Assessment of exposure to pesticides: residues in 24 h duplicate diets versus their metabolites in 24 h urine using suspect screening and target analysis.

Human biomonitoring can add value to chemical risk assessment by reducing the assumptions regarding consumption rates, residue occurrence, and processing effects and by integrating exposures from different sources (diet, household use, environmental). However, the relationship between exposure and concentration in human matrices is unknown for most pesticides. Therefore, we conducted a pilot study to gain more insight into the qualitative and quantitative relationship between dietary intake of pesticides (external exposure) and urinary excretion (reflecting internal exposure). In this cross-sectional observational study, 35 healthy consumers aged 18-65 years from the region of Wageningen, Netherlands, collected an exact duplicate portion of their diets during 24 h. On the same day, they also collected all their urine. The duplicate diets were analyzed using target screening by GC- and LC-HRMS; each duplicate diet contained at least five, up to 21, pesticide residues. The 24 h urine samples were analyzed using LC-HRMS in a suspect screening workflow. Metabolites were tentatively detected in all 24 h urine samples, ranging from six metabolites corresponding to four pesticides up to 40 metabolites originating from 16 pesticides in a single urine sample. In total, 65 metabolites originating from 28 pesticides were tentatively detected. After prioritization and additional confirmation experiments, 28 metabolites originating from 10 pesticides were identified with confidence level 1 or 2b. Next, quantitative analysis was performed for a selection of pesticides in duplicate diets and their metabolites in 24 h urine to assess quantitative relationships. In the quantitative comparisons between duplicate diet and 24 h urine, it was found that some metabolites were already present in the duplicate diet, which may give an overestimation of exposure to the parent pesticide based on measurement of the metabolites in urine. Additionally, the quantitative comparisons suggest a background exposure through other exposure routes. We conclude that suspect screening of 24 h urine samples can disclose exposure to mixtures of pesticide on the same day in the general population. However, more research is needed to obtain quantitative relationships between dietary intake and exposure.

Urinary pesticide mixture patterns and exposure determinants in the adult population from the Netherlands and Switzerland: Application of a suspect screening approach.

INTRODUCTION: Non-occupational sources of pesticide exposure may include domestic pesticide usage, diet, occupational exposure of household members, and agricultural activities in the residential area. We conducted a study with the ambition to characterize pesticide mixture patterns in a sample of the adult population of the Netherlands and Switzerland, using a suspect screening approach and to identify related exposure determinants. METHODS: A total of 105 and 295 adults participated in the Dutch and Swiss studies, respectively. First morning void urine samples were collected and analyzed in the same laboratory. Harmonized questionnaires about personal characteristics, pesticide-related activities, and diet were administered. Detection rates and co-occurrence patterns were calculated to explore internal pesticide exposure patterns. Censored linear and logistic regression models were constructed to investigate the association between exposure and domestic pesticide usage, consumption of homegrown and organic foods, household members' exposure, and distance to agricultural and forest areas. RESULTS: From the 37 detected biomarkers, 3 (acetamiprid (-CH2), chlorpropham (4-HSA), and flonicamid (-C2HN)) were detected in ≥40% of samples. The most frequent combination of biomarkers (acetamiprid-flonicamid) was detected in 22 (5.5%) samples. Regression models revealed an inverse association between high organic vegetable and fruit consumption and exposure to acetamiprid, chlorpropham, propamocarb (+O), and pyrimethanil (+O + SO3). Within-individual correlations in repeated samples (summer/winter) from the Netherlands were low (≤0.3), and no seasonal differences in average exposures were observed in Switzerland. CONCLUSION: High consumption of organic fruit and vegetables was associated with lower pesticide exposure. In the two countries, detection rates and co-occurrence were typically low, and within-person variability was high. Our study results provide an indication for target biomarkers to include in future studies aimed at quantifying urinary exposure levels in European adult populations.

Personal exposure assessment of pesticides in residents: The association between hand wipes and urinary biomarkers.

