Inflammatory bowel diseases (IBDs) comprise primarily two disease manifestations, ulcerative colitis (UC) and Crohn’s disease (CD), each with distinctive clinical and pathological features. Environmental and clinical factors strongly affect the development and clinical outcomes of IBDs. Among environmental factors, cigarette smoke (CS) is considered the most important risk factor for CD, while it attenuates the disease course of UC. Various animal models have been used to assess the impact of CS on intestinal pathophysiology. This chapter examines the suitability of animal inhalation/smoke exposure models for assessing the contrary effects of CS on UC and CD. It presents an updated literature review of IBD mouse models and a description of possible mechanisms relevant to relationships between IBD and smoking. In addition, it summarises various technical inhalation approaches, in the context of mouse disease models of IBD.
Part of the book: Experimental Animal Models of Human Diseases
We describe how the genome-wide transcriptional profiling can be used in network-based systems toxicology, an approach leveraging biological networks for assessing the health risks of exposure to chemical compounds. Driven by the technological advances changing the ways in which data are generated, systems toxicology has allowed traditional toxicity endpoints to be enhanced with far deeper levels of analysis. In combination, new experimental and computational methods have offered the potential for more effective, efficient, and reliable toxicological testing strategies. We illustrate these advances by the “network perturbation amplitude” methodology that quantifies the effects of exposure treatments on biological mechanisms represented by causal networks. We also describe recent developments in the assembly of high-quality causal biological networks using crowdsourcing and text-mining approaches. We further show how network-based approaches can be integrated into the multiscale modeling framework of response to toxicological exposure. Finally, we combine biological knowledge assembly and multiscale modeling to report on the promising developments of the “quantitative adverse outcome pathway” concept, which spans multiple levels of biological organization, from molecules to population, and has direct relevance in the context of the “Toxicity Testing in the 21st century” vision of the US National Research Council.
Part of the book: Bioinformatics in the Era of Post Genomics and Big Data