A Hierarchical Au@PDA-PdCu Nanozyme for Signal- Amplified Immunochromatographic Detection of Carbofuran in Leafy Vegetables

A Hierarchical Au@PDA-PdCu Nanozyme for Signal- Amplified Immunochromatographic Detection of Carbofuran in Leafy Vegetables | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Hierarchical Au@PDA-PdCu Nanozyme for Signal- Amplified Immunochromatographic Detection of Carbofuran in Leafy Vegetables Haofeng Lao, Xuhui Yue, Xiaoqing Weng, Shaokang Zhang, Jiachen Shi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9490663/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Carbofuran residues threaten food safety and public health, yet conventional instrumental methods require expensive equipment and complicated pretreatment, while traditional immunochromatographic assays still lack sufficient sensitivity. Herein, a hierarchical Au@PDA-PdCu nanozyme was developed as a signal probe for a competitive immunochromatographic assay (ICA) for rapid carbofuran detection. The Au core served as a stable nanoplatform, the PDA interlayer enabled antibody immobilization, and the PdCu shell provided strong peroxidase-like activity for post-assay signal amplification. Three probe formats, namely liquid, sprayed, and lyophilized probes, were constructed and optimized. After DAB enhancement, the detection limit of the liquid-format strip decreased from 0.055 to 0.016 ng/mL, while the linear ranges of the sprayed- and lyophilized-format strips expanded to 0–100 ng/mL. In Chinese cabbage, chive, and spinach, all three formats exhibited good quantitative performance (R² > 0.98). The visual limits of detection were 5 ng/mL for the liquid- and sprayed-format strips and 1 ng/mL for the lyophilized-format strip. Recoveries ranged from 70% to 119%, with coefficients of variation of 3.7%–25.7%. Good specificity was observed, with cross-reactivity below 0.1% for most tested compounds except 3-hydroxycarbofuran. The liquid and lyophilized strips showed predicted shelf lives of over 1 year, and ICA results agreed well with LC–MS/MS. Overall, this method provides a rapid, sensitive, and practical tool for on-site carbofuran screening in leafy vegetables. Carbofuran nanozyme lateral flow immunoassay Au@PDA-PdCu DAB enhancement leafy vegetables Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Carbofuran, a broad-spectrum carbamate pesticide, has long been widely used to control a variety of agricultural pests 1 , 2 . However, its excessive application and persistence in the environment have raised global concerns because of the serious threats it poses to food safety and public health 3 , 4 . Acute exposure to carbofuran can cause neurotoxicity, endocrine disruption, and even death, whereas chronic low-dose exposure has been associated with long-term health risks 5 , 6 . Consequently, many countries have established strict maximum residue limits (MRLs), often below 10 µg/kg, particularly for leafy vegetables that are prone to pesticide accumulation 7 , 8 . These regulatory pressures highlight the urgent need to develop rapid, highly sensitive, and reliable detection technologies that can be directly applied at the points of production and distribution. Currently, the detection of carbofuran residues still mainly relies on chromatographic methods and their hyphenated mass spectrometric techniques, such as gas chromatography–mass spectrometry (GC–MS), high-performance liquid chromatography (HPLC), and liquid chromatography–tandem mass spectrometry (LC–MS/MS). Wang et al. established a capillary gas chromatographic method for the determination of carbofuran residues in aquatic products, confirming the feasibility of chromatographic techniques for the analysis of this class of pesticides 9 . In addition, Huertas-Pérez et al. proposed a reversed-phase HPLC method for the simultaneous determination of N-methylcarbamate pesticides, including carbofuran, in water and vegetable samples, demonstrating the applicability of HPLC-based methods for accurate carbamate residue analysis 10 . Osman et al. employed GC–MS to monitor pesticide residues in vegetable samples and identified carbofuran among the detected compounds, highlighting the utility of GC–MS for multiresidue analysis and confirmatory determination in food matrices 11 . Owing to their high sensitivity, high accuracy, and strong confirmatory capability, these methods are still regarded as reference standard methods for pesticide residue analysis, including carbofuran. However, such methods generally require expensive and sophisticated instrumentation, laborious and time-consuming sample pretreatment, and skilled personnel, which confines their use primarily to centralized laboratories and makes them unsuitable for rapid on-site screening. In contrast, immunochromatographic assays (ICAs) based on lateral flow strips have emerged as attractive alternatives because of their operational simplicity, rapid response, portability, and cost-effectiveness 12 – 15 . Abad et al. developed a nanocolloidal gold-based one-step immunochromatographic strip for the rapid detection of carbofuran, demonstrating the feasibility of colloidal gold ICA for fast on-site screening 16 . Yin et al. further constructed a dual-color immunochromatographic assay with two test lines and an independent control line for the simultaneous detection of paclobutrazol and carbofuran in agricultural products, highlighting the advantages of ICA in multiplexed and visualized detection 17 . However, conventional ICAs generally rely on colloidal gold or natural enzymes as signal labels, which often suffer from insufficient signal intensity, limited sensitivity, poor stability, and short storage life, particularly in complex food matrices 18 , 19 . To further improve analytical performance, Zhang et al. reported a double-label time-resolved fluorescent immunochromatographic assay for the rapid quantitative detection of carbofuran residues in agro-products, showing that fluorescent labeling strategies can markedly enhance detection sensitivity 20 . Similarly, Pei et al. employed Au@Ag core–shell nanoparticles as antibody and Raman reporter carriers to construct a surface-enhanced Raman scattering-based lateral flow immunoassay for the ultrasensitive detection of carbofuran residues in fruits and vegetables 21 . Despite their significantly improved sensitivity, these high-performance labeling systems usually depend on specialized instruments such as fluorescence or Raman devices, which still limits their broader application in low-cost, visual, and real-time on-site detection. Therefore, the development of innovative signal labels that integrate high catalytic efficiency, strong visual readout, and excellent stability remains crucial for advancing ICA platforms toward practical applications in food safety monitoring. Nanozymes, as nanomaterials with enzyme-like catalytic activities, have emerged as promising alternatives to conventional ICA labels because of their high stability, low cost, and excellent catalytic performance 22 , 23 . Compared with natural enzymes, nanozymes are less susceptible to environmental conditions such as temperature, pH, and storage, and can be rationally engineered to achieve efficient signal amplification and enhanced analytical sensitivity 24 , 25 . In addition, polydopamine (PDA) provides a favorable surface for antibody conjugation. Its intrinsic dark color can also improve the visual readout. Based on these advantages, we designed a hierarchical core–shell Au@PDA-PdCu nanozyme. In this structure, Au NPs serve as the core. PDA acts as an interfacial layer for antibody immobilization. The outer PdCu shell provides strong peroxidase-like catalytic activity. On this basis, we established a competitive ICA platform for the rapid detection of carbofuran. As shown in Fig. 1 , the antibody-labeled Au@PDA-PdCu nanozyme specifically participates in competitive recognition. It then further enhances the colorimetric signal through a catalytic chromogenic reaction. This platform enables rapid, sensitive, and stable visual detection of carbofuran. 2. Materials and Methods 2.1 Reagents, Materials, and Instruments HAuCl4·4H2O, H2O2, HEPES, Tween 80, trehalose, PEG 6000, PVP, mannitol, and sodium azide were purchased from Aladdin. Trisodium citrate, copper chloride, DMSO, MES, BSA, and NHS were obtained from Sinopharm. Dopamine hydrochloride, TMB, DAB, and EDC were purchased from Macklin. Palladium chloride was obtained from Bide Pharmatech. Proclin 300 was purchased from Shanghai Biochemical Technology. HPLC-grade acetonitrile was purchased from Thermo Fisher Scientific. Carbofuran and its structural analog standards were obtained from Tanmo Biotechnology. Anti-carbofuran monoclonal antibody, carbofuran antigen, goat anti-mouse IgG, NC membrane, sample pad, absorbent pad, PVC backing card, and conjugate pad were purchased from Suzhou Hongxin Technology. Ultrapure water was used throughout the experiments. The main instruments included a magnetic stirrer (HJ-6A), vortex mixer (TS-4500), ultrasonic cleaners (KQ-250B and F-100SD), UV–Vis spectrophotometer (T6PC), ultrapure water system (STU4100UVR), centrifuge (CenLee2050), analytical balance (ME204), refrigerator (BCD-536WpH), transmission electron microscope (TALOS F200X), pH meter (pHSJ-5), drying oven (DHG-9075A), XYZ dispensing and spraying system (HM3035), freeze dryer (LGJ-12A), strip cutter (ZG2000), and refrigerated centrifuge (VELOCITY 14R). 2.2 Preparation and characterization of Au@PDA-PdCu nanozymes Au@PDA-PdCu nanozymes were prepared according to previously reported methods with slight modifications 26 , 27 . Au nanoparticles (Au NPs) were first synthesized by the trisodium citrate reduction method. Briefly, 1 mL of 2% HAuCl₄ solution was added to 200 mL of ultrapure water, heated to boiling, and then rapidly mixed with 3 mL of 1% trisodium citrate. After reaction for 15 min, the solution was cooled to room temperature and stored at 4°C. For the preparation of Au@PDA, 10 mL of the Au NP solution was centrifuged (10000 r/min, 30 min), and the precipitate was resuspended in 10 mL of Tris-HCl buffer (10 mM, pH 8.5). Subsequently, 30 µL of 3% H₂O₂ and an optimized volume of dopamine hydrochloride solution (5 mg/mL) were added, and the mixture was stirred at 250 r/min for 1 h at room temperature in the dark. After centrifugation and washing, the product was redispersed in ultrapure water to obtain Au@PDA. Then, optimized volumes of 50 mM H₂PdCl₄ and 0.64 mg/mL CuCl₂ were added to 10 mL of the Au@PDA dispersion, followed by stirring at 200 r/min at room temperature. Immediately afterward, 1 mL of 50 mM NaBH₄ was added for reduction for 20 min to produce Au@PDA-PdCu nanozymes, which were stored at 4°C until use. To obtain nanozymes with good dispersibility and high catalytic activity, the dosages of dopamine hydrochloride, H₂PdCl₄, and CuCl₂ were optimized. The optimal amount of dopamine hydrochloride was determined by comparing the color changes and UV–vis absorption characteristics of the materials, whereas the Pd and Cu precursor amounts were optimized based on the absorbance change rate in the TMB-H₂O₂ chromogenic system together with the dispersion state of the materials. The corresponding results are shown in Figure S1 and Figure S2. For characterization, appropriately diluted dispersions of Au NPs, Au@PDA, and Au@PDA-PdCu were scanned in the range of 200–800 nm using ultrapure water as the blank. TEM samples were prepared by dropping the diluted dispersions onto carbon-coated copper grids and drying naturally. The particle morphology and shell structure were observed by transmission electron microscopy, and the elemental composition and distribution were further analyzed by EDS. 2.3 Peroxidase-Like Activity and Kinetic Analysis The peroxidase-like activity of Au@PDA-PdCu nanozymes was evaluated using TMB as the chromogenic substrate. Briefly, 2 mL of acetate buffer (0.2 mol/L, pH 3.6) was premixed with 100 µL of TMB solution (10 mg/mL), followed by the addition of 200 µL of Au@PDA-PdCu nanozyme dispersion and 300 µL of 30% H₂O₂. After mixing, the reaction was carried out at 37°C for 1 min, and the absorbance at 652 nm was recorded to assess the peroxidase-like catalytic activity. Kinetic analysis was performed by varying the substrate concentration and recording the initial reaction rate. When TMB was used as the variable substrate, 100 µL of TMB solution at different concentrations was added to a reaction system containing 2 mL of acetate buffer (0.2 mol/L, pH 3.6), 100 µL of Au@PDA-PdCu nanozyme dispersion, and 300 µL of 30% H₂O₂. When H₂O₂ was used as the variable substrate, its concentration was varied under the same conditions. After mixing, the reaction was conducted at 37°C, and the absorbance change at 652 nm was monitored over a certain period. The initial reaction rates were used to construct Michaelis–Menten curves, from which the Michaelis constant (Kₘ) and maximum reaction velocity (Vmax) were calculated to evaluate the substrate affinity and catalytic efficiency of the Au@PDA-PdCu nanozymes. 2.4 Preparation of Immunoprobes and Immunochromatographic Test Strips Immunoprobes were prepared by covalently coupling Au@PDA-PdCu nanozymes with anti-carbofuran monoclonal antibody via EDC/NHS chemistry. Briefly, 600 µL of Au@PDA-PdCu nanozyme dispersion was mixed with 400 µL of 10 mM MES buffer, followed by the addition of 5 µL of 1 mg/mL EDC, 5 µL of 1 mg/mL NHS, and 2 µL of anti-carbofuran monoclonal antibody. After shaking at room temperature for 1 h, 200 µL of 2% BSA was added to block the remaining active sites for another 1 h. The mixture was then centrifuged at 8000 r/min for 10 min, and the pellet was redispersed in the corresponding reconstitution solution to obtain the immunoprobes. According to the subsequent application mode, the probes were prepared in three formats: liquid, sprayed, and lyophilized. The liquid probe was stored directly in dispersion form, the sprayed probe was redispersed in spraying buffer for loading onto the sample pad, and the lyophilized probe was redispersed in lyophilization buffer, aliquoted into a 96-well plate, freeze-dried, and stored until use. The immunochromatographic test strips consisted of a PVC backing card, sample pad, NC membrane, and absorbent pad. The sample pad was pretreated in pretreatment solution for about 3 min, dried at 37°C, and cut into strips of 1.5 cm × 30 cm. The NC membrane was mounted onto the center of the PVC backing card, with the sample pad and absorbent pad overlapping the two ends by about 2 mm. Carbofuran-BSA conjugate and goat anti-mouse IgG were dispensed onto the test line (T line) and control line (C line), respectively, at 1 µL/cm using an XYZ dispensing platform, with a spacing of 5 mm between the two lines. After drying at 37°C, the coated NC membrane was cut into strips about 3.8 mm wide. For the liquid and lyophilized formats, the probes were not pre-immobilized on the strips, but were introduced during detection by pre-mixing with the sample or by reconstitution with the sample, respectively. For the sprayed format, the probes were pre-sprayed onto the sample pad, dried at 37°C for 2–4 h, and then assembled with the NC membrane and absorbent pad. All prepared strips were stored under dry conditions until use. 2.5 Optimization of Assay Conditions and DAB Signal Enhancement To obtain an immunochromatographic system with good stability and satisfactory detection performance, the preparation of nanozymes, immunoprobes, test strips, and assay conditions were systematically optimized. During nanozyme synthesis, the effects of dopamine hydrochloride dosage and the feeding ratio of Pd and Cu on the dispersibility and peroxidase-like activity of the materials were investigated. During immunoprobe preparation, the pH of the coupling system, EDC dosage, and antibody amount were further optimized. In the construction and detection of test strips, the type of NC membrane, the matching relationship between probe amount and coating antigen concentration on the T line, as well as the detection buffer and pH conditions, were compared to achieve better color development and competitive inhibition response. The optimization results of the matching relationship between probe dosage and coating antigen concentration for the three probe formats, as determined by the checkerboard titration method, are shown in Tables S1–S3. For the lyophilized probe, the lyophilization protectant system and solid content were optimized, as shown in Figure S3, while the freeze-drying time was further optimized as shown in Figure S4. For signal enhancement, the post-assay DAB–H₂O₂ system was optimized by comparing different H₂O₂ concentrations and DAB:H₂O₂ ratios in terms of band clarity, background interference, and color stability. After chromatography, the test strips were inserted into the optimized DAB–H₂O₂ substrate solution and reacted for 8 min, followed by rinsing with ultrapure water and drying. The Au@PDA-PdCu nanozymes catalyzed the oxidation of DAB to form brown insoluble precipitates, thereby achieving localized signal amplification at the T and C lines. 