Another approach to understand life and cancer

• Speaker: Faruk Aykan, Istinye University
• Abstract: This review summarizes current biophysical approach to understand life and cancer. There is still not any comprehensive definition of life. From the perspective of biology, the characteristics of life can be categorized as cellular organizations, homeostasis, metabolism, growth, reproduction and heredity, response to stimuli and adaptation to the environment. From a physics perspective, living beings are thermodynamic systems with an organized molecular structure that can reproduce itself. According to the 2nd law of thermodynamics, every system in the universe is going to the disorder spontaneously. Maximum entropy signifies a thermodynamic equilibrium which means the death. Therefore, we can define the death more easily than the life physico-chemically. Energy must be used to produce a highly ordered organizations. The living organisms are highly ordered (complex) dynamic and thermodin-amically open systems and they are in non-equilibrium phase. In the open systems, the entropy increase is slow; living systems defy the entropy. Dissipative structures (living organisms) exchange entropy and during this exchange they gain information from the external environment. Entropy is oppositely linked to the amount of information. Information can be stored as memory and it should be coded. In the solar system, life is possible only in the habitable zone that means not too cold, not too hot, just right position in the universe. Free oxygen production to the atmosphere by first photosynthesis from cyanobacteria which was crucially important for life is approximately 2.5 billion years ago. Another powerful force for life is evolution, because it supports adaptation of living organisms to the environment. The basic units of life are cells. There is an inverse relationship between function and multiplication in a functional tissue unit formed by living cells. In the optimum healthy state there is maximum adaptability with the environment and there are periodic oscillations between an input and an output in many physiological events. Highly ordered, complex adaptive dynamic systems have dynamic multilevel and modular structures and multiscale information flow. Every higher level in the biological systems is characterized by an emergent property that is not possessed by any of the lower-level precursors. Life is a category of emergence like art composed after the integration of correct modules. On the contrary, cancer is the emergence of a disease formed by incorrect modules. Cancer is a chaotic disease and cannot arise from healthy functional tissue units. Chaos of the lower level may be associated with the entropy increase of upper level. Biologic chaos control is possible. There are some successful examples, but we are at the beginning. Chaos control in cancer should be level by level. More and different efforts are needed to conquer cancer.

Constructing Fractal Networks to Study Microvascular Physiology and Pathophysiology in Rat Skeletal Muscle

• Speaker: Yuki Bao, Biomedical Engineering, University of Western Ontario, Canada
• Abstract: At the organ and tissue level, the circulation relies on branching networks of microvessels to supply oxygen and other nutrients to all cells in support of metabolism, as well as remove metabolic waste, and derangement of the structure or function of these networks is directly linked to tissue dysfunction. Over a wide range of diameters, these networks are binary trees and display fractal geometric and hemodynamic properties. Although experiment-based reconstruction of these vascular structures has improved recently, there remains a strong motivation for developing theoretical models that match measured statistical properties of microvascular networks under healthy conditions and with elevated disease risk (e.g., diabetes) and can be used for computational studies of flow, transport, and regulation. These efforts have the ultimate goal of connecting specific vascular defects to observed modes of tissue dysfunction. In the present study, two-dimensional arteriolar networks in rat skeletal muscle are constructed based on the constrained constructive optimization (CCO) algorithm using published geometric and hemodynamic data obtained via intravital video-microscopy. Results obtained assuming blood is a single-phase Newtonian fluid demonstrate how network geometry, fractal dimension, and flow properties depend on the Murray law exponent (g). In addition, using a two-phase (plasma and red blood cells) flow model, we show the importance of microvascular blood rheology in determining network properties. Future work will focus on constructing three-dimensional networks, tissues other than skeletal muscle, and determining the effects of both domain shape and g. Joint work with Amelia C. Frisbee, Physics, University of Guelph, Canada, Jefferson C. Frisbee, Medical Biophysics, University of Western Ontario, Canada, and Daniel Goldman, Medical Biophysics and Biomedical Engineering, University of Western Ontario, Canada.