Search Results (554)

Peroxide is a vital oxidant that can quickly kill bacteria, viruses, and fungi in food and ensure food safety. However, excessive intake will stimulate the gastrointestinal tract, cause abdominal pain and vomiting, and its strong oxidation will also destroy the vitamin and protein structure in food. Cerium-based nanomaterials exhibit good biocompatibility and strong chemical stability, and have significant application value in biological detection. Cu nanoparticles were deposited on the surface of a glassy carbon electrode (GCE) by potentiostatic deposition. The Ce³⁺/PA-Cu²⁺@Cu/GCE sensor was constructed by etching and complexing Cu²⁺ with phytic acid (PA) to form a PA-Cu³⁺ coordination film. By X-ray diffraction (XRD) and Fourier Transform Infrared (FT-IR), the structure of composite material on the electrode surface was characterized. Electrochemical test results: Cu time of electrodeposition 700 s, PA embellishment 60 min, Ce³⁺ coordination 60 min, and H₂O₂ Reaction 15 min. The detection linearity range of the sensor for hydrogen peroxide is 0.1–100 μmol/L, detection limit is 0.89 μmol/L, and there was good selectivity, sensitivity and reproducibility (RSD = 1.013%) and stability (retention of 84% response at 28 days). Full article

Enhancing the visual detection sensitivity of point-of-care (POC) optical sensors without resorting to complex, multistep chemical or enzymatic signal amplification remains a major challenge in sensor nanotechnology. Here, we present a multifunctional bio-nanostructured hybrid platform that integrates engineered Escherichia coli cellular scaffolds with antibody-functionalized gold nanoparticles (AuNPs) for high-sensitivity, solution-phase colorimetric sensing. By exploiting the biotin-streptavidin interaction through the Lpp-OmpA outer-membrane display system, the engineered bacterial cells serve as high-capacity, multivalent biological interfaces with a large effective surface area and high recognition-site density. Using SARS-CoV-2 nucleocapsid protein as a model biomarker, target-mediated bridging between AuNP-antibody probes and bacterial scaffolds promotes localized AuNP assembly and enhanced plasmonic coupling, resulting in a distinct visual color change within 30 min. The optimized assay achieved a naked-eye limit of detection (LOD) of 10⁻¹² mol, representing a 10-fold sensitivity enhancement over conventional scaffold-free AuNP assays. This study provides a proof of concept for leveraging engineered living cells as multifunctional nanostructured templates. The modular, plug-and-play architecture of the biotin-streptavidin coupling interface highlights its potential for adaptation to clinical diagnostics and environmental monitoring. Full article

Increasing frequency and intensity of heat events pose significant challenges for the production and early establishment of urban trees. This study evaluated whether horticultural interventions could mitigate heat stress and improve growth of young red maple (Acer rubrum ‘FranksRed’) under full-sun conditions representative of urban planting environments. Six treatments (control, canopy misting, paclobutrazol, propiconazole, kaolin clay, and potassium phosphite) were evaluated over two growing seasons in the Willamette Valley, Oregon, which were characterized by hot, dry summers and episodic heat waves. Canopy temperature, soil volumetric water content, and growth were monitored using high-resolution sensor networks and analyzed using mixed-effects modeling to account for repeated measures and environmental covariates. Across both years, mean canopy temperature largely tracked ambient conditions, and treatment effects on absolute temperature were modest. However, canopy misting reduced daily canopy temperature amplitude (ΔT) and maintained the highest soil volumetric water content, while both misting and kaolin consistently reduced exposure to the highest canopy temperature thresholds. Although these reductions in cumulative thermal exposure were not statistically significant, they coincided with improved tree growth. The chemical treatments produced smaller, context-dependent effects. Despite modest temperature differences, stem caliper increased by 10–20% under misting relative to the control (p < 0.05). Growth responses indicate that small changes in canopy thermal exposure and soil water availability can translate into meaningful differences in early tree performance. These results demonstrate that the absence of strong treatment effects on mean canopy temperature does not preclude biologically relevant outcomes. Management strategies that modify canopy thermal dynamics or plant water relations may improve growth and establishment potential of young trees under increasingly extreme thermal conditions, even when ambient heat loads cannot be fully mitigated. Full article

