A novel strategy for identification of pesticides in different categories by concentration-independent model based on a nanozyme with multienzyme-like activities

Machine learning-assisted melamine-Cu nanozyme and cholinesterase integrated array for multi-category pesticide intelligent recognition

Expanding target pesticide species and intelligent pesticide recognition were formidable challenges for existing cholinesterase inhibition methods. To improve this status, multi-active Mel-Cu nanozyme with mimetic Cu-N sites was prepared for the first time. It exhibited excellent laccase-like and peroxidase-like activities, and can respond to some pesticides beyond the detected range of enzyme inhibition methods, such as glyphosate, carbendazim, fumonisulfuron, etc., through coordination and hydrogen bonding. Inspired by the signal complementarity of Mel-Cu and cholinesterase, an integrated sensor array based on the Mel-Cu laccase-like activity, Mel-Cu peroxidase-like activity, acetylcholinesterase, and butyrylcholinesterase was creatively constructed. And it could successfully discriminate 12 pesticides at 0.5-50 μg/mL, which was significantly superior to traditional enzyme inhibition methods. Moreover, on the basis of above array, a unified stepwise prediction model was built using classification and regression algorithms in machine learning, which enabled concentration-independent qualitative identification as well as precise quantitative determination of multiple pesticide targets, simultaneously. The sensing accuracy was verified by blind sample analysis, in which the species was correctly identified and the concentration was predicted within 10% error, suggesting great intelligent recognition ability. Further, the proposed method also demonstrated significant immunity to interference and practical application feasibility, providing powerful means for pesticide residue analysis.

Accelerated and precise identification of antioxidants and pesticides using a smartphone-based colorimetric sensor array

The integration of smartphones with conventional analytical approaches plays a crucial role in enhancing on-site detection platforms for point-of-care testing. Here, we developed a simple, rapid, and efficient three-channel colorimetric sensor array, leveraging the peroxidase (POD)-like activity of polydopamine-decorated FeNi foam (PDFeNi foam), to identify antioxidants using both microplate readers and smartphones for signal readouts. The exceptional catalytic capacity of PDFeNi foam enabled the quick catalytic oxidation of three typical peroxidase substrates (TMB, OPD and 4-AT) within 3 min. Consequently, we constructed a colorimetric sensor array with cross-reactive responses, which was successfully applied to differentiate five antioxidants (i.e., glycine (GLY), glutathione (GSH), citric acid (CA), ascorbic acid (AA), and tannic acid (TAN)) within the concentration range of 0.1-10 μM, quantitatively analyze individual antioxidants (with AA and CA as model analytes), and assess binary mixtures of AA and GSH. The practical application was further validated by discriminating antioxidants in serum samples with a smartphone for signal readout. In addition, since pesticides could be absorbed on the surface of PDFeNi foam through π-π stacking and hydrogen bonding, the active sites were differentially masked, leading to featured modulation on POD-like activity of PDFeNi foam, thereby forming the basis for pesticides discrimination on the sensor array. The nanozyme-based sensor array provides a simple, rapid, visual and high-throughput strategy for precise identification of various analytes with a versatile platform, highlighting its potential application in point-care-of diagnostic, food safety and environmental surveillance.

Encapsulation of Enzymes into Hydrophilic and Biocompatible Metal Azolate Framework: Improved Functions of Biocatalyst in Cascade Reactions and its Sensing Applications

Multiple enzyme-triggered cascade biocatalytic reactions are vital in vivo or vitro, considering the basic biofunction preservation in living organisms and signals transduction for biosensing platforms. Encapsulation of such enzymes into carrier endows a sheltering effect and can boost catalytic performance, although the selection and preparation of an appropriate carrier is still a concern. Herein, focusing on MAF-7, a category of metal azolate framework (MAF) with superiority against the topologically identical ZIF-8, this enzyme@MAF system can ameliorate the sustainability of encapsulating natural enzymes into carriers. The proposed biocatalyst composite AChE@ChOx@MAF-7/hemin is constructed via one-pot in situ coprecipitation method. Subsequently, MAF-7 is demonstrated to exhibit an excellent capacity of the carrier and protection against external factors in the counterpart of ZIF-8 through encapsulated and free enzymes. In addition, detections for specific substrates or inhibitors with favorable sensitivity are accomplished, indicating that the properties above expectation of different aspects of the established platform are successfully realized. This biofunctional composite based on MAF-7 can definitely provide a potential approach for optimization of cascade reaction and enzyme encapsulation.

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.

Ultrasmall CuMn-His Nanozymes with Multienzyme Activity at Neutral pH: Construction of a Colorimetric Sensing Array for Biothiol Detection and Disease Identification

Biothiol assays offer vital insights into health assessment and facilitate the early detection of potential health issues, thereby enabling timely and effective interventions. In this study, we developed ultrasmall CuMn-Histidine (His) nanozymes with multiple enzymatic activities. CuMn-His enhanced peroxidase (POD)-like activity at neutral pH was achieved through hydrogen bonding and electrostatic effects. In addition, CuMn-His possesses laccase (LAC)-like and superoxide dismutase (SOD)-like activities at neutral pH. Based on three different enzyme mimetic activities of CuMn-His at neutral pH, the colorimetric sensing array without changing the buffer solution was successfully constructed. The array was successfully used for the identification of three biothiols, glutathione (GSH), cysteine (Cys), and homocysteine (Hcy). Subsequently, excellent application results were shown in complex serum and cellular level analyses. This study provides an innovative strategy for the development of ultrasmall bimetallic nanozymes with multiple enzymatic activities and the construction of colorimetric sensing arrays.

