MoS2/MWCNTs porous nanohybrid network with oxidase-like characteristic as electrochemical nanozyme sensor coupled with machine learning for intelligent analysis of carbendazim

Machine learning in nanozymes: from design to application

Nanozymes, a distinctive class of nanomaterials endowed with enzyme-like activity and kinetics akin to enzyme-catalysed reactions, present several advantages over natural enzymes, including cost-effectiveness, heightened stability, and adjustable activity. However, the conventional trial-and-error methodology for developing novel nanozymes encounters growing challenges as research progresses. The advent of artificial intelligence (AI), particularly machine learning (ML), has ushered in innovative design approaches for researchers in this domain. This review delves into the burgeoning role of ML in nanozyme research, elucidating the advancements achieved through ML applications. The review explores successful instances of ML in nanozyme design and implementation, providing a comprehensive overview of the evolving landscape. A roadmap for ML-assisted nanozyme research is outlined, offering a universal guideline for research in this field. In the end, the review concludes with an analysis of challenges encountered and anticipates future directions for ML in nanozyme research. The synthesis of knowledge in this review aims to foster a cross-disciplinary study, propelling the revolutionary field forward.

Selenium-based nanozyme as a fluorescence-enhanced probe and imaging for chlortetracycline in living cells and foods

Developing rapid monitoring methods to detect antibiotic residues in food plays an important role in safeguarding human health. This study presents the development of a novel fluorescence-enhanced detection method for chlortetracycline (CTC) using a GSH-Se nanozyme. A GSH-Se nanozyme prepared using a one-pot hydrothermal method not only possesses excellent fluorescent properties but also exhibits good glutathione peroxidase-like activity. The results show that the addition of CTC leads to a significant enhancement in the fluorescence intensity of GSH-Se, and this increase exhibits a good linear relationship with the concentration of CTC. The linear range of this method is 0.02-1 µM, and the limit of detection (LOD) for CTC was 0.02 µM. Moreover, the cell toxicity of GSH-Se is low and can be used for monitoring and imaging of CTC in cells, and satisfactory results have been obtained in the analysis of actual food samples.

Unveiling the antibacterial strategies and mechanisms of MoS2: a comprehensive analysis and future directions

Antibiotic resistance is a growing problem that requires alternative antibacterial agents. MoS2, a two-dimensional transition metal sulfide, has gained significant attention in recent years due to its exceptional photocatalytic performance, excellent infrared photothermal effect, and impressive antibacterial properties. This review presents a detailed analysis of the antibacterial strategies and mechanism of MoS2, starting with its morphology and synthesis methods and focusing on the different interaction stages between MoS2 and bacteria. The paper summarizes the main antibacterial mechanisms of MoS2, such as photocatalytic antibacterial, enzyme-like catalytic antibacterial, physical antibacterial, and photothermal-assisted antibacterial. It offers a comprehensive discussion focus on recent research studies of photocatalytic antibacterial mechanisms and categorizes them, guiding the application of MoS2 in the antibacterial field. Overall, the review provides an in-depth understanding of the antibacterial mechanisms of MoS2 and presents the challenges and future directions for the improvement of MoS2 in the field of high-efficiency antibacterial materials.

Machine Learning in Bioelectrocatalysis

At present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high-value chemicals, clean biofuel, and biodegradable new materials. It has been applied in biosensors, biofuel cells, and bioelectrosynthesis. However, there are certain flaws in the application process of bioelectrocatalysis, such as low accuracy/efficiency, poor stability, and limited experimental conditions. These issues can possibly be solved using machine learning (ML) in recent reports although the combination of them is still not mature. To summarize the progress of ML in bioelectrocatalysis, this paper first introduces the modeling process of ML, then focuses on the reports of ML in bioelectrocatalysis, and ultimately makes a summary and outlook about current issues and future directions. It is believed that there is plenty of scope for this interdisciplinary research direction.

