RESUMEN
ObjectiveTo establish a GC-MS method for the detection of 9 halogenated alkanes in toothpastes. MethodsVarious brands of toothpastes on the market were collected as the samples. Methanol was used as the extraction solution. After shaking, vortex and centrifugation, the supernatant was filtered by 0.45 μm microporous filter membrane. The content of 9 halogenated alkanes including chloromethane, dichloromethane, chloroform, 1,1,1-trichloroethane, carbon tetrachloride, 1,2-dichloroethane, 1,1,2-trichloroethane, 1,2-dibromoethane, 1,2,3-trichloropropane in the filtrate were determined by GC-MS. ResultsThe 9 halogenated alkanes showed a good linear relationship in the concentration range of 0.03‒1.00 μg·mL-1. The correlation coefficient was ≥0.998 7 with the detection limits of 0.015‒0.056 mg·kg-1. The spiked recoveries were 83.2%‒108.9% with the RSD of 2.0%‒9.8%. In the actual sample analysis, 1,1,2-trichloroethane and 1,2,3-trichloropropane were respectively detected in 6 toothpaste samples from 5 brands. ConclusionThe method is simple, sensitive, accurate, and has good spiked recoveries. It can be used for the determination of halogenated alkanes in toothpastes.
RESUMEN
ObjectiveTo establish a non-targeted screening method for emerging contaminants in drinking water based on high-resolution mass spectrometry and apply it to actual water samples. MethodsA total of 9 drinking water samples collected from 3 reservoirs in Shanghai were purified and concentrated by HLB solid phase extraction column, then separated and analyzed by liquid chromatography high-resolution mass spectrometer and gas chromatography high⁃resolution mass spectrometer. The acquired data were analyzed by Thermo Tracefinder, Excel and other software combined with mzCloud and NIST databases. The methodology was verified with representative compound standards. Pesticide and perfluorinated compounds were taken as examples to analyze their pollution status. ResultsA non-targeted analysis strategy based on liquid chromatography and gas chromatography tandem high-resolution mass spectrometry was established. The pollution level of 20 kinds of pesticides and 4 kinds of perfluorinated compounds identified in 9 drinking water samples were higher in the Huangpu River than in the Yangtze River estuary. ConclusionThe established non-targeted screening method by high-resolution mass spectrometry can detect potential emerging contaminants in drinking water without relying on the standards, which provides a powerful technical means for water quality monitoring and risk assessment.
RESUMEN
ObjectiveTo study the relationship between the exposure to two kinds of phthalate esters (PAEs) [Di-N-butyl phthalate,(DBP) and Di-(2-ethylhexyl)phthalate (DEHP)] and estrogen homeostasis in pregnant women. MethodsIn 2021, we classified the Jiading District of Shanghai into five geographical areas, east, west, south, north and central. A total of 151 pregnant women from each area were selected for questionnaire survey, with random urine samples during first, second, and third trimesters collected. A DBP metabolite [Mono-N-butyl phthalate (MBP)] and two DEHP metabolites [Mono(2-ethylhexyl) phthalate (MEHP), Mono(2-ethyl5-oxohexyl) phthalate, (MEOHP)] and three estrogens [estrone (E1), 17β -estradiol (E2), and estriol (E3)] in urine were determined by ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry. After a natural logarithmic transformation of PAEs metabolite levels and estrogen concentration, multivariable linear regression was used to control potential confounders and determine the relationship between PAEs metabolite levels and estrogen concentration. ResultsThe detection rates of three PAEs metabolites in urine of pregnant women were more than 98%. The median corrected concentrations of MBP, MEHP and MEOHP were 5.18, 0.59 and 4.23 mg·kg-1, respectively. During the whole pregnancy, MEOHP was positively correlated with E1 (β=0.450, 95%CI: 0.057‒0.844), and MBP was positively correlated with E3 (β=0.250, 95%CI: 0.034‒0.465). Stratified by trimesters, MBP was positively correlated with E3 in the first trimester (β=0.428, 95%CI: 0.103‒0.752). MEOHP was positively correlated with E1 in the second trimester (β=0.734, 95%CI: 0.130‒0.752), and had a possitive trend with E1 in the third trimester (β=0.744, 95%CI: -0.140‒1.629). In addition, MEHP had a negative correlation with E1 in the second trimester (β=-0.498, 95%CI: -1.063‒0.066). MEOHP had a positive correlation trend with E2 (β=0.628, 95%CI: -0.101‒1.356) in the third trimester. ConclusionPAEs exposure may interfere with estrogen homeostasis during pregnancy and differs by trimesters. Given the cross-sectional nature of this study, it warrants further study to validate the findings.