Researchers from Drexel University and Children’s Hospital Boston are using “fuzzy logic” algorithms to better understand the complex mechanisms involved in cell aging. Fuzzy logic refers to algorithms that can handle imprecise input unlike the typical 0 or 1 digital nature of precise algorithms.
The study, which appears in the June issue of PLOS Computational Biology, relates progressive damage and dysfunction in aging, dubbed a vicious cycle, to inflammatory and metabolic stress response pathways. Interestingly, the activation of these pathways remodels the inner functioning of the cell in a protective and adaptive manner and thus extends lifespan.
This is the first time that scientists have applied fuzzy logic modeling to the field of aging. "Since cellular biodynamics in aging may be considered a complex control system, a fuzzy logic approach seems to be particularly suitable," said Dr. William Bosl, co-author of this study. Dr. Bosl, a staff scientist in the Informatics Program at Children’s Hospital Boston, developed a fuzzy logic modeling platform called Bionet together with a cell biologist, Dr. Rong Li of the Stowers Institute for Medical Research in Kansas City, to study the complex interactions that occur in a cell’s machinery using the kind of qualitative information gained from laboratory experiments.
Image: Several key processes related to biological aging can be described by positive feedback-loop motifs, as shown by this “vicious cycle” model. Metabolic fluxes (marked by blue lines) are initially in homeostasis. Reactive oxygen species (ROS) damage intracellular proteins including mitochondrial structures (red lines). This leads to impairment of ATP generation and biosynthesis, further increasing ROS levels. A portion of oxidized proteins is removed by autophagy, which constitutes a sink in this model.
Press release: Fuzzy Logic Predicts Cell Aging…
Abstract in PLoS Computational Biology: Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses
