Search Results (699)

This review systematically summarizes the inherent characteristics and application superiorities of various nanomaterials, including metallic nanomaterials, metal oxides, carbon-based materials, metal–organic frameworks (MOFs), and quantum dots (QDs). State-of-the-art research progress is elaborated on the applications of these nanomaterials in multiple analytical techniques, such as surface-enhanced Raman spectroscopy (SERS), fluorescence spectroscopy, infrared spectroscopy, ultraviolet-visible spectroscopy, and electrochemistry. Furthermore, their pivotal functions in signal amplification, specific molecular recognition, and rapid analyte enrichment are thoroughly discussed. Additionally, this paper analyzes the prevailing challenges, including material heterogeneity, potential biosafety risks, poor anti-interference capacity against complex matrices, and the absence of unified industrial standardization. Future development directions are also proposed, involving green synthesis strategies, precise functional modification, portable intelligent detection, and simultaneous multi-component detection. This work aims to provide a reliable reference for further fundamental research and industrial translation of nanomaterials in the rapid and high-precision detection of pesticide residues. Full article

Heavy metal ion pollution has emerged as a global issue. These contaminants are not only present in water sources but are also commonly detected in air, soil, food, and consumer products, posing serious risks to ecosystems and human health. Even at very low concentrations, heavy metal ions can exhibit substantial toxicity. Traditional methods for the detection of heavy metal ions typically require complex laboratory equipment and specialized technicians, making them inadequate for rapid on-site monitoring. Microfluidic technology, as an innovative platform capable of precisely controlling and manipulating minute volumes of fluid, has demonstrated enormous potential in analytical chemistry, biomedicine, and environmental monitoring. In the rapidly developing field of microfluidics, paper-based microfluidic platforms have become prominent due to their low cost, straightforward fabrication, and eco-friendly nature, offering powerful tools for the detection of heavy metal ions in diverse samples. This survey consolidates the major advances reported from 2015 to 2025 in utilizing paper-based microfluidic systems for identifying heavy metal ion pollutants in diverse sample types, including air, explosive residues, water sources, herbal supplements, skin-whitening cosmetics, environmental aerosols, urine, soil, gunshot residues, cucumber plants, and food. The review analyzes in detail the principles and applications of detection strategies based on colorimetric methods, fluorescent methods, electrochemical methods, dual-detection systems, and other methods, as well as the role of nanomaterials and selective recognition elements in improving detection sensitivity and specificity. These portable, low-cost, and easy-to-operate detection systems provide viable solutions for environmental and public health monitoring, particularly suitable for resource-limited regions and scenarios requiring rapid detection. Full article

The interfacial transition zone (ITZ) in the aggregate periphery is often regarded as the weakest area in concrete. In this study, the results of extensive image analysis provide a new insight. First, fluorescence microscopy (FM) was adopted to obtain the microstructure of “complete ITZ”, which overcomes several limitations of the scanning electron microscope method. Then, an ITZ recognition interactive algorithm was proposed, which quantitatively characterizes the pore distributions in the ITZ and cement paste in both lateral and longitudinal directions. Finally, based on the experimental and statistical results, the pore distributions around aggregates, coarse sand and fine sand were characterized. Along the lateral direction, a high non-uniformity was observed in the porosity between units, taken at the same distance from the aggregate/sand surface. On the contrary, along the longitudinal direction, statistical results show minimal increases in the porosity within the ITZ. This is also applicable even in the innermost ITZs. Full article

Post-translational modification (PTM) neoantigens have emerged as key drivers of autoimmune inflammation. However, standardized protocols for MHC Class II tetramer preparation for the detection of such antigen-specific T cells remain limited, hindering the broader application of this important discovery. This study systematically engineered an HLA-DR4 (HLA-DRB1*04:02 and HLA-DRA*01:01) tetramer platform based on carboxyethyl-modified neoantigen ITGA2B peptide (ITG-CE), a PTM associated with autoimmune diseases (AUIDs) such as Ankylosing Spondylitis (AS). The platform provides a major histocompatibility complex (MHC) Class II tetramer associated with the PTM neoantigen and integrates modular protein construct, a controllable PTM peptide exchange strategy, and a specific T cell receptor (TCR) validation model. It can be employed to investigate PTM neoantigen presentation and CD4⁺ T cell auto-reactivity, providing extensive application value for future research into the mechanisms of PTM-induced AUIDs and immune monitoring. Full article

