Experimental studies investigating the effects of endocrine disruptors frequently identify potential unconventional dose-response relationships called non-monotonic dose-response (NMDR) relationships. Standardized approaches for investigating NMDR relationships in a risk assessment context are missing. The aim of this work was to develop criteria for assessing the strength of NMDR relationships. A literature search was conducted to identify published studies that report NMDR relationships with endocrine disruptors. Fifty-one experimental studies that investigated various effects associated with endocrine disruption elicited by many substances were selected. Scoring criteria were applied by adaptation of an approach previously used for identification of hormesis-type dose-response relationships. Out of the 148 NMDR relationships analyzed, 82 were categorized with this method as having a “moderate” to “high” level of plausibility for various effects. Numerous modes of action described in the literature can explain such phenomena. NMDR can arise from numerous molecular mechanisms such as opposing effects induced by multiple receptors differing by their affinity, receptor desensitization, negative feedback with increasing dose, or dose-dependent metabolism modulation. A stepwise decision tree was developed as a tool to standardize the analysis of NMDR relationships observed in the literature with the final aim to use these results in a Risk Assessment purpose. This decision tree was finally applied to studies focused on the effects of bisphenol A.

Cerium oxide (CeO2) nanoparticles used as a diesel fuel additive can be emitted into the ambient air leading to human inhalation. Although biological studies have shown CeO2 nanoparticles can cause adverse health effects, the extent of the biodistribution of CeO2 nanoparticles through inhalation has not been well characterized. Furthermore, freshly emitted CeO2 nanoparticles can undergo an aging process by interaction with other ambient airborne pollutants that may influence the biodistribution after inhalation. Therefore, understanding the pharmacokinetic of newly-generated and atmospherically-aged CeO2 nanoparticles is needed to assess the risks to human health. A novel experimental system was designed to integrate the generation, aging, and inhalation exposure of Sprague Dawley rats to combustion-generated CeO2 nanoparticles (25 and 90 nm bimodal distribution). Aging was done in a chamber representing typical ambient urban air conditions with UV lights. Following a single 4-hour nose-only exposure to freshly emitted or aged CeO2 for 15 min, 24 h, and 7 days, ICP-MS detection of Ce in the blood, lungs, gastrointestinal tract, liver, spleen, kidneys, heart, brain, olfactory bulb, urine, and feces were analyzed with a mass balance approach to gain an overarching understanding of the distribution. A physiologically based pharmacokinetic (PBPK) model that includes mucociliary clearance, phagocytosis, and entry into the systemic circulation by alveolar wall penetration was developed to predict the biodistribution kinetic of the inhaled CeO2 nanoparticles. Cerium was predominantly recovered in the lungs and feces, with extrapulmonary organs contributing less than 4 % to the recovery rate at 24 h post exposure. No significant differences in biodistribution patterns were found between fresh and aged CeO2 nanoparticles. The PBPK model predicted the biodistribution well and identified phagocytizing cells in the pulmonary region accountable for most of the nanoparticles not eliminated by feces. The biodistribution of fresh and aged CeO2 nanoparticles followed the same patterns, with the highest amounts recovered in the feces and lungs. The slow decrease of nanoparticle concentrations in the lungs can be explained by clearance to the gastrointestinal tract and then to the feces. The PBPK model successfully predicted the kinetic of CeO2 nanoparticles in various organs measured in this study and suggested most of the nanoparticles were captured by phagocytizing cells.

Mixtures risk assessment needs an efficient integration of in vivo, in vitro, and in silico data with epidemiology and human studies data. This involves several approaches, some in current use and others under development. This work extends the Agency for Toxic Substances and Disease Registry physiologically based pharmacokinetic (PBPK) toolkit, available for risk assessors, to include a mixture PBPK model of benzene, toluene, ethylbenzene, and xylenes. The recoded model was evaluated and applied to exposure scenarios to evaluate the validity of dose additivity for mixtures. In the second part of this work, we studied toluene, ethylbenzene, and xylene (TEX)-gene-disease associations using Comparative Toxicogenomics Database, pathway analysis and published microarray data from human gene expression changes in blood samples after short- and long-term exposures. Collectively, this information was used to establish hypotheses on potential linkages between TEX exposures and human health. The results show that 236 genes expressed were common between the short- and long-term exposures. These genes could be central for the interconnecting biological pathways potentially stimulated by TEX exposure, likely related to respiratory and neuro diseases. Using publicly available data we propose a conceptual framework to study pathway perturbations leading to toxicity of chemical mixtures. This proposed methodology lends mechanistic insights of the toxicity of mixtures and when experimentally validated will allow data gaps filling for mixtures’ toxicity assessment. This work proposes an approach using current knowledge, available multiple stream data and applying computational methods to advance mixtures risk assessment.