Facile and rapid one-step mass production of flexible 3D porous graphene nanozyme electrode via direct laser-writing for intelligent evaluation of fish freshness

Advances in machine learning-enhanced nanozymes

Nanozymes, synthetic nanomaterials that mimic the catalytic functions of natural enzymes, have emerged as transformative technologies for biosensing, diagnostics, and environmental monitoring. Since their introduction, nanozymes have rapidly evolved with significant advancements in their design and applications, particularly through the integration of machine learning (ML). Machine learning (ML) has optimized nanozyme efficiency by predicting ideal size, shape, and surface chemistry, reducing experimental time and resources. This review explores the rapid advancements in nanozyme technology, highlighting the role of ML in improving performance across various bioapplications, including real-time monitoring and the development of chemiluminescent, electrochemical and colorimetric sensors. We discuss the evolution of different types of nanozymes, their catalytic mechanisms, and the impact of ML on their property optimization. Furthermore, this review addresses challenges related to data quality, scalability, and standardization, while highlighting future directions for ML-driven nanozyme development. By examining recent innovations, this review highlights the potential of combining nanozymes with ML to drive the development of next-generation diagnostic and detection technologies.

Research progress of chilled meat freshness detection based on nanozyme sensing systems

It is important to develop rapid, accurate, and portable technologies for detecting the freshness of chilled meat to meet the current demands of meat industry. This report introduces freshness indicators for monitoring the freshness changes of chilled meat, and systematically analyzes the current status of existing detection technologies which focus on the feasibility of using nanozyme for meat freshness sensing detection. Furthermore, it examines the limitations and foresees the future development trends of utilizing current nanozyme sensing systems in evaluating chilled meat freshness. Harmful chemicals are produced by food spoilage degradation, including biogenic amines, volatile amines, hydrogen sulfide, and xanthine, which have become new freshness indicators to evaluate the freshness of chilled meat. The recognition mechanisms are clarified based on the special chemical reaction with nanozyme or directly inducting the enzyme-like catalytic activity of nanozyme.

Machine learning assisted biosensing technology: An emerging powerful tool for improving the intelligence of food safety detection

Recently, the application of biosensors in food safety assessment has gained considerable research attention. Nevertheless, the evaluation of biosensors' sensitivity, accuracy, and efficiency is still ongoing. The advent of machine learning has enhanced the application of biosensors in food security assessment, yielding improved results. Machine learning has been preliminarily applied in combination with different biosensors in food safety assessment, with positive results. This review offers a comprehensive summary of the diverse machine learning methods employed in biosensors for food safety. Initially, the primary machine learning methods were outlined, and the integrated application of biosensors and machine learning in food safety was thoroughly examined. Lastly, the challenges and limitations of machine learning and biosensors in the realm of food safety were underscored, and potential solutions were explored. The review's findings demonstrated that algorithms grounded in machine learning can aid in the early detection of food safety issues. Furthermore, preliminary research suggests that biosensors could be optimized through machine learning for real-time, multifaceted analyses of food safety variables and their interactions. The potential of machine learning and biosensors in real-time monitoring of food quality has been discussed.

Degradation mechanism and development of detection technologies of ATP-related compounds in aquatic products: recent advances and remaining challenges

The degradation of ATP-related compounds is an important biochemical process that reflects the freshness of aquatic products after death. There has been considerable interest in investigating the factors affecting the degradation of ATP-related compounds in aquatic products and in developing techniques to detect them. This review provides the latest knowledge on the degradation mechanisms of ATP-related compounds during the storage of aquatic products and discusses the latest advances in ATP-related compound detection techniques. The degradation mechanisms discussed include mainly degradation pathways, endogenous enzymes, and microbial mechanisms of action. Microbial activity is the main reason for the degradation of IMP and related products during the mid to late storage of aquatic products, mainly through the related enzymes produced by microorganisms. Further elucidation of the degradation mechanisms of ATP-related compounds provides new ideas for quality control techniques in raw aquatic products during storage. The development of new technologies for the detection of ATP-related compounds has become a significant area of research. And, biosensors further improve the efficiency and accuracy of detection and have potential application prospects. The development of biosensor back-end modalities (test strips, fluorescent probes, and artificial intelligence) has accelerated the practical application of biosensors for the detection of ATP-related compounds.

