Ensuring food safety by artificial intelligence-enhanced nanosensor arrays.

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

Integrated gold nanorods-based dual-signal platform for accurate total antioxidant capacity assessment in food samples.

Accurate assessment of Total Antioxidant Capacity (TAC) in food is crucial for evaluating nutritional quality and potential health benefits. This study aims to enhance the sensitivity and reliability of TAC detection through a dual-signal method, combining colorimetric and photothermal signals. Gold nanorods (AuNRs) were utilized to establish a dual-signal method duo to the colorimetric and photothermal properties. Fenton reaction can etch the AuNRs from the tips, as a result, a blue shift in the longitudinal LSPR absorption peak was obtained, leading to significant changes in color and photothermal effects, facilitating discrimination through both visual observation and thermometer measurements. In the presence of antioxidants, the Fenton reaction was suppressed or inhibited, protecting the AuNRs from etching. The colorimetric and photothermal signals were therefore positively correlated with TAC levels, enabling dual-signal detection of TAC. The linear range of AA was 4-100 µM in both colorimetry and photothermal modes, with detection limits of 1.60 µM and 1.38 µM, respectively. This dual-signal approach achieves low detection limits, enhancing precision and sensitivity. The method thus has the potential to act as a promising candidate for TAC detection in food samples, contributing to improved food quality and safety assessment.

Visual detection of aldehyde gases using a silver-loaded paper-based colorimetric sensor array.

The small molecule aldehydes are volatile organic compounds (VOCs), possessing cytotoxicity and carcinogenicity. Long-term exposure can pose a serious threat to human health. Based on an in-situ reduction colorimetric method to generate silver nanoparticles and induce colorimetric response, we proposed a silver-loaded paper-based colorimetric sensor array for visually detecting and differentiating five relatively common trace small molecule aldehyde gases. The silver ions are immobilized onto a porous filter paper and stabilized by complexing agents of branched polyethyleneimine, ethylenediamine, and 1,6-diaminohexane, respectively. The as-fabricated sensor array expresses remarkable stability and capacity to resist humidity. The qualitative analysis reveals that the sensor array has excellent selectivity for aldehyde gases and displays remarkable anti-interference ability. The quantitative analysis indicates that the sensor array exhibits superior sensitivity for five aldehyde gases, with limits of detection (LODs) of 9.0 ppb for formaldehyde (FA), 3.1 ppm for acetaldehyde (AA), 3.5 ppm for propionaldehyde (PA), 23.8 ppb for glutaric dialdehyde (GD), and 71.5 ppb for hydroxy formaldehyde (HF), respectively. Importantly, these LODs are all comfortably below their respective permissible exposure limits. A unique colorimetric response fingerprint is observed for each analyte. Standard chemometric methods illustrate that the sensor array has excellent clustering capability for these aldehyde gases. Additionally, the sensor array's response is irreversible and possesses outstanding performance for cumulative monitoring. This colorimetric sensor array based on silver ions reduced to silver nanoparticles offers a novel detection method for the continuous, ultrasensitive, and visual detection of trace airborne pollutants.

Anion-binding-induced selective aggregation and self-degradation: Influence of positional isomerism on the anion selectivity and mode of binding of an imine-based receptor.

Imine based positional isomers (8E)-N-(4-((E)-(perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L and (10E)-N-(3-(E-Perfluorophenylimino)methyl)benzylidene)-2,3,4,5,6-pentafluorobenzenamine, L1 have been designed, and synthesized by functionalizing two electron deficient aromatic moieties at the para-para'/ortho-ortho' positions in the phenyl core of the L and L1 respectively. The responses of L and L1 towards various anionic species are examined. The positional isomers L and L1 differs not only by showing distinguishable color change upon addition of anions but also differentiates themselves by the way of self-assembling together upon binding with cyanide anion. The naked-eye colorimetric experiments, UV-Vis, Nuclear Magnetic Resonance, and Infra-Red spectroscopic analyses reveal that the isomer L binds fluoride anion through 2:1 stoichiometry ratio. Unlike fluoride complex, the isomer L form aggregates while binding with cyanide ion. On the other hand, isomer L1 does not show any instant color change upon additions of any anion. Interestingly, after thirty minutes, only the color of the cyanide complex is turned into dark brown. While analyzing the spectroscopic results of cyanide complex of L1, it is found that the cyanide complex begins to decompose and finally it is completely decomposed within 30 min. This unprecedented phenomenon about the colorimetric sensing of cyanide and destruction of cyanide complex with respect to time has not been reported in the literature yet. To the best of our knowledge this is the first example of study of sensing controlling the selectivity, mode of binding, self-aggregating and degradation properties of anionic complexes under the influence of positional isomeric effects. This present investigation provides simple and effective strategy to construct the sensor molecules with tunable binding properties in terms of easy to prepare as well as easy to use as a colorimetric sensor. _____________________________________________________________________________________________________.