A portable sensor for glucose detection in Huangshui based on blossom-shaped bimetallic organic framework loaded with silver nanoparticles combined with machine learning

In this work, we propose a blossom-like Ni, Co bimetallic metal-organic framework (NiCo-MOF) synthesized hydrothermally and decorated with silver nanoparticles (AgNPs) via chemical reduction for electrochemical enzyme-free glucose sensing. The NiCo-MOF nanostructures had large specific surface area and good sensing performance. The AgNPs enhanced the electrochemical performance of the MOF, resulting in excellent electrochemical activity. The sensor exhibited sensitivities of 1191.84 and 271.19 μA mM-1 cm-2 in the linear ranges of 0.005-1.125 and 1.525-5.325 mM, respectively, with a detection limit of 2.3 μM. The sensor was successfully applied for glucose determination in Huangshui (HS) using an artificial neural network as machine learning (ML) model. The R2 value near 1, low RMSE, and high RPD values of the proposed ML model demonstrate its excellent fitting and prediction performance. This will provide a fast and portable intelligent sensing analysis technology for the detection of glucose in HS.

Bimetallic CoCu nanoparticles anchored on COF/SWCNT for electrochemical detection of carbendazim

Carbendazim (CBZ) is a widespread fungicide used in crop protection, but the CBZ residues in drinking water, fruits, and vegetables can also cause adverse impacts on public health due to direct exposure. In this paper, a ternary synergistic composite of bimetallic CoCu nanoparticles anchored on covalent organic framework/single-walled carbon nanotube (CoCu/COF/SWCNT) was prepared and further applied as an electrochemical sensing platform for detecting CBZ. The sensor showed a sensitive response performance toward CBZ oxidation, as a result of the enhanced charge transfer ability, large electrochemically active surface area, and high electro-catalytic activity from the rational integration of the ternary components in CoCu/COF/SWCNT. Under the optimal conditions, the proposed sensor exhibited a detection range of 0.001 to 10 μM and a limit detection of 0.65 nM for CBZ detection. In addition, the sensor displayed practical feasibility for the determination of CBZ in water and pear samples with a recovery of 96.1 % to 102.1 %.

Fabrication of an Azithromycin Sensor

Azithromycin (AZY) is a well-known top-prioritized antibiotic and is used by humans in strong concentrations. However, the side effects of the AZY antibiotic may cause some serious and significant damage to humans and the environment. Thus, there is a need to develop effective and sensitive sensors to monitor accurate concentrations of AZY. In the last decade, electrochemistry-based sensors have received enormous attention from the scientific community because of their high sensitivity, selectivity, cost-effectiveness, fast response, rapid detection response, simple fabrication, and working principle. It is important to mention that electrochemical sensors rely on the properties of electrode modifiers. Hence, the selection of electrode materials is of great significance when designing and developing efficient and robust electrochemical sensors. In this study, we fabricated an AZY sensor by utilizing a molybdenum disulfide/titanium aluminum carbide (MoS2@Ti3AlC2) composite as the electrode material. The MoS2@Ti3AlC2 composite was synthesized via a simple sonication process. The synthesized MoS2@Ti3AlC2 composite was characterized using a powder X-ray diffraction (XRD) method to examine the phase purity and formation of the MoS2@Ti3AlC2 composite. Scanning electron microscopy (SEM) was used to study the surface morphological features of the prepared MoS2@Ti3AlC2 composite, whereas energy dispersive X-ray spectroscopy (EDAX) was adopted to determine the elemental composition of the prepared MoS2@Ti3AlC2 composite. The glassy carbon (GC) electrode was modified with the prepared MoS2@Ti3AlC2 composite and applied as the AZY sensor. The sensing performance of the MoS2@Ti3AlC2 composite-modified GC electrode was studied using linear sweep voltammetry. The sensor demonstrated excellent performance when determining AZY and showed a good detection limit of 0.009 µM with a sensitivity of 6.77 µA/µM.cm2.

Electroanalytical overview: the sensing of carbendazim

Carbendazim is a broad-spectrum systemic fungicide that is used to control various fungal diseases in agriculture, horticulture, and forestry. Carbendazim is also used in post-harvest applications to prevent fungal growth on fruits and vegetables during storage and transportation. Carbendazim is regulated in many countries and banned in others, thus, there is a need for the sensing of carbendazim to ensure that high levels are avoided which can result in potential health risks. One approach is the use of electroanalytical sensors which present a rapid, but highly selective and sensitive output, whilst being economical and providing portable sensing platforms to support on-site analysis. In this minireview, we report on the electroanalytical sensing of carbendazim overviewing recent advances, helping to elucidate the electrochemical mechanism and provide conclusions and future perspectives of this field.

