Reprogramming cellular identity for regenerative medicine

PubMed Central

Cherry, Anne B.C.; Daley, George Q.

2012-01-01

The choreographed development of over 200 distinct differentiated cell types from a single zygote is a complex and poorly understood process. Whereas development leads unidirectionally towards more restricted cell fates, recent work in cellular reprogramming has proven that striking conversions of one cellular identity into another can be engineered, promising countless applications in biomedical research and paving the way for modeling disease with patient-derived stem cells. To date, there has been little discussion of which disease models are likely to be most informative. We here review evidence demonstrating that because environmental influences and epigenetic signatures are largely erased during reprogramming, patient-specific models of diseases with strong genetic bases and high penetrance are likely to prove most informative in the near term. However, manipulating in vitro culture conditions may ultimately enable cell-based models to recapitulate gene-environment interactions. Here, we discuss the implications of the new reprogramming paradigm in biomedicine and outline how reprogramming of cell identities is enhancing our understanding of cell differentiation and prospects for cellular therapies and in vivo regeneration. PMID:22424223

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Origami-based cellular metamaterial with auxetic, bistable, and self-locking properties

NASA Astrophysics Data System (ADS)

Kamrava, Soroush; Mousanezhad, Davood; Ebrahimi, Hamid; Ghosh, Ranajay; Vaziri, Ashkan

2017-04-01

We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson’s ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments.

Origami-based cellular metamaterial with auxetic, bistable, and self-locking properties

PubMed Central

Kamrava, Soroush; Mousanezhad, Davood; Ebrahimi, Hamid; Ghosh, Ranajay; Vaziri, Ashkan

2017-01-01

We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson’s ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments. PMID:28387345

Modeling of time dependent localized flow shear stress and its impact on cellular growth within additive manufactured titanium implants.

PubMed

Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R

2014-11-01

Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier-Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. © 2014 Wiley Periodicals, Inc.

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

A methodological approach for using high-level Petri Nets to model the immune system response.

PubMed

Pennisi, Marzio; Cavalieri, Salvatore; Motta, Santo; Pappalardo, Francesco

2016-12-22

Mathematical and computational models showed to be a very important support tool for the comprehension of the immune system response against pathogens. Models and simulations allowed to study the immune system behavior, to test biological hypotheses about diseases and infection dynamics, and to improve and optimize novel and existing drugs and vaccines. Continuous models, mainly based on differential equations, usually allow to qualitatively study the system but lack in description; conversely discrete models, such as agent based models and cellular automata, permit to describe in detail entities properties at the cost of losing most qualitative analyses. Petri Nets (PN) are a graphical modeling tool developed to model concurrency and synchronization in distributed systems. Their use has become increasingly marked also thanks to the introduction in the years of many features and extensions which lead to the born of "high level" PN. We propose a novel methodological approach that is based on high level PN, and in particular on Colored Petri Nets (CPN), that can be used to model the immune system response at the cellular scale. To demonstrate the potentiality of the approach we provide a simple model of the humoral immune system response that is able of reproducing some of the most complex well-known features of the adaptive response like memory and specificity features. The methodology we present has advantages of both the two classical approaches based on continuous and discrete models, since it allows to gain good level of granularity in the description of cells behavior without losing the possibility of having a qualitative analysis. Furthermore, the presented methodology based on CPN allows the adoption of the same graphical modeling technique well known to life scientists that use PN for the modeling of signaling pathways. Finally, such an approach may open the floodgates to the realization of multi scale models that integrate both signaling pathways (intra cellular) models and cellular (population) models built upon the same technique and software.

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

Cellular Responses to Mechanical Stress Selected Contribution: A Three-Dimensional Model for Assessment of in Vitro Toxicity in Balaena Mysticetus Renal Tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Molecular and cellular alterations in Down syndrome: toward the identification of targets for therapeutics.

PubMed

Créau, Nicole

2012-01-01

Down syndrome is a complex disease that has challenged molecular and cellular research for more than 50 years. Understanding the molecular bases of morphological, cellular, and functional alterations resulting from the presence of an additional complete chromosome 21 would aid in targeting specific genes and pathways for rescuing some phenotypes. Recently, progress has been made by characterization of brain alterations in mouse models of Down syndrome. This review will highlight the main molecular and cellular findings recently described for these models, particularly with respect to their relationship to Down syndrome phenotypes.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Three dimensional Origami-based metamaterial

NASA Astrophysics Data System (ADS)

Kamrava, Soroush; Mousanezhad, Davood; Ebrahimi, Hamid; Ghosh, Ranajay; Vaziri, Ashkan; High Performance Materials; Structures Labratory Team

We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson's ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

PubMed

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

Sub-cellular force microscopy in single normal and cancer cells.

PubMed

Babahosseini, H; Carmichael, B; Strobl, J S; Mahmoodi, S N; Agah, M

2015-08-07

This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer and significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

NASA Astrophysics Data System (ADS)

Xia, Weiwei; Shen, Lianfeng

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Modeling cell adhesion and proliferation: a cellular-automata based approach.

PubMed

Vivas, J; Garzón-Alvarado, D; Cerrolaza, M

Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

Mathematical Modeling of Cellular Metabolism.

PubMed

Berndt, Nikolaus; Holzhütter, Hermann-Georg

Cellular metabolism basically consists of the conversion of chemical compounds taken up from the extracellular environment into energy (conserved in energy-rich bonds of organic phosphates) and a wide array of organic molecules serving as catalysts (enzymes), information carriers (nucleic acids), and building blocks for cellular structures such as membranes or ribosomes. Metabolic modeling aims at the construction of mathematical representations of the cellular metabolism that can be used to calculate the concentration of cellular molecules and the rates of their mutual chemical interconversion in response to varying external conditions as, for example, hormonal stimuli or supply of essential nutrients. Based on such calculations, it is possible to quantify complex cellular functions as cellular growth, detoxification of drugs and xenobiotic compounds or synthesis of exported molecules. Depending on the specific questions to metabolism addressed, the methodological expertise of the researcher, and available experimental information, different conceptual frameworks have been established, allowing the usage of computational methods to condense experimental information from various layers of organization into (self-) consistent models. Here, we briefly outline the main conceptual frameworks that are currently exploited in metabolism research.

Cellular self-assembly and biomaterials-based organoid models of development and diseases.

PubMed

Shah, Shivem B; Singh, Ankur

2017-04-15

Organogenesis and morphogenesis have informed our understanding of physiology, pathophysiology, and avenues to create new curative and regenerative therapies. Thus far, this understanding has been hindered by the lack of a physiologically relevant yet accessible model that affords biological control. Recently, three-dimensional ex vivo cellular cultures created through cellular self-assembly under natural extracellular matrix cues or through biomaterial-based directed assembly have been shown to physically resemble and recapture some functionality of target organs. These "organoids" have garnered momentum for their applications in modeling human development and disease, drug screening, and future therapy design or even organ replacement. This review first discusses the self-organizing organoids as materials with emergent properties and their advantages and limitations. We subsequently describe biomaterials-based strategies used to afford more control of the organoid's microenvironment and ensuing cellular composition and organization. In this review, we also offer our perspective on how multifunctional biomaterials with precise spatial and temporal control could ultimately bridge the gap between in vitro organoid platforms and their in vivo counterparts. Several notable reviews have highlighted PSC-derived organoids and 3D aggregates, including embryoid bodies, from a development and cellular assembly perspective. The focus of this review is to highlight the materials-based approaches that cells, including PSCs and others, adopt for self-assembly and the controlled development of complex tissues, such as that of the brain, gut, and immune system. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The two populations’ cellular automata model with predation based on the Penna model

NASA Astrophysics Data System (ADS)

He, Mingfeng; Lin, Jing; Jiang, Heng; Liu, Xin

2002-09-01

In Penna's single-species asexual bit-string model of biological ageing, the Verhulst factor has too strong a restraining effect on the development of the population. Danuta Makowiec gave an improved model based on the lattice, where the restraining factor of the four neighbours take the place of the Verhulst factor. Here, we discuss the two populations’ Penna model with predation on the planar lattice of two dimensions. A cellular automata model containing movable wolves and sheep has been built. The results show that both the quantity of the wolves and the sheep fluctuate in accordance with the law that one quantity increases while the other one decreases.

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling. Agent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Selected contribution: a three-dimensional model for assessment of in vitro toxicity in balaena mysticetus renal tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

Modeling the mechanics of cancer: effect of changes in cellular and extra-cellular mechanical properties.

PubMed

Katira, Parag; Bonnecaze, Roger T; Zaman, Muhammad H

2013-01-01

Malignant transformation, though primarily driven by genetic mutations in cells, is also accompanied by specific changes in cellular and extra-cellular mechanical properties such as stiffness and adhesivity. As the transformed cells grow into tumors, they interact with their surroundings via physical contacts and the application of forces. These forces can lead to changes in the mechanical regulation of cell fate based on the mechanical properties of the cells and their surrounding environment. A comprehensive understanding of cancer progression requires the study of how specific changes in mechanical properties influences collective cell behavior during tumor growth and metastasis. Here we review some key results from computational models describing the effect of changes in cellular and extra-cellular mechanical properties and identify mechanistic pathways for cancer progression that can be targeted for the prediction, treatment, and prevention of cancer.

Potential field cellular automata model for pedestrian flow

NASA Astrophysics Data System (ADS)

Zhang, Peng; Jian, Xiao-Xia; Wong, S. C.; Choi, Keechoo

2012-02-01

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

CATS - A process-based model for turbulent turbidite systems at the reservoir scale

NASA Astrophysics Data System (ADS)

Teles, Vanessa; Chauveau, Benoît; Joseph, Philippe; Weill, Pierre; Maktouf, Fakher

2016-09-01

The Cellular Automata for Turbidite systems (CATS) model is intended to simulate the fine architecture and facies distribution of turbidite reservoirs with a multi-event and process-based approach. The main processes of low-density turbulent turbidity flow are modeled: downslope sediment-laden flow, entrainment of ambient water, erosion and deposition of several distinct lithologies. This numerical model, derived from (Salles, 2006; Salles et al., 2007), proposes a new approach based on the Rouse concentration profile to consider the flow capacity to carry the sediment load in suspension. In CATS, the flow distribution on a given topography is modeled with local rules between neighboring cells (cellular automata) based on potential and kinetic energy balance and diffusion concepts. Input parameters are the initial flow parameters and a 3D topography at depositional time. An overview of CATS capabilities in different contexts is presented and discussed.

Simulation of Healing Threshold in Strain-Induced Inflammation Through a Discrete Informatics Model.

PubMed

Ibrahim, Israr Bin M; Sarma O V, Sanjay; Pidaparti, Ramana M

2018-05-01

Respiratory diseases such as asthma and acute respiratory distress syndrome as well as acute lung injury involve inflammation at the cellular level. The inflammation process is very complex and is characterized by the emergence of cytokines along with other changes in cellular processes. Due to the complexity of the various constituents that makes up the inflammation dynamics, it is necessary to develop models that can complement experiments to fully understand inflammatory diseases. In this study, we developed a discrete informatics model based on cellular automata (CA) approach to investigate the influence of elastic field (stretch/strain) on the dynamics of inflammation and account for probabilistic adaptation based on statistical interpretation of existing experimental data. Our simulation model investigated the effects of low, medium, and high strain conditions on inflammation dynamics. Results suggest that the model is able to indicate the threshold of innate healing of tissue as a response to strain experienced by the tissue. When strain is under the threshold, the tissue is still capable of adapting its structure to heal the damaged part. However, there exists a strain threshold where healing capability breaks down. The results obtained demonstrate that the developed discrete informatics based CA model is capable of modeling and giving insights into inflammation dynamics parameters under various mechanical strain/stretch environments.

A computational and cellular solids approach to the stiffness-based design of bone scaffolds.

PubMed

Norato, J A; Wagoner Johnson, A J

2011-09-01

We derive a cellular solids approach to the design of bone scaffolds for stiffness and pore size. Specifically, we focus on scaffolds made of stacked, alternating, orthogonal layers of hydroxyapatite rods, such as those obtained via micro-robotic deposition, and aim to determine the rod diameter, spacing and overlap required to obtain specified elastic moduli and pore size. To validate and calibrate the cellular solids model, we employ a finite element model and determine the effective scaffold moduli via numerical homogenization. In order to perform an efficient, automated execution of the numerical studies, we employ a geometry projection method so that analyses corresponding to different scaffold dimensions can be performed on a fixed, non-conforming mesh. Based on the developed model, we provide design charts to aid in the selection of rod diameter, spacing and overlap to be used in the robotic deposition to attain desired elastic moduli and pore size.

A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

NASA Astrophysics Data System (ADS)

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-03-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent.

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

PubMed Central

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-01-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent. PMID:28272488

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

PubMed

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

PubMed

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models.

Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

PubMed Central

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models. PMID:24244124

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

PubMed Central

Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

2012-01-01

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

Dengue fever spreading based on probabilistic cellular automata with two lattices

NASA Astrophysics Data System (ADS)

Pereira, F. M. M.; Schimit, P. H. T.

2018-06-01

Modeling and simulation of mosquito-borne diseases have gained attention due to a growing incidence in tropical countries in the past few years. Here, we study the dengue spreading in a population modeled by cellular automata, where there are two lattices to model the human-mosquitointeraction: one lattice for human individuals, and one lattice for mosquitoes in order to enable different dynamics in populations. The disease considered is the dengue fever with one, two or three different serotypes coexisting in population. Although many regions exhibit the incidence of only one serotype, here we set a complete framework to also study the occurrence of two and three serotypes at the same time in a population. Furthermore, the flexibility of the model allows its use to other mosquito-borne diseases, like chikungunya, yellow fever and malaria. An approximation of the cellular automata is proposed in terms of ordinary differential equations; the spreading of mosquitoes is studied and the influence of some model parameters are analyzed with numerical simulations. Finally, a method to combat dengue spreading is simulated based on a reduction of mosquito birth and mosquito bites in population.

