1. Evolution of interdependence. Neutral constructive evolution ties genes/cells/tissues/organisms together. A random walk in the space of networks leads to the most likely arrangement: random networks.
  2. Statistics of catastrophes in interdependent systems: Gompertz law, dynamics that are qualitatively independent of network structure and model details.
  3. Aging in synthetic tissues. Cells die at a slower rate when allowed to exchange goodies. Intercellular interactions are more important than chronological age or damage agents. Failures propagates from outwards in. Edges and boundaries are more susceptible to failure.
  4. Failure as a microscope: Failure times can be used to infer the structure of interdependence networks.

Many simple organisms such as ferns, hydra or jellyfish do not age. Their mortality rates remain approximately constant at all ages. In contrast, complex organisms typically have a probability of death m(t) that increases with age, t. Furthermore, the functional form of m(t) for many different organisms show a remarkable degree of similarity. The difference between simple and complex organisms, and the universality of aging patterns among complex organisms strongly suggest that aging is an emergent phenomenon that depends not on the individual properties of biological building blocks,but rather, on the interactions between them. Indeed, we die not because we slowly run out of live cells, but because of systemic failures that manifest in complex organs. In this talk I will present a quantitative theory of aging based on evolutionary and mechanical arguments, and show how aging appears as an emergent phenomenon as one moves across the scale of complexity, from large molecules and cells, to tissues and organs. I will particularly focus on aging in synthetic tissues, since this is the simplest structure that admits controlled experimental observation of emergent systemic damage. I will end my talk by showing how failure can be used as a "microscope". Specifically, how failure times can inform us about the structure of the interdependence network.