Carbon-Based Electrochemical (Bio)sensors for the Detection of Carbendazim: A Review

Carbendazim, a fungicide widely used in agriculture, has been classified as a hazardous chemical by the World Health Organization due to its environmental persistence. It is prohibited in several countries; therefore, detecting it in food and environmental samples is highly necessary. A reliable, rapid, and low-cost method uses electrochemical sensors and biosensors, especially those modified with carbon-based materials with good analytical performance. In this review, we summarize the use of carbon-based electrochemical (bio)sensors for detecting carbendazim in environmental and food matrixes, with a particular interest in the role of carbon materials. Focus on publications between 2018 and 2023 that have been describing the use of carbon nanotubes, carbon nitride, graphene, and its derivatives, and carbon-based materials as modifiers, emphasizing the analytical performance obtained, such as linear range, detection limit, selectivity, and the matrix where the detection was applied.

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).

Application of Nanozymes in Environmental Monitoring, Management, and Protection

Nanozymes are nanomaterials with enzyme-like activity, possessing the unique properties of nanomaterials and natural enzyme-like catalytic functions. Nanozymes are catalytically active, stable, tunable, recyclable, and versatile. Therefore, increasing attention has been paid in the fields of environmental science and life sciences. In this review, we focused on the most recent applications of nanozymes for environmental monitoring, environmental management, and environmental protection. We firstly introduce the tuning catalytic activity of nanozymes according to some crucial factors such as size and shape, composition and doping, and surface coating. Then, the application of nanozymes in environmental fields are introduced in detail. Nanozymes can not only be used to detect inorganic ions, molecules, organics, and foodborne pathogenic bacteria but are also involved in the degradation of phenolic compounds, dyes, and antibiotics. The capability of nanozymes was also reported for assisting air purification, constructing biofuel cells, and application in marine antibacterial fouling removal. Finally, the current challenges and future trends of nanozymes toward environmental fields are proposed and discussed.

Lighting Up Agricultural Sustainability in the New Era through Nanozymology: An Overview of Classifications and Their Agricultural Applications

With the concept of sustainable agriculture receiving increasing attention from humankind, nanozymes, nanomaterials with enzyme-like activity but higher environmental endurance and longer-term stability than natural enzymes, have enabled agricultural technologies to be reformative, economic, and portable. Benefiting from their multiple catalytic activities and renewable nanocharacteristics, nanozymes can shine in agricultural scenarios using enzyme engineering and nanoscience, acting as sustainable toolboxes to improve agricultural production and reduce the risk to agricultural systems. Herein, we comprehensively discuss the classifications of nanozymes applied in current agriculture, including peroxidase-like, oxidase-like, catalase-like, superoxide dismutase-like, and laccase-like nanozymes, as well as their biocatalytic mechanisms. Especially, different applications of nanozymes in agriculture are deeply reviewed, covering crop protection and nutrition, agroenvironmental remediation and monitoring, and agroproduct quality monitoring. Finally, the challenges faced by nanozymes in agricultural applications are proposed, and we expect that our review can further enhance agricultural sustainability through nanozymology.

Mo3Se4 nanoparticle with ROS scavenging and multi-enzyme activity for the treatment of DSS-induced colitis in mice

Ulcerative colitis (UC), as a most common inflammatory bowel disease (IBD), has become a global public health concern. Exploring novel method of treating UC is urgent and necessary. Recently, nanozyme with excellent antioxidant properties may be one useful therapeutic strategy. In this study, a two-dimensional transition metal chalcogenide (TMCs) nano flake and polyethylene glycol (PEG) modified Mo₃Se₄ nano flakes (PMNFs) was synthesized, which had multi-enzyme activity, including peroxidase, glutathione peroxidase (GPx), superoxide dismutase (SOD), and catalase (CAT). The inhibition effect of PMNFs on sodium dextran sulfate (DSS)-induced colitis was explored. UC was effectively inhibited by PMNFs in this work. PMNFs significantly reduced disease activity index (DAI) score, including weight loss, colon shorten and histopathological abnormalities. The possible mechanism of PMNFs-attenuated colitis was investigated. The results showed that PMNFs reversed DSS-induced oxidative damage, and the antioxidant pathway Nrf2-keap1 signal was activated by PMNFs. Moreover, PMNFs suppressed the expression of pro-inflammatory factors including IL-1β, TNF-α, IFN-β and IL-6 via the inactivation of TLR4/NF-κB pathway in DSS-induced colitis and LPS-treated macrophage. Furthermore, PMNFs treatment prevented the reduction of tight junction proteins (ZO-1, occludin, and claudin-1) and mucin-2 (MUC-2) as well as the up-regulation of epithelial apoptosis caused by DSS. These findings demonstrate that the PMNFs against DSS-induced colitis due to its prevention on oxidative damage, inflammation, and intestine barrier breakdown. Thus, PMNFs have a potential application in the treatment of various oxidative stress or inflammation-related diseases.