Grapevine black-foot disease is a destructive trunk disease with a complex pathogen composition that often involves mixed and latent infections, making timely field diagnosis challenging. To improve rapid field detection, we developed a rapid, sensitive, and low instrument-dependent nucleic acid assay. The assay integrates recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)–Cas12a for the detection of Ilyonectria and Dactylonectria, two genera associated with grapevine black-foot disease. Conserved regions of the histone H3 and β-tubulin genes were selected for the design of specific RPA primers and corresponding CRISPR RNAs (crRNAs) for Ilyonectria and Dactylonectria, respectively. A workflow integrating RPA, Cas12a-mediated recognition, and lateral flow assay (LFA)-based visualization was established. The reaction conditions were optimized to enhance amplification efficiency and Cas12a recognition stability. Specificity was evaluated using DNA from target and non-target fungi, and sensitivity was determined using serially diluted templates. Under optimized conditions, the assay detected Ilyonectria DNA at concentrations as low as 3.6 ng/μL within 1 h at 39 °C. For Dactylonectria, the detection limit reached 80 fg/μL within 50 min at 41 °C. No cross-reactivity was observed. The LFA strips exhibited positive and negative bands within minutes, enabling rapid visual interpretation. This RPA-CRISPR/Cas12a-LFA system provides a rapid, visually interpretable approach for detecting selected grapevine black-foot disease-associated species in China. The workflow reduces the requirement for specialized thermocycling and fluorescence detection equipment during amplification and readout, following DNA extraction. Full article

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

Background/Objectives: Mosquitoes, including Culex quinquefasciatus and Aedes aegypti, are important vectors of dengue fever, Zika virus, West Nile virus, Japanese encephalitis virus, Eastern equine encephalitis virus, etc. Biological control has always been urgent in mosquito prevention due to resistance developing to synthetic insecticides and environmental toxicity by insecticides. Methods: The leaf essential oil of Mosla. chinensis was isolated, and major components were identified via GC-MS, followed by olfactory behavior assays to evaluate its repellent activity against C. quinquefasciatus. Additionally, the odorant-binding protein 1 and odorant-binding protein 2 (CquiOBP1-2) genes were prokaryotically expressed, and their fluorescence competitive binding activities with the active components of essential oils were examined. Results: The bioassays indicated this essential oil greatly repels C. quinquefasciatus, which will significantly protect people against vector-borne diseases. In the fluorescence competitive binding experiments, the CquiOBP1-2 proteins exhibit great binding capacities to volatile components, including Citronellal, Citronellol, Geraniol, Limonene and Isopulegol. Furthermore, the behavioral experimental results also indicate that the mixture of these five ligand compounds has an obvious repellent effect on mosquitoes, highlighting that they may be applied as potential mosquito repellent agents. Moreover, molecular docking and site-directed mutation analysis further confirm Phe123 and Gln77 are both key amino acid residues of CquiOBP1-2 proteins involved in the olfactory recognition of repellent ligand compounds from M. chinensis essential oil. Conclusions: The behavioral experimental verification and the exploration of olfactory molecular mechanisms are helpful to promote the biological control of plant essential oils in mosquito pests. Full article

4-Chlorophenoxyacetic acid (4-CPA), a synthetic auxin analog, is employed in agriculture both as a plant growth regulator and as a constituent of herbicide formulations. Consequently, the establishment of simple and rapid detection methods is essential for effective environmental monitoring. This study reports the first development of a homogeneous fluorescence polarization immunoassay (FPIA) for the determination of 4-CPA. The monoclonal antibody (M1), raised against 4-CPA, was evaluated as a recognition element. Furthermore, two fluorescently labeled 4-CPA tracers—with ethylenediamine fluorescein thiocarbamate and aminohexylaminocarbonylfluorescein—were synthesized and purified, and their structures were unequivocally confirmed by high-performance liquid chromatography coupled with high-resolution mass spectrometric detection (HPLC-HRMS). Optimal concentrations of monoclonal antibodies and tracers were established, yielding a limit of detection of 1.2 ng/mL. The assay demonstrated a broad dynamic range of 2.3–300 ng/mL and a rapid analysis time of 15 min. Validation via the standard addition method in authentic open water samples resulted in recovery rates of 98–112%. To address the cross-reactivity with the prevalent herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), two novel strategies were devised and successfully implemented. The first approach involves the concurrent execution of two separate FPIAs—one for 2,4-D and one for 4-CPA—followed by the mathematical resolution of two analyte concentrations from the two measured binding values. The second strategy entails the preliminary selective removal of 2,4-D from sample matrices using affinity chromatography columns with immobilized anti-2,4-D antibodies prior to FPIA for 4-CPA. These proposed methodologies appear highly promising for overcoming the inherent limitations of traditional immunoassays when faced with significant cross-reactivity among structurally analogous compounds. Full article

