Exploring the Influence of Experimental Design on Toxicity Outcomes in Zebrafish Embryo Tests.

Compound toxicity data obtained from independent zebrafish laboratories can vary vastly, complicating the use of zebrafish screening for regulatory decisions. Differences in the assay protocol parameters are the primary source of variability. We investigated this issue by utilizing data from the NTP DNT-DIVER database (https://doi.

Screening for Developmental Neurotoxicity at the National Toxicology Program: The Future Is Here.

The National Toxicology Program (NTP) receives requests to evaluate chemicals with potential to cause adverse health effects, including developmental neurotoxicity (DNT). Some recent requests have included classes of chemicals such as flame retardants, polycyclic aromatic compounds, perfluoroalkyl substances, and bisphenol A analogs with approximately 20-50 compounds per class, many of which include commercial mixtures. However, all the compounds within a class cannot be tested using traditional DNT animal testing guideline studies due to resource and time limitations.

Application of Benchmark Concentration (BMC) Analysis on Zebrafish Data: A New Perspective for Quantifying Toxicity in Alternative Animal Models.

Over the past decade, the zebrafish is increasingly being used as a model to screen for chemical-mediated toxicities including developmental toxicity (DT) and neurotoxicity (NT). One of the major challenges is lack of harmonization in data analysis approaches, thereby posing difficulty in comparing findings across laboratories. To address this, we sought to establish a unified data analysis strategy for both DT and NT data, by adopting the benchmark concentration (BMC) analysis.

Functional and Mechanistic Neurotoxicity Profiling Using Human iPSC-Derived Neural 3D Cultures.

Neurological disorders affect millions of people worldwide and appear to be on the rise. Whereas the reason for this increase remains unknown, environmental factors are a suspected contributor. Hence, there is an urgent need to develop more complex, biologically relevant, and predictive in vitro assays to screen larger sets of compounds with the potential for neurotoxicity.

In vitro cardiotoxicity assessment of environmental chemicals using an organotypic human induced pluripotent stem cell-derived model.

An important target area for addressing data gaps through in vitro screening is the detection of potential cardiotoxicants. Despite the fact that current conservative estimates relate at least 23% of all cardiovascular disease cases to environmental exposures, the identities of the causative agents remain largely uncharacterized. Here, we evaluate the feasibility of a combinatorial in vitro/in silico screening approach for functional and mechanistic cardiotoxicity profiling of environmental hazards using a library of 69 representative environmental chemicals and drugs.

Choosing the right path: enhancement of biologically relevant sets of genes or proteins using pathway structure.

A method is proposed that finds enriched pathways relevant to a studied condition using the measured molecular data and also the structural information of the pathway viewed as a network of nodes and edges. Tests are performed using simulated data and genomic data sets and the method is compared to two existing approaches. The analysis provided demonstrates the method proposed is very competitive with the current approaches and also provides biologically relevant results.

Characterization of the proneural gene regulatory network during mouse telencephalon development.

Background: The proneural proteins Mash1 and Ngn2 are key cell autonomous regulators of neurogenesis in the mammalian central nervous system, yet little is known about the molecular pathways regulated by these transcription factors.

Results: Here we identify the downstream effectors of proneural genes in the telencephalon using a genomic approach to analyze the transcriptome of mice that are either lacking or overexpressing proneural genes. Novel targets of Ngn2 and/or Mash1 were identified, such as members of the Notch and Wnt pathways, and proteins involved in adhesion and signal transduction.

Gene interaction network analysis suggests differences between high and low doses of acetaminophen.

Bayesian networks for quantifying linkages between genes were applied to detect differences in gene expression interaction networks between multiple doses of acetaminophen at multiple time points. Seventeen (17) genes were selected from the gene expression profiles from livers of rats orally exposed to 50, 150 and 1500 mg/kg acetaminophen (APAP) at 6, 24 and 48 h after exposure using a variety of statistical and bioinformatics approaches. The selected genes are related to three biological categories: apoptosis, oxidative stress and other.

The TAO-Gen algorithm for identifying gene interaction networks with application to SOS repair in E. coli.

One major unresolved issue in the analysis of gene expression data is the identification and quantification of gene regulatory networks. Several methods have been proposed for identifying gene regulatory networks, but these methods predominantly focus on the use of multiple pairwise comparisons to identify the network structure. In this article, we describe a method for analyzing gene expression data to determine a regulatory structure consistent with an observed set of expression profiles.

Gene interaction network suggests dioxin induces a significant linkage between aryl hydrocarbon receptor and retinoic acid receptor beta.

Gene expression arrays (gene chips) have enabled researchers to roughly quantify the level of mRNA expression for a large number of genes in a single sample. Several methods have been developed for the analysis of gene array data including clustering, outlier detection, and correlation studies. Most of these analyses are aimed at a qualitative identification of what is different between two samples and/or the relationship between two genes.

Carbon monoxide neurotoxicity: transient inhibition of avoidance response and delayed microglia reaction in the absence of neuronal death.

Carbon monoxide exposure produces neurobehavioral effects associated with the level of carboxyhemoglobin (COHb) in the blood. A threshold has been proposed of approximately 35% COHb for the manifestation of disruption in neurobehavioral tasks. The effects of CO exposure producing 30-40% carboxyhemoglobin (COHb) levels in young adult male Fischer 344 rats were examined with regard to clinical signs of toxicity, performance on a previously learned avoidance procedure, and neuronal and glia histopathology.

The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population.

Population-based estimates of environmental exposures using biomarkers can be difficult to obtain for a variety of reasons, including problems with limits of detection, undersampling of key strata, time between exposure and sampling, variation across individuals, variation within individuals, and the ability to find and interpret a given biomarker. In this article, we apply statistical likelihoods, weighted sampling, and regression methods for censored data to the analysis of biomarker data. Urinary metabolites for seven phthalates, reported by Blount et al.