Wound management continues to represent a major global healthcare challenge, with the wound care market growing each year and a rising incidence of chronic wounds worldwide. Effective wound healing requires dressings that protect injured tissue, prevent infection, and actively modulate the wound microenvironment to promote tissue regeneration. In recent years, smart polymeric wound dressings have emerged as a functional, more advanced class of wound dressings, engineered from materials capable of responding to stimuli. Physically responsive systems include moisture-adaptive dressings that prevent wound dryness or maceration, pressure-sensitive dressings incorporating flexible capacitive sensors for high mechanical stress mapping, thermoresponsive dressings exploiting sol–gel transitions for temperature-controlled drug release, light-responsive dressings enabling photothermal and photodynamic therapy, and electro-responsive dressings integrating conductive polymers for self-powered electrical stimulation or closed-loop wound monitoring. Chemically responsive systems exploit endogenous biochemical signals, including pH shifts for wound monitoring, reactive oxygen species-cleavable bonds for on-demand drug release, and glucose-responsive platforms for autonomous glycemic regulation in diabetic wounds. Biologically responsive dressings use enzymatic triggers, such as matrix metalloproteinases, hyaluronidase, and bacterial proteases, to achieve autonomous drug delivery. Film-forming sprays further expand the versatility of smart polymeric dressings by enabling contactless application adaptable to irregular wound shapes. In this review, we summarize recent advances in the design, stimuli-responsive mechanisms, characterization methods, and therapeutic outcomes of smart polymeric dressings for wound treatment. Despite promising preclinical results, challenges related to clinical translation, regulatory standardization, and scalable production remain and must be addressed to facilitate widespread clinical adoption. Future directions include multi-stimuli responsive platforms, artificial intelligence-guided wound monitoring, bioprinting of specific dressings, and environmentally sustainable biomaterial design. Full article

Acquiring real-time biological data is essential for effective control of microalgae cultivation processes, yet routine monitoring still depended on laborious offline analyses that relied on time-consuming wet-chemical techniques. This study introduces a flow-through, multi-wavelength visible-light (VIS) sensor for real-time monitoring of biomass and pigment concentrations in microalgae cultivation processes. Based on 209 experimental data points, six machine-learning regression models were developed to estimate dry biomass, chlorophyll $\alpha$, chlorophyll $\beta$, total chlorophyll, total carotenoid, and astaxanthin concentrations. Validation under realistic continuous operation showed that potential remains within improved hydrodynamics and operation automatics to reduced biofilm formation. The independent dataset demonstrated that biomass and astaxanthin predictions were within ±10% of offline reference measurements. The proposed low-cost and versatile multi-wavelength sensor platform, together with machine-learning-based calibration, provides a practical soft-sensor concept for real-time monitoring of microalgal bioprocesses and offers a foundation for future integration of model-based and predictive control strategies. Full article

Portable sensing systems are increasingly important in biological and chemical analyses because they can provide analytical information at the point of decision-making. While traditional laboratory methods remain crucial for reference measurements, regulatory validation, and high-precision quantification, portable systems emphasize rapid response, convenience, cost-effectiveness, robustness, and relevance to decision-making. This paper views portable sensing systems as integrated analytical platforms rather than isolated sensing elements. The paper discusses recognition elements, including enzymes, antibodies, nucleic acid probes, aptamers, molecularly imprinted polymers, nanomaterials, and hybrid recognition interfaces, as well as electrochemical, optical, mass-sensitive, thermal, field-effect, and hybrid sensing technologies. Furthermore, this paper reviews platform designs, including paper-based analytical devices, chip lab systems, smartphone-assisted sensors, wearable and flexible sensors, handheld instruments, and wireless sensor networks. It explores their applications in sample handling, calibration, data processing, and field deployment. Applications of this technology include point-of-care diagnostics, pathogen detection, wearable health monitoring, agriculture, veterinary medicine, environmental monitoring, food safety, industrial process control, forensic analysis, public safety, and occupational exposure assessment. The report focuses on sample acquisition, miniaturized preparation, reagent storage, matrix interference, calibration transfer, signal conditioning, machine learning, cloud platforms, analytical validation, and decision support. Furthermore, it identifies key obstacles to translating academic prototypes into industrial products, including reproducibility, stability, manufacturability, ease of use, cybersecurity, regulatory approval, and market acceptance. Future development requires fully integrated sample-to-result systems, multimodal sensing, artificial intelligence, sustainable single-use materials, self-powered devices, and system-level validation under real-world operating conditions. Full article