2.6 Immunochromatographic Detection and Performance Evaluation For detection, carbofuran standard solutions or vegetable extracts were introduced into the corresponding assay systems. For the liquid-format strips, 10 µL of immunoprobe was mixed with 90µL of sample solution in a microwell before chromatography. For the sprayed-format strips, 10 µL of buffer was mixed with 90µL of sample solution and then directly added onto the sample pad. For the lyophilized-format strips, 10 µL of buffer and 90µL of sample solution were added into a microwell containing the freeze-dried probe, mixed thoroughly, and then subjected to chromatography. After 10–15 min of chromatography, the color development of the test line (T line) and control line (C line) was recorded, and the signal intensities were measured using a strip reader or image analysis software. The relative detection response was expressed as the T/C value. Standard curves were established by plotting the T/C values against the logarithm of carbofuran concentration. The inhibition rate was calculated as follows: Inhibition rate (%) = \(\:\left(1-\frac{T/C}{{\left(T/C\right)}_{0}}\right)\times\:100\%\) where \(\:{\left(T/C\right)}_{0}\) is the signal ratio in the absence of carbofuran, and T/C is the signal ratio in the presence of carbofuran. After chromatography, the strips were further immersed in the optimized DAB-H₂O₂ enhancement solution for 8 min, rinsed with ultrapure water, and dried, after which the T-line and C-line signals were recorded again for performance analysis after signal enhancement. The analytical performance of the method was evaluated in terms of sensitivity, specificity, and stability. For sensitivity assessment, carbofuran standards were prepared in buffer at concentrations ranging from 0 to 100 ng/mL, and each concentration was tested in triplicate. Standard curves were constructed based on the T/C values obtained before and after DAB enhancement. For specificity evaluation, 3-hydroxycarbofuran, together with several common carbamate and organophosphorus pesticides, was used as potential interferents. Their effects on strip response were compared, and the cross-reactivity values were calculated. For stability evaluation, the three types of strips were subjected to accelerated aging at 55°C, and the changes in T/C values were monitored periodically to generate aging curves; the related results are shown in Figure S5. The standard curves, detection ranges before and after DAB enhancement, and the main analytical parameters of the three probe formats are presented in the Results section. 2.7 Pretreatment of Vegetable Samples and Method Validation Chinese cabbage, chive, and spinach were selected as representative leafy vegetable samples. After purchase, the edible portions were collected, surface impurities were removed, and the samples were chopped and thoroughly homogenized. For analysis, 2.0 g of homogenized sample was accurately weighed into a centrifuge tube, and 10 mL of 20% acetonitrile-PB buffer was added. After vortexing for 5 min, the mixture was centrifuged at 8000 r/min for 5 min, and the supernatant was collected as the sample extract. To balance carbofuran extraction efficiency and compatibility with the immunochromatographic system, the effects of PB buffer, 20% acetonitrile-PB buffer, 50% acetonitrile-PB buffer, and pure acetonitrile on strip color development were first compared. Based on the results, 20% acetonitrile-PB buffer was selected as the extraction solution for vegetable samples, and the related optimization results are shown in Figure S6. Blank matrix extracts of the three vegetables were then used as diluents to prepare matrix-matched standard solutions ranging from 0 to 100 ng/mL, which were applied to the three probe-based strip systems. After chromatography, DAB post-enhancement was performed as described in Section 2.6 , and calibration curves in vegetable matrices were established to evaluate the matrix applicability of the method. A summary of the calibration curves of the three strip formats in the three vegetable matrices is shown in Figure S7. The accuracy and precision of the method were evaluated by spike-recovery experiments. Carbofuran standards were spiked into blank extracts of the three vegetables at two concentration levels, and each level was tested in triplicate. The measured concentrations, recoveries, and relative standard deviations (RSDs) were calculated based on the matrix-matched calibration curves. In addition, the same samples were analyzed in parallel by LC–MS/MS to verify the reliability of the established immunochromatographic method for real sample analysis. 2.8 Statistical Analysis All experiments were performed independently at least three times, and the results are presented as mean ± standard deviation (mean ± SD). Data processing and statistical analysis were performed using GraphPad Prism 9.0 software (GraphPad Software, San Diego, CA, USA), and some figures were prepared using Origin 2021 software (OriginLab, Northampton, MA, USA). Standard curve fitting, Michaelis–Menten curve fitting, and kinetic parameter calculation were all conducted using GraphPad Prism 9.0. Statistical significance between groups was evaluated by Student’s t -test or one-way analysis of variance (one-way ANOVA), and differences were considered statistically significant at p < 0.05. 3. Results and Discussion 3.1 Synthesis and Characterization of Au@PDA-PdCu Nanozymes To obtain Au@PDA-PdCu nanozymes with uniform morphology, good dispersibility, and high catalytic activity, the synthesis conditions were first systematically optimized, including the amount of DA·HCl and the feeding amounts of Pd and Cu precursors (Figure S1 –S2). The results showed that an appropriate degree of PDA coating and suitable bimetallic loading were crucial for maintaining particle structural stability and enhancing catalytic performance. Excessive precursor amounts tended to cause overdeposition of surface metals and even particle aggregation, whereas insufficient amounts led to inadequate loading of active components and were unfavorable for catalytic improvement. Based on the overall comparison, the optimal synthesis conditions were determined to be 200 µL DA·HCl, 30 µL Pd precursor, and 1.0 µL Cu precursor. The Au@PDA-PdCu nanozymes prepared under these conditions were subsequently used for structural and compositional characterization. As shown in Fig. 2 a, the initially prepared Au NPs exhibited a regular quasi-spherical morphology with a relatively uniform size distribution and an average diameter of approximately 17 nm, indicating a stable nucleation and growth process of the gold nanoparticles. After PDA coating, the particle edges of Au@PDA became relatively blurred, and the particle size increased slightly compared with that of bare Au NPs, suggesting that the PDA layer had been successfully deposited onto the surface of the gold nanoparticles (Fig. 2 b). After further loading of PdCu, the obtained Au@PDA-PdCu nanozymes still maintained good dispersibility, and small metallic nanostructures could be observed on the particle surface, indicating that PdCu was successfully loaded onto the outer PDA shell to form a hierarchical core-shell structure. These results further confirmed the stepwise synthesis process and structural integrity of the nanozymes (Fig. 2 c). To further confirm the elemental composition and spatial distribution of the material, elemental mapping and EDS analyses were performed on the Au@PDA-PdCu nanozymes. As shown in Fig. 2 d, Au was mainly distributed in the particle core, whereas Pd and Cu were located in the outer layer (Figs. 2 e and 2 h) and showed a high degree of overlap with the signals of O and N. The O and N elements originated from the PDA layer (Figs. 2 f and 2 g), indicating that Pd and Cu were not independently aggregated but were stably anchored onto the surface of the PDA shell. In addition, the EDS spectrum (Fig. 2 i) further detected the characteristic signals of Au, Pd, Cu, O, and N, providing additional evidence for the successful construction of the Au@PDA-PdCu nanozymes. The optical absorption properties of the materials also reflected their stepwise surface modification process. As shown in Fig. 3 , bare Au NPs exhibited a surface plasmon resonance absorption peak at 524 nm. After PDA coating, the absorption peak red-shifted to 536 nm. Following further PdCu loading, the peak shifted further to 538 nm, accompanied by a noticeable broadening of the absorption band. These changes indicate that PDA coating and subsequent PdCu deposition altered the local dielectric environment around the particle surface, leading to the progressive red shift of the characteristic absorption peak and indirectly confirming the successful surface modification of the materials. Taken together, the successfully constructed Au@PDA-PdCu nanozymes possessed a well-defined hierarchical core-shell structure, uniform elemental distribution, and characteristic optical changes, thus providing a solid foundation for subsequent antibody conjugation and signal amplification in immunochromatographic applications. Similar findings were reported by Xu et al., who showed that PDA coating increased the particle size of AuNPs, induced a red shift in the absorption peak, and improved both colloidal stability and antibody conjugation efficiency compared with bare AuNPs. Moreover, an appropriate PDA thickness was beneficial for maintaining particle dispersibility, whereas excessively thick coating could lead to aggregation. These observations are consistent with the morphological and optical changes of the Au@PDA-PdCu nanozymes observed in this study, further indicating that the PDA layer not only helps maintain particle dispersion stability but also serves as an important functional interface for subsequent component assembly and bioconjugation 27 . 3.2 Peroxidase-Like Catalytic Activity and Kinetic Analysis of Au@PDA-PdCu Nanozymes The peroxidase-like catalytic activity of Au@PDA-PdCu nanozymes was evaluated using TMB as the chromogenic substrate and H₂O₂ as the oxidizing agent. As shown in Fig. 4 a, an obvious absorption peak at 652 nm appeared only in the complete reaction system containing TMB, H₂O₂, and Au@PDA-PdCu. No significant absorption signal was observed in the control groups without the nanozyme or without H₂O₂. This result indicates that Au@PDA-PdCu can effectively catalyze the oxidation of TMB and produce the blue product oxTMB. These findings confirm that the nanozyme has good peroxidase-like activity. Steady-state kinetic analysis was further performed using TMB at different concentrations (0.021–0.625 mM) as the substrate. As shown in Fig. 4 b, the rate of absorbance increase at 652 nm gradually increased with increasing TMB concentration. This result indicates that a higher substrate concentration promoted the catalytic reaction. The relationship between the initial reaction rate and substrate concentration was fitted using the Michaelis–Menten model (Fig. 4 c). The apparent kinetic parameters were calculated as Kₘ = 0.21 mM and Vmax = 5.20 µM min⁻¹, with a fitting correlation coefficient of R² = 0.987. The relatively low Kₘ value suggests that the nanozyme has good affinity for TMB. The TMB-H₂O₂ system has been widely used to evaluate the peroxidase-like activity of nanomaterials. In this system, nanozymes can catalyze the oxidation of TMB to produce the blue product oxTMB, which shows a characteristic absorption peak at 652 nm. In recent years, PDA modification and bimetallic synergistic strategies have also been reported to improve the catalytic performance and analytical potential of nanozymes 28 . For example, Zhang et al. reported that a polydopamine-dressed PdCu nanozyme showed enhanced enzyme-like activity, indicating a good synergistic effect between PDA and PdCu 29 . Therefore, the present results further demonstrate that Au@PDA-PdCu nanozymes can efficiently catalyze substrate oxidation in the TMB-H₂O₂ system and provide a reliable catalytic basis for subsequent signal amplification in immunochromatographic assays. 3.3 Construction and Optimization of Nanozyme-Labeled Probes To optimize the construction conditions of Au@PDA-PdCu nanozyme-labeled probes, the pH of the coupling system, the amount of EDC, and the amount of antibody were systematically evaluated. The T₀/C₀ value and inhibition rate were used as the main indicators (Fig. 5 ). The results showed that the pH of the coupling system had a strong effect on probe performance. Both the T₀/C₀ value and the inhibition rate increased with increasing pH. The best results were obtained at pH 10. When the pH further increased to 11, both values decreased significantly. This result suggests that excessively alkaline conditions were not favorable for maintaining the bioactivity of the probe (Fig. 5 a). As the EDC amount increased, the T₀/C₀ value and inhibition rate first increased and then decreased. The highest inhibition rate was obtained at 1 µL EDC. A further increase in EDC may have reduced probe performance because of excessive crosslinking or stronger nonspecific interactions (Fig. 5 b). In addition, increasing the antibody amount improved the T₀/C₀ value, but the inhibition rate did not show the same trend. At an antibody amount of 2 µL, the probe showed the highest inhibition rate and good repeatability. This result indicates a better balance between antibody loading and probe activity under this condition (Fig. 5 c). Therefore, the optimal coupling conditions were determined to be pH 10, 1 µL EDC, and 2 µL antibody for the following experiments. The pH of the coupling system, the amount of EDC, and the amount of antibody can strongly affect the immobilization efficiency, spatial orientation, and bioactivity of antibodies on the nanozyme surface. Therefore, a balance is needed between coupling strength and recognition activity. When the pH is too high or the amount of crosslinker is excessive, the surface coupling level may increase, but probe performance may decrease because of antibody conformational changes, over-crosslinking, or enhanced nonspecific adsorption. In addition, a higher antibody amount does not always lead to better performance. An appropriate coating amount helps improve recognition efficiency. However, excessive surface loading may increase steric hindrance or reduce the exposure of binding sites, which can weaken the specific antigen-antibody interaction 30 . After determining the probe coupling conditions, the strip substrate and other key construction parameters were further optimized. Previous studies have shown that different NC membranes differ in pore size, pore structure, capillary flow rate, and protein adsorption capacity. These differences can affect sample migration, reaction time, and band uniformity. Therefore, membrane selection should be optimized for the specific assay system 31 . As shown in Fig. 6 , the color development on WXJ-140, WXT-140, and WXJ-95-3 membranes was uneven. The CN-95 membrane showed a strong T line, but the C line was not uniform. The CN-140 membrane showed a relatively weak C line. In contrast, the WXJ-95 membrane showed clearer and more uniform color development on both the T line and C line. Therefore, it was selected as the optimal NC membrane for subsequent strip construction. After the probe coupling conditions and NC membrane were determined, the probe amount and coating antigen concentration were further optimized for the three strip formats by checkerboard titration, and the results are shown in Tables S1–S3. Overall, the combination of probe amount and coating antigen concentration had a significant effect on both band intensity and inhibition performance. For the liquid-format strip, the best performance was obtained with 10 µL probe and 0.5 mg/mL coating antigen. Under this condition, the strip showed a lower T/C value and a higher inhibition rate (Table S1 ). For the sprayed-format strip, the optimal condition was 3 µL/cm probe loading and 0.4 mg/mL coating antigen (Table S2). For the lyophilized-format strip, the best detection performance was achieved with 5 µL probe and 0.3 mg/mL coating antigen (Table S3). These results indicate that, in competitive lateral flow immunoassays, the probe amount and coating antigen concentration should be properly matched to balance band intensity and competitive inhibition. Similar studies have also shown that competitive lateral flow immunoassays are sensitive to the concentration of each component. Excessive loading of one component may enhance the signal but reduce sensitivity. Therefore, the working parameters usually need to be optimized separately for different probe formats 32 . 