Autonomous unmanned aerial vehicles (UAVs) must decide when to trust onboard perception, when to request edge support, and when to avoid acting under poor visual or communication conditions. This study develops a risk-aware edge-assisted UAV perception framework that combines calibrated visual confidence with next-window service-level agreement (SLA) feasibility. The local branch uses MobileNetV3-Small for fast onboard color recognition, while the edge branch uses ResNet-18 for stronger remote inference. Low-confidence samples are offloaded only when the SLA predictor estimates that the wireless link is feasible; otherwise, the system enters fallback, meaning that the current prediction is not treated as immediately actionable. The evaluation follows a hard cross-illumination split: indoor and fluorescent light samples are used for training and validation, and indoor night and sunlight samples are reserved for testing. Under this setting, the local model achieves 76.89% accuracy and 73.25% macro-F1, while the edge model achieves 81.26% accuracy and 77.58% macro-F1. The SLA predictor, trained on enhanced telemetry features while preserving the original target label, achieves 85.74% accuracy, 85.57% macro-F1, 0.9420 ROC-AUC, and 0.9585 PR-AUC on temporally held-out records. The joint policy achieves 93.23% coverage and 79.90% success over active decisions, using local inference for 82.76% of the samples, edge offloading for 10.47%, and fallback for 6.77%. These results indicate that the framework is best understood as a tunable risk management layer for UAV perception rather than a pure accuracy maximization classifier. It avoids blind offloading and reduces forced decisions when both visual confidence and communication feasibility are weak. Full article

Nanomaterials with multiple enzyme-like activities offer significant opportunity for constructing multifunctional sensing methods. In this work, a hydrangea flower-like cerium dioxide nanomaterial (CeO₂ NF) with both peroxidase (POD)- and hydrolase-like activities, which was surface-modified by polyvinylpyrrolidone (PVP) in situ, was prepared through an oil bath method. Based on the POD-like activity of CeO₂ NFs, an “on-off” fluorescence method was established for chiral recognition of arginine (Arg) enantiomers. Meanwhile, utilizing the hydrolase-like activity of CeO₂ NFs and their synergistic interaction with alkaline phosphatase (ALP), an “on-off-on” fluorescence method was developed for the detection of p-nitrophenol (p-NP) and ALP. The sensor demonstrated excellent chiral selectivity for Arg enantiomers, with a high enantiomeric factor (ef) of up to 2.48, allowing for the quantitative detection of L-Arg in the range of 770–940 μM, with a limit of detection (LOD) of 26.00 μM. Furthermore, it exhibited high sensitivity for p-NP and ALP detection, with linear ranges of 10.0–84.3 μM and 300–2000 mU/mL, and LODs of 7.07 μM and 200 mU/mL, respectively. Through an enzyme kinetic analysis, fluorescence lifetime measurement, zeta potential analysis, and density functional theory (DFT) calculations, the underlying catalytic and chiral recognition mechanisms were proposed. Finally, the method was validated through the accurate detection of L-Arg, p-NP, and ALP in real samples (rabbit plasma, food-grade amino acid, and water samples). Full article

The question of verification of food quality has stood before scientists since ancient times, and, nowadays, the advances in science and technology have made it a very challenging task. Laser-induced fluorescence (LIF) spectroscopy has become a very useful instrument for sample characterization. Nevertheless, analysis of complex multi-component spectra is difficult to approach. In recent years, the capabilities of artificial intelligence have attracted a lot of attention, as they open doors to efficient solutions of many problems that otherwise require a lot of time, effort, expenses and often inspiration. In the present work, we use LIF spectra of mixtures of sunflower and extra virgin olive oils with different concentrations and apply neural network (NN) algorithms with the aim of improving the strategies for concentration determination. Two different approaches have been applied and their output has been compared and commented. More specifically, the task of concentration recognition has been targeted as a classification and as a fitting problem. We formulate four diagnostic parameters with biochemical meaning and compare the NN performance when training with raw spectra and with the diagnostic parameters. The correct choice of appropriate diagnostic parameters is of importance from the point of view of biochemical interpretability and analysis, whereas “black box” full-spectra training might be beneficial for end-user applications. Our results show that these methods perform well even with very scarce data and outline preliminary strategies for defining diagnostic criteria. Full article

The western corn rootworm (Diabrotica virgifera virgifera) relies on odorant-binding proteins (OBPs) to locate maize hosts and mates via volatile organic compounds (VOCs). However, the molecular recognition mechanisms of specific attractants, such as (E)-β-caryophyllene, 6-methoxy−2-benzoxazolinone (6-MBOA), and the sex pheromone 8R-methyl−2R-decyl propanoate (2R,8R-MDP), remain elusive. Here, we integrated phylogenetic analysis, AlphaFold2 structural prediction, molecular docking, molecular dynamics (MD) simulations, and in vitro fluorescence competitive binding assays to characterize the binding specificity of DvirOBPs toward these key ligands. Pan-family screening identified DvirOBP54b as possessing the highest ligand-binding specificity, resolving its evolutionary divergence from its tandem duplicative paralog DvirOBP54a. Structural and dynamic analyses revealed that DvirOBP54b binding to (E)-β-caryophyllene and 2R,8R-MDP is predominantly driven by hydrophobic interactions within a core pocket (Phe7, Phe69, Ile70, Ala121). Conversely, its interaction with 6-MBOA is further stabilized by a specific hydrogen bond at Thr66. Dynamic trajectories confirmed the high stability of the DvirOBP54b complexes, while in vitro assays validated the strong binding affinities toward the core host-derived volatiles. These findings elucidate the structural basis of VOC-mediated olfactory recognition in D. v. virgifera, providing critical molecular targets for developing high-efficiency attractants and novel pest management strategies. Full article

Nanomaterial-based biosensors have advanced analytical methodologies by enhancing signal transduction, interfacial reactivity, and molecular recognition across diverse sensing platforms. In parallel, the diversity of nanomaterial compositions, architectures, and interfacial designs has expanded the range of available sensing strategies and performance outcomes. This review addresses limitations through a structure–property–function framework that links nanomaterial characteristics to sensing behavior, performance determinants, and application-specific requirements. Within this framework, nanomaterials are classified according to their dominant functional roles in biosensing, including plasmonic, electroactive, fluorescent and quantum-confined, porous, and hybrid architectures. The influence of morphology, surface chemistry, conductivity, and interfacial design on electrochemical, optical, and hybrid transduction mechanisms is critically examined, and key performance parameters, including sensitivity, selectivity, limit of detection, response time, stability, and reproducibility, are discussed in relation to material properties and sensing configuration. Recent advances in clinical biomarker detection, pathogen and nucleic acid analysis, and environmental and food safety monitoring are also evaluated to illustrate how nanomaterial design is tailored to different analytical contexts. Current limitations related to reproducibility, interface engineering, long-term stability, and scalable device integration are highlighted, together with future directions for the rational development of robust and application-oriented biosensor platforms. Full article

Vitamin D₃ is an essential fat-soluble vitamin for the human body. Its metabolite, 25-hydroxyvitamin D₃ (25(OH)D₃), serves as the primary biomarker to assess vitamin D levels. The monitoring of 25(OH)D₃ concentration is crucial for human health assessment. While traditional detection methods offer high sensitivity and accuracy, they are operationally complex and costly. This review systematically summarizes the most recent progress in 25(OH)D₃ detection technologies. Special attention is given to the recognition modes of 25(OH)D₃ by antibodies, nucleic acids, and molecularly imprinted recognition elements. Subsequently, the design strategies of diverse types of biosensors, including fluorescent, colorimetric, and electrochemical biosensors, are analyzed. Moreover, the development of portable devices, smartphone software, and flexible wearable devices for detection applications is also examined. Biosensing detection platforms are compared from the perspectives of target recognition, signal conversion, signal output, and application scenarios. Additionally, the potential of biosensor detection platforms in clinical diagnosis, health management, and community health surveillance is further investigated. Finally, the future trends of intelligent, portable, accurate, and home-use 25(OH)D₃ detection systems are delineated. This review offers a comprehensive reference for researchers developing next-generation 25(OH)D₃ diagnostic sensors and provides insights for the early prevention and treatment of vitamin D deficiency-related diseases. Full article

The transient protoplast transformation system is a vital tool for studying protein subcellular localization and phase separation in wheat. However, current protocols remain underdeveloped, and the lack of systematic vector design analysis frequently leads to localization artifacts. Here, we established a simplified wheat mesophyll protoplast transformation method featuring a shortened cycle, streamlined handling, and no variety limitations, enabling stable acquisition of high-quality confocal imaging data. Using this method, we systematically examined the effects of the fluorescent tag position (N- vs. C-terminal) and promoter type (native, single CaMV35S and double CaMV35S) on protein localization and phase separation. Tag position proved decisive: improper fusion can affect the recognition of localization signals, leading to inaccurate patterns. Regarding promoters, the native promoter represents the optimal choice for physiological accuracy. Constitutive strong promoters such as CaMV35S boost gene expression and thereby enhance fluorescent signals for easier imaging, but overexpression may compromise localization fidelity and exacerbate molecular crowding effects, resulting in false-positive phase-separated aggregates. Conversely, insufficient expression will lead to false-negative outcomes. This standardized transformation system and the defined vector design principles offer a robust framework for minimizing artifacts in wheat protein localization and phase separation research. Full article