Use of the IC50 for predicting joint toxic effects of mixtures

Cytotoxicity and oxidative stress induced by atmospheric mono-nitrophenols in human lung cells

Nitrophenols (NPs) are hazardous pollutants found in various environmental matrices, including ambient fine particulate matter (PM_2.5), agricultural residues, rainwater, wildfires, and industrial wastes. This study showed for the first time the effect of three pure nitrophenols and their mixture on human lung cells to provide basic understanding of the NP influence on cell elements and processes. We identified NPs in ambient PM_2.5 and secondary organic aerosol (SOA) particles generated from the photooxidation of monocyclic aromatic hydrocarbons in the U.S. EPA smog chamber. We assessed the toxicity of identified NPs and their equimolar mixture in normal bronchial epithelial (BEAS-2B) and alveolar epithelial cancer (A549) lung cell lines. The inhibitory concentration-50 (IC₅₀) values were highest and lowest in BEAS-2B cells treated with 2-nitrophenol (2NP) and 4-nitrophenol (4NP), respectively, at 24 h of exposure. The lactate dehydrogenase (LDH) assay showed that 4NP, the most abundant NP we identified in PM_2.5, was the most cytotoxic NP examined in both cell lines. The annexin-V/fluorescein isothiocyanate (FITC) analysis showed that the populations of late apoptotic/necrotic BEAS-2B and A549 cells exposed to 3NP, 4NP, and NP equimolar mixture increased between 24 and 48 h. Cellular reactive oxygen species (ROS) buildup led to cellular death post exposure to 3NP, 4NP and the NP mixtures, while 2NP induced the lowest ROS buildup. An increased mitochondrial ROS signal following NP exposure occurred only in BEAS-2B cells. The tetramethylrhodamine, methyl ester, perchlorate (TMRM) assay showed that exposed cells exhibited collapse of the mitochondrial membrane potential. TMRM signals decreased significantly only in BEAS-2B cells, and most strongly with 4NP exposures. Our results suggest that acute atmospheric exposures to NPs may be toxic at high concentrations, but not at ambient PM_2.5 concentrations. Further chronic studies with NP and NP-containing PM_2.5 are warranted to assess their contribution to lung pathologies.

Pharmacokinetic-pharmacodynamic modelling of atazanavir in hair among adolescents on antiretroviral treatment in Zimbabwe

BACKGROUND

Drug potency is a pharmacological parameter defining dose or concentration of drug required to obtain 50% of the drug's maximal effect. Pharmacokinetic-pharmacodynamic modelling and simulation allows estimation of potency and evaluate strategies improving treatment outcome. The objective of our study is to determine potency of atazanavir in hair, defined as atazanavir level in hair associated with 50% probability of failing to achieve viral load below 1000 copies/ml among adolescents, and explore the effect of participant specific variables on potency.

METHODS

A secondary analysis was performed on data from a previous study conducted in HIV-infected adolescents failing 2nd line ART from Harare central hospital, Zimbabwe, between 2015 and 2016. We simulated atazanavir concentrations in hair using NONMEM (version 7.3) ADVAN 13, based on a previously established pharmacokinetic model. Logistic regression methods were used for PKPD analysis. Simulations utilising PKPD model focused on estimation of potency and exploring the effect of covariates.

RESULTS

The potency of atazanavir in hair was found to be 4.5 ng/mg hair before adjusting for covariate effects. Participants at three months follow-up, reporting adequate adherence, having normal BMI-for-age, and cared for by mature guardians had increased potency of atazanavir in hair of 2.6 ng/mg, however the follow-up event was the only statistically significant factor at 5% level.

CONCLUSION

Atazanavir in hair in the range 2.6 to 4.5 ng/mg is associated with above 50% probability of early viral load suppression. Adherence monitoring to adolescents with lower potency of atazanavir is recommended. The effect self-reported adherence level, BMI-for-age, and caregiver status require further evaluation.

Using molecular docking-based binding energy to predict toxicity of binary mixture with different binding sites

The flood of chemical substances in the environment result in the complexity of chemical mixtures, and one of the reasons for complexity is that their individual chemicals bind to different binding sites on different (or same) target proteins within the organism. A general approaches therefore are proposed in this study to predict the toxicity of chemical mixtures with different binding sites by using molecular docking-based binding energy (Ebinding). Aldehydes and cyanogenic toxicants were selected as the example of chemical mixtures with same binding site. Triazines and urea herbicide were selected as the example of chemical mixtures with different binding sites but on same target protein. Sulfonamides and trimethoprim toxicants were selected as the example of chemical mixtures with different target proteins. Although these chemical mixtures bind to their binding sites by different ways, there is a general relationship between their binary mixture toxicity (EC50M) and their corresponding Ebinding of individual chemicals and logKow(mix). By using the Ebinding to describe how the individual chemicals work in the different binding sites, the approach may provide a general and simply model to predict mixture toxicity to microorganism.