Symbolic logic model of cellular adaptation

Human disease can be viewed as a set of quantitative alterations in existing metabolic pathways. We had previously constructed a symbolic logic model of quantitative organelle pathology, based upon the general pathology of growth disorders. The symbolic components of this model are cellular organelle compartments, measurements (number, surface, volume), and quantifiers (low, normal, high). These components allow one to deduce descriptive growth states, reaction patterns of cellular injury, and interorganelle homology patterns. Homologies have proved to be very useful in helping to elucidate difficult relationships in general pathology. In this report, we attempt to show that this usefulness also holds for quantitative organelle pathology. The types of cellular homology occurring in the nuclear-ergastoplasmic-mitochondrial-peroxisomal system reveal the evidence of existing interactions that can be determined rapidly and consistently by means of symbolic logic analysis. These cellular homology types allow us to draw conclusions regarding the capacity of the cell to adapt itself and the extent of cellular injury.