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COMPLEX TIME: Adaptation, Aging, & Arrow of Time

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Difference between revisions of "Dynamic Multi-System Resilience in Human Aging/Emergence of Aging in Natural and Synthetic Multicellular Structures"

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# Ravi, Chhanda: How can theorists make themselves useful for NIH? How to communicate "theoretically driven" projects to NIH?
 
# Ravi, Chhanda: How can theorists make themselves useful for NIH? How to communicate "theoretically driven" projects to NIH?
 
# Chhanda: Resilience builds up over time. Effect of early life history on aging. Comparative biology approaches e.g. naked mole rat  
 
# Chhanda: Resilience builds up over time. Effect of early life history on aging. Comparative biology approaches e.g. naked mole rat  
# Ravi, Chhanda: Very interesting plasticity effect: Physiological state does not come back exactly to the same point after perturbation. A theoretical description of physiological elasticity vs. plasticity.
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# Ravi, Chhanda: Very interesting plasticity effect: Physiological state does not come back exactly to the same point after perturbation. A theoretical description of physiological elasticity vs. plasticity
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# Ingrid: Idea on multiple tipping points that are coupled. I recommend checking out Kramer's escape problem. Chhanda excellent question: Are young ecosystems more resilient, just like young people. Alfons had an excellent question: what can you say about the dynamics by knowing only qualitative causal relationships. An idea: if there are multiple models describing the same subsystems and their interactions, can these be combined/reconciled to get a result more accurate than all models individually?
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# Peter: Potentially useful model but one should be careful about drawing conclusions from single runs. e.g. Flipping coins would also yield similar ups and downs if one looked at  individual runs. It would be good to check if the model gives Gompertz (exponential) mortality curves or Weibull. I would also have critical questions about sensitivity to parameters and system size, i.e. if the damage rate was close to repair rate I suspect that the system would never collapse (given large system size).
 
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Revision as of 18:17, November 13, 2018

November 12, 2018
10:00 am - 10:40 am

Presenter

Dervis Can Vural (Univ. Notre Dame)

Description
  1. Evolution of interdependence
  2. Statistics of catastrophes in interdependent systems
  3. Aging in synthetic tissues. Intercellular interactions are more important than chronological age or damage agents.
  4. Failure as a microscope: Failure times can be used to infer the structure of interdependence networks
Abstract

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.

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