The Society of Toxicology (SOT) Component Groups (Regional Chapters, Special Interest Groups, and Specialty Sections) host many webinars throughout the year. Webinars are an effective distance-learning method intended to impart scientific knowledge to members of their group as well as the SOT membership at large. These webinars are just one of the many benefits of SOT membership.
Upcoming webinars for December 2017 are listed below.
Occupational and Public Health Specialty Section (OPHSS)
Topic: Evaluation of the Experimental Basis for Assessment Factors to Protect Individuals with Asthma
Date and Time: Wednesday, December 6, 2017, 12:00 pm–1:00 pm Eastern Time
Asthmatic individuals constitute a large subpopulation that is often considered particularly susceptible to the deleterious effects of airborne chemicals. However, information on the effects of most of these chemicals in asthmatics is lacking. Join the OPHSS and special guest Dr. Mattias Öberg for a presentation on whether a general difference in airway response during short-term exposure between healthy and asthmatic individuals can be identified, and what inter-individual assessment factor (AF) provides sufficient protection for asthmatics. Dr. Öberg will describe the comparison of findings between healthy and asthmatic subjects for several extensively tested air contaminants and the results from benchmark dose concentration (BMC) analysis, as well as the implications for selecting appropriate AFs for the derivation of health-based guideline values.
Dr. Öberg has more than 10 years of experience in research and education in toxicology and environmental medicine. His research has focused on risk assessment and science-to-policy at the Swedish Center for Toxicological Sciences and the Institute of Environmental Medicine (Swetox). Dr. Öberg has led several multi-disciplinary risk assessment-related projects and is the Chair of the National Committee of European Registered Toxicologists (ERT). His main research areas are health risk assessment of chemicals, hormone disorders, environmental factors and health, disaster oxology, occupational ecotoxicology, and alternatives to animal experiments.
Registration is required.
Risk Assessment Specialty Section (RASS) and Biological Modeling Specialty Section (BMSS)
Topic and Presenter: A Liver-Centric Multiscale Modeling Framework for Xenobiotics, James Sluka, PhD, Biocomplexity Institute, Indiana University
Date and Time: Wednesday, December 13, 2017, 3:00 pm–4:00 pm Eastern Time
Abstract: We present a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We will focus on a computational model that characterize whole body uptake and clearance, liver transport, and Phase I and Phase II metabolism. The model incorporates sub-models at three scales: (1) Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, (2) cell and blood flow modeling at the tissue/organ level and (3) metabolism, both Phase I and Phase II, at the sub-cellular level. We used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us not only to run the individual sub-models separately but also to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML allows us to include biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation in the sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose multi-scale pharmacokinetic model for xenobiotics.
Registration for RASS webinars is not required.
Association of Scientists of Indian Origin Special Interest Group (ASIO)
Topic and Presenter: Regulatory Network Models of Chemical-Induced Gene Perturbation, Sudin Bhattacharya, Assistant Professor, Biomedical Engineering, Pharmacology and Toxicology, Michigan State University
Date and Time: Friday, December 15, 2017, 12:00 pm – 1:00 pm Eastern Time
Tissue-specific network models of chemical-induced gene perturbation can improve our mechanistic understanding of the intracellular events leading to adverse health effects resulting from chemical exposure. The aryl hydrocarbon receptor (AHR) is a ligand-inducible transcription factor (TF) that activates a battery of genes and produces a variety of species-specific adverse effects in response to the potent and persistent environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Here we assemble a global map of the AHR gene regulatory network in the mouse liver from a combination of previously published gene expression and genome-wide TF binding data sets. Using various computational methods, we show that genes co-regulated by common upstream TFs in the AHR network show a pattern of co-expression. Specifically, directly-bound, indirectly-bound, and non-genomic AHR target genes exhibit distinct patterns of gene expression, with the directly bound targets generally associated with highest median expression. Further, among the directly bound AHR target genes, the expression level tends to increase with the number of AHR binding sites in the proximal promoter regions. Finally, we show that co-regulated genes in the AHR network activate distinct groups of downstream biological processes, with the AHR-bound target genes enriched for metabolic processes and the AHR-unbound target genes primarily activating immune responses in the mouse liver. In summary, this work presents one approach to the reconstruction and analysis of the transcriptional regulatory cascades underlying adverse cellular response using bioinformatic and statistical tools.
Registration is required.