role in enhancing enzyme-based biosensors by mimicking natural enzyme activity while offering improved stability, cost-effectiveness, and scalability. Their integration can significantly boost sensor performance by increasing the catalytic efficiency and durability. Additionally, lab-on-a-chip and microfluidic devices enable the miniaturization of biosensors, allowing for the development of compact, portable devices that require minimal sample volumes for complex diagnostic tests. The functionality of enzyme-based biosensors is built on three essential components: enzymes as biocatalysts, transducers, and immobilization techniques. Enzymes serve as the biological recognition elements, catalyzing specific reactions with target molecules to produce detectable signals. Transducers, including electrochemical, optical, thermal, and mass-sensitive types, convert these biochemical reactions into measurable outputs. Effective immobilization strategies, such as physical adsorption, covalent bonding, and entrapment, enhance the enzyme stability and reusability, enabling consistent performance. In medical diagnostics, they are widely used for glucose monitoring, cholesterol detection, and biomarker identification. Environmental monitoring benefits from these biosensors by detecting pollutants like pesticides, heavy metals, and nerve agents. The food industry employs them for quality control and contamination monitoring. Their advantages include high sensitivity, rapid response times, cost-effectiveness, and adaptability to field applications. Enzyme-based biosensors face challenges such as enzyme instability, interference from biological matrices, and limited operational lifespans. Addressing these issues involves innovations like the use of synthetic enzymes, advanced immobilization techniques, and the integration of nanomaterials, such as graphene and carbon nanotubes. These advancements enhance the enzyme stability, improve sensitivity, and reduce detection limits, making the technology more robust and scalable. Full article

Gel-type electrofluorochromic (EFC) devices, which reversibly modulate photoluminescence under electrical stimuli, have emerged as versatile platforms for advanced optoelectronic applications. By integrating redox-active luminophores with soft, ion-conductive gel matrices, these systems combine the structural robustness of solids with the ionic mobility of liquids, enabling a high-contrast, flexible, and multifunctional operation. This review provides a comprehensive overview of gel-based EFC technologies, outlining fundamental working principles, device architectures, and key performance metrics such as contrast ratio, switching time, and cycling stability. Gel matrices are categorized into ionogels, organogels, and hydrogels, and their physicochemical properties are discussed in relation to EFC device performance. Recent advances are highlighted across applications ranging from flexible displays and rewritable electronic paper to strain and biosensors, data encryption, smart windows, and hybrid energy-interactive systems. Finally, current challenges and emerging strategies are analyzed to guide the design of next-generation adaptive, intelligent, and energy-efficient optoelectronic platforms. Full article

Amperometric biosensors, due to their high sensitivity, fast response time, low cost, simple control, miniaturization capabilities, and other advantages, are receiving significant attention in the field of medical diagnostics, especially in monitoring blood glucose levels in diabetic patients. In this study, an amperometric glucose biosensor based on immobilized enzyme glucose oxidase (GOx) and bimetallic platinum cobalt (PtCo) nanoparticles was developed. The PtCo nanoparticles, deposited on a graphite rod electrode, exhibited peroxidase-like catalytic properties and were able to electrocatalyze the reduction of H₂O₂. After immobilization of the GOx, an amperometric signal generated by the biosensor was directly proportional to the glucose concentration in the range of 0.04–2.18 mM. The biosensor demonstrated a sensitivity of 19.38 μA mM⁻¹ cm⁻², with a detection limit of 0.021 mM and a quantification limit of 0.064 mM. In addition to this analytical performance, the biosensor exhibited excellent repeatability (relative standard deviation (RSD) was 4.90%); operational and storage stability, retaining 98.93% and 95.33% of its initial response after 26 cycles of glucose detection and over a 14-day period, respectively; and anti-interference ability against electroactive species, as well as exceptional selectivity for glucose and satisfactory reproducibility (RSD 8.90%). Additionally, the biosensor was able to detect glucose levels in blood serum with a high accuracy (RSD 5.89%), indicating potential suitability for glucose determination in real samples. Full article

In the present paper, the interaction between metal oxide nanoparticles and carbon materials was studied, and the results showed a synergetic effect, leading to an improvement in the properties of the obtained hybrid composites. The In₂O₃ NPs were prepared by the precipitation method and thermal treatment at 550 °C. The composites were obtained using an ex situ method, by mixing the In₂O₃ NPs with reduced oxide graphene (rGO) in a ratio of 10:1. The structural, morphological, and chemical composition studies of the In₂O₃ NPs and In₂O₃-rGO composites were investigates by FTIR and EDX spectroscopy, SEM microscopy, and XRD analysis. These techniques have highlighted the obtaining of In₂O₃ of high purity, and crystallinity, with the mean particle size in the range of 8–25 nm, but also, the dispersion of In₂O₃ NPs onto rGO sheets. We examined the influence of the In₂O₃ nanostructure morphology and In₂O₃-rGO composites on the electrochemical properties using cyclic voltammetry. The surface properties of the In₂O₃ and composite films were studied by contact angles, which indicate the maintenance of the hydrophilic nature. The obtained results establish the synergy between the main components to form In₂O₃-rGO, which can be used for the development of biosensors to enhance the device performance. Full article

