Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

Combining influence maps and cellular automata for reactive game agents

Agents make up an important part of game worlds, ranging from the characters and monsters that live in the world to the armies that the player controls. Despite their importance, agents in current games rarely display an awareness of their environment or react appropriately, which severely detracts from the believability of the game. Some games have included agents with a basic awareness of other agents, but they are still unaware of important game events or environmental conditions. This paper presents an agent design we have developed, which combines cellular automata for environmental modeling with influence maps for agent decision-making. The agents were implemented into a 3D game environment we have developed, the EmerGEnT system, and tuned through three experiments. The result is simple, flexible game agents that are able to respond to natural phenomena (e.g. rain or fire), while pursuing a goal.

Influence of internal fixator stiffness on murine fracture healing : two types of fracture healing lead to two distinct cellular events and FGF-2 expressions

This study aimed to clarify the relationship between the mechanical environment at the fracture site and endogenous fibroblast growth factor-2 (FGF-2). We compared two types of fracture healing with different callus formations and cellular events using MouseFix(TM) plate fixation systems for murine fracture models. Left femoral fractures were induced in 72 ten-week-old mice and then fixed with a flexible (Group F) or rigid (Group R) Mouse Fix(TM) plate. Mice were sacrificed on days 3, 5, 7, 10, 14, and 21. The callus volumes were measured by 3D micro-CT and tissues were histologically stained with hematoxylin & eosin or safranin-O. Sections from days 3, 5, and 7 were immunostained for FGF-2 and Proliferating Cell Nuclear Antigen (PCNA). The callus in Group F was significantly larger than that in Group R. The rigid plate allowed bone union without a marked external callus or chondrogenesis. The flexible plate formed a large external callus as a result of endochondral ossification. Fibroblastic cells in the granulation tissue on days 5 and 7 in Group F showed marked FGF-2 expression compared with Group R. Fibroblastic cells showed ongoing proliferation in granulation tissue in group F, as indicated by PCNA expression, which explained the relative granulation tissue increase in group F. There were major differences in early phase endogenous FGF-2 expression between these two fracture healing processes, due to different mechanical environments.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

Atomistic exploration of deformation properties of copper nanowires with pre-existing defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, in this paper, the tensile deformation properties of Cu nanowires (NWs) with different pre-existing defects, including single surface defects, surface bi-defects and single internal defects, are systematically studied. In-depth deformation mechanisms of NWs with pre-existing defects are also explored. It is found that Young's modulus is insensitive to different pre-existing defects, but yield strength shows an obvious decrease. Defects are observed influencing greatly on NWs' tensile deformation mechanisms, and playing a role of dislocation sources. Besides of the traditional deformation process dominated by the nucleation and propagation of partial dislocations, the generations of twins, grain boundaries, fivefold deformation twins, hexagonal close-packed (HCP) structure and phase transformation from face-centred cubic (FCC) structure to HCP structure have been triggered by pre-existing defects. It is found that surface defect intends to induce larger influence to yield strength than internal defect. Most importantly, the defect that lies on slip planes exerts larger influence than other defects. As expected, it is also found that the more or longer of the defect, the bigger influence will be induced.

Vibrational spectroscopic study of the copper silicate mineral kinoite Ca2Cu2Si3O10(OH)4

Kinoite Ca2Cu2Si3O10(OH)4 is a mineral named after a Jesuit missionary. Raman and infrared spectroscopy have been used to characterise the structure of the mineral. The Raman spectrum is characterised by an intense sharp band at 847 cm-1 assigned to the ν1 (A1g) symmetric stretching vibration. Intense sharp bands at 951, 994 and 1000 cm-1 are assigned to the ν3 (Eu, A2u, B1g) SiO4 antisymmetric stretching vibrations. Multiple ν2 SiO4 vibrational modes indicate strong distortion of the SiO4 tetrahedra. Multiple CaO and CuO stretching bands are observed. Raman spectroscopy confirmed by infrared spectroscopy clearly shows that hydroxyl units are involved in the kinoite structure. Based upon the infrared spectra, it is proposed that water is also involved in the kinoite structure. Based upon vibrational spectroscopy, the formula of kinoite is defined as Ca2Cu2Si3O10(OH)4•xH2O.

Plant programmed cell death : Can't live with it; Can't live without it

The decision of whether a cell should live or die is fundamental for the wellbeing of all organisms. Despite intense investigation into cell growth and proliferation, only recently has the essential and equally important idea that cells control/programme their own demise for proper maintenance of cellular homeostasis gained recognition. Furthermore, even though research into programmed cell death (PCD) has been an extremely active area of research there are significant gaps in our understanding of the process in plants. In this review, we discuss PCD during plant development and pathogenesis, and compare/contrast this with mammalian apoptosis. © 2008 Blackwell Publishing Ltd.

