Based on the results of a Horizon Scanning exercise sponsored by the Society of Environmental Toxicology and Chemistry that focused on advancing the adverse outcome pathway (AOP) framework, the development of guidance related to AOP network development was identified as a critical need. This not only included questions focusing directly on AOP networks, but also on related topics such as mixture toxicity assessment and the implementation of feedback loops within the AOP framework. A set of two articles has been developed to begin exploring these concepts. In the present article (part I), we consider the derivation of AOP networks in the context of how it differs from the development of individual AOPs. We then propose the use of filters and layers to tailor AOP networks to suit the needs of a given research question or application. We briefly introduce a number of analytical approaches that may be used to characterize the structure of AOP networks. These analytical concepts are further described in a dedicated, complementary article (part II). Finally, we present a number of case studies that illustrate concepts underlying the development, analysis, and application of AOP networks. The concepts described in the present article and in its companion article (which focuses on AOP network analytics) are intended to serve as a starting point for further development of the AOP network concept, and also to catalyze AOP network development and application by the different stakeholder communities. Environ Toxicol Chem 2018;37:1723-1733. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734-1748. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

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This study investigated the short-term memory of dynamic changes in acute pain using psychophysical methods. Pain intensity or unpleasantness induced by painful contact-heat stimuli of 8, 9, or 10s was rated continuously during the stimulus or after a 14-s delay using an electronic visual analog scale in 10 healthy volunteers. Because the continuous visual analog scale time courses contained large amounts of redundant information, a principal component analysis was applied to characterize the main features inherent to both the concurrent rating and retrospective evaluations. Three components explained about 90% of the total variance across all trials and subjects, with the first component reflecting the global perceptual profile, and the second and third components explaining finer perceptual aspects (eg, changes in slope at onset and offset and shifts in peak latency). We postulate that these 3 principal components may provide some information about the structure of the mental representations of what one perceives, stores, and remembers during the course of few seconds. Analysis performed on the components confirmed significant memory distortions and revealed that the discriminative information about pain dimensions in concurrent ratings was partly or completely lost in retrospective ratings. Importantly, our results highlight individual differences affecting these memory processes. These results provide further evidence of the important transformations underlying the processing of pain in explicit memory and raise fundamental questions about the conversion of dynamic nociceptive signals into a mental representation of pain in perception and memory.

Background: Lead (Pb) exposure has been associated with a host of pathological conditions in humans. In rodents Pb exposure has been shown to alter the hypothalamic–pituitary–adrenal (HPA) axis function.Objective: We investigated the effects of lead on responses of the HPA axis to a psychosocial laboratory stressor administered to Pb-exposed workers.Methods: Seventy male participants completed the Trier Social Stress Test (TSST). Serum cortisol (CORT) and plasma adrenocorticotropic hormone (ACTH) were assessed in response to and during recovery from the stressor. We measured Pb in blood, a biomarker of recent exposure, and in tibia bone by X-ray fluorescence (XRF), a biomarker of chronic exposure.Results: The TSST induced statistically significant increases in ACTH and CORT in the participants. At baseline, ACTH was not significantly higher (p = 0.052) in participants with higher blood Pb concentration, but CORT was significantly lower in these participants (p = 0.016). Adjusted linear regression models indicated a positive association between blood and bone Pb and the increase in ACTH in response to stress. However, Pb was not strongly associated with changes in CORT in response to stress. Pb was also associated with the ACTH:CORT ratio at baseline and throughout the course of the protocol, suggesting an adrenal hyporesponsiveness in participants with higher Pb concentrations.Conclusion: The altered HPA-axis stress response observed in participants exposed to higher levels of Pb further supports the idea that lead may contribute to a host of biological dysfunctions beyond the classical neurotoxic effects.

Measured REE did not significantly differ from predicted resting energy requirements. This indicates that REE for the parenterally fed pediatric patients with CD can be accurately predicted using the FAO/WHO/UNU equations.

Epigenetic modifications, such as DNA methylation, play key roles in transcriptional regulation of gene expression. More recently, global DNA methylation levels have been documented to be altered in several diseases, including cancer, and as the result of exposure to environmental toxicants. Based on the potential use of global DNA methylation status as a biomarker of disease status and exposure to environmental toxicants, we sought to develop a rapid, sensitive, and precise analytical method for the quantitative measurement of global DNA methylation status using ultra performance liquid chromatography with detection by ion trap tandem mass spectrometry. Using a fused-core silica column, 2′-deoxyguanosine (2dG) and 5-methyl-2′-deoxycytidine (5mdC) were resolved in less than 1 minute, with detection limits of 0.54 and 1.47 fmol for 5mdC and 2dG respectively. The accuracy of detection was 95% or above and the day-today coefficient of variations was found to be 3.8%. The method was validated by quantification of global DNA methylation status following treatment of cells with the DNA methyltransferase inhibitor 5-aza-2′deoxycytidine, which reduced DNA methylation from 3.1% in control cells to 1.1% in treated cells. The sensitivity and high throughput of this method rend it suitable for large scale analysis of epidemiological or clinical DNA samples.