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Mo₃Se₄ nano flakes (PMNFs) can effective scavenge ROS in vivo and in vitro.

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PMNFs have multi-enzyme activity, including the peroxidase, GPx, SOD, and CAT.

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PMNFs can prevent symptoms of colitis induced by DSS in mice.

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PMNFs against DSS-induced colitis through prevention on oxidative damage, inflammation, and intestine barrier breakdown.

Recent Progress in Non-Enzymatic Electroanalytical Detection of Pesticides Based on the Use of Functional Nanomaterials as Electrode Modifiers

This review presents recent advances in the non-enzymatic electrochemical detection and quantification of pesticides, focusing on the use of nanomaterial-based electrode modifiers and their corresponding analytical response. The use of bare glassy carbon electrodes, carbon paste electrodes, screen-printed electrodes, and other electrodes in this research area is presented. The sensors were modified with single nanomaterials, a binary composite, or triple and multiple nanocomposites applied to the electrodes’ surfaces using various application techniques. Regardless of the type of electrode used and the class of pesticides analysed, carbon-based nanomaterials, metal, and metal oxide nanoparticles are investigated mainly for electrochemical analysis because they have a high surface-to-volume ratio and, thus, a large effective area, high conductivity, and (electro)-chemical stability. This work demonstrates the progress made in recent years in the non-enzymatic electrochemical analysis of pesticides. The need for simultaneous detection of multiple pesticides with high sensitivity, low limit of detection, high precision, and high accuracy remains a challenge in analytical chemistry.

A portable wireless intelligent electrochemical sensor based on layer-by-layer sandwiched nanohybrid for terbutaline in meat products

The aim of this study is to develop a portable wireless intelligent nanosensor (PWIN) for rapid cost-effective on-site determination of terbutaline (TRA) residue in meat products outdoors in comparison with traditional nanosensor and high-performance liquid chromatography (HPLC). The layer-by-layer sandwiched nanohybrid fabricated by platinum-palladium nanoparticles, carboxylated graphene and graphene-like molybdenum disulfide displayed a wide linear range of 0.55-14.9 μmol/L using the portable potentiostat with smartphone, and the result was almost close to the linear range (0.4-14 μmol/L) using the traditional potentiostat with desktop computer for TRA. The limit of detections were identified as 0.44 μmol/L and 0.18 μmol/L, respectively. PWIN displayed satisfactory recovery (91%-98.43%) of TRA in samples by the standard addition method and in comparison with both traditional sensor (93.79%-98%) and HPLC (93.4%-98.6%), revealing that PWIN for rapid cost-effective on-site analysis in the food safety field is feasible.

A Competitive Assay Based on Dual-Mode Au@Pt-DNA Biosensors for On-Site Sensitive Determination of Carbendazim Fungicide in Agricultural Products