Carbon-Based Enzyme Mimetics for Electrochemical Biosensing

Natural enzymes are used as special reagents for the preparation of electrochemical (bio)sensors due to their ability to catalyze processes, improving the selectivity of detection. However, some drawbacks, such as denaturation in harsh experimental conditions and their rapid de- gradation, as well as the high cost and difficulties in recycling them, restrict their practical applications. Nowadays, the use of artificial enzymes, mostly based on nanomaterials, mimicking the functions of natural products, has been growing. These so-called nanozymes present several advantages over natural enzymes, such as enhanced stability, low cost, easy production, and rapid activity. These outstanding features are responsible for their widespread use in areas such as catalysis, energy, imaging, sensing, or biomedicine. These materials can be divided into two main groups: metal and carbon-based nanozymes. The latter provides additional advantages compared to metal nanozymes, i.e., stable and tuneable activity and good biocompatibility, mimicking enzyme activities such as those of peroxidase, catalase, oxidase, superoxide dismutase, nuclease, or phosphatase. In this review article, we have focused on the use of carbon-based nanozymes for the preparation of electrochemical (bio)sensors. The main features of the most recent applications have been revised and illustrated with examples selected from the literature over the last four years (since 2020).

Prospects for the next generation of artificial enzymes for ensuring the quality of chilled meat: Opportunities and challenges

As living standards rise, the demand for high-quality chilled meat among consumers also grows. Researchers and enterprises have been interested in ensuring the quality of chilled meat in all links of the downstream industry. Nanozyme has shown the potential to address the aforementioned requirements. Reasons and approaches for the application of nanozymes in the freshness assessment or shelf life extension of chilled meat were discussed. The challenges for applying these nanozymes to ensure the quality of chilled meat were also summarized. Finally, this review examined the safety, regulatory status, and consumer attitudes toward nanozymes. This review revealed that the freshness assessment of chilled meat is closely related to mimicking the enzyme activities of nanozymes, whereas the shelf life changes of chilled meat are mostly dependent on the photothermal activities and pseudophotodynamic activities of nanozymes. In contrast, studies regarding the shelf life of chilled meat are more challenging to develop, as excessive heat or reactive oxygen species impair its quality. Notably, meat contains a complex matrix composition that may interact with the nanozyme, reducing its effectiveness. Nanopollution and mass manufacturing are additional obstacles that must be overcome. Therefore, it is vital to choose suitable approaches to ensure meat quality. Furthermore, the safety of nanozymes in meat applications still needs careful consideration owing to their widespread usage.

A Highly Sensitive Electrochemical Sensor for Cd2+ Detection Based on Prussian Blue-PEDOT-Loaded Laser-Scribed Graphene-Modified Glassy Carbon Electrode

Heavy metal ion pollution has had a serious influence on human health and the environment. Therefore, the monitoring of heavy metal ions is of great practical significance. In this work, we describe the development of an electrochemical sensor to detect cadmium (Cd2+) using a Prussian blue (PB), poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT)-loaded laser-scribed graphene (LSG) nanocomposite-modified glassy carbon electrode (GCE). In this nanocomposite material, we successfully brought together the advantages of an extraordinarily large surface area. The accumulation of PB nanoparticles results in an efficient electrochemical sensor with high sensitivity and selectivity and fast detection ability, developed for the trace-level detection of Cd2+. Electrochemical features were explored via cyclic voltammetry (CV), whereas the stripping voltammetry behavior of modified electrodes was analyzed by utilizing differential pulse voltammetry. Compared with bare GCE, the LSG/PB-PEDOT/GCE modified electrode greatly increased the anodic stripping peak currents of Cd2+. Under the optimized conditions, the direct and facile detection of Cd2+ was achieved with a wide linear range (1 nM–10 µM) and a low LOD (0.85 nM).

Laser-scribed Graphene Electrodes Functionalized with Nafion/Fe3O4 Nanohybrids for the Ultrasensitive Detection of Neurotoxin Drug Clioquinol

The analysis of pharmaceutical active ingredients plays an important role in quality control and clinical trials because they have a significant physiological effect on the human body even at low concentrations. Herein, a flexible three-electrode system using laser-scribed graphene (LSG) technology, which consists of Nafion/Fe₃O₄ nanohybrids immobilized on LSG as the working electrode and LSG counter and reference electrodes on a single polyimide film, is presented. A Nafion/Fe₃O₄/LSG electrode is constructed by drop coating a solution of Nafion/Fe₃O₄, which is electrostatically self-assembled between positively charged Fe₃O₄ and negatively charged Nafion on the LSG electrode and is used for the first time to determine a neurotoxicity drug (clioquinol; CQL) in biological samples. Owing to their porous 3D structure, an enriched surface area at the active edges and polar groups (OH, COOH, and -SO₃H) in Nafion/Fe₃O₄/LSG electrodes resulted in excellent wettability to facilitate electrolyte diffusion, which gave ∼twofold enhancement in electrocatalytic activity over LSG electrodes. The experimental parameters affecting the analytical performance were investigated. The quantification of clioquinol on the Nafion/Fe₃O₄/LSG electrode surface was examined using differential pulse voltammetry and chronoamperometry techniques. The fabricated sensor displays preferable sensitivity (17.4 μA μM^-1 cm^-2), a wide linear range (1 nM to 100 μM), a very low detection limit (0.73 nM), and acceptable selectivity toward quantitative analysis of CQL. Furthermore, the reliability of the sensor was checked by CQL detection in spiked human blood serum and urine samples, and satisfactory recoveries were obtained.

Green synthesis of kudzu vine biochar decorated graphene-like MoSe2 with the oxidase-like activity as intelligent nanozyme sensing platform for hesperetin

It is an urgent need to exploit a potentially green, cost efficient and eco-friendly strategy for the utilization of waste kudzu vine. We developed a one-step green preparation of kudzu vine biochar (BC) decorated graphene-like molybdenum selenide (MoSe₂) with the oxidase-like activity as intelligent nanozyme sensing platform for voltametric detection of hesperetin (HP) in orange peel using the in-situ hydrothermal synthesis method. The structure and properties of MoSe₂-BC was characterized, and found that BC significantly improved electrochemical cycle stability, electronic conductivity, electrochemical active area, and electrocatalytic activity of MoSe₂. The oxidase-like activity of MoSe₂-BC was confirmed by the oxidization of the colorless substrate 3,3',5,5'-tetramethylbenzidine (TMB) to form blue products and the change of absorbance intensity of UV-vis absorption spectra. The MoSe₂-BC exhibited excellent electrochemical sensing performance for the detection of HP in wide linear ranges from 10 nM to 9.5 μM with a low limit of detection of 2 nM using differential pulse voltammetric method. An emerging machine learning technique is used to realize the intelligent sensing of HP, and the performance evaluation of regression analysis was selected to evaluate this technique. This work will provide a guidance for the preparation and application of biochar decorated graphene-like nanomaterials with the oxidase-like activity and the development of intelligent nanozyme sensing platform.

