Temporal evolution of organochlorine and organophosphate pesticide residues in wells in the Akkar Region (Lebanon).

The Akkar plain is the second largest agricultural area in Lebanon. This region produces huge amount of regular crops such as maize, fruits, and vegetables. In order to protect the crops, farmers use large quantities of many pesticides (including authorized and prohibited molecules) without respecting the recommended doses. In this work, we wanted to study the evolution of OCP and OPP residues at 3-year intervals in water wells in the Akkar region. Twenty OCPs and 8 OPPs were monitored in eight wells in different villages in the plain and mountains of Akkar. Solid phase extraction (SPE) method was used for pesticide extraction, followed by gas chromatography-mass spectrometry (GC-MS) analysis. The results revealed an increasing concentration of OCPs and OPPs in groundwater over the last 3 years (between 2017 and 2019-2020). This increase in contamination is due to the uncontrolled and still unregulated (by the authorities) use of pesticides, and also to the introduction of new crops. The concentrations found in groundwater confirm that some banned pesticides are still widely used. The calculation of the theoretical pesticide intake suggests that pesticide concentrations in Akkar represent a greater health risk for the population consuming well water during the rainy season.

Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors.

The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure-activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures.