Abstract
As explained in Chap. 2, mechanistic causal models of how effects propagate through a system typically require more detailed information to build and validate than other forms of causal analysis, including predictive and attributive causal modeling. Substantial applied and computational mathematical research, modeling, and algorithm development is sometimes needed to describe with useful accuracy how a system evolves over time. On the other hand, mathematical analysis can also reveal robust qualitative properties of a system’s dynamic response to inputs. For example, many complex feedback control networks exhibit the qualitative property of bistability, in which a sufficiently long and intense stimulus or exogenous input causes the system to shift from its normal state to a new one with different properties that then becomes the new stable state of the system. Such stimulus-driven switches in behaviors occur frequently in biological regulatory networks and in other (e.g., socioeconomic) systems with positive feedback loops. This chapter considers the implications of recent advances in molecular biological understanding of the causal mechanisms of inflammation-mediated diseases for quantitative dose-response modeling. It focuses on the dynamic behavior of the NLRP3 (nucleotide-binding oligomerization domain-, leucine-rich repeat- and pyrin domain-containing) inflammasome, a signaling complex that is activated in response to sufficiently large exposures to potentially injurious agents including Staphylococcus aureus or Listeria monocytogenes bacteria, influenza and other viruses, radiation, asbestos fibers, and respirable crystalline silica (RCS) and that has been implicated in a host of inflammation-mediated diseases including asbestosis, fibrosis, mesothelioma, lung cancer, heart disease, gout, arthritis, and diabetes. Given this large and diverse array of agents and diseases for which NRLP3 provides a key to pathological responses, we will focus on how mineral particles and fibers such as asbestoscan activate the NRLP3 inflamasome and on the consequences for the shape of the dose-response relationship for inflammation-mediated responses to exposure.
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Cox Jr., L.A., Popken, D.A., Sun, R.X. (2018). Mechanistic Causality: Biological Mechanisms of Dose-Response Thresholds for Inflammation-Mediated Diseases Caused by Asbestos Fibers and Mineral Particles. In: Causal Analytics for Applied Risk Analysis. International Series in Operations Research & Management Science, vol 270. Springer, Cham. https://doi.org/10.1007/978-3-319-78242-3_9
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