Residue, dissipation and dietary intake risk assessment of tolfenpyrad in four leafy green vegetables under greenhouse conditions

Combination of biotransformation and metabolomics reveals tolfenpyrad-induced hepatocytotoxicity

Tolfenpyrad (TFP) is an extensively used pesticide that inevitably leads to human exposure to both TFP and its transformation product residues. However, the biotransformation of TFP in humans has not been elucidated, and the toxicity of TFP along with its biotransformation products remains largely unknown. In this study, the biotransformation process of TFP was investigated using human liver microsomes and human hepatic cells. Endogenous metabolic changes in the cells were studied to investigate the hepatocytotoxicity of TFP at environmentally relevant concentrations. Fourteen phase I biotransformation products and four phase II TFP products were characterized, among which twelve products were identified for the first time. The oxidative product tolfenpyrad-benzoic acid (PT-CA) was particularly abundant and stable. Further hepatotoxicity assessments and metabolic studies demonstrated comparable metabolic profiles for TFP and PT-CA in HepG2 cells, with both significantly disrupting purine and glutathione metabolism. These processes are closely associated with oxidative stress, mitochondrial damage, and cell death. Our results provide novel perspectives on the biotransformation, metabolism, and hepatotoxicity of TFP, thereby highlighting the non-negligible toxicity of its crucial biotransformation product PT-CA in environmental risk assessments.

A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide

A novel deep learning-enabled smartphone platform is developed to assist a colorimetric aptamer biosensor for fast and highly sensitive detection of dimethoate. The colorimetric determination of dimethoate is based on the specific binding of dimethoate and aptamer, which leads to the aggregation of AuNPs in high-concentration NaCl solution, resulting in an obvious color change from red to blue. This color change provides sufficient data for self-learning enabled by a convolutional neural network (CNN) model, which is established to predict dimethoate concentration based on images acquired from a smartphone. To enhance user-friendliness for non-experts, the CNN model is then embedded into a smartphone app, enabling offline detection of dimethoate pesticide in real environments within just 15 min using a pre-configured colorimetric probe. The developed platform exhibits superior performance, achieving a regression coefficient of 0.9992 in the concentration range of 0-10 μM. Moreover, the app's performance is found to be consistent with the ELISA kit. These remarkable findings demonstrate the potential of combining colorimetric biosensors with smartphone-based deep learning methods for the development of portable and affordable tools for pesticide detection.

Dissipation patterns, residue analysis, and risk evaluation of hexaflumuron in turnip and cauliflower under Chinese growth conditions

Hexaflumuron has been globally registered over 2 decades to control the pests in brassicaceous vegetables, while data on its dissipation and residues in turnip and cauliflower is scarce. Herein, field trials were carried out at six representative experimental sites to study the dissipation behaviors and terminal residues of hexaflumuron in turnip and cauliflower. The residual amounts of hexaflumuron were extracted using a modified QuEChERS and analyzed with liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), the chronic dietary risk to Chinese populations was evaluated, and the maximum residue limit (MRL) in cauliflower, turnip tubers, and turnip leaves was calculated by the OECD MRL calculator. The single first-order kinetics model was the best-fitted kinetics model for hexaflumuron dissipation in cauliflower. The indeterminate order rate equation and first-order multi-compartment kinetic model were the best formulae for hexaflumuron dissipation in turnip leaves. The half-lives of hexaflumuron ranged from 0.686 to 1.35 and 2.41 to 6.71 days in cauliflower and turnip leaves, respectively. The terminal residues of hexaflumuron in turnip leaves of 0.321-9.59 mg/kg were much higher than in turnip tubers of < 0.01-0.708 mg/kg and cauliflower of < 0.01-1.49 mg/kg at sampling intervals of 0, 5, 7, and 10 days. The chronic dietary risk of hexaflumuron in the preharvest interval of 7 days was lower than 100% and much higher than 0.01%, indicating acceptable but nonnegligible health hazards for Chinese consumers. Therefore, MRL values of hexaflumuron were proposed as 2, 0.8, and 10 mg/kg in cauliflower, turnip tubers, and turnip leaves, respectively.

Immunochromatographic test strip for quantitative and rapid detection of tolfenpyrad in food samples

In the study, a hapten was designed to preserve the molecular structure of tolfenpyrad while introducing a carboxyl group and was coupled with a carrier protein to synthesize an immunogen and coating antigen. A monoclonal antibody was fabricated against tolfenpyrad and its performance was assessed by indirect competitive enzyme-linked immunosorbent assay. Finally, we developed a colloidal gold nanoparticle immunochromatographic test strip (CGN-ICTS) for the detection of tolfenpyrad in kale, Chinese cabbage, and eggplant samples. The results shows that CGN-ICTS was sensitive, with calculated detection limits of 0.49 ng/g for kale and Chinese cabbage and 0.99 ng/g for eggplant. Subsequently, CGN-ICTS and LC-MS were used to analyze the tolfenpyrad-spiked samples. The recovery rate of the CGN-ICTS for kale samples was 97.1-103.0%, for Chinese cabbage samples was 93.7-103.4%, and for eggplant samples was 92.7-105.7%. Recovery rates were similar between CGN-ICTS and LC-MS. Therefore, CGN-ICTS can be used to quickly screen tolfenpyrad residues in foods.

