1,721,226 research outputs found
A phenomenological approach to the simulation of metabolism and proliferation dynamics of large tumour cell populations
No full textA major goal of modern computational biology is to simulate the collective behaviour of large
cell populations starting from the intricate web of molecular interactions occurring at the
microscopic level. In this paper we describe a simplified model of cell metabolism, growth
and proliferation, suitable for inclusion in a multicell simulator, now under development
(Chignola R and Milotti E 2004 Physica A 338 261–6). Nutrients regulate the proliferation
dynamics of tumour cells which adapt their behaviour to respond to changes in the
biochemical composition of the environment. This modelling of nutrient metabolism and cell
cycle at a mesoscopic scale level leads to a continuous flow of information between the two
disparate spatiotemporal scales of molecular and cellular dynamics that can be simulated with
modern computers and tested experimentally
Erratum to "Model-based fit procedure for power-law-like spectra" [J. Comput. Phys. 217 (2006) 834-844] (DOI:10.1016/j.jcp.2006.01.033)
No full textExpression (18) in paper [1] contains a couple of misprint
Tumor microenvironment in a real-life model of tumor spheroids
No full textTumors are complex bio-systems and cell growth is coupled to the chemical modifications of the extracellular microenvironment. Tumor cells and their microenvironment, therefore, constitute an evolving cellular ecosystem and a detailed understanding of the underlying dynamics might provide insights into tumor development and resistance to therapy. Here we present a real-life computer program for the simulation of multicell tumor spheroids. Simulation results compare quite well with experimental data and yields unique view of tumor microenvironment
Physical and computational issues in a simulation of multicellular tumor spheroids
No full textWe have developed a computer program which simulates the growth and development of multicellular tumor spheroids. The program implements a basic description of the metabolism, growth and proliferation of single cells, a full 3-dimensional geometry, and handles the complex problem of diffusion and transport of nutrients and metabolites into and out of cells, and in their surrounding environment. Here we discuss some of the challenging computational problems that arise in the implementation of this biophysical model
Crescita dei tumori solidi: un approccio multidisciplinare che attraversa la fenomenologia e la modellizzazione biofisica per approdare alla clinica
No full textInterplay between distribution of live cells and growth dynamics of solid tumours
Full text linkExperiments show that simple diffusion of nutrients and waste molecules is not sufficient to explain the typical multilayered structure of solid tumours, where an outer rim of proliferating cells surrounds a layer of quiescent but viable cells and a central necrotic region. These experiments challenge models of tumour growth based exclusively on diffusion. Here we propose a model of tumour growth that incorporates the volume dynamics and the distribution of cells within the viable cell rim. The model is suggested by in silico experiments and is validated using in vitro data. The results correlate with in vivo data as well, and the model can be used to support experimental and clinical oncology
Neighbor search algorithm for lattice-free simulations with short-range forces
No full textWe have recently developed a lattice-free simulation program in computational cell biology which needs the introduction and management of the biomechanical interactions of cells. These interactions are associated with short range forces which act on nearest-neighbors only. The forces act in the rearrangement of cells due to proliferation and cell growth and this requires a recalculation of the proximity relations at each time step. Here we describe the implementation of an algorithm to efficiently compute the proximity relations and designed to run on Graphics Processing Units (GPUs). The results of the first test runs on an NVidia Fermi GPU are encouraging: the algorithm has the potential to significantly boost the simulation program and to map the disordered lattice also on other multicore machines with hypercubic connectivity
Bridging the gap between the micro- and the macro-world of tumors
No full textAt present it is still quite difficult to match the vast knowledge on the behavior of individual tumor cells with macroscopic measurements on clinical tumors. On the modeling side, we already know how to deal with many molecular pathways and cellular events, using systems of differential equations and other modeling tools, and ideally, we should be able to extend such a mathematical description up to the level of large tumor masses. An extended model should thus help us forecast the behavior of large tumors from our basic knowledge of microscopic processes. Unfortunately, the complexity of these processes makes it very difficult – probably impossible – to develop comprehensive analytical models. We try to bridge the gap with a simulation program which is based on basic biochemical and biophysical processes – thereby building an effective computational model – and in this paper we describe its structure, endeavoring to make the description sufficiently detailed and yet understandable
Thresholds, long delays and stability from generalized allosteric effect in protein networks
No full textPost-transductional modifications tune the functions of proteins and regulate the collective dynamics of biochemical networks that determine how cells respond to environmental signals. For example, protein phosphorylation and nitrosylation are well known to play a pivotal role in the intracellular transduction of activation and death signals. A protein can have multiple sites where chemical groups can reversibly attach in processes such as phosphorylation or nitrosylation. A microscopic description of these processes must take into account the intrinsic probabilistic nature of the underlying reactions. We apply combinatorial considerations to standard enzyme kinetics and in this way we extend to the dynamic regime a simplified version of the traditional models on the allosteric regulation of protein functions. We link a generic modification chain to a downstream Michaelis–Menten enzymatic reaction and we demonstrate numerically that this accounts both for thresholds and long time delays in the conversion of the substrate by the enzyme. The proposed mechanism is stable and robust and the higher the number of modification sites, the greater the stability. We show that a high number of modification sites converts a fast reaction into a slow process, and the slowing down depends on the number of sites and may span many orders of magnitude; in this way multisite modification of proteins stands out as a general mechanism that allows the transfer of information from the very short time scales of enzyme reactions (milliseconds) to the long time scale of cell response (hours)
Oxygen in the Tumor Microenvironment: Mathematical and Numerical Modeling
No full textThere are many reasons to try to achieve a good grasp of the distribution of oxygen in the tumor microenvironment. The lack of oxygen - hypoxia - is a main actor in the evolution of tumors and in their growth and appears to be just as important in tumor invasion and metastasis. Mathematical models of the distribution of oxygen in tumors which are based on reaction-diffusion equations provide partial but qualitatively significant descriptions of the measured oxygen concentrations in the tumor microenvironment, especially when they incorporate important elements of the blood vessel network such as the blood vessel size and spatial distribution and the pulsation of local pressure due to blood circulation. Here, we review our mathematical and numerical approaches to the distribution of oxygen that yield insights both on the role of the distribution of blood vessel density and size and on the fluctuations of blood pressure
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