A huge effort has been directed towards research and development of new measurement systems for maximizing comfort and safety in public buildings by monitoring indoor air quality (IAQ). In fact, according to World Health Organization, exposure to chemical, biological, and physical agents in poorly ventilated spaces can lead to psycho-physical discomfort as well as respiratory and neurological diseases. Recent advances in the Internet of Things (IoT) have paved the ground for the design and implementation of distributed measurement systems with higher sensor density and computational capacity. While these systems provide accurate assessments of individual rooms, they do not account for personal exposure to varying air quality levels over time. In public buildings such as schools, universities, and workplaces, occupants frequently move between rooms according to predefined schedules, resulting in heterogeneous exposure patterns. To address this issue, this paper proposes an innovative IAQ measurement technique for public buildings, shifting the focus from room-based assessment to occupant-centered assessment. Unlike wearable or portable personal monitors, the proposed technique infers occupant location from the institutional timetable and combines it with the fixed sensor infrastructure already installed in the rooms, requiring no additional devices to be worn. Individual conditions are quantified through a new personalized metric that integrates instantaneous air quality, cumulative individual exposure over time, and thermal comfort into a single index that is evaluated against occupant-specific thresholds. The technique is validated using real-world data, demonstrating higher potential to ensure safety and comfort compared to the state of the art. Full article

Soil health refers to the combined physical, chemical, and biological properties of soils that allow them to function as a living system that sustains life. While numerous reviews summarize several methods to measure soil health, this review critically evaluates how the Soil Management Assessment Framework (SMAF) performs across diverse ecosystems, including croplands, agroforestry, coastal mangrove, and rangelands. We explore the evolutionary shift from single indicators to integrated assessment frameworks, tracing how targeted management practices, such as conservation tillage, crop rotation, cover cropping, organic amendments, and water management, alter physical, chemical, and biological indicator performance. The SMAF framework and scoring system are outlined using examples from around the world. This synthesis concludes that while SMAF provides an exceptionally rigorous, non-linear platform for quantitative Soil Quality Index (SQI), its practical execution remains deeply constrained by data-intensive requirements, selection of appropriate indicators, and adaptation to local contexts. To close this gap, we outline critical future directions, integrating the framework with AI and machine learning, real-time Internet of Things (IoT) field sensors, and dynamic digital twins. Ultimately, this work aims to shift soil monitoring from descriptive reporting to predictive, automated intelligence to provide the exact data needed for sustainable land management decisions. Full article

Conventional chemical analysis relies on costly laboratory instrumentation, while current e-nose systems are expensive for widespread deployment. New opportunities for low-cost, accessible e-nose applications are emerging for diverse fields due to the rapid evolution of inexpensive sensor technologies. We developed a framework that enables rapid integration of newly available low-cost gas sensors into functional e-nose systems, continuously evaluating them as they become commercially available. By characterizing their performance in multi-sensor arrays that mimic biological olfaction, the framework demonstrates effective odor discrimination in a low-cost e-nose system through coordinated behavior of a heterogeneous sensor array. Our testing approach includes sensor sensitivity, selectivity, and stability, which are to be combined with appropriate pattern recognition and AI algorithms in the future for effective chemical discrimination. This work provides a pathway for continuously updating e-nose technology with the latest available sensors in a cost-effective manner, thereby making advanced chemical sensing accessible for resource-limited settings and enabling large-scale deployment in real-world applications with future potential applications such as food quality monitoring, environmental sensing, smart agriculture, etc. Full article