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

PubMed

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

PubMed

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

PubMed Central

Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

2010-01-01

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

Mathematical Modeling and Experimental Validation of Nanoemulsion-Based Drug Transport across Cellular Barriers.

PubMed

Kadakia, Ekta; Shah, Lipa; Amiji, Mansoor M

2017-07-01

Nanoemulsions have shown potential in delivering drug across epithelial and endothelial cell barriers, which express efflux transporters. However, their transport mechanisms are not entirely understood. Our goal was to investigate the cellular permeability of nanoemulsion-encapsulated drugs and apply mathematical modeling to elucidate transport mechanisms and sensitive nanoemulsion attributes. Transport studies were performed in Caco-2 cells, using fish oil nanoemulsions and a model substrate, rhodamine-123. Permeability data was modeled using a semi-mechanistic approach, capturing the following cellular processes: endocytotic uptake of the nanoemulsion, release of rhodamine-123 from the nanoemulsion, efflux and passive permeability of rhodamine-123 in aqueous solution. Nanoemulsions not only improved the permeability of rhodamine-123, but were also less sensitive to efflux transporters. The model captured bidirectional permeability results and identified sensitive processes, such as the release of the nanoemulsion-encapsulated drug and cellular uptake of the nanoemulsion. Mathematical description of cellular processes, improved our understanding of transport mechanisms, such as nanoemulsions don't inhibit efflux to improve drug permeability. Instead, their endocytotic uptake, results in higher intracellular drug concentrations, thereby increasing the concentration gradient and transcellular permeability across biological barriers. Modeling results indicated optimizing nanoemulsion attributes like the droplet size and intracellular drug release rate, may further improve drug permeability.

Geometric confinement influences cellular mechanical properties I -- adhesion area dependence.

PubMed

Su, Judith; Jiang, Xingyu; Welsch, Roy; Whitesides, George M; So, Peter T C

2007-06-01

Interactions between the cell and the extracellular matrix regulate a variety of cellular properties and functions, including cellular rheology. In the present study of cellular adhesion, area was controlled by confining NIH 3T3 fibroblast cells to circular micropatterned islands of defined size. The shear moduli of cells adhering to islands of well defined geometry, as measured by magnetic microrheometry, was found to have a significantly lower variance than those of cells allowed to spread on unpatterned surfaces. We observe that the area of cellular adhesion influences shear modulus. Rheological measurements further indicate that cellular shear modulus is a biphasic function of cellular adhesion area with stiffness decreasing to a minimum value for intermediate areas of adhesion, and then increasing for cells on larger patterns. We propose a simple hypothesis: that the area of adhesion affects cellular rheological properties by regulating the structure of the actin cytoskeleton. To test this hypothesis, we quantified the volume fraction of polymerized actin in the cytosol by staining with fluorescent phalloidin and imaging using quantitative 3D microscopy. The polymerized actin volume fraction exhibited a similar biphasic dependence on adhesion area. Within the limits of our simplifying hypothesis, our experimental results permit an evaluation of the ability of established, micromechanical models to predict the cellular shear modulus based on polymerized actin volume fraction. We investigated the "tensegrity", "cellular-solids", and "biopolymer physics" models that have, respectively, a linear, quadratic, and 5/2 dependence on polymerized actin volume fraction. All three models predict that a biphasic trend in polymerized actin volume fraction as a function of adhesion area will result in a biphasic behavior in shear modulus. Our data favors a higher-order dependence on polymerized actin volume fraction. Increasingly better experimental agreement is observed for the tensegrity, the cellular solids, and the biopolymer models respectively. Alternatively if we postulate the existence of a critical actin volume fraction below which the shear modulus vanishes, the experimental data can be equivalently described by a model with an almost linear dependence on polymerized actin volume fraction; this observation supports a tensegrity model with a critical actin volume fraction.

QUANTITATIVE IN VITRO MEASUREMENT OF CELLULAR PROCESSES CRITICAL TO THE DEVELOPMENT OF NEURAL CONNECTIVITY USING HCA.

EPA Science Inventory

New methods are needed to screen thousands of environmental chemicals for toxicity, including developmental neurotoxicity. In vitro, cell-based assays that model key cellular events have been proposed for high throughput screening of chemicals for developmental neurotoxicity. Whi...

Role of cellular adhesions in tissue dynamics spectroscopy

NASA Astrophysics Data System (ADS)

Merrill, Daniel A.; An, Ran; Turek, John; Nolte, David

2014-02-01

Cellular adhesions play a critical role in cell behavior, and modified expression of cellular adhesion compounds has been linked to various cancers. We tested the role of cellular adhesions in drug response by studying three cellular culture models: three-dimensional tumor spheroids with well-developed cellular adhesions and extracellular matrix (ECM), dense three-dimensional cell pellets with moderate numbers of adhesions, and dilute three-dimensional cell suspensions in agarose having few adhesions. Our technique for measuring the drug response for the spheroids and cell pellets was biodynamic imaging (BDI), and for the suspensions was quasi-elastic light scattering (QELS). We tested several cytoskeletal chemotherapeutic drugs (nocodazole, cytochalasin-D, paclitaxel, and colchicine) on three cancer cell lines chosen from human colorectal adenocarcinoma (HT-29), human pancreatic carcinoma (MIA PaCa-2), and rat osteosarcoma (UMR-106) to exhibit differences in adhesion strength. Comparing tumor spheroid behavior to that of cell suspensions showed shifts in the spectral motion of the cancer tissues that match predictions based on different degrees of cell-cell contacts. The HT-29 cell line, which has the strongest adhesions in the spheroid model, exhibits anomalous behavior in some cases. These results highlight the importance of using three-dimensional tissue models in drug screening with cellular adhesions being a contributory factor in phenotypic differences between the drug responses of tissue and cells.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Sub-cellular force microscopy in single normal and cancer cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Babahosseini, H.; Carmichael, B.; Strobl, J.S.

2015-08-07

This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer andmore » significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. - Highlights: • The cells are modeled as a triple-layered structure using Generalized Maxwell model. • The sub-domains include membrane/cortex, cytoplasm/nucleus, and nuclear/integrin. • Biomechanics of corresponding sub-domains are compared among normal and cancer cells. • Viscoelasticity of sub-domains show a decreasing trend from normal to cancer cells. • The decreasing trend becomes most significant in the deeper sub-domain.« less

IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES)

PubMed Central

Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

2016-01-01

Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5′ untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

Challenges in structural approaches to cell modeling.

PubMed

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A

2016-07-31

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells

PubMed Central

Chudasama, Vaishali L.; Ovacik, Meric A.; Abernethy, Darrell R.

2015-01-01

Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. PMID:26163548

Does Aspartic Acid Racemization Constrain the Depth Limit of the Subsurface Biosphere?

NASA Technical Reports Server (NTRS)

Onstott, T C.; Magnabosco, C.; Aubrey, A. D.; Burton, A. S.; Dworkin, J. P.; Elsila, J. E.; Grunsfeld, S.; Cao, B. H.; Hein, J. E.; Glavin, D. P.;

Does aspartic acid racemization constrain the depth limit of the subsurface biosphere?

PubMed

Onstott, T C; Magnabosco, C; Aubrey, A D; Burton, A S; Dworkin, J P; Elsila, J E; Grunsfeld, S; Cao, B H; Hein, J E; Glavin, D P; Kieft, T L; Silver, B J; Phelps, T J; van Heerden, E; Opperman, D J; Bada, J L

2014-01-01

Previous studies of the subsurface biosphere have deduced average cellular doubling times of hundreds to thousands of years based upon geochemical models. We have directly constrained the in situ average cellular protein turnover or doubling times for metabolically active micro-organisms based on cellular amino acid abundances, D/L values of cellular aspartic acid, and the in vivo aspartic acid racemization rate. Application of this method to planktonic microbial communities collected from deep fractures in South Africa yielded maximum cellular amino acid turnover times of ~89 years for 1 km depth and 27 °C and 1-2 years for 3 km depth and 54 °C. The latter turnover times are much shorter than previously estimated cellular turnover times based upon geochemical arguments. The aspartic acid racemization rate at higher temperatures yields cellular protein doubling times that are consistent with the survival times of hyperthermophilic strains and predicts that at temperatures of 85 °C, cells must replace proteins every couple of days to maintain enzymatic activity. Such a high maintenance requirement may be the principal limit on the abundance of living micro-organisms in the deep, hot subsurface biosphere, as well as a potential limit on their activity. The measurement of the D/L of aspartic acid in biological samples is a potentially powerful tool for deep, fractured continental and oceanic crustal settings where geochemical models of carbon turnover times are poorly constrained. Experimental observations on the racemization rates of aspartic acid in living thermophiles and hyperthermophiles could test this hypothesis. The development of corrections for cell wall peptides and spores will be required, however, to improve the accuracy of these estimates for environmental samples. © 2013 John Wiley & Sons Ltd.

A multi-physics model for ultrasonically activated soft tissue.

PubMed

Suvranu De, Rahul

2017-02-01

A multi-physics model has been developed to investigate the effects of cellular level mechanisms on the thermomechanical response of ultrasonically activated soft tissue. Cellular level cavitation effects have been incorporated in the tissue level continuum model to accurately determine the thermodynamic states such as temperature and pressure. A viscoelastic material model is assumed for the macromechanical response of the tissue. The cavitation model based equation-of-state provides the additional pressure arising from evaporation of intracellular and cellular water by absorbing heat due to structural and viscoelastic heating in the tissue, and temperature to the continuum level thermomechanical model. The thermomechanical response of soft tissue is studied for the operational range of frequencies of oscillations and applied loads for typical ultrasonically activated surgical instruments. The model is shown to capture characteristics of ultrasonically activated soft tissue deformation and temperature evolution. At the cellular level, evaporation of water below the boiling temperature under ambient conditions is indicative of protein denaturation around the temperature threshold for coagulation of tissues. Further, with increasing operating frequency (or loading), the temperature rises faster leading to rapid evaporation of tissue cavity water, which may lead to accelerated protein denaturation and coagulation.

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

PubMed Central

Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan

2004-01-01

Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335

Three-dimensional cellular automata as a model of a seismic fault

NASA Astrophysics Data System (ADS)

Gálvez, G.; Muñoz, A.

2017-01-01

The Earth's crust is broken into a series of plates, whose borders are the seismic fault lines and it is where most of the earthquakes occur. This plating system can in principle be described by a set of nonlinear coupled equations describing the motion of the plates, its stresses, strains and other characteristics. Such a system of equations is very difficult to solve, and nonlinear parts leads to a chaotic behavior, which is not predictable. In 1989, Bak and Tang presented an earthquake model based on the sand pile cellular automata. The model though simple, provides similar results to those observed in actual earthquakes. In this work the cellular automata in three dimensions is proposed as a best model to approximate a seismic fault. It is noted that the three-dimensional model reproduces similar properties to those observed in real seismicity, especially, the Gutenberg-Richter law.

Surface tension and modeling of cellular intercalation during zebrafish gastrulation.

PubMed

Calmelet, Colette; Sepich, Diane

2010-04-01

In this paper we discuss a model of zebrafish embryo notochord development based on the effect of surface tension of cells at the boundaries. We study the process of interaction of mesodermal cells at the boundaries due to adhesion and cortical tension, resulting in cellular intercalation. From in vivo experiments, we obtain cell outlines of time-lapse images of cell movements during zebrafish embryo development. Using Cellular Potts Model, we calculate the total surface energy of the system of cells at different time intervals at cell contacts. We analyze the variations of total energy depending on nature of cell contacts. We demonstrate that our model can be viable by calculating the total surface energy value for experimentally observed configurations of cells and showing that in our model these configurations correspond to a decrease in total energy values in both two and three dimensions.

Particle acceleration in a complex solar active region modelled by a Cellular automata model

NASA Astrophysics Data System (ADS)

Dauphin, C.; Vilmer, N.; Anastasiadis, A.

2004-12-01

The models of cellular automat allowed to reproduce successfully several statistical properties of the solar flares. We use a cellular automat model based on the concept of self-organised critical system to model the evolution of the magnetic energy released in an eruptive active area. Each burst of magnetic energy released is assimilated to a process of magnetic reconnection. We will thus generate several current layers (RCS) where the particles are accelerated by a direct electric field. We calculate the energy gain of the particles (ions and electrons) for various types of magnetic configuration. We calculate the distribution function of the kinetic energy of the particles after their interactions with a given number of RCS for each type of configurations. We show that the relative efficiency of the acceleration of the electrons and the ions depends on the selected configuration.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

2011-11-01

There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

An efficient Cellular Potts Model algorithm that forbids cell fragmentation

NASA Astrophysics Data System (ADS)

Durand, Marc; Guesnet, Etienne

2016-11-01

The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in the scientific literature to evolve this model preserves connectivity of cells on a limited range of simulation temperature only. We present a new algorithm in which cell fragmentation is forbidden for all simulation temperatures. This allows to significantly enhance realism of the simulated patterns. It also increases the computational efficiency compared with the standard CPM algorithm even at same simulation temperature, thanks to the time spared in not doing unrealistic moves. Moreover, our algorithm restores the detailed balance equation, ensuring that the long-term stage is independent of the chosen acceptance rate and chosen path in the temperature space.

Cellularized Cellular Solids via Freeze-Casting.