Two-Photon Fluorescence Microscopy Imaging of Cellular Oxidative Stress Using Profluorescent Nitroxides

A range of varying chromophore nitroxide free radicals and their nonradical methoxyamine analogues were synthesized and their linear photophysical properties examined. The presence of the proximate free radical masks the chromophore’s usual fluorescence emission, and these species are described as profluorescent. Two nitroxides incorporating anthracene and fluorescein chromophores (compounds 7 and 19, respectively) exhibited two-photon absorption (2PA) cross sections of approximately 400 G.M. when excited at wavelengths greater than 800 nm. Both of these profluorescent nitroxides demonstrated low cytotoxicity toward Chinese hamster ovary (CHO) cells. Imaging colocalization experiments with the commercially available CellROX Deep Red oxidative stress monitor demonstrated good cellular uptake of the nitroxide probes. Sensitivity of the nitroxide probes to H2O2-induced damage was also demonstrated by both one- and two-photon fluorescence microscopy. These profluorescent nitroxide probes are potentially powerful tools for imaging oxidative stress in biological systems, and they essentially “light up” in the presence of certain species generated from oxidative stress. The high ratio of the fluorescence quantum yield between the profluorescent nitroxide species and their nonradical adducts provides the sensitivity required for measuring a range of cellular redox environments. Furthermore, their reasonable 2PA cross sections provide for the option of using two-photon fluorescence microscopy, which circumvents commonly encountered disadvantages associated with one-photon imaging such as photobleaching and poor tissue penetration.

MD investigations for mechanical properties of copper nanowires with and without surface defects

Based on the molecular dynamics (MD) method, the single-crystalline copper nanowire with different surface defects is investigated through tension simulation. For comparison, the MD tension simulations of perfect nanowire are firstly carried out under different temperatures, strain rates, and sizes. It has concluded that the surface-volume ratio significantly affects the mechanical properties of nanowire. The surface defects on nanowires are then systematically studied in considering different defect orientation and distribution. It is found that the Young’s modulus is insensitive of surface defects. However, the yield strength and yield point show a significant decrease due to the different defects. Different defects are observed to serve as a dislocation source.

Vibrational spectroscopic study of the copper silicate mineral ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O

Ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O is a mineral named after the Ajo district of Arizona. Raman and infrared spectroscopy were used to characterise the molecular structure of ajoite. The structure of the mineral shows disorder which is reflected in the difficulty of obtaining quality Raman spectra. The Raman spectrum is characterised by a broad spectral profile with a band at 1048 cm-1 assigned to the ν1 (A1g) symmetric stretching vibration. Strong bands at 962, 1015 and 1139 cm-1 are assigned to the ν3 SiO4 antisymmetric stretching vibrations. Multiple ν4 SiO4 vibrational modes indicate strong distortion of the SiO4 tetrahedra. Multiple AlO and CuO stretching bands are observed. Raman spectroscopy and confirmed by infrared spectroscopy clearly shows that hydroxyl units are involved in the ajoite structure. Based upon the infrared spectra, water is involved in the ajoite structure, probably as zeolitic water.

Cellular settings mediating Src Substrate switching between Focal Adhesion Kinase Tyrosine 861 and CUB-domain-containing protein 1 (CDCP1) Tyrosine 734

Reciprocal interactions between Src family kinases (SFKs) and focal adhesion kinase (FAK) are critical during changes in cell attachment. Recently it has been recognized that another SFK substrate, CUB-domain-containing protein 1 (CDCP1), is differentially phosphorylated during these events. However, the molecular processes underlying SFK-mediated phosphorylation of CDCP1 are poorly understood. Here we identify a novel mechanism in which FAK tyrosine 861 and CDCP1-Tyr-734 compete as SFK substrates and demonstrate cellular settings in which SFKs switch between these sites. Our results show that stable CDCP1 expression induces robust SFK-mediated phosphorylation of CDCP1-Tyr-734 with concomitant loss of p-FAK-Tyr-861 in adherent HeLa cells. SFK substrate switching in these cells is dependent on the level of expression of CDCP1 and is also dependent on CDCP1-Tyr-734 but is independent of CDCP1-Tyr-743 and -Tyr-762. In HeLa CDCP1 cells, engagement of SFKs with CDCP1 is accompanied by an increase in phosphorylation of Src-Tyr-416 and a change in cell morphology to a fibroblastic appearance dependent on CDCP1-Tyr-734. SFK switching between FAK-Tyr-861 and CDCP1-Tyr-734 also occurs during changes in adhesion of colorectal cancer cell lines endogenously expressing these two proteins. Consistently, increased p-FAK-Tyr-861 levels and a more epithelial morphology are seen in colon cancer SW480 cells silenced for CDCP1. Unlike protein kinase Cδ, FAK does not appear to form a trimeric complex with Src and CDCP1. These data demonstrate novel aspects of the dynamics of SFK-mediated cell signaling that may be relevant during cancer progression.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.