Perfluoroalkyl functionalized-Au nanoparticle sensor: Employing rate of spectrum shifting for highly selective and sensitive detection of per- and polyfluoroalkyl substances (PFASs) in aqueous environments.

Per- and polyfluoroalkyl substances (PFASs) are emerging contaminants detected ubiquitously and have negative impacts on human health and ecosystem; thus, developing in-situ sensing technique is important to ensure safety. Herein, we report a novel colorimetric-based sensor with perfluoroalkyl receptor attached to citrate coated gold nanoparticles (Citrate-Au NPs) that can detect several PFASs including perfluorocarboxylates with different chain lengths (PFHxA, PFOA, PFNA, PFDA), perfluorooctanoic sulfonate (PFOS), and perfluorooctanoic phosphonate (PFOPA). The sensor detects PFASs utilizing fluorous interaction between PFASs and the perfluoroalkyl receptor of Citrate-Au NPs in a solution at a fixed salt concentration, inducing changes in nanoparticle dispersity and the solution color. The rate of spectrum shift was linearly dependent on PFASs concentrations. Citrate-Au NPs with size between 29 - 109 nm were synthesized by adjusting citrate/Au molar ratios, and 78 nm showed the best sensitivity to PFOA concentration (with level of detection of 4.96 µM). Citrate-Au NPs only interacted with PFASs with perfluoroalkyl length > 4 and not with non-fluorinated alkyl compound (nonanoic acid). The performance of Citrate-Au NP based sensor was strongly dependent on the chain length of the perfluoroalkyl group and the head functional group; higher sensitivity was observed with longer chain over shorter chain, and with sulfonate functional group over carboxylate and phosphonate. The sensor was tested using real water samples (i.e., tap water, filtered river water), and it was found that the sensor is capable of detecting PFASs in these conditions if calibrated with the corresponding water matrix. While further optimization is needed, this study demonstrated new capability of Citrate-Au NPs based sensor for detection of PFASs in water.

Nanozyme-catalyzed and zwitterion-modified swabs based for the detection of Listeria monocytogenes in complex matrices.

In recent years, nanozymes have been widely used in the field of biosensing and food safety testing due to their advantages of low cost, high stability, easy modification and adjustable catalytic activity. However, how to reduce the signal interference generated by reducing substances, macromolecules and colored substances in the food matrix in nanozymes-based colorimetric sensing is still a major challenge. In this paper, using Listeria monocytogenes as a model analyte, sodium sulfonyl methacrylate (SBMA) polymers were modified onto cotton swabs by photothermal polymerization and combined with Listeria monocytogenes-specific aptamer (Apt1) to prepare swabs that can specifically capture and isolate Listeria monocytogenes from complex matrices (SBMA/Apt1 cotton swab). In addition, in combination with the inhibitory effect of the aptamer (Apt2) on the oxidase activity of Mn3O4 NPs, a colorimetric biosensor based on nanozymes that can quantitatively, sensitively, and specifically identify Listeria monocytogenes in food products was constructed. The results showed that the colorimetric signal of the method was linear with the concentration of Listeria monocytogenes in the range of 2.83-2.83 × 105 CFU/mL, and the limit of detection was 2.64 CFU/mL, which can be used for the detection of Listeria monocytogenes in complex environments and food samples.

Portable Sensing Probe for Real-Time Quantification of Ammonia in Blood Samples.

