Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels.

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale.

Numerical study of ultra-large von Willebrand factor multimers in coagulopathy.

An excessive von Willebrand factor (VWF) secretion, coupled with a moderate to severe deficiency of ADAMTS13 activity, serves as a linking mechanism between inflammation to thrombosis. The former facilitates platelet adhesion to the vessel wall and the latter is required to cleave VWF multimers. As a result, the ultra-large VWF (UL-VWF) multimers released by Weibel-Palade bodies remain uncleaved.

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation.

Understanding and predicting metastatic progression and developing novel diagnostic methods can highly benefit from accurate models of the deformability of cancer cells. Spring-based network models of cells can provide a versatile way of integrating deforming cancer cells with other physical and biochemical phenomena, but these models have parameters that need to be accurately identified. In this study we established a systematic method for identifying parameters of spring-network models of cancer cells.