PubMed

Christoph, Sarah; Kwiatoszynski, Julien; Coradin, Thibaud; Fernandes, Francisco M

2016-02-01

The elaboration of metabolically active cell-containing materials is a decisive step toward the successful application of cell based technologies. The present work unveils a new process allowing to simultaneously encapsulate living cells and shaping cell-containing materials into solid-state macroporous foams with precisely controlled morphology. Our strategy is based on freeze casting, an ice templating materials processing technique that has recently emerged for the structuration of colloids into macroporous materials. Our results indicate that it is possible to combine the precise structuration of the materials with cellular metabolic activity for the model organism Saccharomyces cerevisiae. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios

NASA Astrophysics Data System (ADS)

Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William

Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.

Advances in Reprogramming-Based Study of Neurologic Disorders

PubMed Central

Baldwin, Kristin K.

2015-01-01

The technology to convert adult human non-neural cells into neural lineages, through induced pluripotent stem cells (iPSCs), somatic cell nuclear transfer, and direct lineage reprogramming or transdifferentiation has progressed tremendously in recent years. Reprogramming-based approaches aimed at manipulating cellular identity have enormous potential for disease modeling, high-throughput drug screening, cell therapy, and personalized medicine. Human iPSC (hiPSC)-based cellular disease models have provided proof of principle evidence of the validity of this system. However, several challenges remain before patient-specific neurons produced by reprogramming can provide reliable insights into disease mechanisms or be efficiently applied to drug discovery and transplantation therapy. This review will first discuss limitations of currently available reprogramming-based methods in faithfully and reproducibly recapitulating disease pathology. Specifically, we will address issues such as culture heterogeneity, interline and inter-individual variability, and limitations of two-dimensional differentiation paradigms. Second, we will assess recent progress and the future prospects of reprogramming-based neurologic disease modeling. This includes three-dimensional disease modeling, advances in reprogramming technology, prescreening of hiPSCs and creating isogenic disease models using gene editing. PMID:25749371

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

Computational modelling of cellular level metabolism

NASA Astrophysics Data System (ADS)

Calvetti, D.; Heino, J.; Somersalo, E.

2008-07-01

The steady and stationary state inverse problems consist of estimating the reaction and transport fluxes, blood concentrations and possibly the rates of change of some of the concentrations based on data which are often scarce noisy and sampled over a population. The Bayesian framework provides a natural setting for the solution of this inverse problem, because a priori knowledge about the system itself and the unknown reaction fluxes and transport rates can compensate for the insufficiency of measured data, provided that the computational costs do not become prohibitive. This article identifies the computational challenges which have to be met when analyzing the steady and stationary states of multicompartment model for cellular metabolism and suggest stable and efficient ways to handle the computations. The outline of a computational tool based on the Bayesian paradigm for the simulation and analysis of complex cellular metabolic systems is also presented.

Transfer matrix modeling and experimental validation of cellular porous material with resonant inclusions.

PubMed

Doutres, Olivier; Atalla, Noureddine; Osman, Haisam

2015-06-01

Porous materials are widely used for improving sound absorption and sound transmission loss of vibrating structures. However, their efficiency is limited to medium and high frequencies of sound. A solution for improving their low frequency behavior while keeping an acceptable thickness is to embed resonant structures such as Helmholtz resonators (HRs). This work investigates the absorption and transmission acoustic performances of a cellular porous material with a two-dimensional periodic arrangement of HR inclusions. A low frequency model of a resonant periodic unit cell based on the parallel transfer matrix method is presented. The model is validated by comparison with impedance tube measurements and simulations based on both the finite element method and a homogenization based model. At the HR resonance frequency (i) the transmission loss is greatly improved and (ii) the sound absorption of the foam can be either decreased or improved depending on the HR tuning frequency and on the thickness and properties of the host foam. Finally, the diffuse field sound absorption and diffuse field sound transmission loss performance of a 2.6 m(2) resonant cellular material are measured. It is shown that the improvements observed at the Helmholtz resonant frequency on a single cell are confirmed at a larger scale.

Genetic GIScience: Toward a Place-Based Synthesis of the Genome, Exposome, and Behavome

PubMed Central

Jacquez, Geoffrey M.; Sabel, Clive E.; Shi, Chen

2015-01-01

The exposome, defined as the totality of an individual’s exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic geographic information science (Genetic GISc) that is founded on the exposome, genome+ and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal and behavioral determinants (the behavome). Genetic GISc poses three key needs: First, a mathematical foundation for emergent theory; Second, process-based models that bridge biological and geographic scales; Third, biologically plausible estimates of space-time disease lags. Compartmental models are a possible solution; this article develops two models using pancreatic cancer as an exemplar. The first models carcinogenesis based on the cascade of mutations and cellular changes that lead to metastatic cancer. The second models cancer stages by diagnostic criteria. These provide empirical estimates of the distribution of latencies in cellular states and disease stages, and maps of the burden of yet to be diagnosed disease. This approach links our emerging knowledge of genomics to cancer progression at the cellular level, to individuals and their cancer stage at diagnosis, to geographic distributions of cancer in extant populations. These methodological developments and exemplar provide the basis for a new synthesis in health geography: genetic geographic information science. PMID:26339073

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

An outline of cellular automaton universe via cosmological KdV equation

NASA Astrophysics Data System (ADS)

Christianto, V.; Smarandache, F.; Umniyati, Y.

2018-03-01

It has been known for long time that the cosmic sound wave was there since the early epoch of the Universe. Signatures of its existence are abound. However, such a sound wave model of cosmology is rarely developed fully into a complete framework. This paper can be considered as our second attempt towards such a complete description of the Universe based on soliton wave solution of cosmological KdV equation. Then we advance further this KdV equation by virtue of Cellular Automaton method to solve the PDEs. We submit wholeheartedly Robert Kuruczs hypothesis that Big Bang should be replaced with a finite cellular automaton universe with no expansion [4][5]. Nonetheless, we are fully aware that our model is far from being complete, but it appears the proposed cellular automaton model of the Universe is very close in spirit to what Konrad Zuse envisaged long time ago. It is our hope that the new proposed method can be verified with observation data. But we admit that our model is still in its infancy, more researches are needed to fill all the missing details.

[Risk-oriented model of the control of the level of electric magnetic fields of base stations of cellular communications].

PubMed

Lutsenko, L A; Tulakin, A V; Egorova, A M; Mikhailova, O M; Gvozdeva, L L; Chigryay, E K

The purpose of this study was to give the description of harmful effects of the impact of electromagnetic radiations from base stations of cellular communication as the most common sources of radio frequencies of electromagnetic fields in the environment. The highest values of the energy flux density were measured on the roofs of houses where antennas are installed - more than 10 pW/cm. The lowest values were recorded in inside premises with expositions of 0.1-1 pW/cm. In the close location of the railway station to the base stations of the cellular communication there was seen a cumulative effect. There are proposed both new safe hygienic approaches to the control for the safety of the work of base station and protective measures.

Characterizing heterogeneous cellular responses to perturbations.

PubMed

Slack, Michael D; Martinez, Elisabeth D; Wu, Lani F; Altschuler, Steven J

2008-12-09

Cellular populations have been widely observed to respond heterogeneously to perturbation. However, interpreting the observed heterogeneity is an extremely challenging problem because of the complexity of possible cellular phenotypes, the large dimension of potential perturbations, and the lack of methods for separating meaningful biological information from noise. Here, we develop an image-based approach to characterize cellular phenotypes based on patterns of signaling marker colocalization. Heterogeneous cellular populations are characterized as mixtures of phenotypically distinct subpopulations, and responses to perturbations are summarized succinctly as probabilistic redistributions of these mixtures. We apply our method to characterize the heterogeneous responses of cancer cells to a panel of drugs. We find that cells treated with drugs of (dis-)similar mechanism exhibit (dis-)similar patterns of heterogeneity. Despite the observed phenotypic diversity of cells observed within our data, low-complexity models of heterogeneity were sufficient to distinguish most classes of drug mechanism. Our approach offers a computational framework for assessing the complexity of cellular heterogeneity, investigating the degree to which perturbations induce redistributions of a limited, but nontrivial, repertoire of underlying states and revealing functional significance contained within distinct patterns of heterogeneous responses.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

PubMed Central

Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

2013-01-01

Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

An improved cellular automaton method to model multispecies biofilms.

PubMed

Tang, Youneng; Valocchi, Albert J

2013-10-01

Biomass-spreading rules used in previous cellular automaton methods to simulate multispecies biofilm introduced extensive mixing between different biomass species or resulted in spatially discontinuous biomass concentration and distribution; this caused results based on the cellular automaton methods to deviate from experimental results and those from the more computationally intensive continuous method. To overcome the problems, we propose new biomass-spreading rules in this work: Excess biomass spreads by pushing a line of grid cells that are on the shortest path from the source grid cell to the destination grid cell, and the fractions of different biomass species in the grid cells on the path change due to the spreading. To evaluate the new rules, three two-dimensional simulation examples are used to compare the biomass distribution computed using the continuous method and three cellular automaton methods, one based on the new rules and the other two based on rules presented in two previous studies. The relationship between the biomass species is syntrophic in one example and competitive in the other two examples. Simulation results generated using the cellular automaton method based on the new rules agree much better with the continuous method than do results using the other two cellular automaton methods. The new biomass-spreading rules are no more complex to implement than the existing rules. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interface Pattern Selection in Directional Solidification

NASA Technical Reports Server (NTRS)

Trivedi, Rohit; Tewari, Surendra N.

2001-01-01

The central focus of this research is to establish key scientific concepts that govern the selection of cellular and dendritic patterns during the directional solidification of alloys. Ground-based studies have established that the conditions under which cellular and dendritic microstructures form are precisely where convection effects are dominant in bulk samples. Thus, experimental data can not be obtained terrestrially under pure diffusive regime. Furthermore, reliable theoretical models are not yet possible which can quantitatively incorporate fluid flow in the pattern selection criterion. Consequently, microgravity experiments on cellular and dendritic growth are designed to obtain benchmark data under diffusive growth conditions that can be quantitatively analyzed and compared with the rigorous theoretical model to establish the fundamental principles that govern the selection of specific microstructure and its length scales. In the cellular structure, different cells in an array are strongly coupled so that the cellular pattern evolution is controlled by complex interactions between thermal diffusion, solute diffusion and interface effects. These interactions give infinity of solutions, and the system selects only a narrow band of solutions. The aim of this investigation is to obtain benchmark data and develop a rigorous theoretical model that will allow us to quantitatively establish the physics of this selection process.

Single-cell topological RNA-Seq analysis reveals insights into cellular differentiation and development

PubMed Central

Rizvi, Abbas H.; Camara, Pablo G.; Kandror, Elena K.; Roberts, Thomas J.; Schieren, Ira; Maniatis, Tom; Rabadan, Raul

2017-01-01

Transcriptional programs control cellular lineage commitment and differentiation during development. Understanding cell fate has been advanced by studying single-cell RNA-seq, but is limited by the assumptions of current analytic methods regarding the structure of data. We present single-cell topological data analysis (scTDA), an algorithm for topology-based computational analyses to study temporal, unbiased transcriptional regulation. Compared to other methods, scTDA is a non-linear, model-independent, unsupervised statistical framework that can characterize transient cellular states. We applied scTDA to the analysis of murine embryonic stem cell (mESC) differentiation in vitro in response to inducers of motor neuron differentiation. scTDA resolved asynchrony and continuity in cellular identity over time, and identified four transient states (pluripotent, precursor, progenitor, and fully differentiated cells) based on changes in stage-dependent combinations of transcription factors, RNA-binding proteins and long non-coding RNAs. scTDA can be applied to study asynchronous cellular responses to either developmental cues or environmental perturbations. PMID:28459448

A Nanoflare-Based Cellular Automaton Model and the Observed Properties of the Coronal Plasma

NASA Technical Reports Server (NTRS)

Lopez-Fuentes, Marcelo; Klimchuk, James Andrew

2016-01-01

We use the cellular automaton model described in Lopez Fuentes and Klimchuk to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode/XRT and SDOAIA instruments. The comparison is based on the statistical properties of synthetic and observed loop light curves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasma in AR coronal loops. The typical intensity fluctuations have amplitudes of 10 percent - 15 percent both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.

A NANOFLARE-BASED CELLULAR AUTOMATON MODEL AND THE OBSERVED PROPERTIES OF THE CORONAL PLASMA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fuentes, Marcelo López; Klimchuk, James A., E-mail: lopezf@iafe.uba.ar

2016-09-10

We use the cellular automaton model described in López Fuentes and Klimchuk to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode /XRT and SDO /AIA instruments. The comparison is based on the statistical properties of synthetic and observed loop light curves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasmamore » in AR coronal loops. The typical intensity fluctuations have amplitudes of 10%–15% both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.« less

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

Quantifying the driving factors for language shift in a bilingual region.

PubMed

Prochazka, Katharina; Vogl, Gero

2017-04-25

Many of the world's around 6,000 languages are in danger of disappearing as people give up use of a minority language in favor of the majority language in a process called language shift. Language shift can be monitored on a large scale through the use of mathematical models by way of differential equations, for example, reaction-diffusion equations. Here, we use a different approach: we propose a model for language dynamics based on the principles of cellular automata/agent-based modeling and combine it with very detailed empirical data. Our model makes it possible to follow language dynamics over space and time, whereas existing models based on differential equations average over space and consequently provide no information on local changes in language use. Additionally, cellular automata models can be used even in cases where models based on differential equations are not applicable, for example, in situations where one language has become dispersed and retreated to language islands. Using data from a bilingual region in Austria, we show that the most important factor in determining the spread and retreat of a language is the interaction with speakers of the same language. External factors like bilingual schools or parish language have only a minor influence.

