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

Differentiation between malignant melanomas and benign melanocytic nevi by computerized DNA cytometry of imprint specimens

Recently image analysis (IA) and DNA-cytophotometry (CP) have proved to be useful for the differentiation between benign and malignant melanocytic lesions on paraffin sections. Since, on sections, these procedures are very time-consuming, we tested in the present study whether IA of imprint specimens, which can be evaluated in less than 30 minutes, might also be sufficient. In 39 malignant melanomas (MM), 18 melanocytic nevi (MN), and 6 dysplastic nevi (DN), 12 different morphometric and DNA cytometric features were determined in 100 randomly selected nuclei. In univariate analysis, 5 features were found to be significantly different between the benign and malignant groups (p < 0.0001): mean value (MAREA) and standard deviation (SAREA) of nuclear area and the 80th, 90th, and 95th percentiles of DNA distribution. Using SAREA, the best univariate feature, 82.5% of the cases could be correctly separated. In multivariate analysis with a combination of three features--standard deviation of nuclear area (SAREA), mean DNA value (MDNA), and 95th percentile of DNA distribution (PERC95)--a correct diagnosis was achieved in 89.5% of the cases. Results obtained in the cases of DN indicated an increased proliferation, but did not allow the separation of DN from MM and MN. Since our technique allows a rapid analysis without loss of tissue, which might be important for histological analysis, and the classification rates are equal or still higher than reported in studies on sections, imprints of melanocytic lesions seem to be most appropriate for the calculation of DNA cytometric features as helpful diagnostic criteria in equivocal melanocytic lesions