Construction and Application of Nanozyme Sensor Arrays

Compared with traditional "lock-key mode" biosensors, a sensor array consists of a series of sensing elements based on intermolecular interactions (typically hydrogen bonds, van der Waals forces, and electrostatic interactions). At the same time, sensor arrays also have the advantages of fast response, high sensitivity, low energy consumption, low cost, rich output signals, and imageability, which have attracted widespread attention from researchers. Nanozymes are nanomaterials which own enzyme-like properties. Because of the adjustable activity, high stability, and cost effectiveness of nanozymes, they are potential candidates for construction of sensor arrays to output different signals from analytes through the chemoresponse of colorants, which solves the shortcomings of traditional sensors that they cannot support multiple detection and lack universality. Recently, a sensor array based on nanozymes as nonspecific recognition receptors has attracted much more attention from researchers and has been applied to precise recognition of proteins, bacteria, and heavy metals. In this perspective, attention is given to nanozymes and the regulation of their enzyme-like activity. Particularly, the building principles and methods for sensor arrays based on nanozymes are analyzed, and the applications are summarized. Finally, the approaches to overcome the challenges and perspectives are also presented and analyzed for facilitating further research and development of nanozyme sensor arrays. This perspective should be helpful for gaining insight into research ideas within the field of nanozyme sensor arrays.

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.

Iron-Doped Polymer Dots with Enhanced Fluorescence and Dual Enzyme Activity for Versatile Bioassays

Nanozymes with multiple functionalities endow biochemical sensing with more sensitive and efficient analytical performance by widening the sensing modes. Meanwhile, the target-oriented design of multifunctional nanozymes for certain biosensing remains challenging. Herein, a constructive strategy of doping iron into polymer dots (PDs) to achieve nanozymes with excellent oxidase-mimicking and peroxidase-mimicking activity is proposed. Compared with the Fe-free PDs prepared under the same mild condition, the Fe-doped PDs (Fe-PDs) exhibit greatly boosted fluorescence at 500 nm. While applying 3,3',5,5'-tetramethylbenzidine (TMB) as a chromogenic substrate, the fluorescence of the Fe-PDs can be further quenched by oxTMB due to the inner filter effect (IFE). Inspired by this, a simple but efficient colorimetric and fluorometric dual-mode sensing platform is developed for monitoring the reducing substances ascorbic acid (AA), α-glucosidase (α-Glu), and its inhibitors (AGIs). We believe that such multifunctional enzyme-mimic materials will provoke the exploration of multimode sensing strategy with strong practicality to serve as a versatile tool in biochemical sensing.

Perspectives for the Role of Single-Atom Nanozymes in Assisting Food Safety Inspection and Food Nutrition Evaluation

Single-atom nanozymes (SAzymes) have been greatly developed for rapid detection, owing to their rich active sites and excellent catalytic activity. Although several excellent reviews concentrating on SAzymes have been reported, they mainly focused on advanced synthesis, sensing mechanisms, and biomedical applications. To date, few reviews elaborate on the promising applications of SAzymes in food safety inspection and food nutrition evaluation. In this paper, we systematically reviewed the enzyme-like activity of SAzymes and the catalytic mechanism, in addition to recent research advances of SAzymes in the domain of food safety inspection and food nutrition evaluation in the past few years. Furthermore, current challenges hampering practical applications of SAzymes in food assay are summarized and analyzed, and possible research areas focusing on SAzyme-based sensors in rapid food testing are also proposed.

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.

A colorimetric sensor array based on nanoceria crosslinked and heteroatom-doped graphene oxide nanoribbons for the detection and discrimination of multiple pesticides

Nanozymes have demonstrated high potential in constructing colorimetric sensor array for pesticides. However, rarely array for pesticides constructed without bio-enzyme were reported. Herein, nanoceria crosslinked graphene oxide nanoribbons (Ce-GONRs) and heteroatom-doped graphene oxide nanoribbons (Ce-BGONRs and Ce-NGONRs) were prepared, demonstrating excellent peroxidase-like activities. A colorimetric sensor array was developed based on directly inhibiting the peroxidase-like activities of the above three nanozymes, which realized the discrimination and quantitative analysis of six pesticides. In the presence of pesticides including carbaryl (Car), fluroxypyr-mepthyl (Flu), thiophanate-methyl (Thio), thiram (Thir), diafenthiuron (Dia) and fomesafen (Fom), the peroxidase-like activities of three nanozymes were inhibited to different degrees, resulting in different fingerprint responses. The six pesticides in the concentration range of 0.1-50 μg/mL and two pesticides mixtures at varied ratios could be detected and discriminated, and minimum detection limit for pesticides was 0.022 μg/mL. In addition, this sensor array has been successfully applied for pesticides discrimination in lake water and apple samples. This work provided a new strategy of constructing simple and sensitive colorimetric sensor array for pesticides based on directly inhibiting the catalytic activities of nanozymes.