Simulating Microdosimetry of Environmental Chemicals for EPA’s Virtual Liver

EPA Science Inventory

US EPA Virtual Liver (v-Liver) is a cellular systems model of hepatic tissues aimed at predicting chemical-induced adverse effects through agent-based modeling. A primary objective of the project is to extrapolate in vitro data to in vivo outcomes. Agent-based approaches to tissu...

Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers

PubMed Central

Thomas-Vaslin, Véronique; Six, Adrien; Ganascia, Jean-Gabriel; Bersini, Hugues

2013-01-01

Dynamic modeling of lymphocyte behavior has primarily been based on populations based differential equations or on cellular agents moving in space and interacting each other. The final steps of this modeling effort are expressed in a code written in a programing language. On account of the complete lack of standardization of the different steps to proceed, we have to deplore poor communication and sharing between experimentalists, theoreticians and programmers. The adoption of diagrammatic visual computer language should however greatly help the immunologists to better communicate, to more easily identify the models similarities and facilitate the reuse and extension of existing software models. Since immunologists often conceptualize the dynamical evolution of immune systems in terms of “state-transitions” of biological objects, we promote the use of unified modeling language (UML) state-transition diagram. To demonstrate the feasibility of this approach, we present a UML refactoring of two published models on thymocyte differentiation. Originally built with different modeling strategies, a mathematical ordinary differential equation-based model and a cellular automata model, the two models are now in the same visual formalism and can be compared. PMID:24101919

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

Body composition analysis: Cellular level modeling of body component ratios.

PubMed

Wang, Z; Heymsfield, S B; Pi-Sunyer, F X; Gallagher, D; Pierson, R N

2008-01-01

During the past two decades, a major outgrowth of efforts by our research group at St. Luke's-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively 'stable', for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Mathematical Modeling of Tuberculosis Bacillary Counts and Cellular Populations in the Organs of Infected Mice

PubMed Central

Bru, Antonio; Cardona, Pere-Joan

2010-01-01

Background Mycobacterium tuberculosis is a particularly aggressive microorganism and the host's defense is based on the induction of cellular immunity, in which the creation of a granulomatous structure has an important role. Methodology We present here a new 2D cellular automata model based on the concept of a multifunctional process that includes key factors such as the chemokine attraction of the cells; the role of innate immunity triggered by natural killers; the presence of neutrophils; apoptosis and necrosis of infected macrophages; the removal of dead cells by macrophages, which induces the production of foamy macrophages (FMs); the life cycle of the bacilli as a determinant for the evolution of infected macrophages; and the immune response. Results The results obtained after the inclusion of two degrees of tolerance to the inflammatory response triggered by the infection shows that the model can cover a wide spectrum, ranging from highly-tolerant (i.e. mice) to poorly-tolerant hosts (i.e. mini-pigs or humans). Conclusions This model suggest that stopping bacillary growth at the onset of the infection might be difficult and the important role played by FMs in bacillary drainage in poorly-tolerant hosts together with apoptosis and innate lymphocytes. It also shows the poor ability of the cellular immunity to control the infection, provides a clear protective character to the granuloma, due its ability to attract a sufficient number of cells, and explains why an already infected host can be constantly reinfected. PMID:20886087

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

PubMed

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

A novel chaotic based image encryption using a hybrid model of deoxyribonucleic acid and cellular automata

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi

2015-08-01

Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.

Establishment of a translational endothelial cell model using directed differentiation of induced pluripotent stem cells from Cynomolgus monkey.

PubMed

Thoma, Eva C; Heckel, Tobias; Keller, David; Giroud, Nicolas; Leonard, Brian; Christensen, Klaus; Roth, Adrian; Bertinetti-Lapatki, Cristina; Graf, Martin; Patsch, Christoph

2016-10-25

Due to their broad differentiation potential, pluripotent stem cells (PSCs) offer a promising approach for generating relevant cellular models for various applications. While human PSC-based cellular models are already advanced, similar systems for non-human primates (NHPs) are still lacking. However, as NHPs are the most appropriate animals for evaluating the safety of many novel pharmaceuticals, the availability of in vitro systems would be extremely useful to bridge the gap between cellular and animal models. Here, we present a NHP in vitro endothelial cell system using induced pluripotent stem cells (IPSCs) from Cynomolgus monkey (Macaca fascicularis). Based on an adapted protocol for human IPSCs, we directly differentiated macaque IPSCs into endothelial cells under chemically defined conditions. The resulting endothelial cells can be enriched using immuno-magnetic cell sorting and display endothelial marker expression and function. RNA sequencing revealed that the differentiation process closely resembled vasculogenesis. Moreover, we showed that endothelial cells derived from macaque and human IPSCs are highly similar with respect to gene expression patterns and key endothelial functions, such as inflammatory responses. These data demonstrate the power of IPSC differentiation technology to generate defined cell types for use as translational in vitro models to compare cell type-specific responses across species.

Convergence and attractivity of memristor-based cellular neural networks with time delays.

PubMed

Qin, Sitian; Wang, Jun; Xue, Xiaoping

2015-03-01

This paper presents theoretical results on the convergence and attractivity of memristor-based cellular neural networks (MCNNs) with time delays. Based on a realistic memristor model, an MCNN is modeled using a differential inclusion. The essential boundedness of its global solutions is proven. The state of MCNNs is further proven to be convergent to a critical-point set located in saturated region of the activation function, when the initial state locates in a saturated region. It is shown that the state convergence time period is finite and can be quantitatively estimated using given parameters. Furthermore, the positive invariance and attractivity of state in non-saturated regions are also proven. The simulation results of several numerical examples are provided to substantiate the results. Copyright © 2014 Elsevier Ltd. All rights reserved.

The effect of nanoparticle size on in vivo pharmacokinetics and cellular interaction

PubMed Central

Hoshyar, Nazanin; Gray, Samantha; Han, Hongbin; Bao, Gang

2016-01-01

Nanoparticle-based technologies offer exciting new approaches to disease diagnostics and therapeutics. To take advantage of unique properties of nanoscale materials and structures, the size, shape and/or surface chemistry of nanoparticles need to be optimized, allowing their functionalities to be tailored for different biomedical applications. Here we review the effects of nanoparticle size on cellular interaction and in vivo pharmacokinetics, including cellular uptake, biodistribution and circulation half-life of nanoparticles. Important features of nanoparticle probes for molecular imaging and modeling of nanoparticle size effects are also discussed. PMID:27003448

Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences

NASA Astrophysics Data System (ADS)

Ding, Ning; Zhang, Hui; Chen, Tao; Peter, B. Luh

2015-06-01

As a physical model, the cellular automata (CA) model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees’ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees’ walk preference and how evacuee’s psychology influences their behaviors are introduced into this model. Evacuees’ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants. Project supported by the National Basic Research Program of China (Grant No. 2012CB719705) and the National Natural Science Foundation of China (Grant Nos. 91224008, 91024032, and 71373139).

Origami interleaved tube cellular materials

NASA Astrophysics Data System (ADS)

Cheung, Kenneth C.; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

2014-09-01

A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis.

Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

NASA Astrophysics Data System (ADS)

Liu, Z.; Li, Y.

2018-04-01

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS).

PubMed

Vempati, Uma D; Chung, Caty; Mader, Chris; Koleti, Amar; Datar, Nakul; Vidović, Dušica; Wrobel, David; Erickson, Sean; Muhlich, Jeremy L; Berriz, Gabriel; Benes, Cyril H; Subramanian, Aravind; Pillai, Ajay; Shamu, Caroline E; Schürer, Stephan C

2014-06-01

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available. © 2014 Society for Laboratory Automation and Screening.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Ciona intestinalis notochord as a new model to investigate the cellular and molecular mechanisms of tubulogenesis.

PubMed

Denker, Elsa; Jiang, Di

2012-05-01

Biological tubes are a prevalent structural design across living organisms. They provide essential functions during the development and adult life of an organism. Increasing progress has been made recently in delineating the cellular and molecular mechanisms underlying tubulogenesis. This review aims to introduce ascidian notochord morphogenesis as an interesting model system to study the cell biology of tube formation, to a wider cell and developmental biology community. We present fundamental morphological and cellular events involved in notochord morphogenesis, compare and contrast them with other more established tubulogenesis model systems, and point out some unique features, including bipolarity of the notochord cells, and using cell shape changes and cell rearrangement to connect lumens. We highlight some initial findings in the molecular mechanisms of notochord morphogenesis. Based on these findings, we present intriguing problems and put forth hypotheses that can be addressed in future studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling mechanical interactions in growing populations of rod-shaped bacteria

NASA Astrophysics Data System (ADS)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

A fuzzy-theory-based behavioral model for studying pedestrian evacuation from a single-exit room

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lo, Siuming

2016-08-01

Many mass events in recent years have highlighted the importance of research on pedestrian evacuation dynamics. A number of models have been developed to analyze crowd behavior under evacuation situations. However, few focus on pedestrians' decision-making with respect to uncertainty, vagueness and imprecision. In this paper, a discrete evacuation model defined on the cellular space is proposed according to the fuzzy theory which is able to describe imprecise and subjective information. Pedestrians' percept information and various characteristics are regarded as fuzzy input. Then fuzzy inference systems with rule bases, which resemble human reasoning, are established to obtain fuzzy output that decides pedestrians' movement direction. This model is tested in two scenarios, namely in a single-exit room with and without obstacles. Simulation results reproduce some classic dynamics phenomena discovered in real building evacuation situations, and are consistent with those in other models and experiments. It is hoped that this study will enrich movement rules and approaches in traditional cellular automaton models for evacuation dynamics.

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

An instructional design process based on expert knowledge for teaching students how mechanisms are explained.

PubMed

Trujillo, Caleb M; Anderson, Trevor R; Pelaez, Nancy J

2016-06-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. Copyright © 2016 The American Physiological Society.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained

PubMed Central

Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. PMID:27231262

An image-based skeletal dosimetry model for the ICRP reference adult female—internal electron sources

NASA Astrophysics Data System (ADS)

O'Reilly, Shannon E.; DeWeese, Lindsay S.; Maynard, Matthew R.; Rajon, Didier A.; Wayson, Michael B.; Marshall, Emily L.; Bolch, Wesley E.

2016-12-01

An image-based skeletal dosimetry model for internal electron sources was created for the ICRP-defined reference adult female. Many previous skeletal dosimetry models, which are still employed in commonly used internal dosimetry software, do not properly account for electron escape from trabecular spongiosa, electron cross-fire from cortical bone, and the impact of marrow cellularity on active marrow self-irradiation. Furthermore, these existing models do not employ the current ICRP definition of a 50 µm bone endosteum (or shallow marrow). Each of these limitations was addressed in the present study. Electron transport was completed to determine specific absorbed fractions to both active and shallow marrow of the skeletal regions of the University of Florida reference adult female. The skeletal macrostructure and microstructure were modeled separately. The bone macrostructure was based on the whole-body hybrid computational phantom of the UF series of reference models, while the bone microstructure was derived from microCT images of skeletal region samples taken from a 45 years-old female cadaver. The active and shallow marrow are typically adopted as surrogate tissue regions for the hematopoietic stem cells and osteoprogenitor cells, respectively. Source tissues included active marrow, inactive marrow, trabecular bone volume, trabecular bone surfaces, cortical bone volume, and cortical bone surfaces. Marrow cellularity was varied from 10 to 100 percent for active marrow self-irradiation. All other sources were run at the defined ICRP Publication 70 cellularity for each bone site. A total of 33 discrete electron energies, ranging from 1 keV to 10 MeV, were either simulated or analytically modeled. The method of combining skeletal macrostructure and microstructure absorbed fractions assessed using MCNPX electron transport was found to yield results similar to those determined with the PIRT model applied to the UF adult male skeletal dosimetry model. Calculated skeletal averaged absorbed fractions for each source-target combination were found to follow similar trends of more recent dosimetry models (image-based models) but did not follow results from skeletal models based upon assumptions of an infinite expanse of trabecular spongiosa.

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Current State-of-the-Art 3D Tissue Models and Their Compatibility with Live Cell Imaging.

PubMed

Bardsley, Katie; Deegan, Anthony J; El Haj, Alicia; Yang, Ying

2017-01-01

Mammalian cells grow within a complex three-dimensional (3D) microenvironment where multiple cells are organized and surrounded by extracellular matrix (ECM). The quantity and types of ECM components, alongside cell-to-cell and cell-to-matrix interactions dictate cellular differentiation, proliferation and function in vivo. To mimic natural cellular activities, various 3D tissue culture models have been established to replace conventional two dimensional (2D) culture environments. Allowing for both characterization and visualization of cellular activities within possibly bulky 3D tissue models presents considerable challenges due to the increased thickness and subsequent light scattering features of such 3D models. In this chapter, state-of-the-art methodologies used to establish 3D tissue models are discussed, first with a focus on both scaffold-free and scaffold-based 3D tissue model formation. Following on, multiple 3D live cell imaging systems, mainly optical imaging modalities, are introduced. Their advantages and disadvantages are discussed, with the aim of stimulating more research in this highly demanding research area.

