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In all sciences, models are used to represent, usually

In
all sciences, models are used to represent, usually in an simplified form, a
more complex and detailed reality. Models and simulations are used because in
some way, they are more accessible, convenient, or familiar to practitioners
than the in vivo experiments. They 
represent more explicitly the state of knowledge, predict results, or
act as the objects of further experiments. Most importantly, a model is a
representation of some reality that embodies some essential and interesting
aspects of that reality, but not all of it.

Creating
a cellular model has been a particularly challenging task of systems in biology
and mathematical biology . Through this kind of models is easier to analyze and
visualize the complex connections of these cellular processes. It involves the
use of computer simulations environment that allows rapid and intuitive
modeling and simulation of cellular and multicellular behaviors in the context
of tissue formation .

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Collective
cell migration describes the movements of group of cells and the emergence of
collective behavior from cell-environment interactions and cell-cell
communication.1 Collective cell migration is an essential process in
the lives of multicellular organisms. Cells can migrate as a cohesive group
(e.g. epithelial cells) or have transient cell-cell adhesion sites (e.g.
mesenchymal cells).They can also migrate in different modes like sheets,
strands, tubes, and clusters. While single-cell migration has been extensively
studied, collective cell migration is a relatively new field with applications.

In
vitro studies have shown that cells become more prone to collective migration
when they are confined onto micropatterned surfaces. To study this in vivo,
scientists mainly focus on neural crest cells migration and they experimentally
came up with results that NCC migration in vivo is enhanced by spatial
confinement. The confining factor plays a contradictory role acting as an
inhibitor of migration to form exclusionary boundaries and, at the same time,
required for collective migration of NCCs. In particular this confining factor
is about to be the versican. 1,2

This
confinement forms an inhibitory boundary around NC streams and the loss of versican in vivo leads to altered NC migration and directionally
collective movement of the cells in silico without affecting cell motility.
Also it is essential the width of the confinement and the size of the cell
cluster for the efficiency of the migration.Furthermore, studying the
widespread biological phenomenon of cell migration, it was observed ,that upon
exposure to chemokine gradients (CCL19 or CXCL12) lymphocytes assembled into
clusters that migrate directionally and display a wider chemotactic sensitivity
than individual cells. Single cells undergo chemorepulsion when exposed to high
doses of chemokine and collective lymphoid cells are stack together through
adhesive receptors that are critical to establish the differential polarity of
individual cells within the clusters and for collective directional migration.

The
analysis and the understanding of the behavior of the single cells in contrast
to clusters, as they move up to a chemoattractant gradient, leads to consider
all the significant factors that influence this procedure. Specifically ,
parameters like temperature , positive and negative chemotaxis ?, the boundary
value that determines the polarizing from a cell type to another seem to affect
the evolution of the process and the differences between the collective or
individual cell performance.

 

METHODS

Multi-cell
computer simulation methods, ranging from relatively simple cellular automata
to complex immersed-boundary models, allow in silico study of multi-cell
phenomena at the tissue scale based on biologically observed cell behaviors and
interactions such as movement, adhesion, growth,secretion of chemicals,
chemotaxis, etc. CompuCell3D simulation environment allows rapid and intuitive
modeling and simulation of cellular and multi-cellular behaviors in the context
of tissue formation and subsequent dynamics. This way models are  useful in both  suggesting 
hypotheses and testing them. CC3D allows users to build sophisticated
models more easily and quickly than specialized custom code. A CC3D model
consists of CC3DML scripts (an XML-based format), Python scripts, and files specifying
the initial configurations of the cell lattice. The CC3DML script specifies
basic GGH (Glazier-Graner-Hogeweg) parameters such as lattice dimensions, cell
types, biological mechanisms.  Python
scripts primarily monitor the state of the simulation and implement changes in
cell behaviors.3

The
model that we built using CompuCell3D is meant to get an insight into the
behaviour of single and cluster cells under the influence of a chemical field.

In
the model we imposed two different type of cells: the attract-cell and the
repel-cell. The attract-cell is attracted to the gradient and the repel-cell is
repulsed. At the beginning of the simulation we had an attract-cell. As the
gradient got steeper this cell flipped to a repel-cell and on the other side as
the gradient got smoother the repel-cell changed to an attract-cell . To
compare the differences in  the behaviour
of the cells we used three different cluster sizes. At first we  did the simulations for 1 cell , afterwards
for one small cluster of cells ( 9 cells) and finally for a bigger cluster (21
cells). In every simulation after 
varying one parameter (chemotaxis ?, flipping values, temperature) of
the model and  analyzing the observations
we could see what influence the variable had on the system. 

 

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