3.4 Sensitivity and Standard Curve Performance of the Au@PDA-PdCu Nanozyme-Based ICA Before systematically evaluating the ICA performance of the three Au@PDA-PdCu nanozyme-labeled probes, the preparation parameters specific to the lyophilized probe were first optimized. The formulation composition and freeze-drying conditions can strongly affect the shape of the lyophilized product, its reconstitution efficiency, and its subsequent assay performance. Therefore, the effects of lyophilization formulation, dilution factor, and freeze-drying time on probe performance were further investigated 33 . The results showed that, among the three tested lyophilization formulations, formulation B produced the most intact lyophilized probe. After reconstitution, it also gave the clearest color development of both the T line and C line on the test strip. Its overall performance was better than that of formulations A and C. In formulation A, the lyophilized product showed a lighter color and weaker strip signals. In formulation C, the probe in some microwells did not form completely, and the band color development was slightly poorer than that of formulation B. Further optimization of formulation B showed that the undiluted probe could not form a complete structure after freeze-drying. Partial poor formation was still observed at 5-fold and 7-fold dilution. In contrast, both 10-fold and 20-fold dilution produced lyophilized probes with good shape and clear color development. Considering both probe morphology and strip performance, a 10-fold dilution was finally selected as the optimal condition (Figure S3). In addition, insufficient freeze-drying time caused the probe to remain as a film-like or liquid residue, making it difficult to form a stable structure at the bottom of the microwell. When the freeze-drying time reached 4 h, the probe was basically fully formed and showed good color development performance. Therefore, 4 h was selected as the optimal freeze-drying time. Based on these results, the subsequent evaluation of lyophilized probe performance was carried out using formulation B, 10-fold dilution, and 4 h freeze-drying (Figure S4). Similar studies have shown that a proper combination of sugars and surface-active components can effectively reduce the aggregation of gold nanoparticles during freeze-drying and improve their dispersion after reconstitution. This may explain why formulation B showed the best performance in this study, as it was more favorable for forming a stable protective matrix during freeze-drying and for maintaining good probe dispersibility after reconstitution 34 . The assay systems of the liquid, sprayed, and lyophilized Au@PDA-PdCu nanozyme-labeled probes were further optimized by evaluating the effects of buffer type and pH on the T₀/C₀ value, inhibition rate, and color development performance. As shown in Fig. 7 , both buffer type and pH had clear effects on the color development and inhibition performance of the three probe systems. For the liquid-format probe system, HBS produced a relatively high T₀/C₀ value, but the C line was weak. In contrast, PB buffer provided more balanced color development together with a higher inhibition rate, and was therefore selected as the optimal buffer. The best detection pH for this system was 8.0 (Fig. 7 a). For the sprayed-format probe system, the C line was weak under both HBS and PBS conditions. This result suggests that a higher salt concentration may affect the migration and release of the probe on the sample pad. In comparison, PB buffer gave better inhibition performance and repeatability. The best detection pH for this system was 7.0 (Fig. 7 b). For the lyophilized-format probe system, PB buffer gave the clearest and most stable band color development. When the pH was above 8, the inhibition rate decreased significantly. This result indicates that alkaline conditions were not suitable for the detection performance of the lyophilized probe. Therefore, the optimal detection condition for this system was PB buffer at pH 7.0 (Fig. 7 c). After the optimal detection buffer and pH were determined for the three probe systems, the DAB enhancement system was further optimized to improve band contrast and signal readability. As shown in Fig. 8, DAB treatment significantly enhanced the gray values of both the T line and C line. However, an excessively high H₂O₂ concentration caused the color reaction to proceed too quickly and produced a darker background, which affected signal interpretation. As the H₂O₂ concentration decreased from 30% to 5%, the background color of the strips gradually became lighter. Further comparison of different DAB-to-H₂O₂ ratios showed that uneven band color development occurred under some conditions. When the DAB:H₂O₂ ratio was 1:2 and the H₂O₂ concentration was 5%, the T line and C line showed the most uniform color development and the cleanest background. This condition gave the best enhancement effect. Therefore, it was selected for subsequent signal enhancement and standard curve construction. After the optimal preparation parameters and detection conditions were determined, the sensitivity of the liquid-format, sprayed-format, and lyophilized-format Au@PDA-PdCu nanozyme probe-based immunochromatographic test strips was further evaluated. The standard curves before and after DAB enhancement were also established, as shown in Fig. 9 . The results showed that all three probe formats could effectively detect carbofuran under the optimized conditions. The T/C value gradually decreased as the carbofuran concentration increased. This result indicates a clear dose-response relationship. After curve fitting, all three systems showed good correlation. These results suggest that the constructed nanozyme-based ICA system has good potential for quantitative analysis. Further comparison of the detection performance before and after DAB enhancement showed that DAB treatment clearly strengthened the visual signal of the test strips and, to some extent, expanded the detection range. For the liquid-format probe strip, the linear range remained 0–100 ng/mL after DAB enhancement, but the LOD decreased from 0.055 ng/mL to 0.016 ng/mL, indicating a clear improvement in sensitivity (Fig. 9 a). For the sprayed-format probe strip, the linear range was extended from 0–50 ng/mL to 0–100 ng/mL after DAB enhancement. This result suggests that signal enhancement helped broaden the effective detection range. In contrast, the lyophilized-format probe strip already showed relatively high sensitivity before enhancement. Its linear range was 0–50 ng/mL, and the LOD was 0.078 ng/mL. After DAB enhancement, the detection range was extended to 0–100 ng/mL, but the LOD changed only slightly. Overall, the effect of DAB enhancement was not the same for the three probe systems. For the liquid-format probe, the main effect was improved sensitivity. For the sprayed-format and lyophilized-format probes, the main effects were an expanded detection range and better band readability. Similar studies have also shown that nanozyme-catalyzed 3,3′-diaminobenzidine enhancement can greatly amplify the test-line signal through substrate oxidation and deposition, thereby improving the analytical performance of lateral flow assays. In the delayed substrate release nanozyme-based lateral flow system reported by Sun et al., 3,3′-diaminobenzidine underwent oxidation and deposition under the catalysis of Au@Pt nanozymes. As a result, the detection limit for H1N1 was reduced by 25-fold compared with that before enhancement, while a good linear response range was maintained. This finding suggests that this type of post-assay color enhancement strategy can effectively improve the distinguishability of low-concentration samples 35 . 3.5 Specificity and Storage Stability of the Au@PDA-PdCu Nanozyme-Based ICA After the sensitivity and standard curve characteristics of the three immunochromatographic test strips had been clarified, their analytical performance was further evaluated in terms of specificity and storage stability. First, to examine the specificity of the method for carbofuran, several related carbamate pesticides, including carbaryl, pirimicarb, methomyl, aldicarb, and isoprocarb, as well as the common organophosphorus pesticides chlorpyrifos and dichlorvos, were selected as potential interferents. The cross-reactivity of 3-hydroxycarbofuran, a metabolite of carbofuran, was also evaluated. The results showed that the three test strips exhibited no obvious cross-reactivity toward the tested pesticides other than 3-hydroxycarbofuran, and all cross-reactivity values were below 0.1%, indicating good specificity of the method (Table 1 ). Notably, the cross-reactivity values of 3-hydroxycarbofuran were 8.6% for the liquid-format strip, 8.9% for the sprayed-format strip, and 8.0% for the lyophilized-format strip. This result may be related to the high structural similarity between 3-hydroxycarbofuran and carbofuran, since 3-hydroxycarbofuran is a metabolite of carbofuran. According to GB 2763—2021, the residue limit of carbofuran is expressed as the sum of carbofuran and 3-hydroxycarbofuran. Therefore, this level of cross-reactivity is reasonable to some extent. Overall, the three probe-based test strips showed good analytical specificity. Table 1 Specificity evaluation of ICA strips based on three types of probes. Target IC 50 (ng/mL) Cross reaction rate (%) Liquid Sprayed Lyophilized Liquid Sprayed Lyophilized Carbofuran 8.57 9.41 7.78 100 100 100 3-Hydroxy-carbofuran 100.28 105.47 97.29 8.6 8.9 8.0 Carbaryl >1000 1000 1000 1000 1000 1000 <0.1 To evaluate the storage stability of the three test strips, an accelerated aging experiment was carried out to monitor their performance changes under simulated high-temperature storage conditions. The T₀/C₀ value was used as the indicator of stability. The results showed that the T₀/C₀ value of the liquid-format probe strip changed only slightly over 20 d and remained relatively stable. The lyophilized-format probe strip also showed only small fluctuations, indicating good stability. In contrast, the T₀/C₀ value of the sprayed-format probe strip first increased and then decreased as the storage time was extended (Figure S5). This trend in the sprayed-format strip may be related to the gradual inactivation of probe antibodies under high-temperature conditions. At the early stage of storage, partial antibody denaturation may first weaken its binding to the secondary antibody on the C line. This change would reduce the C-line signal and increase the T₀/C₀ value. As aging became more severe, the binding ability of the probe to both the coating antigen on the T line and the secondary antibody on the C line decreased markedly. As a result, the T₀/C₀ ratio decreased after reaching a peak. Based on the accelerated aging results and Arrhenius equation prediction, the expected shelf life of the liquid-format and lyophilized-format probe strips at room temperature was both longer than 1 year, while that of the sprayed-format probe strip was about 9 months. Maksin et al. evaluated the stability of lyophilized gold nanoparticle conjugates by monitoring changes in the test-line signal during storage. They pointed out that smaller signal decay indicates better system stability. Therefore, in this study, the liquid-format and lyophilized-format probe strips showed only small fluctuations during accelerated aging and had better stability. In contrast, the sprayed-format probe strip showed more obvious signal changes, suggesting that it was more sensitive to thermal aging 36 . 3.6 Detection of Carbofuran in Real Vegetable Samples To select a suitable pretreatment extraction system for carbofuran detection in vegetable samples, the effects of PB buffer, 20% acetonitrile-PB buffer, 50% acetonitrile-PB buffer, and pure acetonitrile on the color development performance of the immunochromatographic test strips were first compared. As shown in Figure S6a, both the T line and C line were clearly visible when PB buffer and 20% acetonitrile-PB buffer were used. This result indicates that these two systems had good compatibility with the test strip assay. In contrast, when the acetonitrile content increased to 50%, the color development of the strips became much weaker. When pure acetonitrile was used, almost no color appeared on either the T line or C line. These results indicate that a high proportion of organic solvent can strongly interfere with the normal immunoreaction on the test strip. Considering both the extraction efficiency of pesticide residues from the samples and the color development compatibility with the immunochromatographic assay, 20% acetonitrile-PB buffer was selected as the extraction solution for subsequent vegetable sample pretreatment. The applicability of this extraction system was then further evaluated in the three test strip formats. As shown in Figure S6b, under blank sample conditions, both the T line and C line were clearly visible on all three test strips. Under the spiked condition of 20 ng/mL carbofuran, the T line of all three strips became weaker to different degrees, while the C line remained clearly visible. These results indicate that the sample matrix extracted with 20% acetonitrile-PBS did not cause obvious interference with strip interpretation and was suitable for the detection of real vegetable samples. After optimization of the sample pretreatment conditions, the performance of the three carbofuran immunochromatographic test strips with different probe formats was evaluated using extracts of Shanghai green, Chinese chive, and spinach as sample matrices. The working curves obtained under DAB enhancement are shown in Fig. 10 , and the original curves before enhancement are shown in Figure S7. The results showed that all three strip formats exhibited good dose-response relationships in the three vegetable matrices. The curve-fitting coefficients (R²) were all higher than 0.98. These results indicate that the method has good quantitative analytical capability in real sample matrices. The detailed analytical parameters are listed in Table S4. The results showed that the vLOD values of the liquid-format and sprayed-format probe strips were both 5 ng/mL in all three vegetable samples, while the vLOD of the lyophilized-format probe strip was 1 ng/mL in all three vegetable samples, indicating higher visual detection sensitivity. Overall, the detection range of all three strip formats in real vegetable samples was 0–100 ng/mL. This range is sufficient for carbofuran residue detection in leafy vegetables according to GB 2763—2021. Similar studies have also shown that immunochromatographic methods for carbofuran can maintain good detection performance in real fruit and vegetable matrices. Previous reports showed good linear relationships and low detection limits for carbofuran in samples such as mustard cabbage, orange, and grape. Another study reported that a quantum dot-based lateral flow assay for carbofuran detection in vegetables achieved spike recoveries of 83%–111% and showed results consistent with those of HPLC–MS. These findings are consistent with the results of this study. In the present work, all three strip formats showed good dose-response relationships in extracts of Shanghai green, Chinese chive, and spinach, and all fitting coefficients were higher than 0.98. This result further indicates that the established method has good matrix adaptability and good potential for practical sample analysis 17 . To further evaluate the applicability of the method in real samples, recovery experiments were carried out using Shanghai green, Chinese chive, and spinach as sample matrices at two spiking levels, 1 ng/mL and 10 ng/mL. The results are shown in Table 2 . The liquid-format probe strip showed recoveries of 75%–107% and coefficients of variation of 4.3%–25.7% in the three vegetable samples. The sprayed-format probe strip showed recoveries of 76%–112% and coefficients of variation of 3.7%–12.4%. The lyophilized-format probe strip showed recoveries of 70%–119% and coefficients of variation of 4.0%–8.4%. Overall, the immunochromatographic test strips based on the three probe formats showed good accuracy and precision in the three vegetable samples. These results indicate that the established method has good capability for real sample analysis. Table 2 Accuracy and precision of carbofuran ICA strips based on three probe types. Test strip type Vegetable species Spiked Conc. (ng/mL) Mean (ng/mL) Recovery (%) CV (%) Liquid probe strip Chinese cabbage 1 1.01 101 11.9 10 8.38 84 4.9 chive 1 0.75 75 4.3 10 10.23 102 5.1 spinach 1 1.03 103 18 10 10.74 107 25.7 Sprayed probe strip Chinese cabbage 1 1.12 112 7.7 10 7.61 76 3.7 chive 1 0.83 83 11.6 10 8.59 86 12.1 spinach 1 1.1 110 9.1 10 8.6 86 12.4 Lyophilized probe strip Chinese cabbage 1 1.13 113 8.3 10 11.07 111 4.0 chive 1 0.94 94 7.3 10 9.34 93 8.4 spinach 1 1.19 119 7.6 10 7.04 70 6.4 From the results in different matrices, the liquid-format probe strip showed relatively larger variation in spinach samples. At the spiking level of 10 ng/mL, the coefficient of variation reached 25.7%. This result may be related to the higher chlorophyll content and darker matrix color of spinach. After homogenization, pigments and other co-extracted components may interfere with the gray value reading of the T line and C line. This effect may increase the difference among parallel measurements. In contrast, the sprayed-format and lyophilized-format probe strips showed lower coefficients of variation in all three vegetable samples, indicating better result stability. For samples with darker color and more complex matrices, the detection error may be further reduced by optimizing the extraction procedure, reducing pigment co-extraction, or increasing the number of parallel measurements. Similar studies have shown that carbofuran immunoassays usually provide good recovery and repeatability in real vegetable samples. Wu et al. validated a quantum dot-based lateral flow assay for carbofuran in vegetable samples and reported recoveries of 83%–111% with coefficients of variation below 10%. Their results were also consistent with those of HPLC–MS. Similar to that study, the three strip formats in the present work also showed good overall accuracy and precision in Shanghai green, Chinese chive, and spinach samples. These results indicate that the established method has good applicability for real sample analysis 13 . 