Dynamic behavior of cellular materials and cellular structures: Experiments and modeling

NASA Astrophysics Data System (ADS)

Gao, Ziyang

Cellular solids, including cellular materials and cellular structures (CMS), have attracted people's great interests because of their low densities and novel physical, mechanical, thermal, electrical and acoustic properties. They offer potential for lightweight structures, energy absorption, thermal management, etc. Therefore, the studies of cellular solids have become one of the hottest research fields nowadays. From energy absorption point of view, any plastically deformed structures can be divided into two types (called type I and type II), and the basic cells of the CMS may take the configurations of these two types of structures. Accordingly, separated discussions are presented in this thesis. First, a modified 1-D model is proposed and numerically solved for a typical type II structure. Good agreement is achieved with the previous experimental data, hence is used to simulate the dynamic behavior of a type II chain. Resulted from different load speeds, interesting collapse modes are observed, and the parameters which govern the cell's post-collapse behavior are identified through a comprehensive non-dimensional analysis on general cellular chains. Secondly, the MHS specimens are chosen as an example of type I foam materials because of their good uniformity of the cell geometry. An extensive experimental study was carried out, where more attention was paid to their responses to dynamic loadings. Great enhancement of the stress-strain curve was observed in dynamic cases, and the energy absorption capacity is found to be several times higher than that of the commercial metal foams. Based on the experimental study, finite elemental simulations and theoretical modeling are also conducted, achieving good agreements and demonstrating the validities of those models. It is believed that the experimental, numerical and analytical results obtained in the present study will certainly deepen the understanding of the unsolved fundamental issues on the mechanical behavior of cellular solids and make substantial contributions to the theoretical advance of impact dynamics.

Agent-Based Computational Modeling of Cell Culture ...

EPA Pesticide Factsheets

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

Transport of fluid and solutes in the body I. Formulation of a mathematical model.

PubMed

Gyenge, C C; Bowen, B D; Reed, R K; Bert, J L

1999-09-01

A compartmental model of short-term whole body fluid, protein, and ion distribution and transport is formulated. The model comprises four compartments: a vascular and an interstitial compartment, each with an embedded cellular compartment. The present paper discusses the assumptions on which the model is based and describes the equations that make up the model. Fluid and protein transport parameters from a previously validated model as well as ionic exchange parameters from the literature or from statistical estimation [see companion paper: C. C. Gyenge, B. D. Bowen, R. K. Reed, and J. L. Bert. Am. J. Physiol. 277 (Heart Circ. Physiol. 46): H1228-H1240, 1999] are used in formulating the model. The dynamic model has the ability to simulate 1) transport across the capillary membrane of fluid, proteins, and small ions and their distribution between the vascular and interstitial compartments; 2) the changes in extracellular osmolarity; 3) the distribution and transport of water and ions associated with each of the cellular compartments; 4) the cellular transmembrane potential; and 5) the changes of volume in the four fluid compartments. The validation and testing of the proposed model against available experimental data are presented in the companion paper.

The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

PubMed

Agnati, L F; Guidolin, D; Fuxe, K

2007-01-01

A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed.

Towards mechanism-based simulation of impact damage using exascale computing

NASA Astrophysics Data System (ADS)

Shterenlikht, Anton; Margetts, Lee; McDonald, Samuel; Bourne, Neil K.

2017-01-01

Over the past 60 years, the finite element method has been very successful in modelling deformation in engineering structures. However the method requires the definition of constitutive models that represent the response of the material to applied loads. There are two issues. Firstly, the models are often difficult to define. Secondly, there is often no physical connection between the models and the mechanisms that accommodate deformation. In this paper, we present a potentially disruptive two-level strategy which couples the finite element method at the macroscale with cellular automata at the mesoscale. The cellular automata are used to simulate mechanisms, such as crack propagation. The stress-strain relationship emerges as a continuum mechanics scale interpretation of changes at the micro- and meso-scales. Iterative two-way updating between the cellular automata and finite elements drives the simulation forward as the material undergoes progressive damage at high strain rates. The strategy is particularly attractive on large-scale computing platforms as both methods scale well on tens of thousands of CPUs.

Quantifying the driving factors for language shift in a bilingual region

PubMed Central

Prochazka, Katharina; Vogl, Gero

2017-01-01

Many of the world’s around 6,000 languages are in danger of disappearing as people give up use of a minority language in favor of the majority language in a process called language shift. Language shift can be monitored on a large scale through the use of mathematical models by way of differential equations, for example, reaction–diffusion equations. Here, we use a different approach: we propose a model for language dynamics based on the principles of cellular automata/agent-based modeling and combine it with very detailed empirical data. Our model makes it possible to follow language dynamics over space and time, whereas existing models based on differential equations average over space and consequently provide no information on local changes in language use. Additionally, cellular automata models can be used even in cases where models based on differential equations are not applicable, for example, in situations where one language has become dispersed and retreated to language islands. Using data from a bilingual region in Austria, we show that the most important factor in determining the spread and retreat of a language is the interaction with speakers of the same language. External factors like bilingual schools or parish language have only a minor influence. PMID:28298530

Effect of porous material heating on the drag force of a cylinder with gas-permeable porous inserts in a supersonic flow

NASA Astrophysics Data System (ADS)

Mironov, S. G.; Poplavskaya, T. V.; Kirilovskiy, S. V.

2017-10-01

The paper presents the results of an experimental investigation of supersonic flow around a solid cylinder with a gas-permeable porous insert on its front end and of supersonic flow around a hollow cylinder with internal porous inserts in the presence of heating of the porous material. The experiments were performed in a supersonic wind tunnel with Mach number 4.85 and 7 with porous inserts of cellular-porous nickel. The results of measurements on the filtration stand of the air filtration rate through the cellular-porous nickel when it is heated are also shown. For a number of experiments, numerical modeling based on the skeletal model of a cellular-porous material was carried out.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM.

PubMed

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2015-07-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.

Failover in Cellular Automata

NASA Astrophysics Data System (ADS)

Kumar, Shailesh; Rao, Shrisha

This paper studies a phenomenon called failover, and shows that this phenomenon (in particular, stateless failover) can be modeled by Game of Life cellular automata. This is the first time that this sophisticated real-life system behavior has been modeled in abstract terms. A cellular automata (CA) configuration is constructed that exhibits emergent failover. The configuration is based on standard Game of Life rules. Gliders and glider-guns form the core messaging structure in the configuration. The blinker is represented as the basic computational unit, and it is shown how it can be recreated in case of a failure. Stateless failover using the primary-backup mechanism is demonstrated. The details of the CA components used in the configuration and its working are described, and a simulation of the complete configuration is also presented.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM

PubMed Central

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2016-01-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918

Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

PubMed

Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

2008-12-01

The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis.

PubMed

Wang, Zi; Ramsey, Benjamin J; Wang, Dali; Wong, Kwai; Li, Husheng; Wang, Eric; Bao, Zhirong

2016-01-01

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

"A Cellular Encounter": Constructing the Cell as a Whole System Using Illustrative Models

ERIC Educational Resources Information Center

Cohen, Joel I.

2014-01-01

A standard part of biology curricula is a project-based assessment of cell structure and function. However, these are often individual assignments that promote little problem-solving or group learning and avoid the subject of organelle chemical interactions. I evaluate a model-based cell project designed to foster group and individual guided…

Insights on Localized and Systemic Delivery of Redox-Based Therapeutics

PubMed Central

Batrakova, Elena V.; Mota, Roberto

2018-01-01

Reactive oxygen and nitrogen species are indispensable in cellular physiology and signaling. Overproduction of these reactive species or failure to maintain their levels within the physiological range results in cellular redox dysfunction, often termed cellular oxidative stress. Redox dysfunction in turn is at the molecular basis of disease etiology and progression. Accordingly, antioxidant intervention to restore redox homeostasis has been pursued as a therapeutic strategy for cardiovascular disease, cancer, and neurodegenerative disorders among many others. Despite preliminary success in cellular and animal models, redox-based interventions have virtually been ineffective in clinical trials. We propose the fundamental reason for their failure is a flawed delivery approach. Namely, systemic delivery for a geographically local disease limits the effectiveness of the antioxidant. We take a critical look at the literature and evaluate successful and unsuccessful approaches to translation of redox intervention to the clinical arena, including dose, patient selection, and delivery approach. We argue that when interpreting a failed antioxidant-based clinical trial, it is crucial to take into account these variables and importantly, whether the drug had an effect on the redox status. Finally, we propose that local and targeted delivery hold promise to translate redox-based therapies from the bench to the bedside. PMID:29636836

Algorithm for repairing the damaged images of grain structures obtained from the cellular automata and measurement of grain size

NASA Astrophysics Data System (ADS)

Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.

2012-10-01

Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.

Toxicity evaluations of nanoclays and thermally degraded byproducts through spectroscopical and microscopical approaches

PubMed Central

Wagner, Alixandra; Eldawud, Reem; White, Andrew; Agarwal, Sushant; Stueckle, Todd A.; Sierros, Konstantinos A.; Rojanasakul, Yon; Gupta, Rakesh K.; Dinu, Cerasela Zoica

2016-01-01

Background Montmorillonite is a type of nanoclay that originates from the clay fraction of the soil and is incorporated into polymers to form nanocomposites with enhanced mechanical strength, barrier, and flammability properties used for food packaging, automotive, and medical devices. However, with implementation in such consumer applications, the interaction of montmorillonite-based composites or derived byproducts with biological systems needs to be investigated. Methods Herein we examined the potential of Cloisite Na+ (pristine) and Cloisite 30B (organically modified montmorillonite nanoclay) and their thermally degraded byproducts’ to induce toxicity in model human lung epithelial cells. The experimental set-up mimicked biological exposure in manufacturing and disposal areas and employed cellular treatments with occupationally relevant doses of nanoclays previously characterized using spectroscopical and microscopical approaches. For nanoclay-cellular interactions and for cellular analyses respectively, biosensorial-based analytical platforms were used, with induced cellular changes being confirmed via live cell counts, viability assays, and cell imaging. Results Our analysis of byproducts’ chemical and physical properties revealed both structural and functional changes. Real-time high throughput analyses of exposed cellular systems confirmed that nanoclay induced significant toxic effects, with Cloisite 30B showing time-dependent decreases in live cell count and cellular viability relative to control and pristine nanoclay, respectively. Byproducts produced less toxic effects; all treatments caused alterations in the cell morphology upon exposure. Conclusions Our morphological, behavioral, and viability cellular changes show that nanoclays have the potential to produce toxic effects when used both in manufacturing or disposal environments. General significance The reported toxicological mechanisms prove the extensibility of a biosensorial-based platform for cellular behavior analysis upon treatment with a variety of nanomaterials. PMID:27612663

Tetraspanin CD37 contributes to the initiation of cellular immunity by promoting dendritic cell migration.

PubMed

Gartlan, Kate H; Wee, Janet L; Demaria, Maria C; Nastovska, Roza; Chang, Tsz Man; Jones, Eleanor L; Apostolopoulos, Vasso; Pietersz, Geoffrey A; Hickey, Michael J; van Spriel, Annemiek B; Wright, Mark D

2013-05-01

Previous studies on the role of the tetraspanin CD37 in cellular immunity appear contradictory. In vitro approaches indicate a negative regulatory role, whereas in vivo studies suggest that CD37 is necessary for optimal cellular responses. To resolve this discrepancy, we studied the adaptive cellular immune responses of CD37(-/-) mice to intradermal challenge with either tumors or model antigens and found that CD37 is essential for optimal cell-mediated immunity. We provide evidence that an increased susceptibility to tumors observed in CD37(-/-) mice coincides with a striking failure to induce antigen-specific IFN-γ-secreting T cells. We also show that CD37 ablation impairs several aspects of DC function including: in vivo migration from skin to draining lymph nodes; chemo-tactic migration; integrin-mediated adhesion under flow; the ability to spread and form actin protrusions and in vivo priming of adoptively transferred naïve T cells. In addition, multiphoton microscopy-based assessment of dermal DC migration demonstrated a reduced rate of migration and increased randomness of DC migration in CD37(-/-) mice. Together, these studies are consistent with a model in which the cellular defect that underlies poor cellular immune induction in CD37(-/-) mice is impaired DC migration. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Metabolism of dinosaurs as determined from their growth.

PubMed

Lee, Scott A

2015-09-01

A model based on cellular properties is used to analyze the mass growth curves of 20 dinosaurs. This analysis yields the first measurement of the average cellular metabolism of dinosaurs. The organismal metabolism is also determined. The cellular metabolism of dinosaurs is found to decrease with mass at a slower rate than is observed in extant animals. The organismal metabolism increases with the mass of the dinosaur. These results come from both the Saurischia and Ornithischia branches of Dinosauria, suggesting that the observed metabolic features were common to all dinosaurs. The results from dinosaurs are compared to data from extant placental and marsupial mammals, a monotreme, and altricial and precocial birds, reptiles, and fish. Dinosaurs had cellular and organismal metabolisms in the range observed in extant mesotherms.

Metabolism of dinosaurs as determined from their growth

NASA Astrophysics Data System (ADS)

Lee, Scott A.

2015-09-01

A model based on cellular properties is used to analyze the mass growth curves of 20 dinosaurs. This analysis yields the first measurement of the average cellular metabolism of dinosaurs. The organismal metabolism is also determined. The cellular metabolism of dinosaurs is found to decrease with mass at a slower rate than is observed in extant animals. The organismal metabolism increases with the mass of the dinosaur. These results come from both the Saurischia and Ornithischia branches of Dinosauria, suggesting that the observed metabolic features were common to all dinosaurs. The results from dinosaurs are compared to data from extant placental and marsupial mammals, a monotreme, and altricial and precocial birds, reptiles, and fish. Dinosaurs had cellular and organismal metabolisms in the range observed in extant mesotherms.

Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

PubMed

Vivek-Ananth, R P; Samal, Areejit

2016-09-01

A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Agent-based modeling of the interaction between CD8+ T cells and Beta cells in type 1 diabetes.

