Trade-offs between acquired and innate immune defenses in humans

Immune defenses provide resistance against infectious disease that is critical to survival. But immune defenses are costly, and limited resources allocated to immunity are not available for other physiological or developmental processes. We propose a framework for explaining variation in patterns of investment in two important subsystems of anti-pathogen defense: innate (non-specific) and acquired (specific) immunity. The developmental costs of acquired immunity are high, but the costs of maintenance and activation are relatively low. Innate immunity imposes lower upfront developmental costs, but higher operating costs. Innate defenses are mobilized quickly and are effective against novel pathogens. Acquired responses are less effective against novel exposures, but more effective against secondary exposures due to immunological memory. Based on their distinct profiles of costs and effectiveness, we propose that the balance of investment in innate versus acquired immunity is variable, and that this balance is optimized in response to local ecological conditions early in development. Nutritional abundance, high pathogen exposure and low signals of extrinsic mortality risk during sensitive periods of immune development should all favor relatively higher levels of investment in acquired immunity. Undernutrition, low pathogen exposure, and high mortality risk should favor innate immune defenses. The hypothesis provides a framework for organizing prior empirical research on the impact of developmental environments on innate and acquired immunity, and suggests promising directions for future research in human ecological immunology.     

Application of the adverse outcome pathway framework to genotoxic modes of action

In May 2017, the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee hosted a workshop to discuss whether mode of action (MOA) investigation is enhanced through the application of the adverse outcome pathway (AOP) framework. As AOPs are a relatively new approach in genetic toxicology, this report describes how AOPs could be harnessed to advance MOA analysis of genotoxicity pathways using five example case studies. Each of these genetic toxicology AOPs proposed for further development includes the relevant molecular initiating events, key events, and adverse outcomes (AOs), identification and/or further development of the appropriate assays to link an agent to these events, and discussion regarding the biological plausibility of the proposed AOP. A key difference between these proposed genetic toxicology AOPs versus traditional AOPs is that the AO is a genetic toxicology endpoint of potential significance in risk characterization, in contrast to an adverse state of an organism or a population. The first two detailed case studies describe provisional AOPs for aurora kinase inhibition and tubulin binding, leading to the common AO of aneuploidy. The remaining three case studies highlight provisional AOPs that lead to chromosome breakage or mutation via indirect DNA interaction (inhibition of topoisomerase II, production of cellular reactive oxygen species, and inhibition of DNA synthesis). These case studies serve as starting points for genotoxicity AOPs that could ultimately be published and utilized by the broader toxicology community and illustrate the practical considerations and evidence required to formalize such AOPs so that they may be applied to genetic toxicity evaluation schemes. Environ. Mol. Mutagen. 61:114–134, 2020. © 2019 Wiley Periodicals, Inc.     

Assessment of toxicity using dehydrogenases activity and mathematical modeling

Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (T_MDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and T_MDTE are more appropriate than EC₅₀ and IC₅₀ for toxicity assessments, except for long exposure times.