Honeybees (Apis mellifera) serve as biological sentinels because their foraging behavior links colony health to environmental conditions. Traditional hive inspections are invasive, observer-dependent, and often detect problems only after symptoms appear. This review synthesizes advances in precision beekeeping, environmental DNA (eDNA) metabarcoding, exposomics, and artificial intelligence to propose the Honeybee-Based Early Warning System (H-BEWS), a unified framework that integrates digital sensors, molecular and chemical monitoring, and ecological data into a predictive early warning system for both colony and ecosystem health. By linking anomalies detected by hive sensors to targeted molecular and chemical analyses, H-BEWS enables proactive interventions and environmental surveillance, supporting a One Health perspective. Unlike previous reviews that focus on individual technologies, H-BEWS emphasizes multi-layered integration, predictive risk assessment, and ecosystem-level insights, providing a novel conceptual framework for early detection of colony stress and environmental hazards. The approach offers practical applications for beekeepers, researchers, and policymakers by converting real-time data into actionable insights and informing management decisions. Challenges include sensor standardization, data integration, AI validation, and equitable access for small-scale beekeepers. Future directions will focus on real-time sequencing, multimodal AI models, digital twin creation, and the development of global surveillance networks. H-BEWS demonstrates how an integrative, multi-layered approach can transform honeybee colonies into living biosensors, providing actionable insights for both apiculture management and ecosystem monitoring. Full article

Airports, as Critical National Infrastructure (CNI), operate as tightly coupled socio-technical systems exposed to multifaceted threats, including cyber, physical, social, environmental, and Chemical, Biological and Radiological (CBR) threats. This study presents a structured review of the synthesis of conceptual frameworks, airport structural configurations, sensor networks, and multi-domain threat landscapes, as well as airport security and resilience analysis, while comparatively examining risk assessment approaches. The review shows that existing approaches are effective for threat identification and prioritisation but remain predominantly static, with limitations in scalability, data dependency, and real-time applicability. To address these limitations, Threat-Vulnerability-Risk Assessment (TVRA) is adopted as a structured, reusable approach to support metric allocation, redundancy design, and emergency capability development. It further serves as a bridge between traditional risk assessment and resilience-oriented system design by enabling the transformation of static risk scores into scenario-based inputs, thereby supporting stress-testing and lifecycle-based resilience planning across the prepare, act, and recover phases. However, its inherently static structure limits its ability to capture temporal dynamics and cascading interdependencies, highlighting the need to integrate it with dynamic modelling approaches. Full article

In the present research, lanthanum ferrite nanoparticles (LaFeO₃ NPs) and lanthanum ferrite polypyrrole (LaFeO₃/PPy) nanocomposites were synthesized and evaluated for electrochemical sensing of TNZ in biological and pharmaceutical samples. LaFeO₃ NPs were synthesized using the sol–gel auto-combustion method, whereas LaFeO₃/PPy nanocomposites were produced through an in situ chemical oxidative polymerization process. The obtained materials were subjected to comprehensive characterization by multiple analytical techniques, including XRD, which confirms an orthorhombic crystal structure; SEM micrographs of LaFeO₃ NPs and LaFeO₃/PPy nanocomposites exhibit a highly agglomerated structure with non-uniform particle distribution and a more homogeneous, smoother surface morphology, respectively, with an average size of <70 nm. The LaFeO₃/PPy nanocomposites exhibited an electron-transfer process governed by diffusion, as evidenced by cyclic voltammetry (CV) analysis. Using differential pulse voltammetry (DPV), the sensor achieved quantitative detection across a linear concertation range of 0.1–230 µM (R² = 0.997), with a detection limit (0.023 µM). The developed sensor demonstrated excellent stability, remarkable sensitivity, and high reproducibility, confirming reliability and suitability (RSD% < 4.0) for the quantitative determination of TNZ in both biological and pharmaceutical matrices. Full article