PubMed

Ozturk, Mustafa Cagdas; Xu, Qian; Cinar, Ali

2018-01-01

We propose an agent-based model for the simulation of the autoimmune response in T1D. The model incorporates cell behavior from various rules derived from the current literature and is implemented on a high-performance computing system, which enables the simulation of a significant portion of the islets in the mouse pancreas. Simulation results indicate that the model is able to capture the trends that emerge during the progression of the autoimmunity. The multi-scale nature of the model enables definition of rules or equations that govern cellular or sub-cellular level phenomena and observation of the outcomes at the tissue scale. It is expected that such a model would facilitate in vivo clinical studies through rapid testing of hypotheses and planning of future experiments by providing insight into disease progression at different scales, some of which may not be obtained easily in clinical studies. Furthermore, the modular structure of the model simplifies tasks such as the addition of new cell types, and the definition or modification of different behaviors of the environment and the cells with ease.

Mechanical characterization of disordered and anisotropic cellular monolayers

NASA Astrophysics Data System (ADS)

Nestor-Bergmann, Alexander; Johns, Emma; Woolner, Sarah; Jensen, Oliver E.

2018-05-01

We consider a cellular monolayer, described using a vertex-based model, for which cells form a spatially disordered array of convex polygons that tile the plane. Equilibrium cell configurations are assumed to minimize a global energy defined in terms of cell areas and perimeters; energy is dissipated via dynamic area and length changes, as well as cell neighbor exchanges. The model captures our observations of an epithelium from a Xenopus embryo showing that uniaxial stretching induces spatial ordering, with cells under net tension (compression) tending to align with (against) the direction of stretch, but with the stress remaining heterogeneous at the single-cell level. We use the vertex model to derive the linearized relation between tissue-level stress, strain, and strain rate about a deformed base state, which can be used to characterize the tissue's anisotropic mechanical properties; expressions for viscoelastic tissue moduli are given as direct sums over cells. When the base state is isotropic, the model predicts that tissue properties can be tuned to a regime with high elastic shear resistance but low resistance to area changes, or vice versa.

Physiologically Based Pharmacokinetic Model for Long-Circulating Inorganic Nanoparticles.

PubMed

Liang, Xiaowen; Wang, Haolu; Grice, Jeffrey E; Li, Li; Liu, Xin; Xu, Zhi Ping; Roberts, Michael S

2016-02-10

A physiologically based pharmacokinetic model was developed for accurately characterizing and predicting the in vivo fate of long-circulating inorganic nanoparticles (NPs). This model is built based on direct visualization of NP disposition details at the organ and cellular level. It was validated with multiple data sets, indicating robust inter-route and interspecies predictive capability. We suggest that the biodistribution of long-circulating inorganic NPs is determined by the uptake and release of NPs by phagocytic cells in target organs.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.

A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function

PubMed Central

Röhrle, O.; Davidson, J. B.; Pullan, A. J.

2012-01-01

Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509

Microstructure-based hyperelastic models for closed-cell solids

PubMed Central

Wyatt, Hayley

2017-01-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson’s ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases. PMID:28484340

Microstructure-based hyperelastic models for closed-cell solids.

PubMed

Mihai, L Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Microstructure-based hyperelastic models for closed-cell solids

NASA Astrophysics Data System (ADS)

Mihai, L. Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Multi-Cellular Logistics of Collective Cell Migration

PubMed Central

Yamao, Masataka; Naoki, Honda; Ishii, Shin

2011-01-01

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems. PMID:22205934

Cellular burdens and biological effects on tissue level caused by inhaled radon progenies.

PubMed

Madas, B G; Balásházy, I; Farkas, Á; Szoke, I

2011-02-01

In the case of radon exposure, the spatial distribution of deposited radioactive particles is highly inhomogeneous in the central airways. The object of this research is to investigate the consequences of this heterogeneity regarding cellular burdens in the bronchial epithelium and to study the possible biological effects at tissue level. Applying computational fluid and particle dynamics techniques, the deposition distribution of inhaled radon daughters has been determined in a bronchial airway model for 23 min of work in the New Mexico uranium mine corresponding to 0.0129 WLM exposure. A numerical epithelium model based on experimental data has been utilised in order to quantify cellular hits and doses. Finally, a carcinogenesis model considering cell death-induced cell-cycle shortening has been applied to assess the biological responses. Present computations reveal that cellular dose may reach 1.5 Gy, which is several orders of magnitude higher than tissue dose. The results are in agreement with the histological finding that the uneven deposition distribution of radon progenies may lead to inhomogeneous spatial distribution of tumours in the bronchial airways. In addition, at the macroscopic level, the relationship between cancer risk and radiation burden seems to be non-linear.

Embryo as an active granular fluid: stress-coordinated cellular constriction chains

NASA Astrophysics Data System (ADS)

Gao, Guo-Jie Jason; Holcomb, Michael C.; Thomas, Jeffrey H.; Blawzdziewicz, Jerzy

2016-10-01

Mechanical stress plays an intricate role in gene expression in individual cells and sculpting of developing tissues. However, systematic methods of studying how mechanical stress and feedback help to harmonize cellular activities within a tissue have yet to be developed. Motivated by our observation of the cellular constriction chains (CCCs) during the initial phase of ventral furrow formation in the Drosophila melanogaster embryo, we propose an active granular fluid (AGF) model that provides valuable insights into cellular coordination in the apical constriction process. In our model, cells are treated as circular particles connected by a predefined force network, and they undergo a random constriction process in which the particle constriction probability P is a function of the stress exerted on the particle by its neighbors. We find that when P favors tensile stress, constricted particles tend to form chain-like structures. In contrast, constricted particles tend to form compact clusters when P favors compression. A remarkable similarity of constricted-particle chains and CCCs observed in vivo provides indirect evidence that tensile-stress feedback coordinates the apical constriction activity. Our particle-based AGF model will be useful in analyzing mechanical feedback effects in a wide variety of morphogenesis and organogenesis phenomena.

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

PubMed Central

Kraft, Reuben H.; Mckee, Phillip Justin; Dagro, Amy M.; Grafton, Scott T.

2012-01-01

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight. PMID:22915997

Agent-Based Computational Modeling of Cell Culture: Understanding Dosimetry In Vitro as Part of In Vitro to In Vivo Extrapolation

EPA Science Inventory

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assu...

Phenomenology based multiscale models as tools to understand cell membrane and organelle morphologies

PubMed Central

Ramakrishnan, N.; Radhakrishnan, Ravi

2016-01-01

An intriguing question in cell biology is “how do cells regulate their shape?” It is commonly believed that the observed cellular morphologies are a result of the complex interaction among the lipid molecules (constituting the cell membrane), and with a number of other macromolecules, such as proteins. It is also believed that the common biophysical processes essential for the functioning of a cell also play an important role in cellular morphogenesis. At the cellular scale—where typical dimensions are in the order of micrometers—the effects arising from the molecular scale can either be modeled as equilibrium or non-equilibrium processes. In this chapter, we discuss the dynamically triangulated Monte Carlo technique to model and simulate membrane morphologies at the cellular scale, which in turn can be used to investigate several questions related to shape regulation in cells. In particular, we focus on two specific problems within the framework of isotropic and anisotropic elasticity theories: namely, (i) the origin of complex, physiologically relevant, membrane shapes due to the interaction of the membrane with curvature remodeling proteins, and (ii) the genesis of steady state cellular shapes due to the action of non-equilibrium forces that are generated by the fission and fusion of transport vesicles and by the binding and unbinding of proteins from the parent membrane. PMID:27087801

A white-box model of S-shaped and double S-shaped single-species population growth

PubMed Central

Kalmykov, Lev V.

2015-01-01

Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717

A sunblock based on bioadhesive nanoparticles

NASA Astrophysics Data System (ADS)

Deng, Yang; Ediriwickrema, Asiri; Yang, Fan; Lewis, Julia; Girardi, Michael; Saltzman, W. Mark

2015-12-01

The majority of commercial sunblock preparations use organic or inorganic ultraviolet (UV) filters. Despite protecting against cutaneous phototoxicity, direct cellular exposure to UV filters has raised a variety of health concerns. Here, we show that the encapsulation of padimate O (PO)--a model UV filter--in bioadhesive nanoparticles (BNPs) prevents epidermal cellular exposure to UV filters while enhancing UV protection. BNPs are readily suspended in water, facilitate adherence to the stratum corneum without subsequent intra-epidermal or follicular penetration, and their interaction with skin is water resistant yet the particles can be removed via active towel drying. Although the sunblock based on BNPs contained less than 5 wt% of the UV-filter concentration found in commercial standards, the anti-UV effect was comparable when tested in two murine models. Moreover, the BNP-based sunblock significantly reduced double-stranded DNA breaks when compared with a commercial sunscreen formulation.

In silico biology of bone modelling and remodelling: adaptation.

PubMed

Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

2009-05-28

Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

Towards a virtual lung: multi-scale, multi-physics modelling of the pulmonary system.

PubMed

Burrowes, K S; Swan, A J; Warren, N J; Tawhai, M H

2008-09-28

The essential function of the lung, gas exchange, is dependent on adequate matching of ventilation and perfusion, where air and blood are delivered through complex branching systems exposed to regionally varying transpulmonary and transmural pressures. Structure and function in the lung are intimately related, yet computational models in pulmonary physiology usually simplify or neglect structure. The geometries of the airway and vascular systems and their interaction with parenchymal tissue have an important bearing on regional distributions of air and blood, and therefore on whole lung gas exchange, but this has not yet been addressed by modelling studies. Models for gas exchange have typically incorporated considerable detail at the level of chemical reactions, with little thought for the influence of structure. To date, relatively little attention has been paid to modelling at the cellular or subcellular level in the lung, or to linking information from the protein structure/interaction and cellular levels to the operation of the whole lung. We review previous work in developing anatomically based models of the lung, airways, parenchyma and pulmonary vasculature, and some functional studies in which these models have been used. Models for gas exchange at several spatial scales are briefly reviewed, and the challenges and benefits from modelling cellular function in the lung are discussed.

Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis.

PubMed

Antoniewicz, Maciek R

2015-12-01

Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Schiff bases of putrescine with methylglyoxal protect from cellular damage caused by accumulation of methylglyoxal and reactive oxygen species in Dictyostelium discoideum.

PubMed

Park, Seong-Jun; Kwak, Min-Kyu; Kang, Sa-Ouk

2017-05-01

Polyamines protect protein glycation in cells against the advanced glycation end product precursor methylglyoxal, which is inevitably produced during glycolysis, and the enzymes that detoxify this α-ketoaldehyde have been widely studied. Nonetheless, nonenzymatic methylglyoxal-scavenging molecules have not been sufficiently studied either in vitro or in vivo. Here, we hypothesized reciprocal regulation between polyamines and methylglyoxal modeled in Dictyostelium grown in a high-glucose medium. We based our hypothesis on the reaction between putrescine and methylglyoxal in putrescine-deficient (odc - ) or putrescine-overexpressing (odc oe ) cells. In these strains, growth and cell cycle were found to be dependent on cellular methylglyoxal and putrescine contents. The odc - cells showed growth defects and underwent G1 phase cell cycle arrest, which was efficiently reversed by exogenous putrescine. Cellular methylglyoxal, reactive oxygen species (ROS), and glutathione levels were remarkably changed in odc oe cells and odc̄ cells. These results revealed that putrescine may act as an intracellular scavenger of methylglyoxal and ROS. Herein, we observed interactions of putrescine and methylglyoxal via formation of a Schiff base complex, by UV-vis spectroscopy, and confirmed this adduct by liquid chromatography with mass spectrometry via electrospray ionization. Schiff bases were isolated, analyzed, and predicted to have molecular masses ranging from 124 to 130. We showed that cellular putrescine-methylglyoxal Schiff bases were downregulated in proportion to the levels of endogenous or exogenous putrescine and glutathione in the odc mutants. The putrescine-methylglyoxal Schiff base affected endogenous metabolite levels. This is the first report showing that cellular methylglyoxal functions as a signaling molecule through reciprocal interactions with polyamines by forming Schiff bases. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation and analysis of traffic flow based on cellular automaton

NASA Astrophysics Data System (ADS)

Ren, Xianping; Liu, Xia

2018-03-01

In this paper, single-lane and two-lane traffic model are established based on cellular automaton. Different values of vehicle arrival rate at the entrance and vehicle departure rate at the exit are set to analyze their effects on density, average speed and traffic flow. If the road exit is unblocked, vehicles can pass through the road smoothly despite of the arrival rate at the entrance. If vehicles enter into the road continuously, the traffic condition is varied with the departure rate at the exit. To avoid traffic jam, reasonable vehicle departure rate should be adopted.

VISIBIOweb: visualization and layout services for BioPAX pathway models

PubMed Central

Dilek, Alptug; Belviranli, Mehmet E.; Dogrusoz, Ugur

2010-01-01

With recent advancements in techniques for cellular data acquisition, information on cellular processes has been increasing at a dramatic rate. Visualization is critical to analyzing and interpreting complex information; representing cellular processes or pathways is no exception. VISIBIOweb is a free, open-source, web-based pathway visualization and layout service for pathway models in BioPAX format. With VISIBIOweb, one can obtain well-laid-out views of pathway models using the standard notation of the Systems Biology Graphical Notation (SBGN), and can embed such views within one's web pages as desired. Pathway views may be navigated using zoom and scroll tools; pathway object properties, including any external database references available in the data, may be inspected interactively. The automatic layout component of VISIBIOweb may also be accessed programmatically from other tools using Hypertext Transfer Protocol (HTTP). The web site is free and open to all users and there is no login requirement. It is available at: http://visibioweb.patika.org. PMID:20460470

Ontological representation, integration, and analysis of LINCS cell line cells and their cellular responses.

