Consumer, industrial, and commercial product usage is a source of exposure to potentially hazardous chemicals. In addition, cleaning agents, personal care products, coatings, and other volatile chemical products (VCPs), evaporate and react in the atmosphere producing secondary pollutants. Here, we show high air emissions from VCP usage (≥ 14 kg person −1 yr −1 , at least 1.7× higher than current operational estimates) are supported by multiple estimation methods and constraints imposed by ambient levels of ozone, hydroxyl radical (OH) reactivity, and the organic component of fine particulate matter (PM 2.5 ) in Pasadena, California. A near-field model, which estimates human chemical exposure during or in the vicinity of product use, indicates these high air emissions are consistent with organic product usage up to ~75 kg person −1 yr −1 , and inhalation of consumer products could be a non-negligible exposure pathway. After constraining the PM 2.5 yield to 5% by mass, VCPs produce ~41% of the photochemical organic PM 2.5 (1.1 ± 0.3 μ g m −3 ) and ~17% of maximum daily 8-hr average ozone (9 ± 2 ppb) in summer Los Angeles. Therefore, both toxicity and ambient criteria pollutant formation should be considered when organic substituents are developed for VCPs in pursuit of safer and sustainable products and cleaner air.

Computational methods are needed to more efficiently leverage data from in vitro cell-based models to predict what occurs within whole body systems after chemical insults. This study set out to test the hypothesis that in vitro high-throughput screening (HTS) data can more effectively predict in vivo biological responses when chemical disposition and toxicokinetic (TK) modeling are employed. In vitro HTS data from the Tox21 consortium were analyzed in concert with chemical disposition modeling to derive nominal, aqueous, and intracellular estimates of concentrations eliciting 50% maximal activity. In vivo biological responses were captured using rat liver transcriptomic data from the DrugMatrix and TG-Gates databases and evaluated for pathway enrichment. In vivo dosing data were translated to equivalent body concentrations using HTTK modeling. Random forest models were then trained and tested to predict in vivo pathway-level activity across 221 chemicals using in vitro bioactivity data and physicochemical properties as predictor variables, incorporating methods to address imbalanced training data resulting from high instances of inactivity. Model performance was quantified using the area under the receiver operator characteristic curve (AUC-ROC) and compared across pathways for different combinations of predictor variables. All models that included toxicokinetics were found to outperform those that excluded toxicokinetics. Biological interpretation of the model features revealed that rather than a direct mapping of in vitro assays to in vivo pathways, unexpected combinations of multiple in vitro assays predicted in vivo pathway-level activities. To demonstrate the utility of these findings, the highest-performing model was leveraged to make new predictions of in vivo biological responses across all biological pathways for remaining chemicals tested in Tox21 with adequate data coverage (n = 6617). These results demonstrate that, when chemical disposition and toxicokinetics are carefully considered, in vitro HT screening data can be used to effectively predict in vivo biological responses to chemicals.

We study the spiral arm morphology of a sample of the local spiral galaxies in the Illustris simulation and explore the supermassive black hole−galaxy connection beyond the bulge (e.g., spiral arm pitch angle, total stellar mass, dark matter mass, and total halo mass), finding good agreement with other theoretical studies and observational constraints. It is important to study the properties of supermassive black holes and their host galaxies through both observations and simulations and compare their results in order to understand their physics and formative histories. We find that Illustris prediction for supermassive black hole mass relative to pitch angle is in rather good agreement with observations and that barred and non-barred galaxies follow similar scaling relations. Our work shows that Illustris presents very tight correlations between supermassive black hole mass and large-scale properties of the host galaxy, not only for early-type galaxies but also low-mass, blue and star-forming galaxies. These tight relations beyond the bulge suggest that halo properties determine those of a disc galaxy and its supermassive black hole.

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