20,448 research outputs found
A modelling approach towards Epidermal homoeostasis control
In order to grasp the features arising from cellular discreteness and
individuality, in large parts of cell tissue modelling agent-based models are
favoured. The subclass of off-lattice models allows for a physical motivation
of the intercellular interaction rules. We apply an improved version of a
previously introduced off-lattice agent-based model to the steady-state flow
equilibrium of skin. The dynamics of cells is determined by conservative and
drag forces,supplemented with delta-correlated random forces. Cellular
adjacency is detected by a weighted Delaunay triangulation. The cell cycle time
of keratinocytes is controlled by a diffusible substance provided by the
dermis. Its concentration is calculated from a diffusion equation with
time-dependent boundary conditions and varying diffusion coefficients. The
dynamics of a nutrient is also taken into account by a reaction-diffusion
equation. It turns out that the analysed control mechanism suffices to explain
several characteristics of epidermal homoeostasis formation. In addition, we
examine the question of how {\em in silico} melanoma with decreased basal
adhesion manage to persist within the steady-state flow-equilibrium of the
skin.Interestingly, even for melanocyte cell cycle times being substantially
shorter than for keratinocytes, tiny stochastic effects can lead to completely
different outcomes. The results demonstrate that the understanding of initial
states of tumour growth can profit significantly from the application of
off-lattice agent-based models in computer simulations.Comment: 23 pages, 7 figures, 1 table; version that is to appear in Journal of
Theoretical Biolog
Higher nucleoporin-Importinβ affinity at the nuclear basket increases nucleocytoplasmic import.
Several in vitro studies have shown the presence of an affinity gradient in nuclear pore complex proteins for the import receptor Importinβ, at least partially contributing to nucleocytoplasmic transport, while others have historically argued against the presence of such a gradient. Nonetheless, the existence of an affinity gradient has remained an uncharacterized contributing factor. To shed light on the affinity gradient theory and better characterize how the existence of such an affinity gradient between the nuclear pore and the import receptor may influence the nucleocytoplasmic traffic, we have developed a general-purpose agent based modeling (ABM) framework that features a new method for relating rate constants to molecular binding and unbinding probabilities, and used our ABM approach to quantify the effects of a wide range of forward and reverse nucleoporin-Importinβ affinity gradients. Our results indicate that transport through the nuclear pore complex is maximized with an effective macroscopic affinity gradient of 2000 µM, 200 µM and 10 µM in the cytoplasmic, central channel and nuclear basket respectively. The transport rate at this gradient is approximately 10% higher than the transport rate for a comparable pore lacking any affinity gradient, which has a peak transport rate when all nucleoporins have an affinity of 200 µM for Importinβ. Furthermore, this optimal ratio of affinity gradients is representative of the ratio of affinities reported for the yeast nuclear pore complex--suggesting that the affinity gradient seen in vitro is highly optimized
Collective motion of cells: from experiments to models
Swarming or collective motion of living entities is one of the most common
and spectacular manifestations of living systems having been extensively
studied in recent years. A number of general principles have been established.
The interactions at the level of cells are quite different from those among
individual animals therefore the study of collective motion of cells is likely
to reveal some specific important features which are overviewed in this paper.
In addition to presenting the most appealing results from the quickly growing
related literature we also deliver a critical discussion of the emerging
picture and summarize our present understanding of collective motion at the
cellular level. Collective motion of cells plays an essential role in a number
of experimental and real-life situations. In most cases the coordinated motion
is a helpful aspect of the given phenomenon and results in making a related
process more efficient (e.g., embryogenesis or wound healing), while in the
case of tumor cell invasion it appears to speed up the progression of the
disease. In these mechanisms cells both have to be motile and adhere to one
another, the adherence feature being the most specific to this sort of
collective behavior. One of the central aims of this review is both presenting
the related experimental observations and treating them in the light of a few
basic computational models so as to make an interpretation of the phenomena at
a quantitative level as well.Comment: 24 pages, 25 figures, 13 reference video link
A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT
Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualisation toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery
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