This numerical study introduces a surface plasmon resonance (SPR)-based biosensor utilizing a kagome lattice-inspired hollow core photonic crystal fiber (PCF) for the highly sensitive detection of various blood biomarkers and analytical components. The sensor is designed to detect key blood biomarkers such as water, glucose, plasma, and hemoglobin (Hb), as well as analytical targets including krypton, sylgard, ethanol, polyacrylamide (PA), and bovine serum albumin (BSA), by monitoring shifts in the resonance wavelength (RW). A dual-polarization approach is employed by analyzing both transverse magnetic (TM) and transverse electric (TE) modes. The proposed sensor demonstrates exceptional performance, achieving maximum wavelength sensitivities (Sw) of 18,900 nm RIU⁻¹ for TM pol. and 16,800 nm RIU⁻¹ for TE pol. Corresponding peak amplitude sensitivities (S_A) of 71,224 RIU⁻¹ for TM pol. and 58,112 RIU⁻¹ for TE pol. were also observed. The peak sensor resolution (S_R) for both modes is on the order of 10⁻⁶ RIU, underscoring its high precision. Owing to its enhanced sensitivity, compact design, and robust dual-polarization capability, the proposed biosensor holds strong promise for point-of-care diagnostics and real-time blood component analysis. Full article

Water pollution poses serious threats to public health and the environment, therefore requiring efficient and scalable monitoring solutions. This paper presents a cyber–physical system (CPS) that integrates paper-based biosensors with an edge IoT architecture and long-range wide area network (LoRaWAN) for real-time assessment of water quality. The biosensors detect pollutants such as arsenic, lead, and nitrates with a detection limit of 0.5 ppb. The system proposed was compared with existing LSTM systems based on two performance metrics: detection accuracy and latency. Paper-based biosensors were fabricated using silver nanoparticle-functionalized substrates to show high sensitivity and low-cost pollutant detection. TCN algorithm deployment at the edge allows for real-time processing for time-series data analysis due to its high accuracy and low latency properties compared with LSTM models, which were mainly chosen due to their usage in most applications dealing with time-series-based analysis. Experimentation was carried out by deploying the developed CPS in controlled environments, simulating pollutants at different levels, and executing the models to test their accuracy in detecting pollutants and the latency of data processing. The TCN framework achieved a detection accuracy of 98.7%, which surpassed LSTM by 92.4%. In addition, TCN reduced latency in processing by 38% to enable fast data analysis and decision making. LoRaWAN allowed for perfect packet transmission of up to 15 km, while the loss rate stayed as low as 2.1%. These results establish the proposed CPS as reliable, efficient, and scalable for real-time water contamination monitoring. Thus, this research introduces the integration of paper-based biosensors with advanced computational frameworks. Full article

Organic photodetectors (OPDs) offer considerable promise for low-power, solution-processable biosensing and imaging applications; however, their performance remains limited by spectral mismatch and interfacial trap states. In this study, a highly sensitive polymer photodiode was developed via trace incorporation (0.8 wt%) of InP/ZnSe/ZnS quantum dots (QDs) into a PTB7-Th:PC₇₁BM bulk heterojunction (BHJ) matrix. This QD doping approach enhanced the external quantum efficiency (EQE) across the 540–660 nm range and suppressed the dark current density at −2 V by passivating interface trap states. Despite a slight decrease in optical absorption at the optimized composition, the internal quantum efficiency (IQE) increased significantly from ~80% to nearly 95% resulting in a net EQE improvement. This suggests that QD incorporation improved charge transport without compromising charge separation efficiency. As a result, the device achieved a specific detectivity (D*) of 1.8 × 10¹³ Jones, representing a 93% improvement over binary BHJs, along with an ultra-low dark current density of 7.76 × 10⁻¹⁰ A/cm². Excessive QD loading, however, led to optical losses and increased dark current, underscoring the need for precise compositional control. Furthermore, the enhanced detectivity led to a 4 dB improvement in the signal-to-noise ratio (SNR) of photoplethysmography (PPG) signals in the target wavelength range, enabling more reliable biophotonic sensing without increased power consumption. This work demonstrates that QD-based spectral and interfacial engineering offers an effective and scalable route for advancing the performance of OPDs, with broad applicability to low-power biosensors and high-resolution polymer–QD imaging systems. Full article