Carbendazim (CBZ), a systemic, broad-spectrum benzimidazole fungicide, is widely used to control fungal diseases in agricultural products. Its residues might pose risks to human health and the environment. Therefore, it is warranted to establish a rapid and reliable method for its residual quantification. Herein, we proposed a competitive assay that combined aptamer (DNA) specific recognition and bimetallic nanozyme gold@platinum (Au@Pt) catalysis to trace the CBZ residue. The DNA was labeled onto bimetallic nanozyme Au@Pt surface to produce Au@Pt probes (Au@Pt-DNA). The magnetic Fe₃O₄ was functionalized with a complementary strand of DNA (C-DNA) to form Fe₃O₄ probes (Fe₃O₄-C-DNA). Subsequently, the CBZ and the Fe₃O₄ probes competitively react with Au@Pt probes to form two Au@Pt-DNA biosensors (Au@Pt-ssDNA-CBZ and Au@Pt-dsDNA-Fe₃O₄). The Au@Pt-ssDNA-CBZ biosensor was designed for qualitative analysis through a naked-eye visualization strategy in the presence of CBZ. Meanwhile, Au@Pt-dsDNA-Fe₃O₄ biosensor was developed to quantitatively analyze CBZ using a multifunctional microplate reader. A competitive assay based on the dual-mode Au@Pt-DNA biosensors was established for onsite sensitive determination of CBZ. The limit of detection (LOD) and recoveries of the developed assay were 0.038 ng/mg and 71.88-110.11%, with relative standard deviations (RSDs) ranging between 3.15 and 10.91%. The assay demonstrated a good correlation with data acquired from liquid chromatography coupled with mass spectrometry/mass spectrometry analysis. In summary, the proposed competitive assay based on dual-mode Au@Pt-DNA biosensors might have a great potential for onsite sensitive detection of pesticides in agro-products.

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.

Electrochemical Sensors and Biosensors for the Analysis of Tea Components: A Bibliometric Review

Tea is a popular beverage all around the world. Tea composition, quality monitoring, and tea identification have all been the subject of extensive research due to concerns about the nutritional value and safety of tea intake. In the last 2 decades, research into tea employing electrochemical biosensing technologies has received a lot of interest. Despite the fact that electrochemical biosensing is not yet the most widely utilized approach for tea analysis, it has emerged as a promising technology due to its high sensitivity, speed, and low cost. Through bibliometric analysis, we give a systematic survey of the literature on electrochemical analysis of tea from 1994 to 2021 in this study. Electrochemical analysis in the study of tea can be split into three distinct stages, according to the bibliometric analysis. After chromatographic separation of materials, electrochemical techniques were initially used only as a detection tool. Many key components of tea, including as tea polyphenols, gallic acid, caffeic acid, and others, have electrochemical activity, and their electrochemical behavior is being investigated. High-performance electrochemical sensors have steadily become a hot research issue as materials science, particularly nanomaterials, and has progressed. This review not only highlights these processes, but also analyzes and contrasts the relevant literature. This evaluation also provides future views in this area based on the bibliometric findings.

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 Enhances the Performance of Bioreceptor-Free Biosensors

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.

Recent Advances in Two-Dimensional Transition Metal Dichalcogenide Nanocomposites Biosensors for Virus Detection before and during COVID-19 Outbreak

The deadly Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) outbreak has become one of the most challenging pandemics in the last century. Clinical diagnosis reports a high infection rate within a large population and a rapid mutation rate upon every individual infection. The polymerase chain reaction has been a powerful and gold standard molecular diagnostic technique over the past few decades and hence a promising tool to detect the SARS-CoV-2 nucleic acid sequences. However, it can be costly and involved in complicated processes with a high demand for on-site tests. This pandemic emphasizes the critical need for designing cost-effective and fast diagnosis strategies to prevent a potential viral source by ultrasensitive and selective biosensors. Two-dimensional (2D) transition metal dichalcogenide (TMD) nanocomposites have been developed with unique physical and chemical properties crucial for building up nucleic acid and protein biosensors. In this review, we cover various types of 2D TMD biosensors available for virus detection via the mechanisms of photoluminescence/optical, field-effect transistor, surface plasmon resonance, and electrochemical signals. We summarize the current state-of-the-art applications of 2D TMD nanocomposite systems for sensing proteins/nucleic acid from different types of lethal viruses. Finally, we identify and discuss the advantages and limitations of TMD-based nanocomposites biosensors for viral recognition.

Portable wireless intelligent sensing of ultra-trace phytoregulator α-naphthalene acetic acid using self-assembled phosphorene/Ti3C2-MXene nanohybrid with high ambient stability on laser induced porous graphene as nanozyme flexible electrode

