Exploiting the combination of latest microfabrication technologies and single cell measurement technologies, we can measure the interactions of single cells, and cell networks from “algebraic” and “geometric” perspectives under the full control of their environments and interactions. However, the experimental constructive single cell-based approach still remains the limitations regarding the quality and condition control of those cells. To overcome these limitations, mathematical modeling is one of the most powerful complementary approaches. In this review, we first explain our on-chip experimental methods for constructive approach, and we introduce the results of the “community effect” of beating cardiomyocyte networks as an example of this approach. On-chip analysis revealed that (1) synchronized interbeat intervals (IBIs) of cell networks were followed to the more stable beating cells even their IBIs were slower than the other cells, which is against the conventional faster firing regulation or “overdrive suppression,” and (2) fluctuation of IBIs of cardiomyocyte networks decreased according to the increase of the number of connected cells regardless of their geometry. The mathematical simulation of this synchronous behavior of cardiomyocyte networks also fitted well with the experimental results after incorporating the fluctuation-dissipation theorem into the oscillating stochastic phase model, in which the concept of spatially arranged cardiomyocyte networks was involved. The constructive experiments and mathematical modeling indicated the dominant rule of synchronization behavior of beating cardiomyocyte networks is a kind of stability-oriented synchronization phenomenon as the “community effect” or a fluctuation-dissipation phenomenon. Finally, as a practical application of this approach, the predictive cardiotoxicity is introduced.
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