Next-generation pilot suits are evolving into intelligent, adaptive platforms that integrate advanced polymeric materials, smart textiles, and on-body artificial intelligence. High-performance polymers have advanced in mechanical strength, thermal regulation, and environmental resilience, with fabrication methods like electrospinning, weaving, and 3D/4D printing enabling structural versatility and sensor integration. In particular, functional nanomaterials and hierarchical nanostructures contribute critical properties such as conductivity, flexibility, and responsiveness, forming the foundation for miniaturized sensing and integrated electronics. The integration of flexible fiber-based electronics such as biosensors, strain sensors, and energy systems enables real-time monitoring of physiological and environmental conditions. Coupled with on-body AI for multimodal data processing, autonomous decision-making, and adaptive feedback, these systems enhance pilot safety while reducing cognitive load during flight. This review places a special focus on system-level integration, where polymers and nanomaterials serve as both structural and functional components in wearable technologies. By highlighting the role of nanostructured and functional materials within intelligent textiles, we underline a potential shift toward active human–machine interfaces in aerospace applications. Future trends and advancements in self-healing materials, neuromorphic computing, and dynamic textile systems will further elevate the capabilities of intelligent pilot suits. This review discusses interdisciplinary strategies for developing pilot wearables capable of responding to real-time physiological and operational needs. Full article

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

Early and accurate detection of plant diseases is critical for ensuring global food security and agricultural resilience. Ratoon stunting disease (RSD), caused by the bacterium Leifsonia xyli subsp. xyli (Lxx), is among the most economically significant diseases of sugarcane worldwide. Its cryptic nature—characterized by an absence of visible symptoms—renders timely diagnosis particularly difficult, contributing to substantial undetected yield losses across major sugar-producing regions. Here, we report the development of a potential-induced electrochemical (EC) nanobiosensor platform for the rapid, low-cost, and field-deployable detection of Lxx DNA directly from crude sugarcane sap. This method eliminates the need for conventional nucleic acid extraction and thermal cycling by integrating the following: (i) a boiling lysis-based DNA release from xylem sap; (ii) sequence-specific magnetic bead-based purification of Lxx DNA using immobilized capture probes; and (iii) label-free electrochemical detection using a potential-driven DNA adsorption sensing platform. The biosensor shows exceptional analytical performance, achieving a detection limit of 10 cells/µL with a broad dynamic range spanning from 10⁵ to 1 copy/µL (r = 0.99) and high reproducibility (SD < 5%, n = 3). Field validation using genetically diverse sugarcane cultivars from an inoculated trial demonstrated a strong correlation between biosensor signals and known disease resistance ratings. Quantitative results from the EC biosensor also showed a robust correlation with qPCR data (r = 0.84, n = 10, p < 0.001), confirming diagnostic accuracy. This first-in-class EC nanobiosensor for RSD represents a major technological advance over existing methods by offering a cost-effective, equipment-free, and scalable solution suitable for on-site deployment by non-specialist users. Beyond sugarcane, the modular nature of this detection platform opens up opportunities for multiplexed detection of plant pathogens, making it a transformative tool for early disease surveillance, precision agriculture, and biosecurity monitoring. This work lays the foundation for the development of a universal point-of-care platform for managing plant and crop diseases, supporting sustainable agriculture and global food resilience in the face of climate and pathogen threats. Full article

Under normal conditions, the novel zinc blende beryllium oxide (zb BeO) exhibits in a metastable crystalline phase, which is less stable than its wurtzite counterpart. Ultrathin zb BeO epifilms have recently gained significant interest to create a wide range of advanced high-resolution, high-frequency, flexible, transparent, nano-electronic and nanophotonic modules. BeO-based ultraviolet photodetectors and biosensors are playing important roles in providing safety and efficiency to nuclear reactors for their optimum operations. In thermal management, BeO epifilms have also been used for many high-tech devices including medical equipment. Phonon characteristics of zb BeO at ambient and high-pressure P ≠ 0 GPa are required in the development of electronics that demand enhanced heat dissipation for improving heat sink performance to lower the operating temperature. Here, we have reported methodical simulations to comprehend P-dependent structural, phonon and thermodynamical properties by using a realistic rigid-ion model (RIM). Unlike zb ZnO, the study of the Grüneisen parameter γ(T) and thermal expansion coefficient α(T) in zb BeO has revealed atypical behavior. Possible reasons for such peculiar trends are attributed to the combined effect of the short bond length and strong localization of electron charge close to the small core size Be atom in BeO. Results of RIM calculations are compared/contrasted against the limited experimental and first-principle data. Full article