The detection of ammonia levels in blood is critical for diagnosing and monitoring various medical conditions, including liver dysfunction and metabolic disorders. However, traditional diagnostic methods are slow and cumbersome, often involving multiple contact-based steps such as ammonia separation in alkali conditions followed by distillation or microdiffusion, leading to delays in diagnosis and treatment. Herein, we developed a colorimetric assay capable of rapid detection of ammonia in whole blood or plasma samples, utilizing 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO)-oxidized cellulose nanocrystals (TCNC) coupled with gold nanoparticles (AuNPs). The basis of our assay relies on either (i) the interaction between the carboxylate group (-COO) of TEMPO and ammonium ions or (ii) the manipulation of AuNPs surface plasmon resonance (SPR) through the formation of Au(NH3)43+, which displaces a redox mediator, resazurin, resulting in observable multicolor displays at various concentrations of ammonia. The colorimetric assay exhibits a wide linear detection range for dissolved NH4+ (0.1-37 µM) with a low limit of detection (LOD) of 0.1 µM. Additionally, it effectively measures NH3(g) concentrations in the range of 0.5-144 µM. The fabricated electrochemical nose (E-nose) device demonstrates excellent analytical performance for plasma ammonia sensing (0.05-256 µM). Experimental results demonstrate a linear detection range suitable for clinical applications, with excellent correlation to standard laboratory methods, offering a practical solution for point-of-care (PoC) testing. We anticipate that this approach can be applied broadly to improve patient monitoring and treatment by providing immediate and accurate ammonia measurements in a clinical setting.

Nanozyme-based colorimetric sensor arrays coupling with smartphone for discrimination and "segmentation-extraction-regression" deep learning assisted quantification of flavonoids.

Achieving rapid, cost effective, and intelligent identification and quantification of flavonoids is challenging. For fast and uncomplicated flavonoid determination, a sensing platform of smartphone-coupled colorimetric sensor arrays (electronic noses) was developed, relying on the differential competitive inhibition of hesperidin, nobiletin, and tangeretin on the oxidation reactions of nanozymes with a 3,3',5,5'-tetramethylbenzidine substrate. First, density functional theory calculations predicted the enhanced peroxidase-like activities of CeO2 nanozymes after doping with Mn, Co, and Fe, which was then confirmed by experiments. The self-designed mobile application, Quick Viewer, enabled a rapid evaluation of the red, green, and blue values of colorimetric images using a multi-hole parallel acquisition strategy. The sensor array based on three channels of CeMn, CeFe, and CeCo was able to discriminate between different flavonoids from various categories, concentrations, mixtures, and the various storage durations of flavonoid-rich Citri Reticulatae Pericarpium through a linear discriminant analysis. Furthermore, the integration of a "segmentation-extraction-regression" deep learning algorithm enabled single-hole images to be obtained by segmenting from a 3 × 4 sensing array to augment the featured information of array images. The MobileNetV3-small neural network was trained on 37,488 single-well images and achieved an excellent predictive capability for flavonoid concentrations (R2 = 0.97). Finally, MobileNetV3-small was integrated into a smartphone as an application (Intelligent Analysis Master), to achieve the one-click output of three concentrations. This study developed an innovative approach for the qualitative and simultaneous multi-ingredient quantitative analysis of flavonoids.

Developing colorimetric ammonia-sensing nanocomposite films based on potato starch/PVA and ZnCu-BTC nanorods for real-time monitoring food freshness.

Smart packaging material capable of real-time monitoring of food freshness is essential for ensuring food safe. At present, colorimetric ammonia-sensing smart film often possesses issues with complicated production, high cost, and inferior long-term colour stability. Herein, Zinc­copper bimetallic organic framework (ZnCu-BTC, BTC = 1,3,5-benzenetricarboxylate acid) nanorods with colorimetric ammonia-responsiveness were synthesized by adopting facile aqueous solution method, which were then explored as nano inclusions in potato starch/polyvinyl alcohol (PS/PVA) composite film towards developing high-performance smart packaging material. The results demonstrated that the introduction of ZnCu-BTC nanorods within PS/PVA brought about remarkable improvement in blend compatibility, accompanied by a boost in tensile strength to 47.2 MPa, as well as enhanced ultraviolet (UV) blocking efficacy (over 95.0 %). Additionally, the barrier properties of PS/PVA film against water vapor and oxygen were fortified due to the addition of ZnCu-BTC. More importantly, the developed PS/PVA/ZnCu-BTC nanocomposite film displayed satisfactory antibacterial activity (over 99 %) against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), favorable colorimetric ammonia-sensing ability, and long-term colour stability. The ZnCu-BTC incorporated PS/PVA nanocomposite film could grant real-time detection of prawn freshness decline via remarkable colour change, indicating vast promise for smart food packaging applications.

Colorimetric IPN hydrogels embedded with colloidal photonic crystals: A novel approach for the detection of ethanol and Ba2+ ions in water.