Determination of tolfenpyrad residues in green tea by GC-MS/MS based on acetonitrile extractant, dispersion solid phase extraction purification

Green tea is one of people's favorite drinks. However, pesticide residues in green tea can cause harm to the human body, and therefore, detection of pesticide residues in green tea is very important. In recent years, the detection of pesticide residues in tea has become a research hotspot. In this paper, a gas chromatography-mass spectrometry/mass spectrometry (GC-MS/MS) detection method of tolfenpyrad pesticide residues in green tea was established by using acetonitrile extractant, dispersive solid-phase extraction purification, temperature programming and application retention time lock with the database. After the sample was extracted with acetonitrile, then the sample was purified by QuEChERS extraction purification tube, afterward isomer B was used as the internal standard for the determination by multiple reaction monitoring mode (MRM) of GC-MS/MS. The results indicated that the experimental data accorded with the criterion on quality control of laboratoris(chemical testing of food), and the requirements of recovery, calibration curve, precision.This method was used to detect tolfenpyrad residues in actual green tea samples in multiple batches, and the satisfactory results were obtained.

The metabolism and dissipation behavior of tolfenpyrad in tea: A comprehensive risk assessment from field to cup

The metabolites of pesticides usually require rational risk assessment. In the present study, the metabolites of tolfenpyrad (TFP) in tea plants were identified using UPLC-QToF/MS analysis, and the transfer of TFP and its metabolites from tea bushes to consumption was studied for a comprehensive risk assessment. Four metabolites, PT-CA, PT-OH, OH-T-CA, and CA-T-CA, were identified, and PT-CA and PT-OH were detected along with dissipation of the parent TFP under field conditions. During processing, 3.11-50.00 % of TFP was further eliminated. Both PT-CA and PT-OH presented a downward trend (7.97-57.89 %) during green tea processing but an upward trend (34.48-124.17 %) during black tea manufacturing. The leaching rate (LR) of PT-CA (63.04-101.03 %) from dry tea to infusion was much higher than that of TFP (3.06-6.14 %). As PT-OH was no longer detected in tea infusions after 1 d of TFP application, TFP and PT-CA were taken into account in the comprehensive risk assessment. The risk quotient (RQ) assessment indicated a negligible health risk, but PT-CA posed a greater potential risk than TFP to tea consumers. Therefore, this study provides guidance for rational TFP application and suggests the sum of TFP and PT-CA residues as the maximum residual limit (MRL) in tea.

Computer-Aided Prediction, Synthesis, and Characterization of Magnetic Molecularly Imprinted Polymers for the Extraction and Determination of Tolfenpyrad in Lettuce

Tolfenpyrad, a pyrazolamide insecticide, can be effectively used against pests resistant to carbamate and organophosphate insecticides. In this study, a molecular imprinted polymer using tolfenpyrad as a template molecule was synthesized. The type of functional monomer and the ratio of functional monomer to template were predicted by density function theory. Magnetic molecularly imprinted polymers (MMIPs) were synthesized using 2-vinylpyridine as a functional monomer in the presence of ethylene magnetite nanoparticles at a monomer/tolfenpyrad ratio of 7:1. The successful synthesis of MMIPs is confirmed by the results of the characterization analysis by scanning electron microscopy, nitrogen adsorption-desorption isotherms, Fourier transform infrared spectroscopy, X-ray diffractometer, thermogravimetric analyzer, and vibrational sample magnetometers. A pseudo-second-order kinetic model fit the adsorption of tolfenpyrad, and the kinetic data are in good agreement with the Freundlich isothermal model. The adsorption capacity of the polymer to the target analyte was 7.20 mg/g, indicating an excellent selective extraction capability. In addition, the adsorption capacity of the MMIPs is not significantly lost after several reuses. The MMIPs showed great analytical performance in tolfenpyrad-spiked lettuce samples, with acceptable accuracy (intra- and inter-day recoveries of 90.5-98.8%) and precision (intra- and inter-day relative standard deviations of 1.4-5.2%).

Dissipation, Residue and Dietary Intake Risk Assessment of Penthiopyrad in Eggplants and Its Removal Using Various Household Processing Techniques

A field trial was conducted to illustrate the dissipation and residue and assess the dietary intake risk of penthiopyrad in eggplants, and the distribution was further estimated after different household processing methods. Penthiopyrad dissipated quickly in eggplants, with half-lives of 1.85−2.56 days. The final residue data indicated that following the recommended spraying method, penthiopyrad would not threaten human health. Risk quotient results (<<100%) also demonstrated that the dietary intake risk of penthiopyrad in eggplants for Chinese consumers could be negligible. Washing, peeling and thermal treatments had significant removal effects on penthiopyrad from eggplants (0 < processing factor < 0.60). The characterization of the dissipation and distribution of penthiopyrad in field and processed eggplant samples could provide a more realistic reference for risk assessment of processed products, as well as some information for humans who may be exposed to penthiopyrad.