How pesticides affect neonates? - Exposure, health implications and determination of metabolites

Expression of carboxylesterase and paraoxonase in the placenta and their association with chlorpyrifos exposure during pregnancy

Exposure to environmental chemicals during pregnancy, including organophosphate pesticides, can affect the health of both the mother and the fetus, and have repercussions later in life. The present study aimed to determine whether the A-esterases paraoxonases (PON) and the B-esterases carboxylesterases (CES) are modulated in the placenta of pregnant women residing in an intensive pesticide use scenario. A total of 104 healthy pregnant women were recruited between 2018 and 2022 and were classified according to their residential settings in rural (RG) and urban (UG) groups. Chlorpyrifos (CP) level in the placenta was determined by GC-ECD, and confirmed by GC-MS. To analyze possible impacts in esterases, the CES and PON activity, mRNA transcript and protein expression levels were studied. Significantly higher CP levels were detected in RG vs UG. Also, CES activity determined with 1-naphthyl acetate substrate was significantly lower in RG vs UG. In contrast, PON arylesterase and lactonase activities were up modulated in RG vs UG. Likewise, mRNA transcript levels of CES1, CES2 and PON2 were upregulated in the RG along with increases in CES2 and PON2 protein expressions. Moreover, a positive significant correlation was determined between CP concentration and CES1 and CES2 mRNA levels. Rural samples showed elevated CP concentrations and alterations in esterases, which elucidate the impact of CP exposure in mRNA CES and PON regulation. These findings highlight the need for further investigation into the effects of pesticide exposure during pregnancy and to deepen the knowledge about the function that esterases play in the placenta.

Assessment of baby disposable diapers application for urine collection and determination of phthalate metabolites

The baby disposable diapers were investigated as a sampling material for urine collection and validated for the evaluation of the exposure of children to xenobiotics. Phthalate metabolites detected in urine samples were chosen as proof-of-concept analytes. For the determination of phthalate metabolites in children's urine samples, high performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) was used. Two sampling approaches were compared, namely sterile containers and baby disposable diapers. Thirty urine samples from infants and toddlers were analyzed by both methods in parallel and the results were compared. It was found that for diaper sampling, lower concentrations of the metabolites were observed, however, the general distribution for particular metabolites remains the same for both methods. For most of the metabolites high determination coefficients were obtained, namely 0.9929 for MEHHP, 0.9836 for MMP, 0.9796 for MECPP, and 0.9784 for 2-cx-MMHP. For MEOHP the determination correlation coefficient was 0.9154, while for MBP was - 0.7771 and MEHP was - 0.5228. In general, for diaper sampling an underestimation for 2-cx-MMHP and MEOHP was observed, while for MMP diaper-based approach provides overestimation. However, the proposed procedure confirms the possibility of using baby disposable diapers as a material for the collection of urine samples for biomonitoring purposes and fast screening of phthalates exposure.

Transcriptomic and biochemical insights into fall armyworm (Spodoptera frugiperda) responses on silicon-treated maize

Background

The fall armyworm, Spodoptera frugiperda, is an agricultural pest of significant economic concern globally, known for its adaptability, pesticide resistance, and damage to key crops such as maize. Conventional chemical pesticides pose challenges, including the development of resistance and environmental pollution. The study aims to investigate an alternative solution: the application of soluble silicon (Si) sources to enhance plant resistance against the fall armyworm.

Methods

Silicon dioxide (SiO2) and potassium silicate (K2SiO3) were applied to maize plants via foliar spray. Transcriptomic and biochemical analyses were performed to study the gene expression changes in the fall armyworm feeding on Si-treated maize.

Results

Results indicated a significant impact on gene expression, with a large number of differentially expressed genes (DEGs) identified in both SiO2 and K2SiO3 treatments. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis identified critical DEGs involved in specific pathways, including amino acid, carbohydrate, lipid, energy, xenobiotics metabolisms, signal transduction, and posttranslational modification, significantly altered at both Si sources. Biochemical analyses further revealed that Si treatments inhibited several enzyme activities (glutamate dehydrogenase, trehalase, glucose-6-phosphate dehydrogenase, chitinase, juvenile hormone esterase, and cyclooxygenase while simultaneously inducing others (total protein, lipopolysaccharide, fatty acid synthase, ATPase, and cytochrome P450), thus suggesting a toxic effect on the fall armyworm. In conclusion, Si applications on maize influence the gene expression and biochemical activities of the fall armyworm, potentially offering a sustainable pest management strategy.

Different sized gold nanoparticles for array-based sensing of pesticides and its application for strawberry pollution monitoring

The use of pesticides plays an essential role in improving crop quality and yield, however, it causes air, water, and soil pollution and the residue of these pesticides in agricultural products threatens the ecosystem and human life. Therefore, it is highly desirable to develop rapid, simple, and cost-effective methods for regular monitoring of pesticide residues in agricultural products especially strawberry that is consumed fresh and unpeeled. In this study, gold nanoparticles (AuNPs) of varying sizes have been exploited as sensing units to design a non-enzymatic colorimetric sensor array for the detection and discrimination of various pesticides including; bifenazate (BF), paraquat (PQ), diazinon (DZ), thiometon (TM), and carbendazim (CD) and chlorpyrifos (CP). Because of their strong size- and environmentally-dependent properties, AuNPs with different sizes produced distinguished plasmonic patterns in the presence of pesticides at a vast range of concentrations (25-800 ng mL-1). Plasmonic patterns of sensor units have been analyzed by various data visualization (bar plots and heat maps) and pattern recognition methods (linear discriminant analysis (LDA)). The multivariate calibrations showed linear responses ranging from 50 to 800 ng mL-1 for carbendazim, chlorpyrifos, paraquat, and bifenazate and 25-800 ng mL-1 for diazinon and thiometon. The limit of detection (LOD) was calculated to be 17.7, 22.8, 22.4, 9.7, 7.4, and 23.8 ng mL-1 for carbendazim, chlorpyrifos, paraquat, diazinon, thiometon, and bifenazate respectively. Finally, the applicability of the designed sensor was evaluated in real samples comprising tap water, well water, soil, and fruit, leave, drainage water, and culture substrate of strawberry.