3.7 Consistency Evaluation of Test Strip Results with LC–MS/MS To verify the reliability of the established immunochromatographic method, the detection results for carbofuran in three vegetable samples were compared with those obtained by LC–MS/MS as the reference method. As shown in Table 3 , carbofuran was not detected (ND) in the blank samples of Shanghai green, Chinese chive, and spinach by LC–MS/MS, and all three types of test strips also gave negative results. At the spiking levels of 50 ng/mL and 200 ng/mL, carbofuran residues were detected by LC–MS/MS, and the liquid-format, sprayed-format, and lyophilized-format immunochromatographic test strips all showed positive results. These findings indicate good agreement between the three test strips and the LC–MS/MS method in identifying negative samples and judging positive samples above the target level. The results also demonstrate that the established method can accurately reflect carbofuran residues in vegetable samples and has good accuracy and practical reliability, making it suitable for rapid screening of carbofuran residues in vegetables. Table 3 Consistency evaluation of detection results between the Au@PDA-PdCu nanozyme-based ICA and the LC-MS/MS reference method. (“ND” indicates not detected; “+” represents positive; “−” represents negative.) Test strip type Spiked Conc. (ng/mL) Chinese cabbage chive spinach 0 50 200 0 50 200 0 50 200 LC-MS/MS ND 54 224 ND 37 193 ND 61 242 Liquid − + + − + + − + + Sprayed − + + − + + − + + Lyophilized − + + − + + − + + Similarly, Yin et al. developed a dual-color immunochromatographic assay based on Au@PDA and colloidal gold for the simultaneous detection of paclobutrazol and carbofuran in fruit and vegetable samples. Their results showed good agreement with those obtained by LC–MS/MS. This finding further supports the feasibility and necessity of using mass spectrometry as a reference method to verify the reliability of immunochromatographic assays 37 . 4. Conclusion In this study, a hierarchical Au@PDA-PdCu nanozyme was successfully constructed and applied as a signal label for the development of a competitive immunochromatographic assay for carbofuran detection. The nanozyme showed good structural characteristics, dispersibility, and peroxidase-like catalytic activity, providing a reliable basis for antibody conjugation and catalytic signal amplification. After systematic optimization, the liquid-, sprayed-, and lyophilized-format probe strips all showed good dose-response relationships and satisfactory analytical performance, while DAB post-enhancement further improved sensitivity or expanded the detection range depending on the probe format. The established method also exhibited good specificity, stability, and matrix adaptability. In vegetable samples, it provided satisfactory recoveries, good precision, and results consistent with those of LC–MS/MS. Overall, the proposed Au@PDA-PdCu nanozyme-based ICA offers a rapid, sensitive, and practical strategy for carbofuran screening in leafy vegetables and provides useful support for the development of nanozyme-assisted lateral flow assays in food safety monitoring. Declarations Funding This work was supported by the Shanghai Agricultural Science and Technology Innovation Program, “Research and Application of a Gold Nanozyme-Based Rapid Immunoassay for the Detection of Carbofuran-Type Carbamate Pesticide Residues in Shanghai Local Vegetables” (2023-02-08-00-12-F04598); the General Scientific Research Project of the University-Level “Basic Discipline” Interdisciplinary Special Program, “Highly Fluorescent Carbon Dots Derived from Coarse and Aged Green Tea: Construction of an Efficient Fluorescent Sensing Platform for Heavy Metals” (309-AW0203-25-005350); the Key Project of the Shanghai Municipal Science and Technology Commission, “Research on Novel Rapid Immunodetection Technologies and Product Applications for Multiple Heavy Metals in Edible Agricultural Products and Foods” (20392002100); and the Shanghai Engineering Research Center of Plant Germplasm Resources (No. 17DZ2252700). Author Contribution Haofeng Lao: Investigation; Methodology; Formal analysis; Data curation; Writing - original draft.Xuhui Yue: Investigation; Methodology; Validation. Writing - original draft.Xiaoqing Weng: Investigation; Methodology; Validation. Writing - original draft.Shaokang Zhang: Investigation; Formal analysis.Jiachen Shi: Resources; Supervision.Yuanfeng Wang: Conceptualization; Funding acquisition; Project administration; Supervision; Writing - review & editing. References Mishra S, Zhang W, Lin Z, Pang S, Huang Y, Bhatt P, Chen S (2020) Chemosphere 259:127419 Alves KVB, Martinez DST, Alves OL, Barbieri E (2022) Chemosphere 288:132359 Cao N, Zong X, Guo X, Chen X, Nie D, Huang L, Li L, Ma Y, Wang C, Pang S (2024) Chemosphere 350:140992 Alves Senabio J, Correia Da Silva R, Guariz Pinheiro D, Gomes L, De Vasconcelos, Soares MA (2024) PLoS ONE 19:e0314492 Khan A, Fahad TM, Akther T, Zaman T, Hasan MF, Islam Khan MR, Islam MS, Kishi S (2021) J Cell Mol Medi 25:1048–1059 Zhang L, Lang Z, Lu B, Yang T, Zhang X, Wang M, Zhang X, Cao H, Ye D (2025) Spectrochim Acta Part A Mol Biomol Spectrosc 327:125415 European Food Safety Authority (EFSA) EFS2 , 10.2903/j.efsa.2025.9299 Zhao Y, Tan G, Wang M, Lin H, He L, Li L, Wang B (2019) J Food Sci 84:3296–3302 Wang M, Li R, Zou S (2008) Determination of carbofuran residue in aquatic products by gas chromatography. Se pu= Chin J Chromatogr 26(6):775–777 Huertas-Pérez JF, García-Campaña AM (2008) Anal Chim Acta 630:194–204 Osman KA, Al-Humaid AM (2010) Al-Rehiayani and K. N. Al-Redhaiman. Ecotoxicol Environ Saf 73:1433–1439 Wang J, Bu T, Cui Q, Li Z, Xu Q, Jiang Z, Mao Y, Huang X, Song L, Peng D, Zhang X (2025) Food Chem 465:142062 Wu Y, Fan Q, Chen Y, Sun X, Shi G (2022) Biosensors 12:560 Zhai S, Dong H, Wang H, Huang J, Li D, Li Z, Li Z, Li P, Zhang P, Zhao M, Sun X, Guo Y (2024) J Hazard Mater 477:135296 Zou R, Guo Y, Chen Y, Zhao Y, Zhao L, Zhu G, Liu Y, Peters J, Guo Y (2022) J Hazard Mater 426:127845 Zhou P, Lu Y, Zhu J, Hong J, Li B, Zhou J, Gong D, Montoya A (2004) J Agric Food Chem 52:4355–4359 Yin J, Yan Y, Zhang K, Fu H, Lu M, Zhu H, Wei D, Peng J, Lai W (2022) Foods 11:1564 Chen Z-J, Wu H-L, Xiao Z-L, Fu H-J, Shen Y-D, Luo L, Wang H, Lei H-T, Hongsibsong S, Xu Z-L (2021) J Hazard Mater 412:125241 Zhang J, Wang Y, Dong J, Yang J, Zhang Y, Wang F, Si R, Xu Z, Wang H, Xiao Z, Shen Y (2019) Biomolecules 9:576 Zhang Q, Qu Q, Chen S, Liu X, Li P (2017) Food Chem 231:295–300 Pei J, Jin Y, Ren C, Chen Y, Zou M, Qi X (2024) Anal Methods 16:3938–3948 Ouyang H, Wang W, Shu Q, Fu Z (2018) Analyst 143:2883–2888 Cho I-H, Bhunia A, Irudayaraj J (2015) Int J Food Microbiol 206:60–66 Soni H, Verma N, Chaudhari DY, Gandhi SA, Pandya A, Sutariya PG (2024) Anal Methods 16:2400–2411 Dai S, Hu M, Zhang W, Lei Z (2025) Anal Chim Acta 1336:343519 Dong S, Guan L, Zhao Y, Wang Y, Liu P, Li P, Han C, Liu B, Zhang C (2022) Microchem J 183:108070 Xu S, Zhang G, Fang B, Xiong Q, Duan H, Lai W (2019) ACS Appl Mater Interfaces 11:31283–31290 Luo C, Li X, Li Y (2024) IJN 19:441–452 Zhang C, Liu W, Li Z, Yan B, Lin J, Chen C, Zhang L, Lu Y (2022) ACS Sustainable Chem Eng 10:1653–1663 Coluccio ML, Grillo F, Onesto V, Garo V, Scala C, Cuzzola P, Calfa M, Candeloro P, Gentile F, Piletsky S, Malara N (2021) Nanomaterials 11:2620 Nuntawong P, Putalun W, Tanaka H, Morimoto S, Sakamoto S (2022) J Nat Med 76:521–545 Pedreira-Rincón J, Rivas L, Comenge J, Skouridou V, Camprubí-Ferrer D, Muñoz J, O’Sullivan CK, Chamorro-Garcia A, Parolo C (2025) Lab Chip 25:2578–2608 Liu D, Galvanin F, Yu Y (2018) AAPS PharmSciTech 19:541–550 Yokota H, Kadowaki M, Matsuura T, Imanaka H, Ishida N, Imamura K (2020) Langmuir 36:6698–6705 Sun Y, Mao M, Tai S, Chao M, Xu H, Cai Y, Peng C, Ma W, Wang Z (2025) Talanta 286:127557 Maksin IV, Kuandykova A, Polyakova DI, Kesareva VA, Luzyanin TA, Ivanov VS, Simonova EI, Khunteev GA, Kirillova YG (2025) Biosensors 15:592 Yin J, Yan Y, Zhang K, Fu H, Lu M, Zhu H, Wei D, Peng J, Lai W (2022) Foods 11:1564 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 04 May, 2026 Editor assigned by journal 22 Apr, 2026 Submission checks completed at journal 22 Apr, 2026 First submitted to journal 22 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9490663","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638197668,"identity":"e498fecb-3e5e-4f9c-901c-ad68cbca95f2","order_by":0,"name":"Haofeng Lao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Haofeng","middleName":"","lastName":"Lao","suffix":""},{"id":638197669,"identity":"0bfc2d9e-746d-4d2d-8545-18ead7c0823b","order_by":1,"name":"Xuhui Yue","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xuhui","middleName":"","lastName":"Yue","suffix":""},{"id":638197670,"identity":"cf214aa7-3b79-43a2-80b1-4dca45cc361e","order_by":2,"name":"Xiaoqing Weng","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqing","middleName":"","lastName":"Weng","suffix":""},{"id":638197671,"identity":"0be7251d-bf0b-4a5a-9ab3-32e7dd5241a1","order_by":3,"name":"Shaokang Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Shaokang","middleName":"","lastName":"Zhang","suffix":""},{"id":638197672,"identity":"15d6e4f6-c8b8-4afb-b17d-3e6c24c687d7","order_by":4,"name":"Jiachen Shi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jiachen","middleName":"","lastName":"Shi","suffix":""},{"id":638197673,"identity":"dbe57977-8d44-4635-afe0-f9af56e1211c","order_by":5,"name":"Yuanfeng Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDAC5gMg0oaHjZmx8cEHAxs7wlrYEkBkmhwfe/NhwxkFacnEajlsLMdzLE2a58MhxgZCOgyO8Rh+LvjFnNgmkWNsbGNwgJmB/fDRDQS0GEvP7GMDaTF8nGNwh4+BJy3tBl4t93s3SPP28EBsyTF4xswgwWOGX8sx3s2/eXskQFrMpC0MDjM2EKFlmzTPDwNjNpD3GYjRInmM/5s1b0OCHBsokHsM0pLZCPmF7xhb8m2eP/955JuBUfnjj40dP/vhY3i1KBwAEoxtSCJs+JSDgHwDiPxDSNkoGAWjYBSMaAAAHRFLN/xtZIoAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Yuanfeng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-04-22 04:25:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9490663/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9490663/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109098629,"identity":"0031f5a4-c99f-482d-876e-bc2a8b77e134","added_by":"auto","created_at":"2026-05-12 14:14:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":415430,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic illustration of the synthesis process and detection principle of the Au@PDA-PdCu nanozyme-based immunochromatographic assay (ICA) for carbofuran detection.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/86126dc27ce17b0c30743f48.jpeg"},{"id":109099219,"identity":"d6ded1c8-7bc9-4dfe-a39c-91e3f591751a","added_by":"auto","created_at":"2026-05-12 14:16:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":508780,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) TEM image of Au NPs; (b) TEM image of Au@PDA; (c) TEM image of Au@PDA-PdCu; (d–h) elemental mapping images of Au, Cu, N, O, and Pd; (i) EDS spectrum.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/41fc9674708ed55b3dfcf012.png"},{"id":109099232,"identity":"24912349-538a-4ba5-986f-6166fce80418","added_by":"auto","created_at":"2026-05-12 14:16:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":144916,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUV–Vis absorption spectra of Au NPs, Au@PDA, and Au@PDA-PdCu.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/49310eb156dcdcae6fd26cf0.png"},{"id":109098918,"identity":"d7d6d7f7-c0fe-43c2-8a69-d7bb24daf99e","added_by":"auto","created_at":"2026-05-12 14:15:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":186474,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePeroxidase-like catalytic activity and kinetic analysis of Au@PDA-PdCu nanozymes. (a) Comparison of the catalytic colorimetric performance of different materials in the TMB-H₂O₂ system; (b) Time-dependent absorbance changes at 652 nm under different TMB concentrations; (c) Michaelis–Menten steady-state kinetic fitting curve using TMB as the substrate.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/99d5eb84423c54f4740e2bd2.png"},{"id":109099190,"identity":"2de863fb-eaef-4cca-9077-89c2f23b329e","added_by":"auto","created_at":"2026-05-12 14:16:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":482492,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOptimization of the coupling conditions for Au@PDA-PdCu nanozyme-labeled probes. (a) Effect of coupling system pH on probe performance; (b) Effect of EDC amount on probe performance; (c) Effect of antibody amount on probe performance.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/6873856093e9e371e7ebcf87.png"},{"id":109099188,"identity":"ff07230c-7ee1-44ce-a495-981bf7278f31","added_by":"auto","created_at":"2026-05-12 14:16:01","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":461249,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of different NC membranes on the color development performance of the immunochromatographic test strips.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/bd5f30bde4510c6ed46212ef.png"},{"id":109099220,"identity":"8882bc1a-8acd-4567-8ea9-e599961a6b13","added_by":"auto","created_at":"2026-05-12 14:16:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":270772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOptimization and analytical performance of the Au@PDA-PdCu nanozyme-based immunochromatographic assay (ICA). (a–c) Optimization of detection buffer and pH for liquid-format (a), sprayed-format (b), and lyophilized-format (c) probes.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/b02ce73f2f730a98d098bdd3.png"},{"id":109098632,"identity":"f79a1c59-5a1e-4750-946a-34625440db9f","added_by":"auto","created_at":"2026-05-12 14:14:43","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":334881,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOptimization of the DAB color development system for the Au@PDA-PdCu nanozyme-based immunochromatographic assay.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/a1893b3a3343c7326a6d7c23.jpeg"},{"id":109099226,"identity":"e5e002d4-8e4a-42bd-b884-6d845facf539","added_by":"auto","created_at":"2026-05-12 14:16:15","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":579060,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of the standard curves of three Au@PDA-PdCu nanozyme probe-based test strips before and after DAB enhancement (left, without DAB enhancement; right, with DAB enhancement). (a) Liquid-format strip; (b) Sprayed-format strip; (c) Lyophilized-format strip.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/5d2318c8926602022cf6c7a5.png"},{"id":109204537,"identity":"5ee1e731-af85-47c3-955c-27fb8eb2df44","added_by":"auto","created_at":"2026-05-13 15:00:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":2875787,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetection of carbofuran in real vegetable samples by the Au@PDA-PdCu nanozyme-based immunochromatographic assay (ICA). (a–c) Liquid-format ICA strips in (a) Chinese cabbage, (b) chive, and (c) spinach extracts after DAB enhancement; (d–f) Sprayed-format ICA strips in (d) Chinese cabbage, (e) chive, and (f) spinach extracts after DAB enhancement; (g–i) Lyophilized-format ICA strips in (g) Chinese cabbage, (h) chive, and (i) spinach extracts after DAB enhancement.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/cb89023a22c661d0a810a251.png"},{"id":109207207,"identity":"98d09479-1060-468a-bbca-ce4ec640d255","added_by":"auto","created_at":"2026-05-13 15:18:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6620942,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/bd4cee6e-6e57-4dbe-bcbd-9bf4d5c0aa5c.pdf"},{"id":109099685,"identity":"981d4212-0c2a-41a9-9ce4-bf8e7917a809","added_by":"auto","created_at":"2026-05-12 14:17:56","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2206607,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9490663/v1/246adc523e7cde876cadcf1a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Hierarchical Au@PDA-PdCu Nanozyme for Signal- Amplified Immunochromatographic Detection of Carbofuran in Leafy Vegetables","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCarbofuran, a broad-spectrum carbamate pesticide, has long been widely used to control a variety of agricultural pests\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. However, its excessive application and persistence in the environment have raised global concerns because of the serious threats it poses to food safety and public health\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Acute exposure to carbofuran can cause neurotoxicity, endocrine disruption, and even death, whereas chronic low-dose exposure has been associated with long-term health risks\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Consequently, many countries have established strict maximum residue limits (MRLs), often below 10 \u0026micro;g/kg, particularly for leafy vegetables that are prone to pesticide accumulation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. These regulatory pressures highlight the urgent need to develop rapid, highly sensitive, and reliable detection technologies that can be directly applied at the points of production and distribution.