PubMed

Ong, Edison; Xie, Jiangan; Ni, Zhaohui; Liu, Qingping; Sarntivijai, Sirarat; Lin, Yu; Cooper, Daniel; Terryn, Raymond; Stathias, Vasileios; Chung, Caty; Schürer, Stephan; He, Yongqun

2017-12-21

Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration. CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL. Using MCF 10A cell line cells as an example, we demonstrated how to ontologically model LINCS cellular signatures such as their non-tumorigenic epithelial cell type, three-dimensional growth, latrunculin-A-induced actin depolymerization and apoptosis, and cell line transfection. A CLO subset view of LINCS cell lines, named LINCS-CLOview, was generated to support systematic LINCS cell line analysis and queries. In summary, LINCS cell lines are currently associated with 43 cell types, 131 tissues and organs, and 121 cancer types. The LINCS-CLO view information can be queried using SPARQL scripts. CLO was used to support ontological representation, integration, and analysis of over a thousand LINCS cell line cells and their cellular responses.

Multi-scale continuum modeling of biological processes: from molecular electro-diffusion to sub-cellular signaling transduction

NASA Astrophysics Data System (ADS)

Cheng, Y.; Kekenes-Huskey, P.; Hake, J. E.; Holst, M. J.; McCammon, J. A.; Michailova, A. P.

2012-01-01

This paper presents a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of the time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times, with increasing ionic strength, and demonstrate the role of an enzyme's electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a nonlinear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally derived rodent ventricular myocyte geometries. Results reveal the important role of mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate sub-cellular Ca2+ signals. The model predicts that reduced off-rate in the whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for the integration of molecular-scale information into simulations of cellular-scale systems.

A Liver-centric Multiscale Modeling Framework for Xenobiotics ...

EPA Pesticide Factsheets

We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. To validate the model, we estimated our model parameters by fi?tting serum concentrations of acetaminophen and its glucuronide and sulfate metabolites to experiments, and carried out sensitivity analysis on 35 parameters selected from three modules. Our study focuses on developing a multi-scale computational model to characterize both phase I and phase II metabolism of acetaminophen, by bridging Physiologically Based Pharmacokinetic (PBPK) modeling at the whole body level, cell movement and blood flow at the tissue level and cell signaling and drug metabolism at the sub-cellular level. This multiscale model bridges the CompuCell3D tool used by the Virtual Tissue project with the httk tool developed by the Rapid Exposure and Dosimetry project.

Linking actin networks and cell membrane via a reaction-diffusion-elastic description of nonlinear filopodia initiation.

PubMed

Ben Isaac, Eyal; Manor, Uri; Kachar, Bechara; Yochelis, Arik; Gov, Nir S

2013-08-01

Reaction-diffusion models have been used to describe pattern formation on the cellular scale, and traditionally do not include feedback between cellular shape changes and biochemical reactions. We introduce here a distinct reaction-diffusion-elasticity approach: The reaction-diffusion part describes bistability between two actin orientations, coupled to the elastic energy of the cell membrane deformations. This coupling supports spatially localized patterns, even when such solutions do not exist in the uncoupled self-inhibited reaction-diffusion system. We apply this concept to describe the nonlinear (threshold driven) initiation mechanism of actin-based cellular protrusions and provide support by several experimental observations.

Simulation of root forms using cellular automata model

NASA Astrophysics Data System (ADS)

Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

2016-02-01

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.

A hybrid parallel framework for the cellular Potts model simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less

Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

PubMed

Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

2008-09-09

Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and energetics in skeletal muscle during physiological stresses such as ischemia, hypoxia, and exercise.

PDT-based combinations in overcoming chemoresistance from stromal and heterotypic cellular communication (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rizvi, Imran; Bulin, Anne-Laure; Anbil, Sriram R.; Briars, Emma A.; Vecchio, Daniela; Celli, Jonathan P.; Broekgaarden, Mans; Hasan, Tayyaba

2017-02-01

Targeting the molecular and cellular cues that influence treatment resistance in tumors is critical to effectively treating unresponsive populations of stubborn disease. The informed design of mechanism-based combinations is emerging as increasingly important to targeting resistance and improving the efficacy of conventional treatments, while minimizing toxicity. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Increasing evidence shows that PDT-based combinations cooperate mechanistically with, and improve the therapeutic index of, traditional chemotherapies. These and other findings emphasize the importance of including PDT as part of comprehensive treatment plans for cancer, particularly in complex disease sites. Identifying effective combinations requires a multi-faceted approach that includes the development of bioengineered cancer models and corresponding image analysis tools. The molecular and phenotypic basis of verteporfin-mediated PDT-based enhancement of chemotherapeutic efficacy and predictability in complex 3D models for ovarian cancer will be presented.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Developing the conceptual instructional design with inquiry-based instruction model of secondary students at the 10th grade level on digestion system and cellular degradation issue

NASA Astrophysics Data System (ADS)

Rotjanakunnatam, Boonthida; Chayaburakul, Kanokporn

2018-01-01

The aims of this research study was to develop the conceptual instructional design with the Inquiry-Based Instruction Model (IBIM) of secondary students at the 10th grade level on Digestion System and Cellular Degradation issue using both oxygen and oxygen-degrading cellular nutrients were designed instructional model with a sample size of 45 secondary students at the 10th Grade level. Data were collected by asking students to do a questionnaire pre and post learning processes. The questionnaire consists of two main parts that composed of students' perception questionnaire and the questionnaire that asked the question answer concept for the selected questionnaire. The 10-item Conceptual Thinking Test (CTT) was assessed students' conceptual thinking evaluation that it was covered in two main concepts, namely; Oxygen degradation nutrients and degradation nutrients without oxygen. The data by classifying students' answers into 5 groups and measuring them in frequency and a percentage of students' performances of their learning pre and post activities with the Inquiry-Based Instruction Model were analyzed as a tutorial. The results of this research found that: After the learning activities with the IBIM, most students developed concepts of both oxygen and oxygen-degrading cellular nutrients in the correct, complete and correct concept, and there are a number of students who have conceptual ideas in the wrong concept, and no concept was clearly reduced. However, the results are still found that; some students have some misconceptions, such as; the concept of direction of electron motion and formation of the ATP of bioactivities of life. This cause may come from the nature of the content, the complexity, the continuity, the movement, and the time constraints only in the classroom. Based on this research, it is suggested that some students may take some time, and the limited time in the classroom to their learning activity with content creation content binding and dramatic storytelling increases in a relaxed classroom learning environment.

Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model.

PubMed

Machineni, Lakshmi; Rajapantul, Anil; Nandamuri, Vandana; Pawar, Parag D

2017-03-01

The resistance of bacterial biofilms to antibiotic treatment has been attributed to the emergence of structurally heterogeneous microenvironments containing metabolically inactive cell populations. In this study, we use a three-dimensional individual-based cellular automata model to investigate the influence of nutrient availability and quorum sensing on microbial heterogeneity in growing biofilms. Mature biofilms exhibited at least three structurally distinct strata: a high-volume, homogeneous region sandwiched between two compact sections of high heterogeneity. Cell death occurred preferentially in layers in close proximity to the substratum, resulting in increased heterogeneity in this section of the biofilm; the thickness and heterogeneity of this lowermost layer increased with time, ultimately leading to sloughing. The model predicted the formation of metabolically dormant cellular microniches embedded within faster-growing cell clusters. Biofilms utilizing quorum sensing were more heterogeneous compared to their non-quorum sensing counterparts, and resisted sloughing, featuring a cell-devoid layer of EPS atop the substratum upon which the remainder of the biofilm developed. Overall, our study provides a computational framework to analyze metabolic diversity and heterogeneity of biofilm-associated microorganisms and may pave the way toward gaining further insights into the biophysical mechanisms of antibiotic resistance.

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

PubMed

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

Probing eukaryotic cell mechanics via mesoscopic simulations

PubMed Central

Shang, Menglin; Lim, Chwee Teck

2017-01-01

Cell mechanics has proven to be important in many biological processes. Although there is a number of experimental techniques which allow us to study mechanical properties of cell, there is still a lack of understanding of the role each sub-cellular component plays during cell deformations. We present a new mesoscopic particle-based eukaryotic cell model which explicitly describes cell membrane, nucleus and cytoskeleton. We employ Dissipative Particle Dynamics (DPD) method that provides us with the unified framework for modeling of a cell and its interactions in the flow. Data from micropipette aspiration experiments were used to define model parameters. The model was validated using data from microfluidic experiments. The validated model was then applied to study the impact of the sub-cellular components on the cell viscoelastic response in micropipette aspiration and microfluidic experiments. PMID:28922399

A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.

PubMed

Soleimani, Hamid; Drakakis, Emmanuel M

2017-06-01

Recent studies have demonstrated that calcium is a widespread intracellular ion that controls a wide range of temporal dynamics in the mammalian body. The simulation and validation of such studies using experimental data would benefit from a fast large scale simulation and modelling tool. This paper presents a compact and fully reconfigurable cellular calcium model capable of mimicking Hopf bifurcation phenomenon and various nonlinear responses of the biological calcium dynamics. The proposed cellular model is synthesized on a digital platform for a single unit and a network model. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed cellular model can mimic the biological calcium behaviors with considerably low hardware overhead. The approach has the potential to speed up large-scale simulations of slow intracellular dynamics by sharing more cellular units in real-time. To this end, various networks constructed by pipelining 10 k to 40 k cellular calcium units are compared with an equivalent simulation run on a standard PC workstation. Results show that the cellular hardware model is, on average, 83 times faster than the CPU version.

Human cell structure-driven model construction for predicting protein subcellular location from biological images.

PubMed

Shao, Wei; Liu, Mingxia; Zhang, Daoqiang

2016-01-01

The systematic study of subcellular location pattern is very important for fully characterizing the human proteome. Nowadays, with the great advances in automated microscopic imaging, accurate bioimage-based classification methods to predict protein subcellular locations are highly desired. All existing models were constructed on the independent parallel hypothesis, where the cellular component classes are positioned independently in a multi-class classification engine. The important structural information of cellular compartments is missed. To deal with this problem for developing more accurate models, we proposed a novel cell structure-driven classifier construction approach (SC-PSorter) by employing the prior biological structural information in the learning model. Specifically, the structural relationship among the cellular components is reflected by a new codeword matrix under the error correcting output coding framework. Then, we construct multiple SC-PSorter-based classifiers corresponding to the columns of the error correcting output coding codeword matrix using a multi-kernel support vector machine classification approach. Finally, we perform the classifier ensemble by combining those multiple SC-PSorter-based classifiers via majority voting. We evaluate our method on a collection of 1636 immunohistochemistry images from the Human Protein Atlas database. The experimental results show that our method achieves an overall accuracy of 89.0%, which is 6.4% higher than the state-of-the-art method. The dataset and code can be downloaded from https://github.com/shaoweinuaa/. dqzhang@nuaa.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

One-electron oxidation reactions of purine and pyrimidine bases in cellular DNA

PubMed Central

Cadet, Jean; Wagner, J. Richard; Shafirovich, Vladimir; Geacintov, Nicholas E.

2014-01-01

Purpose The aim of this survey is to critically review the available information on one-electron oxidation reactions of nucleobases in cellular DNA with emphasis on damage induced through the transient generation of purine and pyrimidine radical cations. Since the indirect effect of ionizing radiation mediated by hydroxyl radical is predominant in cells, efforts have been made to selectively ionize bases using suitable one-electron oxidants that consist among others of high intensity UVC laser pulses. Thus, the main oxidation product in cellular DNA was found to be 8-oxo-7,8-dihydroguanine as a result of direct bi-photonic ionization of guanine bases and indirect formation of guanine radical cations through hole transfer reactions from other base radical cations. The formation of 8-oxo-7,8-dihydroguanine and other purine and pyrimidine degradation products was rationalized in terms of the initial generation of related radical cations followed by either hydration or deprotonation reactions in agreement with mechanistic pathways inferred from detailed mechanistic studies. The guanine radical cation has been shown to be implicated in three other nucleophilic additions that give rise to DNA-protein and DNA-DNA cross-links in model systems. Evidence was recently provided for the occurrence of these three reactions in cellular DNA. Conclusion There is growing evidence that one-electron oxidation reactions of nucleobases whose mechanisms have been characterized in model studies involving aqueous solutions take place in a similar way in cells. It may also be pointed out that the above cross-linked lesions are only produced from the guanine radical cation and may be considered as diagnostic products of the direct effect of ionizing radiation. PMID:24369822

One-electron oxidation reactions of purine and pyrimidine bases in cellular DNA.

PubMed

Cadet, Jean; Wagner, J Richard; Shafirovich, Vladimir; Geacintov, Nicholas E

2014-06-01

The aim of this survey is to critically review the available information on one-electron oxidation reactions of nucleobases in cellular DNA with emphasis on damage induced through the transient generation of purine and pyrimidine radical cations. Since the indirect effect of ionizing radiation mediated by hydroxyl radical is predominant in cells, efforts have been made to selectively ionize bases using suitable one-electron oxidants that consist among others of high intensity UVC laser pulses. Thus, the main oxidation product in cellular DNA was found to be 8-oxo-7,8-dihydroguanine as a result of direct bi-photonic ionization of guanine bases and indirect formation of guanine radical cations through hole transfer reactions from other base radical cations. The formation of 8-oxo-7,8-dihydroguanine and other purine and pyrimidine degradation products was rationalized in terms of the initial generation of related radical cations followed by either hydration or deprotonation reactions in agreement with mechanistic pathways inferred from detailed mechanistic studies. The guanine radical cation has been shown to be implicated in three other nucleophilic additions that give rise to DNA-protein and DNA-DNA cross-links in model systems. Evidence was recently provided for the occurrence of these three reactions in cellular DNA. There is growing evidence that one-electron oxidation reactions of nucleobases whose mechanisms have been characterized in model studies involving aqueous solutions take place in a similar way in cells. It may also be pointed out that the above cross-linked lesions are only produced from the guanine radical cation and may be considered as diagnostic products of the direct effect of ionizing radiation.

