An enzymatic activity regulation-based clusterzyme sensor array for high-throughput identification of heavy metal ions

Engineering "three-in-one" fluorescent nanozyme of Ce-Au NCs for on-site visual detection of Hg2

Hg2+ contamination poses a serious threat to the environment and human health. Although gold nanoclusters (Au NCs) have been utilized as fluorescence probes or colorimetric nanozymes for performing Hg2+ assays by using a single method, designing multifunctional nanoclusters as fluorescent nanozyme remains challenging. Herein, Ce-aggregated gold nanoclusters (Ce-Au NCs) were reported with "three in one" functions to generate strong fluorescence, excellent peroxidase-like activity, and the highly specific recognition of Hg2+ via its metallophilic interaction. A portable fluorescence and colorimetric dual-mode sensing device based on Ce-Au NCs was developed for on-site visual analysis of Hg2+. In the presence of Hg2+, fluorescence was effectively quenched and the paper-based chips gradually darkened from green till they became completely absent, while peroxidase-like activity was significantly enhanced. Two independent signals were captured by one identification unit, which provided self-validation to improve reliability and accuracy. Therefore, this work presents a simple synthesis of a multifunctional fluorescent nanozyme, and the developed portable device for on-site visual detection has considerable potential for application in the rapid on-site analysis of heavy metal ions in the environment.

Development of MOF-derived Co3O4 microspheres composed of fiber stacks for simultaneous electrochemical detection of Pb2+ and Cu2

As an ideal transition metal oxide, Co3O4 is a P-type semiconductor with excellent electrical conductivity, non-toxicity and low cost. This work reports the successful construction of Co3O4 materials derived from metal-organic frameworks (MOFs) using a surfactant micelle template-solvothermal method. The modified electrodes are investigated for their ability to electrochemically detect Pb2+ and Cu2+ in aqueous environments. By adjusting the mass ratios of alkaline modifiers, the morphological microstructures of Co3O4-X exhibit a transition from distinctive microspheres composed of fiber stacks to rods. The results indicate that Co3O4-1(NH4F/CO(NH2)2 = 1:0) has a distinctive microsphere structure composed of stacked fibers, unlike the other two materials. Co3O4-1/GCE is used as the active material of the modified electrode, it shows the largest peak response currents to Pb2+ and Cu2+, and efficiently detects Pb2+ and Cu2+ in the aqueous environment individually and simultaneously. The linear response range of Co3O4-1/GCE for the simultaneous detection of Pb2+ and Cu2+ is 0.5-1.5 μM, with the limits of detection (LOD, S/N = 3) are 9.77 nM and 14.97 nM, respectively. The material exhibits a favorable electrochemical response, via a distinctive Co3O4-1 microsphere structure composed of stacked fibers. This structure enhances the number of active adsorption sites on the material, thereby facilitating the adsorption of heavy metal ions (HMIs). The presence of oxygen vacancies (OV) can also facilitate the adsorption of ions. The Co3O4-1/GCE electrode also exhibits excellent anti-interference ability, stability, and repeatability. This is of great practical significance for detecting Pb2+ and Cu2+ in real water samples and provides a new approach for developing high-performance metal oxide electrochemical sensors derived from MOFs.

Construction of fluorescent sensor array with nitrogen-doped carbon dots for sensing Sudan Orange G and identification of various azo compounds

In this study, nitrogen-doped carbon dots (N-CDs) were facilely fabricated by one-pot hydrothermal method with levulinic acid and triethanolamine. A fluorescent sensor array was established for identifying azo compounds including Sudan Orange G (SOG), p-diaminoazobenzene, p-aminoazobenzene, azobenzene and quantitative detection of SOG. Experimental results revealed that azo compounds could quench the fluorescent intensity of N-CDs. Owing to various azo compounds showing different affinities to N-CDs, the sensor array exhibited different fluorescence quenching changes, which were further analyzed with principal component analysis to discriminate azo compounds. The sensor array was able to differentiate and recognize diverse concentrations of azo compounds from 0.25 to 2 mg/L. Simultaneously, a variety of factors affecting the detection of SOG were optimized. Under the optimized conditions, the sensor showed excellent stability and sensitivity. The sensor possessed marvelous linearity in the range of 0.1-1 mg/L and 1-4 mg/L and the detection limit was 27.82 μg/L. Spiked recoveries of 90.8-98.2 % were attained at spiked levels of 0.2 mg/L and 1 mg/L, demonstrating that the constructed fluorescence sensor was dependable and feasible for sensing SOG in environmental water samples.

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Recent advances and trends in innovative biosensor-based devices for heavy metal ion detection in food

Low-cost, reliable, and efficient biosensors are crucial in detecting residual heavy metal ions (HMIs) in food products. At present, based on distance-induced localized surface plasmon resonance of noble metal nanoparticles, enzyme-mimetic reaction of nanozymes, and chelation reaction of metal chelators, the constructed optical sensors have attracted wide attention in HMIs detection. Besides, based on the enrichment and signal amplification strategy of nanomaterials on HMIs and the construction of electrochemical aptamer sensing platforms, the developed electrochemical biosensors have overcome the plague of low sensitivity, poor selectivity, and the inability of multiplexed detection in the optical strategy. Moreover, along with an in-depth discussion of these different types of biosensors, a detailed overview of the design and application of innovative devices based on these sensing principles was provided, including microfluidic systems, hydrogel-based platforms, and test strip technologies. Finally, the challenges that hinder commercial application have also been mentioned. Overall, this review aims to establish a theoretical foundation for developing accurate and reliable sensing technologies and devices for HMIs, thereby promoting the widespread application of biosensors in the detection of HMIs in food.