\u003c/p\u003e \u003cp\u003eCurrently, the detection of carbofuran residues still mainly relies on chromatographic methods and their hyphenated mass spectrometric techniques, such as gas chromatography\u0026ndash;mass spectrometry (GC\u0026ndash;MS), high-performance liquid chromatography (HPLC), and liquid chromatography\u0026ndash;tandem mass spectrometry (LC\u0026ndash;MS/MS). Wang et al. established a capillary gas chromatographic method for the determination of carbofuran residues in aquatic products, confirming the feasibility of chromatographic techniques for the analysis of this class of pesticides\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, Huertas-P\u0026eacute;rez et al. proposed a reversed-phase HPLC method for the simultaneous determination of N-methylcarbamate pesticides, including carbofuran, in water and vegetable samples, demonstrating the applicability of HPLC-based methods for accurate carbamate residue analysis\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Osman et al. employed GC\u0026ndash;MS to monitor pesticide residues in vegetable samples and identified carbofuran among the detected compounds, highlighting the utility of GC\u0026ndash;MS for multiresidue analysis and confirmatory determination in food matrices\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Owing to their high sensitivity, high accuracy, and strong confirmatory capability, these methods are still regarded as reference standard methods for pesticide residue analysis, including carbofuran. However, such methods generally require expensive and sophisticated instrumentation, laborious and time-consuming sample pretreatment, and skilled personnel, which confines their use primarily to centralized laboratories and makes them unsuitable for rapid on-site screening.\u003c/p\u003e \u003cp\u003eIn contrast, immunochromatographic assays (ICAs) based on lateral flow strips have emerged as attractive alternatives because of their operational simplicity, rapid response, portability, and cost-effectiveness\u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Abad et al. developed a nanocolloidal gold-based one-step immunochromatographic strip for the rapid detection of carbofuran, demonstrating the feasibility of colloidal gold ICA for fast on-site screening\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Yin et al. further constructed a dual-color immunochromatographic assay with two test lines and an independent control line for the simultaneous detection of paclobutrazol and carbofuran in agricultural products, highlighting the advantages of ICA in multiplexed and visualized detection\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, conventional ICAs generally rely on colloidal gold or natural enzymes as signal labels, which often suffer from insufficient signal intensity, limited sensitivity, poor stability, and short storage life, particularly in complex food matrices\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. To further improve analytical performance, Zhang et al. reported a double-label time-resolved fluorescent immunochromatographic assay for the rapid quantitative detection of carbofuran residues in agro-products, showing that fluorescent labeling strategies can markedly enhance detection sensitivity\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Similarly, Pei et al. employed Au@Ag core\u0026ndash;shell nanoparticles as antibody and Raman reporter carriers to construct a surface-enhanced Raman scattering-based lateral flow immunoassay for the ultrasensitive detection of carbofuran residues in fruits and vegetables\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Despite their significantly improved sensitivity, these high-performance labeling systems usually depend on specialized instruments such as fluorescence or Raman devices, which still limits their broader application in low-cost, visual, and real-time on-site detection. Therefore, the development of innovative signal labels that integrate high catalytic efficiency, strong visual readout, and excellent stability remains crucial for advancing ICA platforms toward practical applications in food safety monitoring.\u003c/p\u003e \u003cp\u003eNanozymes, as nanomaterials with enzyme-like catalytic activities, have emerged as promising alternatives to conventional ICA labels because of their high stability, low cost, and excellent catalytic performance\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Compared with natural enzymes, nanozymes are less susceptible to environmental conditions such as temperature, pH, and storage, and can be rationally engineered to achieve efficient signal amplification and enhanced analytical sensitivity\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In addition, polydopamine (PDA) provides a favorable surface for antibody conjugation. Its intrinsic dark color can also improve the visual readout. Based on these advantages, we designed a hierarchical core\u0026ndash;shell Au@PDA-PdCu nanozyme. In this structure, Au NPs serve as the core. PDA acts as an interfacial layer for antibody immobilization. The outer PdCu shell provides strong peroxidase-like catalytic activity. On this basis, we established a competitive ICA platform for the rapid detection of carbofuran. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the antibody-labeled Au@PDA-PdCu nanozyme specifically participates in competitive recognition. It then further enhances the colorimetric signal through a catalytic chromogenic reaction. This platform enables rapid, sensitive, and stable visual detection of carbofuran.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Reagents, Materials, and Instruments\u003c/h2\u003e \u003cp\u003eHAuCl4\u0026middot;4H2O, H2O2, HEPES, Tween 80, trehalose, PEG 6000, PVP, mannitol, and sodium azide were purchased from Aladdin. Trisodium citrate, copper chloride, DMSO, MES, BSA, and NHS were obtained from Sinopharm. Dopamine hydrochloride, TMB, DAB, and EDC were purchased from Macklin. Palladium chloride was obtained from Bide Pharmatech. Proclin 300 was purchased from Shanghai Biochemical Technology. HPLC-grade acetonitrile was purchased from Thermo Fisher Scientific. Carbofuran and its structural analog standards were obtained from Tanmo Biotechnology. Anti-carbofuran monoclonal antibody, carbofuran antigen, goat anti-mouse IgG, NC membrane, sample pad, absorbent pad, PVC backing card, and conjugate pad were purchased from Suzhou Hongxin Technology. Ultrapure water was used throughout the experiments.\u003c/p\u003e \u003cp\u003eThe main instruments included a magnetic stirrer (HJ-6A), vortex mixer (TS-4500), ultrasonic cleaners (KQ-250B and F-100SD), UV\u0026ndash;Vis spectrophotometer (T6PC), ultrapure water system (STU4100UVR), centrifuge (CenLee2050), analytical balance (ME204), refrigerator (BCD-536WpH), transmission electron microscope (TALOS F200X), pH meter (pHSJ-5), drying oven (DHG-9075A), XYZ dispensing and spraying system (HM3035), freeze dryer (LGJ-12A), strip cutter (ZG2000), and refrigerated centrifuge (VELOCITY 14R).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Preparation and characterization of Au@PDA-PdCu nanozymes\u003c/h2\u003e \u003cp\u003eAu@PDA-PdCu nanozymes were prepared according to previously reported methods with slight modifications\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Au nanoparticles (Au NPs) were first synthesized by the trisodium citrate reduction method. Briefly, 1 mL of 2% HAuCl₄ solution was added to 200 mL of ultrapure water, heated to boiling, and then rapidly mixed with 3 mL of 1% trisodium citrate. After reaction for 15 min, the solution was cooled to room temperature and stored at 4\u0026deg;C. For the preparation of Au@PDA, 10 mL of the Au NP solution was centrifuged (10000 r/min, 30 min), and the precipitate was resuspended in 10 mL of Tris-HCl buffer (10 mM, pH 8.5). Subsequently, 30 \u0026micro;L of 3% H₂O₂ and an optimized volume of dopamine hydrochloride solution (5 mg/mL) were added, and the mixture was stirred at 250 r/min for 1 h at room temperature in the dark. After centrifugation and washing, the product was redispersed in ultrapure water to obtain Au@PDA. Then, optimized volumes of 50 mM H₂PdCl₄ and 0.64 mg/mL CuCl₂ were added to 10 mL of the Au@PDA dispersion, followed by stirring at 200 r/min at room temperature. Immediately afterward, 1 mL of 50 mM NaBH₄ was added for reduction for 20 min to produce Au@PDA-PdCu nanozymes, which were stored at 4\u0026deg;C until use.\u003c/p\u003e \u003cp\u003eTo obtain nanozymes with good dispersibility and high catalytic activity, the dosages of dopamine hydrochloride, H₂PdCl₄, and CuCl₂ were optimized. The optimal amount of dopamine hydrochloride was determined by comparing the color changes and UV\u0026ndash;vis absorption characteristics of the materials, whereas the Pd and Cu precursor amounts were optimized based on the absorbance change rate in the TMB-H₂O₂ chromogenic system together with the dispersion state of the materials. The corresponding results are shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Figure S2. For characterization, appropriately diluted dispersions of Au NPs, Au@PDA, and Au@PDA-PdCu were scanned in the range of 200\u0026ndash;800 nm using ultrapure water as the blank. TEM samples were prepared by dropping the diluted dispersions onto carbon-coated copper grids and drying naturally. The particle morphology and shell structure were observed by transmission electron microscopy, and the elemental composition and distribution were further analyzed by EDS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Peroxidase-Like Activity and Kinetic Analysis\u003c/h2\u003e \u003cp\u003eThe peroxidase-like activity of Au@PDA-PdCu nanozymes was evaluated using TMB as the chromogenic substrate. Briefly, 2 mL of acetate buffer (0.2 mol/L, pH 3.6) was premixed with 100 \u0026micro;L of TMB solution (10 mg/mL), followed by the addition of 200 \u0026micro;L of Au@PDA-PdCu nanozyme dispersion and 300 \u0026micro;L of 30% H₂O₂. After mixing, the reaction was carried out at 37\u0026deg;C for 1 min, and the absorbance at 652 nm was recorded to assess the peroxidase-like catalytic activity. Kinetic analysis was performed by varying the substrate concentration and recording the initial reaction rate. When TMB was used as the variable substrate, 100 \u0026micro;L of TMB solution at different concentrations was added to a reaction system containing 2 mL of acetate buffer (0.2 mol/L, pH 3.6), 100 \u0026micro;L of Au@PDA-PdCu nanozyme dispersion, and 300 \u0026micro;L of 30% H₂O₂. When H₂O₂ was used as the variable substrate, its concentration was varied under the same conditions. After mixing, the reaction was conducted at 37\u0026deg;C, and the absorbance change at 652 nm was monitored over a certain period. The initial reaction rates were used to construct Michaelis\u0026ndash;Menten curves, from which the Michaelis constant (Kₘ) and maximum reaction velocity (Vmax) were calculated to evaluate the substrate affinity and catalytic efficiency of the Au@PDA-PdCu nanozymes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Preparation of Immunoprobes and Immunochromatographic Test Strips\u003c/h2\u003e \u003cp\u003eImmunoprobes were prepared by covalently coupling Au@PDA-PdCu nanozymes with anti-carbofuran monoclonal antibody via EDC/NHS chemistry. Briefly, 600 \u0026micro;L of Au@PDA-PdCu nanozyme dispersion was mixed with 400 \u0026micro;L of 10 mM MES buffer, followed by the addition of 5 \u0026micro;L of 1 mg/mL EDC, 5 \u0026micro;L of 1 mg/mL NHS, and 2 \u0026micro;L of anti-carbofuran monoclonal antibody. After shaking at room temperature for 1 h, 200 \u0026micro;L of 2% BSA was added to block the remaining active sites for another 1 h. The mixture was then centrifuged at 8000 r/min for 10 min, and the pellet was redispersed in the corresponding reconstitution solution to obtain the immunoprobes. According to the subsequent application mode, the probes were prepared in three formats: liquid, sprayed, and lyophilized. The liquid probe was stored directly in dispersion form, the sprayed probe was redispersed in spraying buffer for loading onto the sample pad, and the lyophilized probe was redispersed in lyophilization buffer, aliquoted into a 96-well plate, freeze-dried, and stored until use.\u003c/p\u003e \u003cp\u003eThe immunochromatographic test strips consisted of a PVC backing card, sample pad, NC membrane, and absorbent pad. The sample pad was pretreated in pretreatment solution for about 3 min, dried at 37\u0026deg;C, and cut into strips of 1.5 cm \u0026times; 30 cm. The NC membrane was mounted onto the center of the PVC backing card, with the sample pad and absorbent pad overlapping the two ends by about 2 mm. Carbofuran-BSA conjugate and goat anti-mouse IgG were dispensed onto the test line (T line) and control line (C line), respectively, at 1 \u0026micro;L/cm using an XYZ dispensing platform, with a spacing of 5 mm between the two lines. After drying at 37\u0026deg;C, the coated NC membrane was cut into strips about 3.8 mm wide. For the liquid and lyophilized formats, the probes were not pre-immobilized on the strips, but were introduced during detection by pre-mixing with the sample or by reconstitution with the sample, respectively. For the sprayed format, the probes were pre-sprayed onto the sample pad, dried at 37\u0026deg;C for 2\u0026ndash;4 h, and then assembled with the NC membrane and absorbent pad. All prepared strips were stored under dry conditions until use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Optimization of Assay Conditions and DAB Signal Enhancement\u003c/h2\u003e \u003cp\u003eTo obtain an immunochromatographic system with good stability and satisfactory detection performance, the preparation of nanozymes, immunoprobes, test strips, and assay conditions were systematically optimized. During nanozyme synthesis, the effects of dopamine hydrochloride dosage and the feeding ratio of Pd and Cu on the dispersibility and peroxidase-like activity of the materials were investigated. During immunoprobe preparation, the pH of the coupling system, EDC dosage, and antibody amount were further optimized. In the construction and detection of test strips, the type of NC membrane, the matching relationship between probe amount and coating antigen concentration on the T line, as well as the detection buffer and pH conditions, were compared to achieve better color development and competitive inhibition response. The optimization results of the matching relationship between probe dosage and coating antigen concentration for the three probe formats, as determined by the checkerboard titration method, are shown in Tables S1\u0026ndash;S3.\u003c/p\u003e \u003cp\u003eFor the lyophilized probe, the lyophilization protectant system and solid content were optimized, as shown in Figure S3, while the freeze-drying time was further optimized as shown in Figure S4. For signal enhancement, the post-assay DAB\u0026ndash;H₂O₂ system was optimized by comparing different H₂O₂ concentrations and DAB:H₂O₂ ratios in terms of band clarity, background interference, and color stability. After chromatography, the test strips were inserted into the optimized DAB\u0026ndash;H₂O₂ substrate solution and reacted for 8 min, followed by rinsing with ultrapure water and drying. The Au@PDA-PdCu nanozymes catalyzed the oxidation of DAB to form brown insoluble precipitates, thereby achieving localized signal amplification at the T and C lines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Immunochromatographic Detection and Performance Evaluation\u003c/h2\u003e \u003cp\u003eFor detection, carbofuran standard solutions or vegetable extracts were introduced into the corresponding assay systems. For the liquid-format strips, 10 \u0026micro;L of immunoprobe was mixed with 90\u0026micro;L of sample solution in a microwell before chromatography. For the sprayed-format strips, 10 \u0026micro;L of buffer was mixed with 90\u0026micro;L of sample solution and then directly added onto the sample pad. For the lyophilized-format strips, 10 \u0026micro;L of buffer and 90\u0026micro;L of sample solution were added into a microwell containing the freeze-dried probe, mixed thoroughly, and then subjected to chromatography. After 10\u0026ndash;15 min of chromatography, the color development of the test line (T line) and control line (C line) was recorded, and the signal intensities were measured using a strip reader or image analysis software. The relative detection response was expressed as the T/C value. Standard curves were established by plotting the T/C values against the logarithm of carbofuran concentration. The inhibition rate was calculated as follows:\u003c/p\u003e \u003cp\u003eInhibition rate (%) = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(1-\\frac{T/C}{{\\left(T/C\\right)}_{0}}\\right)\\times\\:100\\%\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\left(T/C\\right)}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the signal ratio in the absence of carbofuran, and T/C is the signal ratio in the presence of carbofuran. After chromatography, the strips were further immersed in the optimized DAB-H₂O₂ enhancement solution for 8 min, rinsed with ultrapure water, and dried, after which the T-line and C-line signals were recorded again for performance analysis after signal enhancement.