A critical bottleneck in sensor technology is the rapid and precise detection of specific analytes in complex matrices, hindering advancements in environmental monitoring, healthcare, and industrial process control. This study addresses this challenge by introducing a novel composite hydrogel sensor designed for rapid and selective detection of ethanol and barium ions (Ba2+) in aqueous environments. The sensor integrates interpenetrating network (IPN) hydrogels with embedded colloidal photonic crystals (CPCs), synthesized via a solution-based polymerization approach. This innovative configuration allows CPCs to dynamically adjust their photonic bandgap in response to environmental changes, manifesting as a visible, colorimetric shift. This response stems from the synergy between the mechanical properties of the IPN hydrogel and the optical sensitivity of CPCs. Upon exposure to analytes such as ethanol and Ba2+, the sensor exhibits a rapid and reversible color transition that is directly proportional to their concentration. Notably, ethanol (0 vol%-80 vol%) and Ba2+ (5-17.5 mM) induce a distinct blueshift in the photonic bandgap and trigger a color change from red-orange to green due to the alteration in the swelling behavior of the IPN hydrogel, affecting its lattice constant. The IPN hydrogel-CPC composite demonstrates exceptional operational stability and facilitates rapid detection, making it ideal for on-site applications without the need for complex equipment. These characteristics make the composite hydrogel sensor a promising candidate for environmental monitoring, industrial process control, and public health diagnostics, paving the way for the development of next-generation responsive sensor materials.

Cu2Cl(OH)3 nanozyme-based colorimetric sensor array for phosphates discrimination and disease identification.

The identification of phosphates holds significant importance in many physiological processes and disease diagnosis, and traditional detection techniques struggle to simultaneously detect and distinguish phosphates. The complexity of synthesizing sensing units restricts the construction of sensor arrays as well. In this study, a bifunctional dicopper chloride trihydroxide (Cu2Cl(OH)3) nanozyme with conspicuous laccase- and peroxidase-like activities has been synthesized in basic deep eutectic solvents (DES). Exploiting the various regulatory impacts of multiple phosphates on the dual-enzyme mimicking activities, the sensor array based on the laccase mimic and peroxidase mimic properties of Cu2Cl(OH)3 was designed, which has been successfully harnessed for the identification of eight phosphates (ATP, ADP, AMP, PPi, Pi, GTP, GDP, and GMP). This approach streamlines the creation of sensor arrays. Besides, the three simulated actual samples (healthy individuals, moderately ill patients, and severely ill patients) have been accurately distinguished. This work makes a substantial contribution to enhancing the highly effective construction of array channels and promoting discrimination of phosphates in intricate samples.

Vapochromic wool fibers for hazardous ammonia detection using xanthohumol biomolecule from natural extract of common hop (Humulus lupulus L.).

Ammonia is a colorless gas, yet it can be fatal if inhaled or ingested in high enough concentrations. Herein, a solid-state colorimetric smart wool (WL) sensor for ammonia was developed. Common hop (Humulus lupulus L.) is a natural resource of spectroscopical dyestuff known as xanthohumol (XN). Wool fabrics were dyed with different concentrations of xanthohumol extract using the high-temperature high-pressure method in the presence of a mordant. The coloration parameters and absorption spectra were employed to explore the yellow-to-white colorimetric shift of the wool fabric after it was exposed to aqueous ammonia. The wool fabric showed an excellent detection limit of 5 to 125 ppm. When the ammonia concentration was increased, the absorbance spectra demonstrated a hypsochromic shift from 498 nm to 367 nm. This could be attributed to changes in the molecular structure of xanthohumol that happen owing to intramolecular charge delocalization. Using transmission electron microscopy (TEM), the mordant/xanthohumol nanoparticles were measured to have diameters of 15-40 nm. The xanthohumol-finished wool fabrics showed good colorfastness properties. The incorporation of mordant/xanthohumol nanoparticles into wool fabrics showed no negative effects on their stiffness or air-permeability.

Quantitative and qualitative detection of target heavy metals using anti-interference colorimetric sensor Array combined with near-infrared spectroscopy.

An anti-interference colorimetric sensor array (CSA) technique was developed for the qualitative and quantitative detection of target heavy metals in corn oil. This method involves a binding mechanism that triggers changes in atomic energy levels and visible color changes. A custom-built olfactory visualization device was employed to gather spectral data, revealing distinct CSA color difference patterns. Subsequently, three pattern recognition algorithms were used to create an identification model for the target heavy metals. The results showed that the ACO-KNN (Ant Colony Optimization-K-Nearest Neighbor) model outperformed the other models, achieving accuracy rates of 90.28% and 89.58% for the calibration and prediction sets, respectively. The ACO-PLS (Partial Least Square) model was more stable with the lowest root mean square error of prediction (RMSEP), which were 0.1730 and 0.1180, respectively. The limit of detection (LOD) and quantification (LOQ) of Pb and Hg were (0.3, 0.6, 1.1 and 2.2) x 10-3 mg/L, respectively.

