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[01952] Mathematical models of morphogenesis and morphological deformation in living organisms

  • Session Time & Room : 4E (Aug.24, 17:40-19:20) @A512
  • Type : Proposal of Minisymposium
  • Abstract : The objective of our proposal is to present recent development of mathematical theory of morphogenesis and morphological deformation in living organisms. The topics are dynamics of endothelial cells is angiogenesis, i.e., the formation of networks of blood vessels, morphogenetic processes of organs, homeostasis of precursor cells in the brain and the genesis of a glioma and sol-gel transition of teleost muscular proteins. In each talk, both recent experimental results and the mathematical models, which can be used for the analysis of them, are presented.
  • Organizer(s) : Tetsuji Tokihiro
  • Classification : 92-10, 92C15, 92C37
  • Minisymposium Program :
    • 01952 (1/1) : 4E @A512 [Chair: Tetsuji Tokihiro]
      • [02830] A kinetic model for sol-gel transition of teleost muscular proteins
        • Format : Talk at Waseda University
        • Author(s) :
          • Yuri Kominami (The University of Tokyo)
        • Abstract : Various enzymatic reactions have a critical role in control of cellular function in living tissue. The enzymes can be activated in the tissue after organismal death and cause post-mortem changes. The enzymes delivered from animal tissue are also activated during food processing and affect product attributes. In this talk, the enzymatic reactions during sol-gel transition of teleost muscular proteins will be addressed and a kinetic model will be discussed.
      • [03680] Mathematical model for dynamics of endothelial cells in sprouting angiogenesis
        • Format : Talk at Waseda University
        • Author(s) :
          • Tatsuya Hayashi (Yamato University)
        • Abstract : Angiogenesis is a morphogenic process that involves the emergence of new blood vessels from an existing vascular network. We propose a mathematical model based on the characteristic movements of endothelial cells in angiogenesis. In this presentation, we show that our model is able to reproduce the coordinated linear and rotational movements observed in a two-cell state, as well as angiogenic morphogenesis and the effects of cell adhesion molecules in a multicellular simulation.
      • [04407] Measurement and mathematical analysis of organ morphogenetic processes
        • Format : Talk at Waseda University
        • Author(s) :
          • Yoshihiro Morishita (RIKEN Center for Biosystems Dynamics Research)
        • Abstract : The physical processes that govern the formation of almost all organs, namely, collective cell motion and tissue-level deformation, remain largely unknown. However, recent advances in microscopy have enabled the measurement and quantification of these dynamics. In this study, we investigate the early development of the forebrain and heart and present our findings on the morphogenetic rules that underlie their formation, based on our analysis of the measured morphogenetic dynamics.
      • [03395] A mathematical model for the evolution of low-grade gliomas before and after radiotherapy
        • Format : Talk at Waseda University
        • Author(s) :
          • Mathilde Badoual (Paris Cité University)
          • Leo Adenis (CNRS)
          • Stephane Plaszczynski (CNRS)
          • Jean-Eric Campagne (CNRS)
          • Basile Grammaticos (CNRS)
          • Johan Pallud (Sainte-Anne Hospital)
        • Abstract : Diffuse low-grade gliomas are slowly growing tumors that mainly affect adults around 40 years old and are incurable. After tens of years, they transform inexorably into more aggressive forms, jeopardizing the patient’s life. Mathematical modeling could help clinicians to have a better understanding of the underlying biological process involved in the evolution of these tumors and their response to treatments. We present here a model of evolution of these tumors, based on a PDE that describes the evolution of the cell density and the effect of radiotherapy. This model is used to fit clinical data (MRI scans), and to predict the regrowth time after radiotherapy.