\u003c/p\u003e \u003cp\u003eThe analytical performance of the method was evaluated in terms of sensitivity, specificity, and stability. For sensitivity assessment, carbofuran standards were prepared in buffer at concentrations ranging from 0 to 100 ng/mL, and each concentration was tested in triplicate. Standard curves were constructed based on the T/C values obtained before and after DAB enhancement. For specificity evaluation, 3-hydroxycarbofuran, together with several common carbamate and organophosphorus pesticides, was used as potential interferents. Their effects on strip response were compared, and the cross-reactivity values were calculated. For stability evaluation, the three types of strips were subjected to accelerated aging at 55\u0026deg;C, and the changes in T/C values were monitored periodically to generate aging curves; the related results are shown in Figure S5. The standard curves, detection ranges before and after DAB enhancement, and the main analytical parameters of the three probe formats are presented in the Results section.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Pretreatment of Vegetable Samples and Method Validation\u003c/h2\u003e \u003cp\u003eChinese cabbage, chive, and spinach were selected as representative leafy vegetable samples. After purchase, the edible portions were collected, surface impurities were removed, and the samples were chopped and thoroughly homogenized. For analysis, 2.0 g of homogenized sample was accurately weighed into a centrifuge tube, and 10 mL of 20% acetonitrile-PB buffer was added. After vortexing for 5 min, the mixture was centrifuged at 8000 r/min for 5 min, and the supernatant was collected as the sample extract.\u003c/p\u003e \u003cp\u003eTo balance carbofuran extraction efficiency and compatibility with the immunochromatographic system, the effects of PB buffer, 20% acetonitrile-PB buffer, 50% acetonitrile-PB buffer, and pure acetonitrile on strip color development were first compared. Based on the results, 20% acetonitrile-PB buffer was selected as the extraction solution for vegetable samples, and the related optimization results are shown in Figure S6. Blank matrix extracts of the three vegetables were then used as diluents to prepare matrix-matched standard solutions ranging from 0 to 100 ng/mL, which were applied to the three probe-based strip systems. After chromatography, DAB post-enhancement was performed as described in Section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e2.6\u003c/span\u003e, and calibration curves in vegetable matrices were established to evaluate the matrix applicability of the method. A summary of the calibration curves of the three strip formats in the three vegetable matrices is shown in Figure S7.\u003c/p\u003e \u003cp\u003eThe accuracy and precision of the method were evaluated by spike-recovery experiments. Carbofuran standards were spiked into blank extracts of the three vegetables at two concentration levels, and each level was tested in triplicate. The measured concentrations, recoveries, and relative standard deviations (RSDs) were calculated based on the matrix-matched calibration curves. In addition, the same samples were analyzed in parallel by LC\u0026ndash;MS/MS to verify the reliability of the established immunochromatographic method for real sample analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll experiments were performed independently at least three times, and the results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Data processing and statistical analysis were performed using GraphPad Prism 9.0 software (GraphPad Software, San Diego, CA, USA), and some figures were prepared using Origin 2021 software (OriginLab, Northampton, MA, USA). Standard curve fitting, Michaelis\u0026ndash;Menten curve fitting, and kinetic parameter calculation were all conducted using GraphPad Prism 9.0. Statistical significance between groups was evaluated by Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test or one-way analysis of variance (one-way ANOVA), and differences were considered statistically significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Synthesis and Characterization of Au@PDA-PdCu Nanozymes\u003c/h2\u003e \u003cp\u003eTo obtain Au@PDA-PdCu nanozymes with uniform morphology, good dispersibility, and high catalytic activity, the synthesis conditions were first systematically optimized, including the amount of DA\u0026middot;HCl and the feeding amounts of Pd and Cu precursors (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S2). The results showed that an appropriate degree of PDA coating and suitable bimetallic loading were crucial for maintaining particle structural stability and enhancing catalytic performance. Excessive precursor amounts tended to cause overdeposition of surface metals and even particle aggregation, whereas insufficient amounts led to inadequate loading of active components and were unfavorable for catalytic improvement. Based on the overall comparison, the optimal synthesis conditions were determined to be 200 \u0026micro;L DA\u0026middot;HCl, 30 \u0026micro;L Pd precursor, and 1.0 \u0026micro;L Cu precursor. The Au@PDA-PdCu nanozymes prepared under these conditions were subsequently used for structural and compositional characterization.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, the initially prepared Au NPs exhibited a regular quasi-spherical morphology with a relatively uniform size distribution and an average diameter of approximately 17 nm, indicating a stable nucleation and growth process of the gold nanoparticles. After PDA coating, the particle edges of Au@PDA became relatively blurred, and the particle size increased slightly compared with that of bare Au NPs, suggesting that the PDA layer had been successfully deposited onto the surface of the gold nanoparticles (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). After further loading of PdCu, the obtained Au@PDA-PdCu nanozymes still maintained good dispersibility, and small metallic nanostructures could be observed on the particle surface, indicating that PdCu was successfully loaded onto the outer PDA shell to form a hierarchical core-shell structure. These results further confirmed the stepwise synthesis process and structural integrity of the nanozymes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further confirm the elemental composition and spatial distribution of the material, elemental mapping and EDS analyses were performed on the Au@PDA-PdCu nanozymes. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Au was mainly distributed in the particle core, whereas Pd and Cu were located in the outer layer (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh) and showed a high degree of overlap with the signals of O and N. The O and N elements originated from the PDA layer (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg), indicating that Pd and Cu were not independently aggregated but were stably anchored onto the surface of the PDA shell. In addition, the EDS spectrum (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei) further detected the characteristic signals of Au, Pd, Cu, O, and N, providing additional evidence for the successful construction of the Au@PDA-PdCu nanozymes.\u003c/p\u003e \u003cp\u003eThe optical absorption properties of the materials also reflected their stepwise surface modification process. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, bare Au NPs exhibited a surface plasmon resonance absorption peak at 524 nm. After PDA coating, the absorption peak red-shifted to 536 nm. Following further PdCu loading, the peak shifted further to 538 nm, accompanied by a noticeable broadening of the absorption band. These changes indicate that PDA coating and subsequent PdCu deposition altered the local dielectric environment around the particle surface, leading to the progressive red shift of the characteristic absorption peak and indirectly confirming the successful surface modification of the materials. Taken together, the successfully constructed Au@PDA-PdCu nanozymes possessed a well-defined hierarchical core-shell structure, uniform elemental distribution, and characteristic optical changes, thus providing a solid foundation for subsequent antibody conjugation and signal amplification in immunochromatographic applications. Similar findings were reported by Xu et al., who showed that PDA coating increased the particle size of AuNPs, induced a red shift in the absorption peak, and improved both colloidal stability and antibody conjugation efficiency compared with bare AuNPs. Moreover, an appropriate PDA thickness was beneficial for maintaining particle dispersibility, whereas excessively thick coating could lead to aggregation. These observations are consistent with the morphological and optical changes of the Au@PDA-PdCu nanozymes observed in this study, further indicating that the PDA layer not only helps maintain particle dispersion stability but also serves as an important functional interface for subsequent component assembly and bioconjugation\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Peroxidase-Like Catalytic Activity and Kinetic Analysis of Au@PDA-PdCu Nanozymes\u003c/h2\u003e \u003cp\u003eThe peroxidase-like catalytic activity of Au@PDA-PdCu nanozymes was evaluated using TMB as the chromogenic substrate and H₂O₂ as the oxidizing agent. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, an obvious absorption peak at 652 nm appeared only in the complete reaction system containing TMB, H₂O₂, and Au@PDA-PdCu. No significant absorption signal was observed in the control groups without the nanozyme or without H₂O₂. This result indicates that Au@PDA-PdCu can effectively catalyze the oxidation of TMB and produce the blue product oxTMB. These findings confirm that the nanozyme has good peroxidase-like activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSteady-state kinetic analysis was further performed using TMB at different concentrations (0.021\u0026ndash;0.625 mM) as the substrate. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, the rate of absorbance increase at 652 nm gradually increased with increasing TMB concentration. This result indicates that a higher substrate concentration promoted the catalytic reaction. The relationship between the initial reaction rate and substrate concentration was fitted using the Michaelis\u0026ndash;Menten model (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The apparent kinetic parameters were calculated as Kₘ = 0.21 mM and Vmax\u0026thinsp;=\u0026thinsp;5.20 \u0026micro;M min⁻\u0026sup1;, with a fitting correlation coefficient of R\u0026sup2; = 0.987. The relatively low Kₘ value suggests that the nanozyme has good affinity for TMB.\u003c/p\u003e \u003cp\u003eThe TMB-H₂O₂ system has been widely used to evaluate the peroxidase-like activity of nanomaterials. In this system, nanozymes can catalyze the oxidation of TMB to produce the blue product oxTMB, which shows a characteristic absorption peak at 652 nm. In recent years, PDA modification and bimetallic synergistic strategies have also been reported to improve the catalytic performance and analytical potential of nanozymes\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. For example, Zhang et al. reported that a polydopamine-dressed PdCu nanozyme showed enhanced enzyme-like activity, indicating a good synergistic effect between PDA and PdCu\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Therefore, the present results further demonstrate that Au@PDA-PdCu nanozymes can efficiently catalyze substrate oxidation in the TMB-H₂O₂ system and provide a reliable catalytic basis for subsequent signal amplification in immunochromatographic assays.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Construction and Optimization of Nanozyme-Labeled Probes\u003c/h2\u003e \u003cp\u003eTo optimize the construction conditions of Au@PDA-PdCu nanozyme-labeled probes, the pH of the coupling system, the amount of EDC, and the amount of antibody were systematically evaluated. The T₀/C₀ value and inhibition rate were used as the main indicators (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The results showed that the pH of the coupling system had a strong effect on probe performance. Both the T₀/C₀ value and the inhibition rate increased with increasing pH. The best results were obtained at pH 10. When the pH further increased to 11, both values decreased significantly. This result suggests that excessively alkaline conditions were not favorable for maintaining the bioactivity of the probe (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). As the EDC amount increased, the T₀/C₀ value and inhibition rate first increased and then decreased. The highest inhibition rate was obtained at 1 \u0026micro;L EDC. A further increase in EDC may have reduced probe performance because of excessive crosslinking or stronger nonspecific interactions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). In addition, increasing the antibody amount improved the T₀/C₀ value, but the inhibition rate did not show the same trend. At an antibody amount of 2 \u0026micro;L, the probe showed the highest inhibition rate and good repeatability. This result indicates a better balance between antibody loading and probe activity under this condition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Therefore, the optimal coupling conditions were determined to be pH 10, 1 \u0026micro;L EDC, and 2 \u0026micro;L antibody for the following experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe pH of the coupling system, the amount of EDC, and the amount of antibody can strongly affect the immobilization efficiency, spatial orientation, and bioactivity of antibodies on the nanozyme surface. Therefore, a balance is needed between coupling strength and recognition activity. When the pH is too high or the amount of crosslinker is excessive, the surface coupling level may increase, but probe performance may decrease because of antibody conformational changes, over-crosslinking, or enhanced nonspecific adsorption. In addition, a higher antibody amount does not always lead to better performance. An appropriate coating amount helps improve recognition efficiency. However, excessive surface loading may increase steric hindrance or reduce the exposure of binding sites, which can weaken the specific antigen-antibody interaction\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAfter determining the probe coupling conditions, the strip substrate and other key construction parameters were further optimized. Previous studies have shown that different NC membranes differ in pore size, pore structure, capillary flow rate, and protein adsorption capacity. These differences can affect sample migration, reaction time, and band uniformity. Therefore, membrane selection should be optimized for the specific assay system\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the color development on WXJ-140, WXT-140, and WXJ-95-3 membranes was uneven. The CN-95 membrane showed a strong T line, but the C line was not uniform. The CN-140 membrane showed a relatively weak C line. In contrast, the WXJ-95 membrane showed clearer and more uniform color development on both the T line and C line. Therefore, it was selected as the optimal NC membrane for subsequent strip construction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the probe coupling conditions and NC membrane were determined, the probe amount and coating antigen concentration were further optimized for the three strip formats by checkerboard titration, and the results are shown in Tables S1\u0026ndash;S3. Overall, the combination of probe amount and coating antigen concentration had a significant effect on both band intensity and inhibition performance. For the liquid-format strip, the best performance was obtained with 10 \u0026micro;L probe and 0.5 mg/mL coating antigen. Under this condition, the strip showed a lower T/C value and a higher inhibition rate (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). For the sprayed-format strip, the optimal condition was 3 \u0026micro;L/cm probe loading and 0.4 mg/mL coating antigen (Table S2). For the lyophilized-format strip, the best detection performance was achieved with 5 \u0026micro;L probe and 0.3 mg/mL coating antigen (Table S3). These results indicate that, in competitive lateral flow immunoassays, the probe amount and coating antigen concentration should be properly matched to balance band intensity and competitive inhibition. Similar studies have also shown that competitive lateral flow immunoassays are sensitive to the concentration of each component. Excessive loading of one component may enhance the signal but reduce sensitivity. Therefore, the working parameters usually need to be optimized separately for different probe formats\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Sensitivity and Standard Curve Performance of the Au@PDA-PdCu Nanozyme-Based ICA\u003c/h2\u003e \u003cp\u003eBefore systematically evaluating the ICA performance of the three Au@PDA-PdCu nanozyme-labeled probes, the preparation parameters specific to the lyophilized probe were first optimized. The formulation composition and freeze-drying conditions can strongly affect the shape of the lyophilized product, its reconstitution efficiency, and its subsequent assay performance. Therefore, the effects of lyophilization formulation, dilution factor, and freeze-drying time on probe performance were further investigated\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The results showed that, among the three tested lyophilization formulations, formulation B produced the most intact lyophilized probe. After reconstitution, it also gave the clearest color development of both the T line and C line on the test strip. Its overall performance was better than that of formulations A and C. In formulation A, the lyophilized product showed a lighter color and weaker strip signals. In formulation C, the probe in some microwells did not form completely, and the band color development was slightly poorer than that of formulation B. Further optimization of formulation B showed that the undiluted probe could not form a complete structure after freeze-drying. Partial poor formation was still observed at 5-fold and 7-fold dilution. In contrast, both 10-fold and 20-fold dilution produced lyophilized probes with good shape and clear color development.