30 research outputs found

    Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

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    Background Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. Results We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Conclusions Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 10003^{3} voxel-sized cancerous tissue simulation at sub-cellular resolution

    Comparing individual-based approaches to modelling the self-organization of multicellular tissues.

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    The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage

    Collective cell dynamics in cancer metastasis

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    Seven challenges in the multiscale modeling of multicellular tissues

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    The growth and dynamics of multicellular tissues involve tightly regulated and coordinated morphogenetic cell behaviors, such as shape changes, movement, and division, which are governed by subcellular machinery and involve coupling through short- and long-range signals. A key challenge in the fields of developmental biology, tissue engineering and regenerative medicine is to understand how relationships between scales produce emergent tissue-scale behaviors. Recent advances in molecular biology, live-imaging and ex vivo techniques have revolutionized our ability to study these processes experimentally. To fully leverage these techniques and obtain a more comprehensive understanding of the causal relationships underlying tissue dynamics, computational modeling approaches are increasingly spanning multiple spatial and temporal scales, and are coupling cell shape, growth, mechanics, and signaling. Yet such models remain challenging: modeling at each scale requires different areas of technical skills, while integration across scales necessitates the solution to novel mathematical and computational problems. This review aims to summarize recent progress in multiscale modeling of multicellular tissues and to highlight ongoing challenges associated with the construction, implementation, interrogation, and validation of such models

    Optimization of Biogas Production by Use of a Microbially Enhanced Inoculum

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    A renewable energy source, biogas, comprises of methane (80%) and carbon dioxide (15%), and is a great alternative to the conventional fossil-based fuels, such as coal, gas and oil. Biogas is created during anaerobic biological digestion of waste materials, such as landfill material, animal manure, wastewater, algal biomass, industrial organic waste etc. A biogas potential from organic waste in the United States is estimated at about 9 million tons per year and technology allows capture of greenhouse gases, such as methane and carbon dioxide, into a form of a fuel. In the light of global climate change and efforts to decrease carbon footprint of fuels in daily life, usage of biogas as an alternative fuel to fossil fuels looks especially promising. The goal of this research was to develop and test an approach for optimization of biogas production by engineering microorganisms digesting organic waste. Specifically, bacteria that can digest algal biomass, collected from the wastewater lagoons or open waterbodies. The research also expands on the previous efforts to analyze microbial interactions in wastewater treatment systems. A computational model is developed to aid with prognosis of microbial consortia ability to form complex aggregates in reactors with upflow mode of feeding substrate. Combining modeling predictions and laboratory experiments in organic matter digestion will lead to more stable engineered systems and higher yields of biogas

    A diversity-aware computational framework for systems biology

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Phase transitions in quantum chromodynamics

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    The current understanding of finite temperature phase transitions in QCD is reviewed. A critical discussion of refined phase transition criteria in numerical lattice simulations and of analytical tools going beyond the mean-field level in effective continuum models for QCD is presented. Theoretical predictions about the order of the transitions are compared with possible experimental manifestations in heavy-ion collisions. Various places in phenomenological descriptions are pointed out, where more reliable data for QCD's equation of state would help in selecting the most realistic scenario among those proposed. Unanswered questions are raised about the relevance of calculations which assume thermodynamic equilibrium. Promising new approaches to implement nonequilibrium aspects in the thermodynamics of heavy-ion collisions are described.Comment: 156 pages, RevTex. Tables II,VIII,IX and Fig.s 1-38 are not included as postscript files. I would like to ask the requestors to copy the missing tables and figures from the corresponding journal-referenc

    MODELLING CELL POPULATION GROWTH

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    The growth of biological matter, e.g., tumor invasion, depends on various factors, mainly the tissue’s mechanical properties, implying elasticity, stiffness, or apparent viscosity. These properties are impacted by the characteristics of the tissue’s extracellular matrix and constituent cells, including, but not limited to, cell membrane stiffness, cell cytoskeleton mechanical properties, and the intensity and distribution of focal adhesions over the cell membrane. To compute and study the mechanical properties of tissues during growth and confluency, a theoretical and computational framework, called CellSim3D, was developed in our group based on a three-dimensional kinetic division model. In this work, CellSim3D is updated with a new set of cell mechanical parameters and force fields such as the asymmetric division rule, shape diversity, apoptosis process, and boundary conditions, e.g., periodic and Lees-Edwards boundary conditions. The package is upgraded to operate on multiple GPUs to further accelerate computations. This enables the inclusion of more complexity in the system. For instance, the simulation of macroscopic scale bicellular tissue growth with precise control over the mechanical properties of cells is now more feasible than before. The effects of cell-cell adhesion strength and intermembrane friction on growth kinetics and interface roughness dynamics of epithelial tissue were studied. It is reported that with fine alterations of the mechanical parameters such as the cell-cell adhesion strength, one could reliably reproduce different interface roughness scaling behaviors such as Kardar–Parisi–Zhang (KPZ)-like and Molecular Beam Epitaxy (MBE)-like scaling. In addition, it was observed that substrate heterogeneity and geometry have significant impacts on the morphology and interface roughness scaling of epithelial tissue. The results suggest that the interface roughness scaling of epithelial tissues cannot be classified by any well-known scaling universality class. Instead, it strongly depends on several other factors, such as the cell-cell adhesion strength. This explains the controversies observed in earlier experimental works over the interface roughness scaling of expanding epithelial tissue
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