Smartphone-based detection and discrimination of amine vapors by a single dye-adsorbed material.

Smartphone-assisted analysis has become widely utilized for detecting various species in recent years. In such studies, multiple dyes should be employed to ensure selectivity and analyte discrimination. In our research, we have demonstrated the capability of a specially synthesized dye to selectively detect and discriminate liquid amine vapors. The developed material employs meso-toluene-α,ß,α',ß'-tetrabromoBODIPY immobilized on a thin-layer chromatography plate, exhibiting structure-specific color changes in response to amine vapors. The hue values of these colors, observed under both ambient and UV light, enable discrimination even among closely related amine structures. A mobile application has also been developed for the rapid interpretation of test results.

Quantitative determination of zearalenone in wheat by the CSA-NIR technique combined with chemometrics algorithms.

In the current study, a colorimetric sensor array combined with near-infrared (NIR) spectroscopy was used to quantitatively analyze zearalenone in wheat. The portable NIR spectrometer was used to scan the porphyrin reaction points of the wheat colorimetric sensor and collect spectral data. Subsequently, based on all the NIR spectral data, the two models and three feature selection algorithms are compared, and the best performance model and the best feature variable input are selected. Concurrently, the Kernel-based Extreme Learning Machine (KELM) model optimized by the two parameter optimization algorithms was compared, and the best parameter optimization algorithm was selected. Among all evaluation models, the KELM model optimized by the Competitive Adaptive Reweighted Sampling algorithm combined with the rime optimization algorithm has the best prediction effect. The predicted RP2 is 0.9900, and the root mean square error of prediction (RMSEP) is 18.4610 µg∙kg-1.

Fabrication of Highly Sensitive and Selective Nitrite Colorimetric Sensor Based on the Enhanced Peroxidase Mimetic Activity of Using Acetic Acid Capped Zinc Oxide Nanosheets.

Nitrite ions (NO2-), as one of the leading type-A inorganic-anion, showing significant-effects in the aquatic environment and also to humans health. Whereas, the higher uptake causes detrimental threat to human health leading to various chronic diseases, thus demanding efficient, reliable and convenient method for its monitoring. For this purpose, in the present research study we have fabricated the mimetic nonozyme like catalyst based colorimetric nitrite sensor. The acetic acid capped Zinc Oxide (ZnO) nanosheets (NSs) were introduce as per-oxidase mimetic like catalyst which shows high efficiency towards the oxidative catalysis of colorless tetramethylbenzidine (TMB) to oxidized-TMB (blue color) in the presence of Hydrogen-peroxide (H2O2). The present nitrite ions will stimulate the as formed oxidized-TMB (TMBox), and will caused diazotization reaction (diazotized-TMBox), which will not only decreases the peak intensity of UV-visible peak of TMBox at 652 nm but will also produces another peak at 446 nm called as diazotized-TMBox peak, proving the catalytic reaction between the nitrite ions and TMBox. Further, the prepared colorimetric sensor exhibits better sensitivity with a wider range of concentration (1 × 10-3-4.50 × 10-1 µM), lowest limit of detection (LOD) of 0.22 ± 0.05 nM and small limit of quantification (LOQ) 0.78 ± 0.05 nM having R2 value of 0.998. Further, the colorimetric sensor also manifest strong selectivity towards NO2- as compared to other interference in drinking water system. Resultantly, the prepared sensor with outstanding repeatability, stability, reproducibility, re-usability and its practicability in real water samples also exploit its diverse applications in food safety supervision and environmental monitoring.

The Identification of Oral Cariogenic Bacteria through Colorimetric Sensor Array Based on Single-Atom Nanozymes.

