Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses

Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-κB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype

Case-Based Knowledge and Ethics Education: Improving Learning and Transfer Through Emotionally Rich Cases

Case-based instruction is a stable feature of ethics education, however, little is known about the attributes of the cases that make them effective. Emotions are an inherent part of ethical decision-making and one source of information actively stored in case-based knowledge, making them an attribute of cases that likely facilitates case-based learning. Emotions also make cases more realistic, an essential component for effective case-based instruction. The purpose of this study was to investigate the influence of emotional case content, and complementary socio-relational case content, on case-based knowledge acquisition and transfer on future ethical decision-making tasks. Study findings suggest that emotional case content stimulates retention of cases and facilitates transfer of ethical decision-making principles demonstrated in cases