Evaluation of genotoxicity after acute and chronic exposure to 2,4-dichlorophenoxyacetic acid herbicide (2,4-d) in rodents using machine learning algorithms

Abstract

2,4-Dichlorophenoxyacetic acid (2,4-D) is one of the most widely used herbicides in the world, but its mutagenic and carcinogenic potential is still controversial. We simulated environmental exposure to 2,4-D, with the objective of evaluating the genotoxic effect of acute and chronic exposure to 2,4-D in rodents. We also evaluated the performance of machine learning algorithms in detecting dif-ferences in exposure groups through recognition performed from genotoxic characteristics. In the acute phase, 88 Swiss mice were used, distributed in five groups and exposed to nebulizations at different time intervals (24, 48, 72 and 192 hr). In the chronic phase, 88 Wistar rats were used, distributed in two groups (inhaled and oral) and exposed for six months. Femoral bone marrow cells were collected for a micro-nucleus test and comet assay. Data were evaluated by pattern recognition algorithms. In acute exposure, medium and high concentrations induced DNA damage in the comet assay, but these concentrations did not increase micronucleated cells. In the chronic exposure, there was an increase in micronuclei and DNA damage in the comet assay in all exposed groups regardless of the exposure route. The data showed a robust pattern of distinction between exposed and nonexposed groups to 2,4-D. Our data showed that both acute inhalation exposure and chronic oral and inhalation exposure to 2,4-D can cause genotoxic effects regardless of concentration. Machine learning showed a clear distinction between the control groups and those exposed to 2,4-D, and the effects of exposure are not concentration-dependent.