Facile and selective recognition of sulfonylurea pesticides based on the multienzyme-like activities enhancement of nanozymes combining sensor array

Traditional identification methods based on cholinesterase inhibition are limited to recognizing organic phosphorus and carbamate esters, and their response to sulfonylurea pesticides is weak. Residual sulfonylurea pesticides can pose a threat to human health. So, it is very important to develop an effective, rapid and portable method for sulfonylurea pesticides detection. Herein, we first found that sulfonylurea pesticides have activity-enhancing effects on copper-based nanozymes, and then combined them with the array technology to construct a six-channel sensing array method for selectively identifying sulfonylurea pesticides and detecting total concentration of sulfonylurea pesticides (the limit of detection was 0.03 µg/mL). This method has good selectivity towards sulfonylurea pesticides. In addition, a smartphone-based colorimetric paper sensor analysis method was developed to achieve the on-site detection of the total concentration of sulfonylurea pesticides. And this array can also be used for individual differentiation (1-100 µg/mL). Our work not only investigates the specific responses of copper-based nanozymes to sulfonylurea pesticides, but also develops a simple method that contributes to directly detect sulfonylurea pesticides at the source of pollution, providing insights for further research on sulfonylurea pesticides detection and filling the gap in pesticide residue studies.

Gold nanoclusters-based fluorescence sensor array for herbicides qualitative and quantitative analysis

Herbicides have been extensively used around the world, which poses a potential hazard to humans and wildlife. Accurate detection of herbicides is crucial for the environment and human health. Herein, a simple and sensitive fluorescence sensor array was constructed for discrimination and identification of herbicides. Fluorescent gold nanoclusters modified with 11-mercaptoundecanoic acid or reduced glutathione were prepared, respectively. Metal ions quenched the fluorescence of nanoclusters through coordination and leading to the aggregation of gold nanoclusters. The addition of auxin herbicides (2,4-dichlorophenoxyacetic acid, 2-methyl-4-chlorophenoxyacetic acid, decamba, picloram, quinclorac) restored the fluorescence of nanoclusters with different degrees. The mechanism study showed auxin herbicides can bind with metal ions and re-disperse the gold nanoclusters from the aggregation state. The "on-off-on" fluorescent sensor array was constructed basic on above detection mechanism. Combined with principal component analysis (PCA) and hierarchical cluster analysis (HCA) methods, auxin herbicides are well separated on 2D/3D PCA score plots and HCA dendrogram in the range of 40-500 μm. In addition, the fluorescence sensor array performed successful in detecting real samples and blind samples. The developed sensor system shows a promising in practical detection of herbicides.

Triple-Emission Single Sensing Element-Enabled Ratiometric Fluorescent Array Identification of Multiple Antibiotics

Given that intricate toxicological profiles exist among different antibiotics and pose serious threats to the environment and human health, synchronous analysis of multiple residues becomes crucial. Sensor arrays show potential to achieve the above purpose, but it is challenging to develop easy-to-use and high-sensitivity tools because the state-of-the-art arrays often require more than one recognition unit and are monosignal dependent. Here we exquisitely designed a fluorescent nanoprobe (2-aminoterephthalic acid-anchored CdTe quantum dots with Eu3+ coordination, CdTe-ATPA-Eu3+) featuring triple emissions at the same excitation as the only element to fabricate a luminescent sensor array with ratiometric calculations for identifying multiple antibiotics. By taking tetracycline, chlortetracycline, doxycycline, oxytetracycline, penicillin G, and sulfamethoxazole as models, the six species exhibited distinguishable motivation or/and quenching impacts on the three emissions of CdTe-ATPA-Eu3+, which were employed as indicators to perform the ratiometric logical operation and further combined with pattern recognition analysis for multitarget determination. Evidently, such a design exhibits two advances: (1) with the triple-emission probe as the sole receptor requiring neither internal nor external adjustments, the fabricated array acts as an extremely facile tool for multianalyte detection; (2) the ratiometric calculations offer excellent sensitivity and reliability for high-performance determination. Consequently, accurate identification and quantification of individual antibiotics and their combinations at various levels were verified in both laboratory and practical matrices. Our work provides a new tool for simultaneously detecting multiple antibiotics, and it will inspire the development of advanced sensor arrays for multitarget analysis.

Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications

Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.

Silver Nanoparticle Sensor Array-Based Meat Freshness Inspection System

The series of biochemical reactions, metabolic pathways, and regulatory interactions that occur during the storage of meat are the main causes of meat loss and waste. The volatile compounds produced by these reactions, such as hydrogen sulfide, acids, and amines, can directly indicate changes in the freshness of meat during storage and sales. In this study, a one-pot hydrothermal method based on a surface control strategy was used to develop nanoparticles of silver with different reactivities, which were further immobilized in agar powder to develop a colorimetric sensor array. Due to the different chemical interactions with various volatile compounds, the colorimetric sensor array exhibited distinct color changes. The study demonstrates significant differences between 12 different volatile compounds and provides a quantitative and visual method to reveal rich detection indicators. The colorimetric sensor array is an economical and practical multi-analyte identification method. It has many potential applications such as food packaging, anti-counterfeiting, health monitoring, environmental monitoring, and optical filters.