Carbon Dots/Iron Oxide Nanoparticles with Tuneable Composition and Properties.

We present a simple strategy to generate a family of carbon dots/iron oxide nanoparticles (C/Fe-NPs) that relies on the thermal decomposition of iron (III) acetylacetonate in the presence of a highly fluorescent carbon-rich precursor (derived via thermal treatment of ethanolamine and citric acid at 180 °C), while polyethylene glycol serves as the passivation agent. By varying the molar ratio of the reactants, a series of C/Fe-NPs have been synthesized with tuneable elemental composition in terms of C, H, O, N and Fe. The quantum yield is enhanced from 6 to 9% as the carbon content increases from 27 to 36 wt%, while the room temperature saturation magnetization is improved from 4.1 to 17.7 emu/g as the iron content is enriched from 17 to 31 wt%. In addition, the C/Fe-NPs show excellent antimicrobial properties, minimal cytotoxicity and demonstrate promising bioimaging capabilities, thus showing great potential for the development of advanced diagnostic tools.

A Mechanistic Framework for Integrating Chemical Structure and High-Throughput Screening Results to Improve Toxicity Predictions.

Adverse Outcome Pathways (AOPs) establish a connection between a molecular initiating event (MIE) and an adverse outcome. Detailed understanding of the MIE provides the ideal data for determining chemical properties required to elicit the MIE. This study utilized high-throughput screening data from the ToxCast program, coupled with chemical structural information, to generate chemical clusters using three similarity methods pertaining to nine MIEs within an AOP network for hepatic steatosis. Three case studies demonstrate the utility of the mechanistic information held by the MIE for integrating biological and chemical data. Evaluation of the chemical clusters activating the glucocorticoid receptor identified activity differences in chemicals within a cluster. Comparison of the estrogen receptor results with previous work showed that bioactivity data and structural alerts can be combined to improve predictions in a customizable way where bioactivity data are limited. The aryl hydrocarbon receptor (AHR) highlighted that while structural data can be used to offset limited data for new screening efforts, not all ToxCast targets have sufficient data to define robust chemical clusters. In this context, an alternative to additional receptor assays is proposed where assays for proximal key events downstream of AHR activation could be used to enhance confidence in active calls. These case studies illustrate how the AOP framework can support an iterative process whereby in vitro toxicity testing and chemical structure can be combined to improve toxicity predictions. In vitro assays can inform the development of structural alerts linking chemical structure to toxicity. Consequently, structurally related chemical groups can facilitate identification of assays that would be informative for a specific MIE. Together, these activities form a virtuous cycle where the mechanistic basis for the in vitro results and the breadth of the structural alerts continually improve over time to better predict activity of chemicals for which limited toxicity data exist.

The identification of nuclear receptors associated with hepatic steatosis to develop and extend adverse outcome pathways.

The development of adverse outcome pathways (AOPs) is becoming a key component of twenty-first century toxicology. AOPs provide a conceptual framework that links the molecular initiating event to an adverse outcome through organized toxicological knowledge, bridging the gap from chemistry to toxicological effect. As nuclear receptors (NRs) play essential roles for many physiological processes within the body, they are used regularly as drug targets for therapies to treat many diseases including diabetes, cancer and neurodegenerative diseases. Due to the heightened development of NR ligands, there is increased need for the identification of related AOPs to facilitate their risk assessment. Many NR ligands have been linked specifically to steatosis. This article reviews and summarizes the role of NR and their importance with links between NR examined to identify plausible putative AOPs. The following NRs are shown to induce hepatic steatosis upon ligand binding: aryl hydrocarbon receptor, constitutive androstane receptor, oestrogen receptor, glucocorticoid receptor, farnesoid X receptor, liver X receptor, peroxisome proliferator-activated receptor, pregnane X receptor and the retinoic acid receptor. A preliminary, putative AOP was formed for NR binding linked to hepatic steatosis as the adverse outcome.