The harm of pesticide residues to human health via environmental pollution in agriculture has recently become a significant livelihood issue. Herein, a new strategy for smart ultra-trace analysis of phytoregulator α-naphthalene acetic acid (NAA) residues in farmland environments and agro-products via machine learning (ML) using a nanozyme flexible electrode fabricated by two-dimensional phosphorene (BP) nanohybrid with graphene-like titanium carbide MXene (Ti₃C₂-MXene) on the flexible substrate surface of laser-induced porous graphene (LIPG) is proposed. Highly ambient-stable BP nanohybrid with Ti₃C₂-MXene is prepared by ultrasonic-assisted liquid-phase exfoliation in organic solvent containing grinding black phosphorus, cuprous chloride and, Ti₃C₂-MXene that is obtained by selectively etching Al layers of Ti₃AlC₂. Nanozyme flexible electrode is fabricated by drop-coating Ti₃C₂-MXene/BP that is formed through electrostatic self-assembly between positively charged BP and negatively charged Ti₃C₂-MXene onto LIPG that is obtained by direct laser writing on commercial polyimide and patterned via a computer-aided design system as a flexible substrate. The ML model via artificial neural network algorithm for smart output of NAA is discussed. NAA is electrochemically detected in a wide linear range of 0.02-40 μM with a low limit of detection (LOD) of 1.6 nM using a portable mini-workstation. Large and rough surfaces, excellent electrochemical response, and satisfactory practicability demonstrated the feasibility and detectability of the proposed method. This will provide a portable wireless intelligent nanozyme flexible sensing platform for cost-effective, simple, fast and, ultra-trace detection of hazardous substances in the safety of environments, products, and food in agriculture.

A colorimetric sensing strategy based on enzyme@metal-organic framework and oxidase-like IrO2/MnO2 nanocomposite for α-glucosidase inhibitor screening

A highly sensitive colorimetric sensing strategy based on enzyme@metal-organic framework (GAA@Cu-MOF) and IrO₂/MnO₂ nanocomposite was exploited innovatively for screening of α-glucosidase (GAA) inhibitors. IrO₂/MnO₂ nanocomposite exhibits excellent oxidase-mimicking activity which can directly catalyze the oxidation of 3,3^,5,5^,-tetramethylbenzidine (TMB) into a blue product with an absorption maximum at 652 nm. And GAA@Cu-MOF can decompose L-ascorbic acid-2-O-α-D-glucopyranosyl (AAG) to ascorbic acid (AA). The produced AA can destroy the IrO₂/MnO₂ nanocomposite and reduce its oxidase-like activity. However, the generation of AA is restricted when GAA inhibitors are added to the system, which allows the oxidase-like activity of the IrO₂/MnO₂ nanocomposite to be maintained. In view of this, a method for screening of GAA inhibitors was developed. In addition to enhancing the stability of GAA, the method can also effectively avoid the potential interference of H₂O₂ in the screening process of GAA inhibitors, which helps to improve the sensitivity of the method. Therefore, highly sensitive determination for acarbose and ascorbic acid are achieved with detection limits of 6.27 nM and 1.23 μM, respectively. The proposed method was successfully applied to screen potential GAA inhibitors from oleanolic acid derivatives. Graphical abstract.

Multiwalled Carbon Nanotube-N-Doped Graphene/Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) Nanohybrid for Electrochemical Application in Intelligent Sensors and Supercapacitors

In this study, we reported the preparation of a conducting polymeric/inorganic nanohybrid consisting of multiwalled carbon nanotubes (MWCNT), N-doped graphene (NGr), and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), and its electrochemical application in intelligent sensors and supercapacitors. The multilayer thin film of the PEDOT:PSS-supported MWCNT-NGr nanohybrid was prepared by a facile layer-by-layer assembly strategy. The obtained conducting polymeric/inorganic nanohybrid modified electrode displayed superior electron transfer ability and a high specific surface area, which was used for electrochemical applications in intelligent sensors and supercapacitors. Remarkably, the fabricated amaranth sensor exhibited a broad linear range of 0.05-10 μM with a limit of detection of 0.015 μM under the optimal conditions. With the help of the response surface methodology, multivariate optimization was used as a substitute for the traditional single variable optimization to reflect the complete real effects of multivariate optimization in a sensing platform. Machine learning implemented by hybrid genetic algorithm-artificial neural network was used as an intelligent analysis model to replace the traditional regression analysis model for realizing intelligent analysis and output of sensing system. The MWCNT-NGr/PEDOT:PSS modified electrode exhibited a considerable specific capacitance of 6.5 mF cm^-2 at a current density of 2.0 mA cm^-2. The proposed results provided a new thought for a nanosensing platform equipped with a supercapacitor as a self-powered electrochemical energy storage system and machine learning as an intelligent analysis and output system in the near future.