Multigenerational Toxic Effects on Daphnia magna Induced by Silver Nanoparticles and Glyphosate Mixture.

Multigenerational toxicological effects of a binary mixture of silver nanoparticles (AgNPs) with glyphosate were identified in Daphnia magna using acute and chronic toxicity tests. Acute toxicity interactions were analyzed with the Abbott method. In the chronic tests, the survival, growth, reproduction, and age at first brood were evaluated for the parents and the exposed (F1E) and non-exposed (F1NE) descendants. The scales tested for binary mixture, at the acute level, presented antagonistic and additive interactions, possibly associated with the complexation of the AgNPs by glyphosate. Multigenerational chronic effects related to the parameters, reproduction, and age at first brood were observed in the descendants tested with the individual compounds, with no recovery for F1E and F1NE. In organisms exposed to binary mixture, there was a delay in the age at first brood and also a significant change in the reproduction parameter, with a strong reduction for the parents, F1E, and F1NE, indicating a higher toxicity than the compounds tested individually. Although the results for acute interactions between AgNP and glyphosate did not provide clear evidence, multigenerational chronic binary mixture trials have resulted in unexpected toxicity compared with individual treatments, increasing the concerns associated with this co-exposure in other scenarios. Therefore, the interaction of binary mixture with the organisms merits further investigation and the results reported in the present study will be useful in this regard. Environ Toxicol Chem 2021;40:1123-1131. © 2020 SETAC.

Probabilistic model for assessing occupational risk during the handling of nanomaterials.

Exposure to nanomaterials (NMs) can be considered as human, occupational or environmental. Occupational exposure may be experienced by the workers and/or researchers who develop and produce these products and the hazards inherent to exposure are not yet fully known. Quantitative and qualitative methods are available to estimate the occupational risks associated with the handling of NMs, however, both have limitations. In this context, the objective of this study was to create a Bayesian network (BN) that will allow an assessment of the occupational risk associated with the handling of NMs in research laboratories. The BN was developed considered variables related to exposure, the hazards associated with NMs and also the existing control measures in the work environment, such as collective protection equipment (CPE), administrative measures and personal protection equipment (PPE). In addition to assessing the occupational risk, simulations were carried out by the laboratory manager to obtain information on which actions should be taken to reduce the risk. The development of a BN to assess the occupational risk associated with the handling of NMs is a novel aspect of this study. As a distinctive feature, the BN has measurement control variables in addition to considering CPE, administrative measures and PPE. An advantage of this network in relation to other risk assessment models is that it allows the easy execution of simulations and provides a guide for a decision making by identifying which actions should be taken to minimize the risk.