Master Regulators of Causal Networks in Intestinal- and Diffuse-Type Gastric Cancer and the Relation to the RNA Virus Infection Pathway.

Causal networks are important for understanding disease signaling alterations. To reveal the network pathways affected in the epithelial-mesenchymal transition (EMT) and cancer stem cells (CSCs), which are related to the poor prognosis of cancer, the molecular networks and gene expression in diffuse- and intestinal-type gastric cancer (GC) were analyzed. The network pathways in GC were analyzed using Ingenuity Pathway Analysis (IPA).

Male fathead minnow transcriptomes and associated chemical analytes in the Milwaukee estuary system.

Contaminants of Emerging Concern (CECs) can be measured in waters across the United States, including the tributaries of the Great Lakes. The extent to which these contaminants affect gene expression in aquatic wildlife is unclear. This dataset presents the full hepatic transcriptomes of laboratory-reared fathead minnows (Pimephales promelas) caged at multiple sites within the Milwaukee Estuary Area of Concern and control sites.

Current ecotoxicity testing needs among selected U.S. federal agencies.

U.S. regulatory and research agencies use ecotoxicity test data to assess the hazards associated with substances that may be released into the environment, including but not limited to industrial chemicals, pharmaceuticals, pesticides, food additives, and color additives.

Developmental, Behavioral and Transcriptomic Changes in Zebrafish Embryos after Smoke Dye Exposure.

(1) Background: Disperse Blue 14, Disperse Red 9, Solvent Red 169 and Solvent Yellow 33 have been used to color smoke; however, they have not been comprehensively assessed for their potential health hazards. (2) Methods: To assess the effects of these dyes, zebrafish embryos were exposed from 6 to 120 h post fertilization (hpf) to 10-55 µM Disperse Red 9, 1-50 µM Solvent Red 169, 7.5-13.

Integration of Adverse Outcome Pathways, Causal Networks and 'Omics to Support Chemical Hazard Assessment.

Several approaches have been used in an attempt to simplify and codify the events that lead to adverse effects of chemicals including systems biology, 'omics, assays and frameworks such as the Adverse Outcome Pathway (AOP). However, these approaches are generally not integrated despite their complementary nature. Here we propose to integrate toxicogenomics data, systems biology information and AOPs using causal biological networks to define Key Events in AOPs.

Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology.

How to translate insights gained from studies in one organismal species for what is most likely to be germane in another species, such as from mice to humans, is a ubiquitous challenge in basic biology as well as biomedicine. This is an especially difficult problem when there are few molecular features that are obviously important in both species for a given phenotype of interest. Neuropathologies are a prominent realm of this complication.

Morphological and Behavioral Effects in Zebrafish Embryos after Exposure to Smoke Dyes.

Solvent Violet 47 (SV47) and Disperse Blue 14 (DB14) are two anthraquinone dyes that were previously used in different formulations for the production of violet-colored smoke. Both dyes have shown potential for toxicity; however, there is no comprehensive understanding of their effects. Zebrafish embryos were exposed to SV47 or DB14 from 6 to 120 h post fertilization (hpf) to assess the dyes' potential adverse effects on developing embryos.

Perfluorooctanesulfonic Acid-Induced Toxicity on Zebrafish Embryos in the Presence or Absence of the Chorion.

Perfluorooctanesulfonic acid (PFOS) is a perfluorinated compound used in many industrial and consumer products. It has been linked to a broad range of adverse effects in several species, including zebrafish (Danio rerio). The zebrafish embryo is a widely used vertebrate model to elucidate potential adverse effects of chemicals because it is amenable to medium and high throughput.

Stochastically modeling multiscale stationary biological processes.

Large scale biological responses are inherently uncertain, in part as a consequence of noisy systems that do not respond deterministically to perturbations and measurement errors inherent to technological limitations. As a result, they are computationally difficult to model and current approaches are notoriously slow and computationally intensive (multiscale stochastic models), fail to capture the effects of noise across a system (chemical kinetic models), or fail to provide sufficient biological fidelity because of broad simplifying assumptions (stochastic differential equations). We use a new approach to modeling multiscale stationary biological processes that embraces the noise found in experimental data to provide estimates of the parameter uncertainties and the potential mis-specification of models.

AOPERA: A proposed methodology and inventory of effective tools to link chemicals to adverse outcome pathways.