BACKGROUND: Residential exposure to pesticides may occur via inhalation of airborne pesticides, direct skin contacts with pesticide-contaminated surfaces, and consumption of food containing pesticide residues. The aim was to study the association of dermal exposure to pesticides between the use and non-use periods, between farmer and non-farmer families and between dermal exposure and the excretion of metabolites from urine in residents living close to treated agricultural fields. METHODS: In total, 112 hand wipes and 206 spot urine samples were collected from 16 farmer and 38 non-farmer participants living within 50 m from an agricultural field in the Netherlands. The study took place from May 2016 to December 2017 during the use as well as the non-use periods of pesticides. Hand wipes were analysed for the parent compound and urines samples for the corresponding urinary metabolite of five applied pesticides: asulam, carbendazim (applied as thiophanate-methyl), chlorpropham, prochloraz and tebuconazole. Questionnaire data was used to study potential determinants of occurrence and levels of pesticides in hand wipes according to univariate and multivariate analysis. RESULTS: Carbendazim and tebuconazole concentrations in hand wipes were statistically significantly higher in the pesticide-use period compared to the non-use period. In addition, especially during the use periods, concentrations were statistically significantly higher in farmer families compared to non-farmer families. For asulam, chlorpropham and prochloraz, the frequency of non-detects was too high (57-85%) to be included in this analysis. The carbendazim contents in urine samples and hand wipes were correlated on the first and second day after taking the hand wipe, whereas chlorpropham was only observed to be related on the second day following the spray event. CONCLUSIONS: Concentrations in hand wipes were overall higher in pesticide use periods compared to non-use periods and higher in farmer families compared to non-farmer families. Only for carbendazim a strong correlation between concentrations in hand wipes and its main metabolite in urine was observed, indicating dermal exposure via contaminated indoor surfaces. We expect this to be related to the lower vapour pressure and longer environmental lifetime of carbendazim compared to the other pesticides studies.

Hair as a matrix to evaluate cumulative and aggregate exposure to pesticides in winegrowers.

INTRODUCTION: Vineyard is a crop where a large number of pesticides are applied; exposure to pesticides may occur in farmers and the general population living close to the treated area. This work aimed to investigate hair as a matrix for the assessment of cumulative and aggregate exposure to pesticides in potentially exposed individuals. METHODS: Twenty agricultural workers (AW), 4 agricultural worker relatives (AR), and 5 research staff members (RS) were involved in the study. Hair samples were collected before and after the application season (PRE- and POST-EXP samples) to obtain 18 paired samples. Records with the name and the quantity of applied pesticides were obtained; twenty-seven pesticides were measured in hair by solvent extraction and LC-MS/MS. RESULTS: During the study season, AW applied 14 different pesticides with median amount ranging from 12 to 7200 g. The most popular pesticides were dimethomorph, penconazole, cyazofamid, fenamidone and quinoxyfen, applied from 94 to 69% of AW. In AW, in PRE-EXP samples the majority of used pesticides was detectable (with detection rates from 6 to 88%), with median concentrations of few pg/mg hair; in the POST-EXP samples the frequency of detected values increased (from 25 to 100%), with median concentrations up to two orders of magnitude higher. In AR, most pesticides were quantifiable only in POST-EXP samples and with lower concentration in comparison with AW; in RS, in both PRE- and POST-EXP samples only a few pesticides were quantifiable with very low levels. In AW, a linear correlation (r = 0.682 on log-transformed data, p < 0.01) was found between the total amounts of applied pesticides during the season and their concentration in hair. CONCLUSION: The study shows that the majority of assessed pesticides was incorporated into hair of AW and AR. The increased frequency of detection and level at the end of the season and the correlation between pesticide in hair and the amount of applied pesticides, reinforce the use of hair for quantitative biomonitoring of cumulative exposure to pesticides.

Dependence of Streptococcus lactis phosphate transport on internal phosphate concentration and internal pH.

Uptake of phosphate by Streptococcus lactis ML3 proceeds in the absence of a proton motive force, but requires the synthesis of ATP by either arginine or lactose metabolism. The appearance of free Pi internally in arginine-metabolizing cells corresponded quantitatively with the disappearance of extracellular phosphate. Phosphate transport was essentially unidirectional, and phosphate concentration gradients of up to 10(5) could be established. Substrate specificity studies of the transport system indicated no preference for either mono- or divalent phosphate anion. The activity of the phosphate transport system was affected by the intracellular Pi concentration by a feedback inhibition mechanism. Uncouplers and ionophores which dissipate the pH gradient across the cytoplasmic membrane inhibited phosphate transport at acidic but not at alkaline pH values, indicating that transport activity is regulated by the internal proton concentration. Phosphate uptake driven by arginine metabolism increased with the intracellular pH with a pKa of 7.3. Differences in transport activity with arginine and lactose as energy sources are discussed.