Prostate cancer (PCa) is one of the leading causes of cancer-related morbidity and mortality in men worldwide, and early detection remains crucial for ensuring effective treatment and improving patient outcomes. In this context, the development of non-invasive, accurate, and cost-effective screening strategies is of paramount importance. One particularly promising and innovative approach is the analysis of volatile organic compounds (VOCs), a field known as volatolomics. VOCs, which are metabolic by products released by the body, reflect underlying biochemical processes and offer a valuable, non-invasive source of diagnostic information. Recent advances have highlighted the potential of VOC profiling in PCa detection. A variety of biological systems have demonstrated remarkable sensitivity and specificity in recognizing disease-associated VOC signatures. Notably, trained dogs, selected invertebrates, and artificial sensing platforms have all shown the ability to identify PCa-related olfactory patterns. Among technological approaches, electronic noses (eNoses), which combine chemical sensor arrays with pattern recognition algorithms such as neural networks, represent a rapidly evolving diagnostic tool. Together, these biologically inspired and technology-driven strategies are reshaping the landscape of cancer diagnostics. They offer a compelling foundation for the development of rapid, non-invasive, and clinically translatable methods for PCa detection. This narrative review summarizes recent advances in using VOCs for PCa diagnosis and evaluates the reproducibility and clinical robustness of these approaches, focusing on challenges such as standardizing sampling, storage, and analysis, small cohort sizes, and the need for external validation and regulatory integration. Full article

Against the backdrop of intensifying global climate change and water eutrophication, the increasing occurrence of Harmful Algal Blooms (HABs) poses a significant threat to aquatic ecosystems, human health, and socio-economic activities. The occurrence and development of HABs are complex processes governed by the interaction of physical, chemical, and biological factors. Therefore, timely and accurate monitoring is essential for early warning and scientific research. This paper comprehensively reviews recent advances in HAB monitoring technologies, with a focus on two core components: sensors and monitoring platforms. First, organized around key environmental parameters, it summarizes the principles, applications, and limitations of in situ sensors, such as multi-parameter water quality sondes, Imaging Flow Cyto-bots (IFCB), and Environmental Sample Processors (ESP), as well as laboratory-based analytical techniques such as HPLC-MS for measuring physical, chemical, and biological indicators. Second, it compares the technical characteristics of three major monitoring platforms (including field surveys, remote sensing, and autonomous systems) and discusses their potential for synergistic application. Finally, this review proposes a future framework for an integrated “Space–Air–Ground–Sea” intelligent monitoring network and explores possible pathways to address current challenges through cross-platform data fusion, sensor miniaturization, intelligentization, and artificial intelligence-driven decision support. This review aims to provide a comprehensive reference for the optimization and innovation of HAB monitoring technologies and to promote the development of the field toward greater integration, intelligence, and real-time monitoring capability. Full article

The distinct electronic and optical properties of gold nanoparticles (NPs) have made them innovative assets for biomolecular sensing. This review outlines the various gold nanoparticle-based biosensing techniques centred on biomolecule detection and signal relay. We discussed the physical, chemical (Turkevich, Brust, seed-mediated growth, and digestive ripening) and biological syntheses involving bacteria, fungi, and plant extracts. Also discussed were the various ways these techniques affect the shape and functionality of the nanoparticles. Detection techniques are typically classified as the following: colourimetric, fluorescence-based, electrochemical, and surface plasmon resonance (SPR). Colourimetric assays enable visual detection of proteins and oligonucleotides by monitoring gold NP aggregation, while molecular beacons enable precise fluorescent-based detection. Quantitative detection of small molecules and gold NPs can be performed using electrochemical sensing, and biomolecular interactions can be analysed in real time using SPR. With the review focusing on the integration of gold NPs with microfluidics and wearable sensors, this synthesis aims to support the design of more practical, real-world applications of the described techniques. Full article