Organophosphorus pesticides (OPs) remain one of the most commonly used pesticides, and their detection rates and residues in agricultural products, foods and environmental samples have been underestimated. Humans and environmental organisms are at high risk of exposure to OPs. Most OPs can be degraded and metabolized into dialkyl phosphates (DAPs) in organisms and the environment, and can be present in urine as biomarkers for exposure to OPs, of which diethyl phosphate (DEP) is a high-exposure metabolite. Epidemiological and cohort studies have found that DAPs are associated with endocrine hormone disorders, especially sex hormone disorders and thyroid hormone disorders, but there has been no direct causal evidence to support these findings. Our study explored the effects of chronic exposure to DEP on endocrine hormones and related metabolic indicators in adult male rats at actual doses that can be reached in the human body. The results showed that chronic exposure to DEP could cause thyroid-related hormone disorders in the serum of rats, causing symptoms of hyperthyroidism in rats, and could also lead to abnormal expression of thyroid hormone-related genes in the rat liver. However, DEP exposure did not seem to affect serum sex hormone levels, spermatogenesis or sperm quality in rats. The molecular interactions between DEP and thyroid hormone-related enzymes/proteins were investigated by molecular docking and molecular dynamics methods in silico. It was found that DEP could strongly interact with thyroid hormone biosynthesis, blood transport, receptor binding and metabolism-related enzymes/proteins, interfering with the production and signal regulation of thyroid hormones. In vivo and in silico experiments showed that DEP might be a potential thyroid hormone-disrupting chemical, and therefore, we need to be more cautious and rigorous regarding organophosphorus chemical exposure.

The paper reports the study of gel permeation chromatography (GPC), gas chromatography/mass spectrometry (GS/MS), and column chromatography tandem MS (LC/MS/MS) for 839 pesticides and chemical contaminants, through which a GPC data bank has been established for 744 pesticides, a GC/MS data bank for 541 pesticides, and an LC/MS/MS data bank for 464 pesticides. On the basis of this study, a new method for quantitative determination of 587 pesticide residues in animal muscles such as beef, mutton, pork, chicken, and rabbit has been established using GPC cleanup followed by GC/MS and LC/MS/MS. In the method, 10 g animal samples were mixed with 20 g sodium sulfate and extracted twice with 35 mL cyclohexaneethyl acetate (1 + 1) by blender homogenization followed by centrifugation, filtration, and concentration. An equivalent of 5 g sample was injected into a 400 25 mm S-X3 GPC column, with cyclohexaneethyl acetate (1 + 1) as the mobile phase at a flow rate of 5 mL/min. The 2240 min fraction was collected for subsequent analysis. For the 478 pesticides determined by GC/MS, the portions collected from GPC were concentrated to 0.5 mL and exchanged twice with 5 mL hexane. For the 379 pesticides determined by LC/MS/MS, the portions collected from GPC were dissolved with acetonitrilewater (60 + 40) after taking the extract to dryness with nitrogen gas. At the limit of quantification (LOQ) and 10 LOQ fortification levels of 0.116 000 g/kg, recoveries were within 40130, among which 563 pesticide recoveries were between 60 and 130, accounting for 96 of the compounds; 24 analytes were recovered between 40 and 60, accounting for 4 of the compounds. The relative standard deviation was below 30 for all 587 pesticides. The limits of detection for the method were 0.11600 g/kg. In comparison with GC/MS, LC/MS/MS increased the detection sensitivity 21000 times for 236 pesticides.

Matrix effects on 110 pesticides in 28 tea matrixes of different varieties and origins by LC/MS/MS were studied, and most of the pesticides exhibited soft and medium signal suppression. To better understand the influence of the tea varieties and the physicochemical characteristics of pesticides on the matrix effects, the multivariate analysis tool called hierarchical cluster analysis was applied. Tea matrixes were grouped into three clusters: unfermented, fermented, and post-fermented teas. Any type of tea can be chosen from each cluster as a corresponding representative matrix within that cluster to make matrix-matched solutions, which could simplify analysis while guaranteeing its accuracy. Matrix effects on most pesticides were similar despite the physicochemical diversities of the pesticides.