\u003c/p\u003e \u003cp\u003eConsidering both probe morphology and strip performance, a 10-fold dilution was finally selected as the optimal condition (Figure S3). In addition, insufficient freeze-drying time caused the probe to remain as a film-like or liquid residue, making it difficult to form a stable structure at the bottom of the microwell. When the freeze-drying time reached 4 h, the probe was basically fully formed and showed good color development performance. Therefore, 4 h was selected as the optimal freeze-drying time. Based on these results, the subsequent evaluation of lyophilized probe performance was carried out using formulation B, 10-fold dilution, and 4 h freeze-drying (Figure S4). Similar studies have shown that a proper combination of sugars and surface-active components can effectively reduce the aggregation of gold nanoparticles during freeze-drying and improve their dispersion after reconstitution. This may explain why formulation B showed the best performance in this study, as it was more favorable for forming a stable protective matrix during freeze-drying and for maintaining good probe dispersibility after reconstitution\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe assay systems of the liquid, sprayed, and lyophilized Au@PDA-PdCu nanozyme-labeled probes were further optimized by evaluating the effects of buffer type and pH on the T₀/C₀ value, inhibition rate, and color development performance. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, both buffer type and pH had clear effects on the color development and inhibition performance of the three probe systems. For the liquid-format probe system, HBS produced a relatively high T₀/C₀ value, but the C line was weak. In contrast, PB buffer provided more balanced color development together with a higher inhibition rate, and was therefore selected as the optimal buffer. The best detection pH for this system was 8.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). For the sprayed-format probe system, the C line was weak under both HBS and PBS conditions. This result suggests that a higher salt concentration may affect the migration and release of the probe on the sample pad. In comparison, PB buffer gave better inhibition performance and repeatability. The best detection pH for this system was 7.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). For the lyophilized-format probe system, PB buffer gave the clearest and most stable band color development. When the pH was above 8, the inhibition rate decreased significantly. This result indicates that alkaline conditions were not suitable for the detection performance of the lyophilized probe. Therefore, the optimal detection condition for this system was PB buffer at pH 7.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the optimal detection buffer and pH were determined for the three probe systems, the DAB enhancement system was further optimized to improve band contrast and signal readability. As shown in Fig.\u0026nbsp;8, DAB treatment significantly enhanced the gray values of both the T line and C line. However, an excessively high H₂O₂ concentration caused the color reaction to proceed too quickly and produced a darker background, which affected signal interpretation. As the H₂O₂ concentration decreased from 30% to 5%, the background color of the strips gradually became lighter. Further comparison of different DAB-to-H₂O₂ ratios showed that uneven band color development occurred under some conditions. When the DAB:H₂O₂ ratio was 1:2 and the H₂O₂ concentration was 5%, the T line and C line showed the most uniform color development and the cleanest background. This condition gave the best enhancement effect. Therefore, it was selected for subsequent signal enhancement and standard curve construction.\u003c/p\u003e \u003cp\u003eAfter the optimal preparation parameters and detection conditions were determined, the sensitivity of the liquid-format, sprayed-format, and lyophilized-format Au@PDA-PdCu nanozyme probe-based immunochromatographic test strips was further evaluated. The standard curves before and after DAB enhancement were also established, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The results showed that all three probe formats could effectively detect carbofuran under the optimized conditions. The T/C value gradually decreased as the carbofuran concentration increased. This result indicates a clear dose-response relationship. After curve fitting, all three systems showed good correlation. These results suggest that the constructed nanozyme-based ICA system has good potential for quantitative analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther comparison of the detection performance before and after DAB enhancement showed that DAB treatment clearly strengthened the visual signal of the test strips and, to some extent, expanded the detection range. For the liquid-format probe strip, the linear range remained 0\u0026ndash;100 ng/mL after DAB enhancement, but the LOD decreased from 0.055 ng/mL to 0.016 ng/mL, indicating a clear improvement in sensitivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003ea). For the sprayed-format probe strip, the linear range was extended from 0\u0026ndash;50 ng/mL to 0\u0026ndash;100 ng/mL after DAB enhancement. This result suggests that signal enhancement helped broaden the effective detection range. In contrast, the lyophilized-format probe strip already showed relatively high sensitivity before enhancement. Its linear range was 0\u0026ndash;50 ng/mL, and the LOD was 0.078 ng/mL. After DAB enhancement, the detection range was extended to 0\u0026ndash;100 ng/mL, but the LOD changed only slightly.\u003c/p\u003e \u003cp\u003eOverall, the effect of DAB enhancement was not the same for the three probe systems. For the liquid-format probe, the main effect was improved sensitivity. For the sprayed-format and lyophilized-format probes, the main effects were an expanded detection range and better band readability. Similar studies have also shown that nanozyme-catalyzed 3,3\u0026prime;-diaminobenzidine enhancement can greatly amplify the test-line signal through substrate oxidation and deposition, thereby improving the analytical performance of lateral flow assays. In the delayed substrate release nanozyme-based lateral flow system reported by Sun et al., 3,3\u0026prime;-diaminobenzidine underwent oxidation and deposition under the catalysis of Au@Pt nanozymes. As a result, the detection limit for H1N1 was reduced by 25-fold compared with that before enhancement, while a good linear response range was maintained. This finding suggests that this type of post-assay color enhancement strategy can effectively improve the distinguishability of low-concentration samples\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Specificity and Storage Stability of the Au@PDA-PdCu Nanozyme-Based ICA\u003c/h2\u003e \u003cp\u003eAfter the sensitivity and standard curve characteristics of the three immunochromatographic test strips had been clarified, their analytical performance was further evaluated in terms of specificity and storage stability. First, to examine the specificity of the method for carbofuran, several related carbamate pesticides, including carbaryl, pirimicarb, methomyl, aldicarb, and isoprocarb, as well as the common organophosphorus pesticides chlorpyrifos and dichlorvos, were selected as potential interferents. The cross-reactivity of 3-hydroxycarbofuran, a metabolite of carbofuran, was also evaluated. The results showed that the three test strips exhibited no obvious cross-reactivity toward the tested pesticides other than 3-hydroxycarbofuran, and all cross-reactivity values were below 0.1%, indicating good specificity of the method (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Notably, the cross-reactivity values of 3-hydroxycarbofuran were 8.6% for the liquid-format strip, 8.9% for the sprayed-format strip, and 8.0% for the lyophilized-format strip. This result may be related to the high structural similarity between 3-hydroxycarbofuran and carbofuran, since 3-hydroxycarbofuran is a metabolite of carbofuran. According to GB 2763\u0026mdash;2021, the residue limit of carbofuran is expressed as the sum of carbofuran and 3-hydroxycarbofuran. Therefore, this level of cross-reactivity is reasonable to some extent. Overall, the three probe-based test strips showed good analytical specificity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecificity evaluation of ICA strips based on three types of probes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTarget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eIC\u003csub\u003e50\u003c/sub\u003e (ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCross reaction rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiquid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSprayed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLyophilized\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLiquid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSprayed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLyophilized\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Hydroxy-carbofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbaryl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePirimicarb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrometrazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAldicarb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChlorpyrifos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDichlorvos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026gt;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo evaluate the storage stability of the three test strips, an accelerated aging experiment was carried out to monitor their performance changes under simulated high-temperature storage conditions. The T₀/C₀ value was used as the indicator of stability. The results showed that the T₀/C₀ value of the liquid-format probe strip changed only slightly over 20 d and remained relatively stable. The lyophilized-format probe strip also showed only small fluctuations, indicating good stability. In contrast, the T₀/C₀ value of the sprayed-format probe strip first increased and then decreased as the storage time was extended (Figure S5).\u003c/p\u003e \u003cp\u003eThis trend in the sprayed-format strip may be related to the gradual inactivation of probe antibodies under high-temperature conditions. At the early stage of storage, partial antibody denaturation may first weaken its binding to the secondary antibody on the C line. This change would reduce the C-line signal and increase the T₀/C₀ value. As aging became more severe, the binding ability of the probe to both the coating antigen on the T line and the secondary antibody on the C line decreased markedly. As a result, the T₀/C₀ ratio decreased after reaching a peak. Based on the accelerated aging results and Arrhenius equation prediction, the expected shelf life of the liquid-format and lyophilized-format probe strips at room temperature was both longer than 1 year, while that of the sprayed-format probe strip was about 9 months. Maksin et al. evaluated the stability of lyophilized gold nanoparticle conjugates by monitoring changes in the test-line signal during storage. They pointed out that smaller signal decay indicates better system stability. Therefore, in this study, the liquid-format and lyophilized-format probe strips showed only small fluctuations during accelerated aging and had better stability. In contrast, the sprayed-format probe strip showed more obvious signal changes, suggesting that it was more sensitive to thermal aging\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Detection of Carbofuran in Real Vegetable Samples\u003c/h2\u003e \u003cp\u003eTo select a suitable pretreatment extraction system for carbofuran detection in vegetable samples, the effects of PB buffer, 20% acetonitrile-PB buffer, 50% acetonitrile-PB buffer, and pure acetonitrile on the color development performance of the immunochromatographic test strips were first compared. As shown in Figure S6a, both the T line and C line were clearly visible when PB buffer and 20% acetonitrile-PB buffer were used. This result indicates that these two systems had good compatibility with the test strip assay. In contrast, when the acetonitrile content increased to 50%, the color development of the strips became much weaker. When pure acetonitrile was used, almost no color appeared on either the T line or C line. These results indicate that a high proportion of organic solvent can strongly interfere with the normal immunoreaction on the test strip.\u003c/p\u003e \u003cp\u003eConsidering both the extraction efficiency of pesticide residues from the samples and the color development compatibility with the immunochromatographic assay, 20% acetonitrile-PB buffer was selected as the extraction solution for subsequent vegetable sample pretreatment. The applicability of this extraction system was then further evaluated in the three test strip formats. As shown in Figure S6b, under blank sample conditions, both the T line and C line were clearly visible on all three test strips. Under the spiked condition of 20 ng/mL carbofuran, the T line of all three strips became weaker to different degrees, while the C line remained clearly visible. These results indicate that the sample matrix extracted with 20% acetonitrile-PBS did not cause obvious interference with strip interpretation and was suitable for the detection of real vegetable samples.\u003c/p\u003e \u003cp\u003eAfter optimization of the sample pretreatment conditions, the performance of the three carbofuran immunochromatographic test strips with different probe formats was evaluated using extracts of Shanghai green, Chinese chive, and spinach as sample matrices. The working curves obtained under DAB enhancement are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e, and the original curves before enhancement are shown in Figure S7. The results showed that all three strip formats exhibited good dose-response relationships in the three vegetable matrices. The curve-fitting coefficients (R\u0026sup2;) were all higher than 0.98. These results indicate that the method has good quantitative analytical capability in real sample matrices. The detailed analytical parameters are listed in Table S4.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results showed that the vLOD values of the liquid-format and sprayed-format probe strips were both 5 ng/mL in all three vegetable samples, while the vLOD of the lyophilized-format probe strip was 1 ng/mL in all three vegetable samples, indicating higher visual detection sensitivity. Overall, the detection range of all three strip formats in real vegetable samples was 0\u0026ndash;100 ng/mL. This range is sufficient for carbofuran residue detection in leafy vegetables according to GB 2763\u0026mdash;2021. Similar studies have also shown that immunochromatographic methods for carbofuran can maintain good detection performance in real fruit and vegetable matrices. Previous reports showed good linear relationships and low detection limits for carbofuran in samples such as mustard cabbage, orange, and grape. Another study reported that a quantum dot-based lateral flow assay for carbofuran detection in vegetables achieved spike recoveries of 83%\u0026ndash;111% and showed results consistent with those of HPLC\u0026ndash;MS. These findings are consistent with the results of this study. In the present work, all three strip formats showed good dose-response relationships in extracts of Shanghai green, Chinese chive, and spinach, and all fitting coefficients were higher than 0.98. This result further indicates that the established method has good matrix adaptability and good potential for practical sample analysis\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo further evaluate the applicability of the method in real samples, recovery experiments were carried out using Shanghai green, Chinese chive, and spinach as sample matrices at two spiking levels, 1 ng/mL and 10 ng/mL. The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The liquid-format probe strip showed recoveries of 75%\u0026ndash;107% and coefficients of variation of 4.3%\u0026ndash;25.7% in the three vegetable samples. The sprayed-format probe strip showed recoveries of 76%\u0026ndash;112% and coefficients of variation of 3.7%\u0026ndash;12.4%. The lyophilized-format probe strip showed recoveries of 70%\u0026ndash;119% and coefficients of variation of 4.0%\u0026ndash;8.4%. Overall, the immunochromatographic test strips based on the three probe formats showed good accuracy and precision in the three vegetable samples. These results indicate that the established method has good capability for real sample analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAccuracy and precision of carbofuran ICA strips based on three probe types.