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Dissertation
Modeling of human aging using a systems approach
Doctor of Philosophy (Ph.D.), Drexel University
Oct 2011
DOI:
https://doi.org/10.17918/etd-3652
Abstract
The healthy aging process involves a range of biological pathways which were investigated based on data from adult human fibroblasts of various ages. Two hybridcomputational models integrating organelle phenotypes with molecular mechanisms were developed using a fuzzy logic, rule-based approach. One was a vicious cycle model which represents uncontrolled damage accumulation in a positive feedback loop, leading to a rapid cellular degradation. The second model was an adaptive response model which showed that the stress sensors NF-kB and mTOR provide negative feedback loops causing a linear decline with age, observed in many cellular and physiological parameters. Simulations of mortality data led to discovery that a serial linear model of viability decline with a variable stochastic component would result in mortality rates to match recent data from industrialized countries. Further exploration using general computational models of biochemical networks showed the impact of the rate of linear decline, initial stochastic changes in reaction rates, and network topology on resilience and stability. The conclusion is that linear decline with age is observed and modeled at the cellular through organ system levels however mortality rates are compounded by several factors at the somatic level, leading to the serial linear decline model which combines linear decline with power law frailty models.
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Details
- Title
- Modeling of human aging using a systems approach
- Creators
- Glenn R. Booker - DU
- Contributors
- Andres Kriete (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems (1997-2026); Drexel University
- Other Identifier
- 3652; 991014632390704721