New approaches, like the Adverse Outcome Pathway (AOP) framework, have been developed to describe how chemicals cause toxicity by linking in vitro assays to adverse health outcomes. However, approaches, tools and resources for development of AOPs have not been well described. Here we review information resources for AOP development and define a streamlined process for linking a chemical to an existing AOP.

Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment.

Keanu: a novel visualization tool to explore biodiversity in metagenomes.

Background: One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data.

A modular approach for assembly of quantitative adverse outcome pathways.

The adverse outcome pathway (AOP) framework is a conceptual construct that mechanistically links molecular initiating events to adverse biological outcomes through a series of causal key events (KEs) that represent the perturbation of the biological system. Quantitative, predictive AOPs are necessary for screening emerging contaminants and potential substitutes to inform their prioritization for testing. In practice, they are not widely used because they can be costly to develop and validate.

Multiple environmental stressors induce complex transcriptomic responses indicative of phenotypic outcomes in Western fence lizard.

Background: The health and resilience of species in natural environments is increasingly challenged by complex anthropogenic stressor combinations including climate change, habitat encroachment, and chemical contamination. To better understand impacts of these stressors we examined the individual- and combined-stressor impacts of malaria infection, food limitation, and 2,4,6-trinitrotoluene (TNT) exposures on gene expression in livers of Western fence lizards (WFL, Sceloporus occidentalis) using custom WFL transcriptome-based microarrays.

Results: Computational analysis including annotation enrichment and correlation analysis identified putative functional mechanisms linking transcript expression and toxicological phenotypes.

Chemical hazard prediction and hypothesis testing using quantitative adverse outcome pathways.

Current efforts in chemical safety are focused on utilizing human in vitro or alternative animal data in biological pathway context. However, it remains unclear how biological pathways, and toxicology data developed in that context, can be used to quantitatively facilitate decision-making.  The objective of this work is to determine if hypothesis testing using Adverse Outcome Pathways (AOPs) can provide quantitative chemical hazard predictions.

Production of tunable nanomaterials using hierarchically assembled bacteriophages.

Large-scale fabrication of precisely defined nanostructures with tunable functions is critical to the exploitation of nanoscience and nanotechnology for production of electronic devices, energy generators, biosensors, and bionanomedicines. Although self-assembly processes have been developed to exploit biological molecules for functional materials, the resulting nanostructures and functions are still very limited, and scalable synthesis is far from being realized. Recently, we have established a bacteriophage-based biomimetic process, called 'self-templating assembly'.

Rapid effects of the aromatase inhibitor fadrozole on steroid production and gene expression in the ovary of female fathead minnows (Pimephales promelas).

Cytochrome P450 aromatase catalyzes conversion of C19 androgens to C18 estrogens and is critical for normal reproduction in female vertebrates. Fadrozole is a model aromatase inhibitor that has been shown to suppress estrogen production in the ovaries of fish. However, little is known about the early impacts of aromatase inhibition on steroid production and gene expression in fish.

Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges Using Chemical:Gene Interactions in Caged Fish.

We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different wastewater treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream reference site. The biological impact of 51 chemicals detected in the surface water of 133 targeted chemicals was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses, known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the covariance of ovary gene expression with surface water chemistry.

Advancing the adverse outcome pathway framework-An international horizon scanning approach.

Our ability to conduct whole-organism toxicity tests to understand chemical safety has been outpaced by the synthesis of new chemicals for a wide variety of commercial applications. As a result, scientists and risk assessors are turning to mechanistically based studies to increase efficiencies in chemical risk assessment and making greater use of in vitro and in silico methods to evaluate potential environmental and human health hazards. In this context, the adverse outcome pathway (AOP) framework has gained traction in regulatory science because it offers an efficient and effective means for capturing available knowledge describing the linkage between mechanistic data and the apical toxicity end points required for regulatory assessments.

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment.

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework.

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.

A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose-response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications.

Physiological fidelity or model parsimony? The relative performance of reverse-toxicokinetic modeling approaches.

Background: Physiologically-based toxicokinetic (PBTK) models are often developed to facilitate in vitro to in vivo extrapolation (IVIVE) using a top-down, compartmental approach, favoring architectural simplicity over physiological fidelity despite the lack of general guidelines relating model design to dynamical predictions. Here we explore the impact of design choice (high vs. low fidelity) on chemical distribution throughout an animal's organ system.

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA.

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St.