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest strip type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVegetable species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpiked Conc. (ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecovery\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCV\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eLiquid probe strip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChinese cabbage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003echive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003espinach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eSprayed probe strip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChinese cabbage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003echive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003espinach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"5\" nameend=\"c2\" namest=\"c1\" rowspan=\"6\"\u003e \u003cp\u003eLyophilized probe strip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChinese cabbage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003echive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003espinach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFrom the results in different matrices, the liquid-format probe strip showed relatively larger variation in spinach samples. At the spiking level of 10 ng/mL, the coefficient of variation reached 25.7%. This result may be related to the higher chlorophyll content and darker matrix color of spinach. After homogenization, pigments and other co-extracted components may interfere with the gray value reading of the T line and C line. This effect may increase the difference among parallel measurements. In contrast, the sprayed-format and lyophilized-format probe strips showed lower coefficients of variation in all three vegetable samples, indicating better result stability. For samples with darker color and more complex matrices, the detection error may be further reduced by optimizing the extraction procedure, reducing pigment co-extraction, or increasing the number of parallel measurements. Similar studies have shown that carbofuran immunoassays usually provide good recovery and repeatability in real vegetable samples. Wu et al. validated a quantum dot-based lateral flow assay for carbofuran in vegetable samples and reported recoveries of 83%\u0026ndash;111% with coefficients of variation below 10%. Their results were also consistent with those of HPLC\u0026ndash;MS. Similar to that study, the three strip formats in the present work also showed good overall accuracy and precision in Shanghai green, Chinese chive, and spinach samples. These results indicate that the established method has good applicability for real sample analysis\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Consistency Evaluation of Test Strip Results with LC\u0026ndash;MS/MS\u003c/h2\u003e \u003cp\u003eTo verify the reliability of the established immunochromatographic method, the detection results for carbofuran in three vegetable samples were compared with those obtained by LC\u0026ndash;MS/MS as the reference method. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, carbofuran was not detected (ND) in the blank samples of Shanghai green, Chinese chive, and spinach by LC\u0026ndash;MS/MS, and all three types of test strips also gave negative results. At the spiking levels of 50 ng/mL and 200 ng/mL, carbofuran residues were detected by LC\u0026ndash;MS/MS, and the liquid-format, sprayed-format, and lyophilized-format immunochromatographic test strips all showed positive results. These findings indicate good agreement between the three test strips and the LC\u0026ndash;MS/MS method in identifying negative samples and judging positive samples above the target level. The results also demonstrate that the established method can accurately reflect carbofuran residues in vegetable samples and has good accuracy and practical reliability, making it suitable for rapid screening of carbofuran residues in vegetables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConsistency evaluation of detection results between the Au@PDA-PdCu nanozyme-based ICA and the LC-MS/MS reference method. (\u0026ldquo;ND\u0026rdquo; indicates not detected; \u0026ldquo;+\u0026rdquo; represents positive; \u0026ldquo;\u0026minus;\u0026rdquo; represents negative.)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTest strip type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c12\" namest=\"c2\"\u003e \u003cp\u003eSpiked Conc. (ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eChinese cabbage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003echive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003espinach\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLC-MS/MS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLiquid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSprayed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLyophilized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSimilarly, Yin et al. developed a dual-color immunochromatographic assay based on Au@PDA and colloidal gold for the simultaneous detection of paclobutrazol and carbofuran in fruit and vegetable samples. Their results showed good agreement with those obtained by LC\u0026ndash;MS/MS. This finding further supports the feasibility and necessity of using mass spectrometry as a reference method to verify the reliability of immunochromatographic assays\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this study, a hierarchical Au@PDA-PdCu nanozyme was successfully constructed and applied as a signal label for the development of a competitive immunochromatographic assay for carbofuran detection. The nanozyme showed good structural characteristics, dispersibility, and peroxidase-like catalytic activity, providing a reliable basis for antibody conjugation and catalytic signal amplification. After systematic optimization, the liquid-, sprayed-, and lyophilized-format probe strips all showed good dose-response relationships and satisfactory analytical performance, while DAB post-enhancement further improved sensitivity or expanded the detection range depending on the probe format. The established method also exhibited good specificity, stability, and matrix adaptability. In vegetable samples, it provided satisfactory recoveries, good precision, and results consistent with those of LC\u0026ndash;MS/MS. Overall, the proposed Au@PDA-PdCu nanozyme-based ICA offers a rapid, sensitive, and practical strategy for carbofuran screening in leafy vegetables and provides useful support for the development of nanozyme-assisted lateral flow assays in food safety monitoring.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Shanghai Agricultural Science and Technology Innovation Program, \u0026ldquo;Research and Application of a Gold Nanozyme-Based Rapid Immunoassay for the Detection of Carbofuran-Type Carbamate Pesticide Residues in Shanghai Local Vegetables\u0026rdquo; (2023-02-08-00-12-F04598); the General Scientific Research Project of the University-Level \u0026ldquo;Basic Discipline\u0026rdquo; Interdisciplinary Special Program, \u0026ldquo;Highly Fluorescent Carbon Dots Derived from Coarse and Aged Green Tea: Construction of an Efficient Fluorescent Sensing Platform for Heavy Metals\u0026rdquo; (309-AW0203-25-005350); the Key Project of the Shanghai Municipal Science and Technology Commission, \u0026ldquo;Research on Novel Rapid Immunodetection Technologies and Product Applications for Multiple Heavy Metals in Edible Agricultural Products and Foods\u0026rdquo; (20392002100); and the Shanghai Engineering Research Center of Plant Germplasm Resources (No. 17DZ2252700).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHaofeng Lao: Investigation; Methodology; Formal analysis; Data curation; Writing - original draft.Xuhui Yue: Investigation; Methodology; Validation. Writing - original draft.Xiaoqing Weng: Investigation; Methodology; Validation. Writing - original draft.Shaokang Zhang: Investigation; Formal analysis.Jiachen Shi: Resources; Supervision.Yuanfeng Wang: Conceptualization; Funding acquisition; Project administration; Supervision; Writing - review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMishra S, Zhang W, Lin Z, Pang S, Huang Y, Bhatt P, Chen S (2020) Chemosphere 259:127419\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlves KVB, Martinez DST, Alves OL, Barbieri E (2022) Chemosphere 288:132359\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao N, Zong X, Guo X, Chen X, Nie D, Huang L, Li L, Ma Y, Wang C, Pang S (2024) Chemosphere 350:140992\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlves Senabio J, Correia Da Silva R, Guariz Pinheiro D, Gomes L, De Vasconcelos, Soares MA (2024) PLoS ONE 19:e0314492\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan A, Fahad TM, Akther T, Zaman T, Hasan MF, Islam Khan MR, Islam MS, Kishi S (2021) J Cell Mol Medi 25:1048\u0026ndash;1059\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang L, Lang Z, Lu B, Yang T, Zhang X, Wang M, Zhang X, Cao H, Ye D (2025) Spectrochim Acta Part A Mol Biomol Spectrosc 327:125415\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEuropean Food Safety Authority (EFSA) \u003cem\u003eEFS2\u003c/em\u003e, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2903/j.efsa.2025.9299\u003c/span\u003e\u003cspan address=\"10.2903/j.efsa.2025.9299\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao Y, Tan G, Wang M, Lin H, He L, Li L, Wang B (2019) J Food Sci 84:3296\u0026ndash;3302\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang M, Li R, Zou S (2008) Determination of carbofuran residue in aquatic products by gas chromatography. Se pu= Chin J Chromatogr 26(6):775\u0026ndash;777\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuertas-P\u0026eacute;rez JF, Garc\u0026iacute;a-Campa\u0026ntilde;a AM (2008) Anal Chim Acta 630:194\u0026ndash;204\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsman KA, Al-Humaid AM (2010) Al-Rehiayani and K. N. Al-Redhaiman. Ecotoxicol Environ Saf 73:1433\u0026ndash;1439\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Bu T, Cui Q, Li Z, Xu Q, Jiang Z, Mao Y, Huang X, Song L, Peng D, Zhang X (2025) Food Chem 465:142062\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Fan Q, Chen Y, Sun X, Shi G (2022) Biosensors 12:560\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhai S, Dong H, Wang H, Huang J, Li D, Li Z, Li Z, Li P, Zhang P, Zhao M, Sun X, Guo Y (2024) J Hazard Mater 477:135296\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou R, Guo Y, Chen Y, Zhao Y, Zhao L, Zhu G, Liu Y, Peters J, Guo Y (2022) J Hazard Mater 426:127845\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou P, Lu Y, Zhu J, Hong J, Li B, Zhou J, Gong D, Montoya A (2004) J Agric Food Chem 52:4355\u0026ndash;4359\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin J, Yan Y, Zhang K, Fu H, Lu M, Zhu H, Wei D, Peng J, Lai W (2022) Foods 11:1564\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Z-J, Wu H-L, Xiao Z-L, Fu H-J, Shen Y-D, Luo L, Wang H, Lei H-T, Hongsibsong S, Xu Z-L (2021) J Hazard Mater 412:125241\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Wang Y, Dong J, Yang J, Zhang Y, Wang F, Si R, Xu Z, Wang H, Xiao Z, Shen Y (2019) Biomolecules 9:576\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Q, Qu Q, Chen S, Liu X, Li P (2017) Food Chem 231:295\u0026ndash;300\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePei J, Jin Y, Ren C, Chen Y, Zou M, Qi X (2024) Anal Methods 16:3938\u0026ndash;3948\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuyang H, Wang W, Shu Q, Fu Z (2018) Analyst 143:2883\u0026ndash;2888\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCho I-H, Bhunia A, Irudayaraj J (2015) Int J Food Microbiol 206:60\u0026ndash;66\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoni H, Verma N, Chaudhari DY, Gandhi SA, Pandya A, Sutariya PG (2024) Anal Methods 16:2400\u0026ndash;2411\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai S, Hu M, Zhang W, Lei Z (2025) Anal Chim Acta 1336:343519\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong S, Guan L, Zhao Y, Wang Y, Liu P, Li P, Han C, Liu B, Zhang C (2022) Microchem J 183:108070\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu S, Zhang G, Fang B, Xiong Q, Duan H, Lai W (2019) ACS Appl Mater Interfaces 11:31283\u0026ndash;31290\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo C, Li X, Li Y (2024) IJN 19:441\u0026ndash;452\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C, Liu W, Li Z, Yan B, Lin J, Chen C, Zhang L, Lu Y (2022) ACS Sustainable Chem Eng 10:1653\u0026ndash;1663\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColuccio ML, Grillo F, Onesto V, Garo V, Scala C, Cuzzola P, Calfa M, Candeloro P, Gentile F, Piletsky S, Malara N (2021) Nanomaterials 11:2620\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuntawong P, Putalun W, Tanaka H, Morimoto S, Sakamoto S (2022) J Nat Med 76:521\u0026ndash;545\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedreira-Rinc\u0026oacute;n J, Rivas L, Comenge J, Skouridou V, Camprub\u0026iacute;-Ferrer D, Mu\u0026ntilde;oz J, O\u0026rsquo;Sullivan CK, Chamorro-Garcia A, Parolo C (2025) Lab Chip 25:2578\u0026ndash;2608\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu D, Galvanin F, Yu Y (2018) AAPS PharmSciTech 19:541\u0026ndash;550\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYokota H, Kadowaki M, Matsuura T, Imanaka H, Ishida N, Imamura K (2020) Langmuir 36:6698\u0026ndash;6705\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Y, Mao M, Tai S, Chao M, Xu H, Cai Y, Peng C, Ma W, Wang Z (2025) Talanta 286:127557\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaksin IV, Kuandykova A, Polyakova DI, Kesareva VA, Luzyanin TA, Ivanov VS, Simonova EI, Khunteev GA, Kirillova YG (2025) Biosensors 15:592\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin J, Yan Y, Zhang K, Fu H, Lu M, Zhu H, Wei D, Peng J, Lai W (2022) Foods 11:1564\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Carbofuran, nanozyme, lateral flow immunoassay, Au@PDA-PdCu, DAB enhancement, leafy vegetables","lastPublishedDoi":"10.21203/rs.3.rs-9490663/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9490663/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCarbofuran residues threaten food safety and public health, yet conventional instrumental methods require expensive equipment and complicated pretreatment, while traditional immunochromatographic assays still lack sufficient sensitivity. Herein, a hierarchical Au@PDA-PdCu nanozyme was developed as a signal probe for a competitive immunochromatographic assay (ICA) for rapid carbofuran detection. The Au core served as a stable nanoplatform, the PDA interlayer enabled antibody immobilization, and the PdCu shell provided strong peroxidase-like activity for post-assay signal amplification. Three probe formats, namely liquid, sprayed, and lyophilized probes, were constructed and optimized. After DAB enhancement, the detection limit of the liquid-format strip decreased from 0.055 to 0.016 ng/mL, while the linear ranges of the sprayed- and lyophilized-format strips expanded to 0\u0026ndash;100 ng/mL. In Chinese cabbage, chive, and spinach, all three formats exhibited good quantitative performance (R\u0026sup2; \u0026gt; 0.98). The visual limits of detection were 5 ng/mL for the liquid- and sprayed-format strips and 1 ng/mL for the lyophilized-format strip. Recoveries ranged from 70% to 119%, with coefficients of variation of 3.7%\u0026ndash;25.7%. Good specificity was observed, with cross-reactivity below 0.1% for most tested compounds except 3-hydroxycarbofuran. The liquid and lyophilized strips showed predicted shelf lives of over 1 year, and ICA results agreed well with LC\u0026ndash;MS/MS. Overall, this method provides a rapid, sensitive, and practical tool for on-site carbofuran screening in leafy vegetables.\u003c/p\u003e","manuscriptTitle":"A Hierarchical Au@PDA-PdCu Nanozyme for Signal- Amplified Immunochromatographic Detection of Carbofuran in Leafy Vegetables","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 14:03:54","doi":"10.21203/rs.3.rs-9490663/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-04T13:21:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T01:17:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-23T01:16:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Analytical Methods","date":"2026-04-22T04:12:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4fca096d-5579-482d-89b7-44774dca6470","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"22","date":"2026-05-04T13:21:01+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T14:03:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 14:03:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9490663","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9490663","identity":"rs-9490663","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}