Figure 1.
Main components of the biophysical cell-based computational model and workflow of the article
(A) Experimental data from the regeneration of liver lobules after partial hepatectomy in mice (removing part of the liver) have been used to calibrate a quantitative computational cell-based model of liver regeneration by a pipeline of imaging, image processing, and model development and simulation.
(B) The computational model has been recalibrated with experimental data from pig and predictive simulations been performed on the regeneration scenario of a piece of pig tissue that includes the Glisson capsule. The simulated prediction has been confronted with a pilot experiment.
(C) shows a sketch of two interacting cells for the definition of the indention δ and cell radius R i used to calculate the cell-cell interaction force. Each cell’s movement is calculated from all forces on that cell including active forces due to migration.
(D) shows the implementation of cell growth in the interface by radius increase until cell volume doubled, and division by splitting. Biomechanical Growth Control (BGC) assumes that a cell does not enter the cell cycle if the pressure exerted on it exceeds a certain threshold value pth, while in absence of BGC such a constrained is absent. (2D sketch shown for simplicity; the model is 3D.).
(E) Dividing cells align along the closest sinusoid, a mechanism we had named “HSA” (Hoehme et al., 2010).
(F) The dynamics of cells have been simulated by solving a force balance equation for each cell and for each vessel element. Vessels have been mimicked in 3D as a chain of spheres connected by springs (details in text). The force balance equation for each cell includes friction forces between cells and extracellular matrix (including the Glisson capsule), among cells, of cells with vessel elements, as well as adhesion and repulsion forces between cells and substrate (here the Glisson capsule enclosing the liver lobe), among cells, and between cells and vessel elements, and finally an active force to mimic cell migration. Force balance for translational movement is complemented by cell rotations for which a Monte Carlo simulation scheme based on the total interaction energy for the entire system has been used.