Finite element analysis of the influence of cyclic strain on cells anchored to substrates with varying properties

Discrete network models of endothelial cells and their interactions with the substrate

Endothelial cell monolayers line the inner surfaces of blood and lymphatic vessels. They are continuously exposed to different mechanical loads, which may trigger mechanobiological signals and hence play a role in both physiological and pathological processes. Computer-based mechanical models of cells contribute to a better understanding of the relation between cell-scale loads and cues and the mechanical state of the hosting tissue. However, the confluency of the endothelial monolayer complicates these approaches since the intercellular cross-talk needs to be accounted for in addition to the cytoskeletal mechanics of the individual cells themselves. As a consequence, the computational approach must be able to efficiently model a large number of cells and their interaction. Here, we simulate cytoskeletal mechanics by means of molecular dynamics software, generally suitable to deal with large, locally interacting systems. Methods were developed to generate models of single cells and large monolayers with hundreds of cells. The single-cell model was considered for a comparison with experimental data. To this end, we simulated cell interactions with a continuous, deformable substrate, and computationally replicated multistep traction force microscopy experiments on endothelial cells. The results indicate that cell discrete network models are able to capture relevant features of the mechanical behaviour and are thus well-suited to investigate the mechanics of the large cytoskeletal network of individual cells and cell monolayers.

The effect of the properties of cell nucleus and underlying substrate on the response of finite element models of astrocytes undergoing mechanical stimulations

Astrocyte cells play a critical role in the mechanical behaviour of the brain tissue; hence understanding the properties of Astrocytes is a big step toward understanding brain diseases and abnormalities. Conventionally, atomic force microscopy (AFM) has been used as one of the most powerful tools to characterize the mechanical properties of cells. However, due to the complexities of experimental work and the complex behaviour of living cells, the finite element method (FEM) is commonly used to estimate the cells' response to mechanical stimulations. In this study, we developed a finite element model of the Astrocyte cells to investigate the effect of two key parameters that could affect the response of the cell to mechanical loading; the properties of the underlying substrate and the nucleus. In this regard, the cells were placed on two different substrates in terms of thickness and stiffness (gel and glass) with varying properties of the nucleus. The main achievement of this study was to develop an insight to investigate the response of the Astrocytes to mechanical loading for future studies, both experimentally and computationally.

Evaluating the cell migration potential of TiO2 nanorods incorporated in a Ti6Al4V scaffold: A multiscale approach

Improvement of cell migration by the nano-topographical modification of implant surface can directly or indirectly accelerate wound healing and osseointegration between bone and implant. Therefore, modification of the implant surface was done with TiO2 nanorod (NR) arrays to develop a more osseointegration-friendly implant in this study. Modulating the migration of a cell, adhered to a scaffold, by the variations of NR diameter, density and tip diameter in vitro is the primary objective of the study. The fluid structure interaction method was used, followed by the submodelling technique in this multiscale analysis. After completing a simulation over a global model, fluid structure interaction data was applied to the sub-scaffold finite element model to predict the mechanical response over cells at the cell-substrate interface. Special focus was given to strain energy density at the cell interface as a response parameter due to its direct correlation with the migration of an adherent cell. The results showed a huge rise in strain energy density after the addition of NRs on the scaffold surface. It also highlighted that variation in NR density plays a more effective role than the variation in NR diameter to control cell migration over a substrate. However, the effect of NR diameter becomes insignificant when the NR tip was considered. The findings of this study could be used to determine the best nanostructure parameters for better osseointegration.