Dataset Information

Probabilistic Voxel-Fe model for single cell motility in 3D.

ABSTRACT:

Background

Cells respond to a variety of external stimuli regulated by the environment conditions. Mechanical, chemical and biological factors are of great interest and have been deeply studied. Furthermore, mathematical and computational models have been rapidly growing over the past few years, permitting researches to run complex scenarios saving time and resources. Usually these models focus on specific features of cell migration, making them only suitable to study restricted phenomena.

Methods

Here we present a versatile finite element (FE) cell-scale 3D migration model based on probabilities depending in turn on ECM mechanical properties, chemical, fluid and boundary conditions.

Results

With this approach we are able to capture important outcomes of cell migration such as: velocities, trajectories, cell shape and aspect ratio, cell stress or ECM displacements.

Conclusions

The modular form of the model will allow us to constantly update and redefine it as advancements are made in clarifying how cellular events take place.

SUBMITTER: Borau C

PROVIDER: S-EPMC4538854 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Publications

Probabilistic Voxel-Fe model for single cell motility in 3D.

Borau Carlos C Polacheck William J WJ Kamm Roger D RD García-Aznar José Manuel JM

In silico cell and tissue science 20141001

<h4>Background</h4>Cells respond to a variety of external stimuli regulated by the environment conditions. Mechanical, chemical and biological factors are of great interest and have been deeply studied. Furthermore, mathematical and computational models have been rapidly growing over the past few years, permitting researches to run complex scenarios saving time and resources. Usually these models focus on specific features of cell migration, making them only suitable to study restricted phenomen ...[more]

PMID: 26290806

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Project description:The purpose of this work is to develop and validate a new atlas-based metabolite quantification pipeline for edited magnetic resonance spectroscopic imaging (MEGA-MRSI) that enables group comparisons of brain structure-specific GABA levels. By using brain structure masks segmented from high-resolution MPRAGE images and coregistering these to MEGA-LASER 3D MRSI data, an automated regional quantification of neurochemical levels is demonstrated for the example of the thalamus. Thalamic gamma-aminobutyric acid + coedited macromolecules (GABA+) levels from 21 healthy subjects scanned at 3 T were cross-validated both against a single-voxel MEGA-PRESS acquisition in the same subjects and same scan sessions, as well as alternative MRSI processing techniques (ROI approach, four-voxel approach) using Pearson correlation analysis. In addition, reproducibility was compared across the MRSI processing techniques in test-retest data from 14 subjects. The atlas-based approach showed a significant correlation with SV MEGA-PRESS (correlation coefficient r [GABA+] = 0.63, P < 0.0001). However, the actual values for GABA+, NAA, tCr, GABA+/tCr and tNAA/tCr obtained from the atlas-based approach showed an offset to SV MEGA-PRESS levels, likely due to the fact that on average the thalamus mask used for the atlas-based approach only occupied 30% of the SVS volume, ie, somewhat different anatomies were sampled. Furthermore, the new atlas-based approach showed highly reproducible GABA+/tCr values with a low median coefficient of variance of 6.3%. In conclusion, the atlas-based metabolite quantification approach enables a more brain structure-specific comparison of GABA+ and other neurochemical levels across populations, even when using an MRSI technique with only cm-level resolution. This approach was successfully cross-validated against the typically used SVS technique as well as other different MRSI analysis methods, indicating the robustness of this quantification approach.

Dataset Information

Probabilistic Voxel-Fe model for single cell motility in 3D.

Background

Methods

Results

Conclusions

Publications

Probabilistic Voxel-Fe model for single cell motility in 3D.

Similar Datasets

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