Toxicity Of Pesticide Mixtures Research Articles

How well can we predict the toxicity of pesticide mixtures to aquatic life?

Results of publised pesticide mixure toxicity experiments conducted with aquatic organisms were compiled and evaluated to assess the accuracy of predictive mixture models. Three types of models were evaluated: Concentration addition (CA), independent action (IA), and simple interaction (SI). The CA model was the most often tested (207 experiments), followed by SI (59) and IA (37). The reviewed experiments are listed in the Supplemental material to provide a resource for future investigators. The predictive accuracy of each model was quantified for each experiment by the model deviation ratio (MDR), which was calculated by dividing the predicted toxicity by the observed toxicity. Eighty-eight percent of all experiments that evaluated the CA model had observed effective concentrations within a factor of 2 of predicted values (MDR values from 0.5-2.0). The median MDR was 1, about 5% of MDRs were less than 0.5, and about 5% were greater than 2, indicating unbiased estimates overall. The predictive accuracy of CA and IA models was influenced, however, by the different modes of action (MOA) of the pesticides. For experiments with pesticides with the same MOA, CA more accurately predicted effective concentrations for more experiments compared to IA, which tended to underpredict toxicity. The IA model was somewhat more accurate than the CA model for most mixtures with different MOAs, but in most cases there were relatively small differences between the models. Additionally, 80% of SI experiments had an MDR value below 2.0 despite a bias towards experiments that are likely to have an interaction. Thus, results indicate that the CA model may be used as a slightly conservative, but broadly applicable model with a relatively small likelihood of underestimating effects due to interactions.

How well can we predict the toxicity of pesticide mixtures to aquatic life?

How well can we predict the toxicity of pesticide mixtures to aquatic life?

How Well Can We Predict the Toxicity of Pesticide Mixtures to Aquatic Life?

How Well Can We Predict the Toxicity of Pesticide Mixtures to Aquatic Life?

How Well Can We Predict the Toxicity of Pesticide Mixtures to Aquatic Life?

Results of published pesticide mixture toxicity experiments conducted with aquatic organisms were compiled and evaluated to assess the accuracy of predictive mixture models. Three types of models were evaluated: Concentration addition (CA), independent action (IA), and simple interaction (SI). The CA model was the most often tested (207 experiments), followed by SI (59) and IA (37). The reviewed experiments are listed in the Supplemental material to provide a resource for future investigators. The predictive accuracy of each model was quantified for each experiment by the model deviation ratio (MDR), which was calculated by dividing the predicted toxicity by the observed toxicity. Eighty-eight percent of all experiments that evaluated the CA model had observed effective concentrations within a factor of 2 of predicted values (MDR values from 0.5–2.0). The median MDR was 1, about 5% of MDRs were less than 0.5, and about 5% were greater than 2, indicating unbiased estimates overall. The predictive accuracy of CA and IA models was influenced, however, by the different modes of action (MOA) of the pesticides. For experiments with pesticides with the same MOA, CA more accurately predicted effective concentrations for more experiments compared to IA, which tended to underpredict toxicity. The IA model was somewhat more accurate than the CA model for most mixtures with different MOAs, but in most cases there were relatively small differences between the models. Additionally, 80% of SI experiments had an MDR value below 2.0 despite a bias towards experiments that are likely to have an interaction. Thus, results indicate that the CA model may be used as a slightly conservative, but broadly applicable model with a relatively small likelihood of underestimating effects due to interactions.

Assessment of the probabilistic ecological risk assessment-toxic equivalent combination approach for evaluating pesticide mixture toxicity to zooplankton in outdoor microcosms.

The probabilistic ecological risk assessment-toxic equivalent (PERA-TE) combination approach was recently introduced in response to the increased demand for risk assessment approaches that can accommodate mixtures. The effectiveness and validity of the PERA-TE approach was assessed using two types of pesticide mixtures tested in outdoor microcosms. The first type of mixture consisted of pesticides with similar modes of action (the organophosphorus insecticides chlorpyrifos and diazinon) and the second of pesticides with different modes of action (chlorpyrifos, endosulfan, and trifluralin). To assess the toxicity of, and potential interaction within, each type of mixture, theoretically equitoxic TE mixtures were prepared in different proportional ratios. The TE mixtures were based on the 10th centile of acute toxicity effects distributions (data obtained from the literature) and a factor of the sum of the 90th centile field concentrations extrapolated from exposure distributions based on North American surface water monitoring data. Changes in zooplankton population abundances were used as the effect measure. The binary organophosphorus mixtures were equitoxic and conformed to the concentration addition model. The observed response trends of zooplankton exposed to the mixture of chemicals with different modes of action were a result of the susceptibility of individual taxa to the dominating pesticide in each mixture. Overall, the PERA-TE approach was not effective in predicting the toxicity and interaction of all mixture types and should be limited to assessing mixtures of chemicals with similar modes of action.

Effect of pesticide mixtures on in vitro nervous cells: Comparison with single pesticides

The toxicity of dimethoate, azinphos-methyl, diazinon, pirimiphos methyl, organophosphorus insecticides, and benomyl (a benzimidazole fungicide) singly and in mixture was studied in a human neuroblastoma cell line, SH-SY5Y. The cells were incubated for 30 min and 4 h with pesticides at concentrations ranging from 0.4 to 100 μg/ml, or with the same compounds mixed as follows: (a) dimethoate-diazinon-azinphos; (b) benomyl-pirimiphos; (c) all together. Pesticides in the mixtures were at the same concentration used when tested singly. Diazinon, azinphos-methyl and pirimiphos, but not dimethoate and benomyl, inhibited acetylcholine esterase (AchE) activity, whereas all the compounds inhibited protein synthesis in the following order: benomyl > azinphos > diazinon: ⪢ pirimiphos = dimethoate. The mixtures showed a toxicity on AchE activity at a maximum equal to that of the most active compound in the mixture. On the contrary, the mixtures were more toxic than the single compounds on protein synthesis, and in certain cases potentiation occurred. Therefore, we can conclude that it is not feasible to predict the toxicity of pesticide mixtures on the basis of the results of the toxicity of single components.

Acute toxicity of pesticide mixtures to bluegills.

Acute toxicity of pesticide mixtures to bluegills.