Intelligent analysis of maleic hydrazide using a simple electrochemical sensor coupled with machine learning

A simple electrochemical sensing platform based on a low-cost disposable laser-induced porous graphene (LIPG) flexible electrode for the intelligent analysis of maleic hydrazide (MH) in potatoes and peanuts coupled with machine learning (ML) was successfully designed. The LIPG electrode was patterned by a simple one-step laser-induced procedure on commercial polyimide film using a computer-controlled direct laser writing micromachining system and displayed excellent flexibility, 3D porous structure, large specific surface area, and preferable conductivity. A data partitioning technique was proposed for the optimal MH concentration ranges by selecting the size of datasets, including the size of the training set and the size of the test set combined with the performance metrics of ML models. Different algorithms such as artificial neural networks (ANN), random forest (RF), and least squares support vector machine (LS-SVM) were selected to build the ML models. Three ML models were evaluated, and the LS-SVM model displayed unique superiority. Both the recoveries and RSD of practical application were further measured to assess the feasibility of the selected LS-SVM model. This will have important theoretical and practical significance for the intelligent analysis of harmful residuals in agro-product safety using an electrochemical sensing platform.

Machine Learning-Reinforced Noninvasive Biosensors for Healthcare

The emergence and development of noninvasive biosensors largely facilitate the collection of physiological signals and the processing of health-related data. The utilization of appropriate machine learning algorithms improves the accuracy and efficiency of biosensors. Machine learning-reinforced biosensors are started to use in clinical practice, health monitoring, and food safety, bringing a digital revolution in healthcare. Herein, the recent advances in machine learning-reinforced noninvasive biosensors applied in healthcare are summarized. First, different types of noninvasive biosensors and physiological signals collected are categorized and summarized. Then machine learning algorithms adopted in subsequent data processing are introduced and their practical applications in biosensors are reviewed. Finally, the challenges faced by machine learning-reinforced biosensors are raised, including data privacy and adaptive learning capability, and their prospects in real-time monitoring, out-of-clinic diagnosis, and onsite food safety detection are proposed.

Nanozymes-Hitting the Biosensing "Target"

Nanozymes are a class of artificial enzymes that have dimensions in the nanometer range and can be composed of simple metal and metal oxide nanoparticles, metal nanoclusters, dots (both quantum and carbon), nanotubes, nanowires, or multiple metal-organic frameworks (MOFs). They exhibit excellent catalytic activities with low cost, high operational robustness, and a stable shelf-life. More importantly, they are amenable to modifications that can change their surface structures and increase the range of their applications. There are three main classes of nanozymes including the peroxidase-like, the oxidase-like, and the antioxidant nanozymes. Each of these classes catalyzes a specific group of reactions. With the development of nanoscience and nanotechnology, the variety of applications for nanozymes in diverse fields has expanded dramatically, with the most popular applications in biosensing. Nanozyme-based novel biosensors have been designed to detect ions, small molecules, nucleic acids, proteins, and cancer cells. The current review focuses on the catalytic mechanism of nanozymes, their application in biosensing, and the identification of future directions for the field.

Single-emission dual-enzyme magnetosensor for multiplex immunofluorometric assay of adulterated colorants in chili seasoning

In this work, a single-emission, dual-enzyme immunofluorometric magnetosensor was fabricated to simultaneously detect three illegal colorants in chili seasoning. Specifically, two enzymatic reactions catalyzed by horse radish peroxidase-labeled Rhodamine (RhB) antibody and glucose oxidase-labeled Sudan dyes (SuDs) antibody were performed within a functional microfluidic chip, leading to production of strongly fluorescent Resorufin. In addition, a compact analyzer assisted by a smartphone was developed to quantify signals. Compared with the available multiplex optical biosensors, this work demonstrated four superiorities: 1) Simple optical structure. Only single wavelength excitation/emission module was needed; 2) High multiplexing capacity through spatial resolution and signal resolution; 3) Precise determination by discriminant analysis; 4) Easy-operated and high-throughput parallel detection on 16-channel chips. Ultralow detection limits for RhB (0.0072 ng/mL), Sudan I (0.0040 ng/mL) and Sudan II (0.0260 ng/mL) were obtained by this magnetosensor, which opens a new approach in field detection of multiplex illegal dyes in food system.