Effective identification of multiple cariogenic bacteria in saliva samples is important for oral disease prevention and treatment. Here, a simple colorimetric sensor array is developed for the identification of cariogenic bacteria using single-atom nanozymes (SANs) assisted by machine learning. Interestingly, cariogenic bacteria can increase oxidase-like activity of iron (Fe)─nitrogen (N)─carbon (C) SANs by accelerating electron transfer, and inversely reduce the activity of Fe─N─C further reconstruction with urea. Through machine-learning-assisted sensor array, colorimetric responses are developed as "fingerprints" of cariogenic bacteria. Multiple cariogenic bacteria can be well distinguished by linear discriminant analysis and bacteria at different genera can also be distinguished by hierarchical cluster analysis. Furthermore, colorimetric sensor array has demonstrated excellent performance for the identification of mixed cariogenic bacteria in artificial saliva samples. In view of convenience, precise, and high-throughput discrimination, the developed colorimetric sensor array based on SANs assisted by machine learning, has great potential for the identification of oral cariogenic bacteria so as to serve for oral disease prevention and treatment.

Oxidized 3,3',5,5'-tetramethylbenzidine nanobelts enhance colorimetric sensing of H2O2.

Herein, oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB) nanobelts were developed to enhance the colorimetric and paper-based sensing of H2O2. It was found that the minor component of Fe2+ in Na2SO4 reagent could catalyze the oxidization of TMB by H2O2 into positively charged oxTMB, which was further assembled into dark blue oxTMB nanobelts via electrostatic interaction with SO42-. The extinction originating from the absorption and scattering of oxTMB nanobelts was utilized to quantitatively detect H2O2 with a wide linear detection range (1.0-300 µM) and a low limit of detection (0.48 µM). In addition, no coffee-ring effect was observed in the test zone of the paper-based colorimetric array, which was beneficial to judge the color by naked eye. Finally, the colorimetric method was applied to detect H2O2 in contact lens care solution. This work not only proposed a new colorimetric sensing platform for H2O2, but also highlighted the minor component in the reagent might influence the experimental result.

Colorimetric sensor array for identifying antioxidants based on pyrolysis-free synthesis of Fe-N/C single-atom nanozymes.

Iron-anchored nitrogen/doped carbon single-atom nanozymes (Fe-N/C), which possess homogeneous active sites and adjustable catalytic environment, represent an exemplary model for investigating the structure-function relationship and catalytic activity. However, the development of pyrolysis-free synthesis technique for Fe-N/C with adjustable enzyme-mimicking activity still presents a significant challenge. Herein, Fe-N/C anchored three carrier morphologies were created via a pyrolysis-free approach by covalent organic polymers. The peroxidase-like activity of these Fe-N/C nanozymes was regulated via the pores of the anchored carrier, resulting in varying electron transfer efficiency due to disparities in contact efficacy between substrates and catalytic sites within diverse microenvironments. Additionally, a colorimetric sensor array for identifying antioxidants was developed: (1) the Fe-N/C catalytically oxidized two substrates TMB and ABTS, respectively; (2) the development of a colorimetric sensor array utilizing oxTMB and oxABTS as sensing channels enabled accurate discrimination of antioxidants such as ascorbic acid (AsA), glutathione (GSH), cysteine (Cys), gallic acid (GA), and caffeic acid (CA). Subsequently, the sensor array underwent rigorous testing to validate its performance, including assessment of antioxidant mixtures and individual antioxidants at varying concentrations, as well as target antioxidants and interfering substances. In general, the present study offered valuable insights into the active origin and rational design of nanozyme materials, and highlighting their potential applications in food analysis.

Advancements of Glucose Monitoring Biosensor: Current State, Generations of Technological Progress, and Innovation Dynamics.

Glucose monitoring is essential for managing diabetes, and continuous glucose monitoring biosensors can offer real-time monitoring with little invasiveness. However, challenges remain in improving sensor accuracy, selectivity, and overall performance. This article aims to review current trends and recent advancements in glucose-monitoring biosensors while evaluating their benefits and limitations for diabetes monitoring. An analysis of current literature on transdermal glucose sensors was conducted, focusing on detection techniques, novel nanomaterials, and integrated sensor systems. Recent research has led to advancements in electrochemical, optical, electromagnetic, and sonochemical sensors for transdermal glucose detection. The use of novel nanomaterials and integrated sensor designs has improved sensitivity, selectivity, and accuracy. However, issues like calibration requirements, motion artifacts, and skin irritation persist. Transdermal glucose sensors show promise for non-invasive, convenient diabetes monitoring but require further enhancements to address limitations in accuracy, reliability, and biocompatibility. Continued research and innovation focusing on sensor materials, designs, and surface chemistry is needed to optimize biosensor performance and utility. The study offers a comprehensive analysis of the present status of technological advancement and highlights areas that need more research.