Quantifying time-varying cellular secretions with local linear models.

PubMed

Byers, Jeff M; Christodoulides, Joseph A; Delehanty, James B; Raghu, Deepa; Raphael, Marc P

2017-07-01

Extracellular protein concentrations and gradients initiate a wide range of cellular responses, such as cell motility, growth, proliferation and death. Understanding inter-cellular communication requires spatio-temporal knowledge of these secreted factors and their causal relationship with cell phenotype. Techniques which can detect cellular secretions in real time are becoming more common but generalizable data analysis methodologies which can quantify concentration from these measurements are still lacking. Here we introduce a probabilistic approach in which local-linear models and the law of mass action are applied to obtain time-varying secreted concentrations from affinity-based biosensor data. We first highlight the general features of this approach using simulated data which contains both static and time-varying concentration profiles. Next we apply the technique to determine concentration of secreted antibodies from 9E10 hybridoma cells as detected using nanoplasmonic biosensors. A broad range of time-dependent concentrations was observed: from steady-state secretions of 230 pM near the cell surface to large transients which reached as high as 56 nM over several minutes and then dissipated.

Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Khalilnia, M. H.; Ghaemirad, T.; Abbaspour, R. A.

2013-09-01

In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM+ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

Mapping Thermal Habitat of Ectotherms Based on Behavioral Thermoregulation in a Controlled Thermal Environment

NASA Astrophysics Data System (ADS)

Fei, T.; Skidmore, A.; Liu, Y.

2012-07-01

Thermal environment is especially important to ectotherm because a lot of physiological functions rely on the body temperature such as thermoregulation. The so-called behavioural thermoregulation function made use of the heterogeneity of the thermal properties within an individual's habitat to sustain the animal's physiological processes. This function links the spatial utilization and distribution of individual ectotherm with the thermal properties of habitat (thermal habitat). In this study we modelled the relationship between the two by a spatial explicit model that simulates the movements of a lizard in a controlled environment. The model incorporates a lizard's transient body temperatures with a cellular automaton algorithm as a way to link the physiology knowledge of the animal with the spatial utilization of its microhabitat. On a larger spatial scale, 'thermal roughness' of the habitat was defined and used to predict the habitat occupancy of the target species. The results showed the habitat occupancy can be modelled by the cellular automaton based algorithm at a smaller scale, and can be modelled by the thermal roughness index at a larger scale.

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

Opinion evolution based on cellular automata rules in small world networks

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

2010-03-01

In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources.

PubMed

Nev, Olga A; van den Berg, Hugo A

2017-01-01

Variable-Internal-Stores models of microbial metabolism and growth have proven to be invaluable in accounting for changes in cellular composition as microbial cells adapt to varying conditions of nutrient availability. Here, such a model is extended with explicit allocation of molecular building blocks among various types of catalytic machinery. Such an extension allows a reconstruction of the regulatory rules employed by the cell as it adapts its physiology to changing environmental conditions. Moreover, the extension proposed here creates a link between classic models of microbial growth and analyses based on detailed transcriptomics and proteomics data sets. We ascertain the compatibility between the extended Variable-Internal-Stores model and the classic models, demonstrate its behaviour by means of simulations, and provide a detailed treatment of the uniqueness and the stability of its equilibrium point as a function of the availabilities of the various nutrients.

A solution to the biodiversity paradox by logical deterministic cellular automata.

PubMed

Kalmykov, Lev V; Kalmykov, Vyacheslav L

2015-06-01

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence.

Cellular cation transport studied by 6/7Li and 23Na NMR in a porous Mo132 Keplerate type nano-capsule as model system.

PubMed

Rehder, Dieter; Haupt, Erhard T K; Müller, Achim

2008-01-01

Li+ ions can interplay with other cations intrinsically present in the intra- and extra-cellular space (i.e. Na+, K+, Mg2+ and Ca2+) have therapeutic effects (e.g. in the treatment of bipolar disorder) or toxic effects (at higher doses), likely because Li+ interferes with the intra-/extra-cellular concentration gradients of the mentioned physiologically relevant cations. The cellular transmembrane transport can be modelled by molybdenum-oxide-based Keplerates, i.e. nano-sized porous capsules containing 132 Mo centres, monitored through 6/7Li as well as 23Na NMR spectroscopy. The effects on the transport of Li+ cations through the 'ion channels' of these model cells, caused by variations in water amount, temperature, and by the addition of organic cationic 'plugs' and the shift reagent [Dy(PPP)2](7-) are reported. In the investigated solvent systems, water acts as a transport mediator for Li+. Likewise, the counter-transport (Li+/Na+, Li+/K+, Li+/Cs+ and Li+/Ca2+) has been investigated by 7Li NMR and, in the case of Li+/Na+ exchange, by 23Na NMR, and it has been shown that most (in the case of Na+ and K+, all (Ca2+) or almost none (Cs+) of the Li cations is extruded from the internal sites of the artificial cell to the extra-cellular medium, while Na+, K+ and Ca2+ are partially incorporated.

Carbon Ion-Irradiated Hepatoma Cells Exhibit Coupling Interplay between Apoptotic Signaling and Morphological and Mechanical Remodeling

PubMed Central

Zhang, Baoping; Li, Long; Li, Zhiqiang; Liu, Yang; Zhang, Hong; Wang, Jizeng

2016-01-01

A apoptotic model was established based on the results of five hepatocellular carcinoma cell (HCC) lines irradiated with carbon ions to investigate the coupling interplay between apoptotic signaling and morphological and mechanical cellular remodeling. The expression levels of key apoptotic proteins and the changes in morphological characteristics and mechanical properties were systematically examined in the irradiated HCC lines. We observed that caspase-3 was activated and that the Bax/Bcl-2 ratio was significantly increased over time. Cellular morphology and mechanics analyses indicated monotonic decreases in spatial sizes, an increase in surface roughness, a considerable reduction in stiffness, and disassembly of the cytoskeletal architecture. A theoretical model of apoptosis revealed that mechanical changes in cells induce the characteristic cellular budding of apoptotic bodies. Statistical analysis indicated that the projected area, stiffness, and cytoskeletal density of the irradiated cells were positively correlated, whereas stiffness and caspase-3 expression were negatively correlated, suggesting a tight coupling interplay between the cellular structures, mechanical properties, and apoptotic protein levels. These results help to clarify a novel arbitration mechanism of cellular demise induced by carbon ions. This biomechanics strategy for evaluating apoptosis contributes to our understanding of cancer-killing mechanisms in the context of carbon ion radiotherapy. PMID:27731354

Unraveling the non-senescence phenomenon in Hydra.

PubMed

Dańko, Maciej J; Kozłowski, Jan; Schaible, Ralf

2015-10-07

Unlike other metazoans, Hydra does not experience the distinctive rise in mortality with age known as senescence, which results from an increasing imbalance between cell damage and cell repair. We propose that the Hydra controls damage accumulation mainly through damage-dependent cell selection and cell sloughing. We examine our hypothesis with a model that combines cellular damage with stem cell renewal, differentiation, and elimination. The Hydra individual can be seen as a large single pool of three types of stem cells with some features of differentiated cells. This large stem cell community prevents "cellular damage drift," which is inevitable in complex conglomerate (differentiated) metazoans with numerous and generally isolated pools of stem cells. The process of cellular damage drift is based on changes in the distribution of damage among cells due to random events, and is thus similar to Muller's ratchet in asexual populations. Events in the model that are sources of randomness include budding, cellular death, and cellular damage and repair. Our results suggest that non-senescence is possible only in simple Hydra-like organisms which have a high proportion and number of stem cells, continuous cell divisions, an effective cell selection mechanism, and stem cells with the ability to undertake some roles of differentiated cells. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrated cellular network of transcription regulations and protein-protein interactions

PubMed Central

2010-01-01

Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology. PMID:20211003

Integrated cellular network of transcription regulations and protein-protein interactions.

PubMed

Wang, Yu-Chao; Chen, Bor-Sen

2010-03-08

With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

Particle-based membrane model for mesoscopic simulation of cellular dynamics

NASA Astrophysics Data System (ADS)

Sadeghi, Mohsen; Weikl, Thomas R.; Noé, Frank

2018-01-01

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

Agent-based modeling of the immune system: NetLogo, a promising framework.

PubMed

Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2014-01-01

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

Cellular automatons applied to gas dynamic problems

NASA Technical Reports Server (NTRS)

Long, Lyle N.; Coopersmith, Robert M.; Mclachlan, B. G.

1987-01-01

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Fluorescence microscopy: A tool to study autophagy

NASA Astrophysics Data System (ADS)

Rai, Shashank; Manjithaya, Ravi

2015-08-01

Autophagy is a cellular recycling process through which a cell degrades old and damaged cellular components such as organelles and proteins and the degradation products are reused to provide energy and building blocks. Dysfunctional autophagy is reported in several pathological situations. Hence, autophagy plays an important role in both cellular homeostasis and diseased conditions. Autophagy can be studied through various techniques including fluorescence based microscopy. With the advancements of newer technologies in fluorescence microscopy, several novel processes of autophagy have been discovered which makes it an essential tool for autophagy research. Moreover, ability to tag fluorescent proteins with sub cellular targets has enabled us to evaluate autophagy processes in real time under fluorescent microscope. In this article, we demonstrate different aspects of autophagy in two different model organisms i.e. yeast and mammalian cells, with the help of fluorescence microscopy.

A Multi-Paradigm Modeling Framework to Simulate Dynamic Reciprocity in a Bioreactor

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

Despite numerous technology advances, bioreactors are still mostly utilized as functional black-boxes where trial and error eventually leads to the desirable cellular outcome. Investigators have applied various computational approaches to understand the impact the internal dynamics of such devices has on overall cell growth, but such models cannot provide a comprehensive perspective regarding the system dynamics, due to limitations inherent to the underlying approaches. In this study, a novel multi-paradigm modeling platform capable of simulating the dynamic bidirectional relationship between cells and their microenvironment is presented. Designing the modeling platform entailed combining and coupling fully an agent-based modeling platform with a transport phenomena computational modeling framework. To demonstrate capability, the platform was used to study the impact of bioreactor parameters on the overall cell population behavior and vice versa. In order to achieve this, virtual bioreactors were constructed and seeded. The virtual cells, guided by a set of rules involving the simulated mass transport inside the bioreactor, as well as cell-related probabilistic parameters, were capable of displaying an array of behaviors such as proliferation, migration, chemotaxis and apoptosis. In this way the platform was shown to capture not only the impact of bioreactor transport processes on cellular behavior but also the influence that cellular activity wields on that very same local mass transport, thereby influencing overall cell growth. The platform was validated by simulating cellular chemotaxis in a virtual direct visualization chamber and comparing the simulation with its experimental analogue. The results presented in this paper are in agreement with published models of similar flavor. The modeling platform can be used as a concept selection tool to optimize bioreactor design specifications. PMID:23555740

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Simulation Based Optimization of Complex Monolithic Composite Structures Using Cellular Core Technology

NASA Astrophysics Data System (ADS)

Hickmott, Curtis W.

Cellular core tooling is a new technology which has the capability to manufacture complex integrated monolithic composite structures. This novel tooling method utilizes thermoplastic cellular cores as inner tooling. The semi-rigid nature of the cellular cores makes them convenient for lay-up, and under autoclave temperature and pressure they soften and expand providing uniform compaction on all surfaces including internal features such as ribs and spar tubes. This process has the capability of developing fully optimized aerospace structures by reducing or eliminating assembly using fasteners or bonded joints. The technology is studied in the context of evaluating its capabilities, advantages, and limitations in developing high quality structures. The complex nature of these parts has led to development of a model using the Finite Element Analysis (FEA) software Abaqus and the plug-in COMPRO Common Component Architecture (CCA) provided by Convergent Manufacturing Technologies. This model utilizes a "virtual autoclave" technique to simulate temperature profiles, resin flow paths, and ultimately deformation from residual stress. A model has been developed simulating the temperature profile during curing of composite parts made with the cellular core technology. While modeling of composites has been performed in the past, this project will look to take this existing knowledge and apply it to this new manufacturing method capable of building more complex parts and develop a model designed specifically for building large, complex components with a high degree of accuracy. The model development has been carried out in conjunction with experimental validation. A double box beam structure was chosen for analysis to determine the effects of the technology on internal ribs and joints. Double box beams were manufactured and sectioned into T-joints for characterization. Mechanical behavior of T-joints was performed using the T-joint pull-off test and compared to traditional tooling methods. Components made with the cellular core tooling method showed an improved strength at the joints. It is expected that this knowledge will help optimize the processing of complex, integrated structures and benefit applications in aerospace where lighter, structurally efficient components would be advantageous.

Integration of Basic Sciences in Health's Courses

ERIC Educational Resources Information Center

Azzalis, L. A.; Giavarotti, L.; Sato, S. N.; Barros, N. M. T.; Junqueira, V. B. C.; Fonseca, F. L. A.

2012-01-01

Concepts from disciplines such as Biochemistry, Genetics, Cellular and Molecular Biology are essential to the understanding and treatment of an elevated number of illnesses, but often they are studied separately, with no integration between them. This article proposes a model for basic sciences integration based on problem-based learning (PBL) and…

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

NASA Astrophysics Data System (ADS)

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Zoica Dinu, Cerasela

2016-02-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

PubMed Central

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Dinu, Cerasela Zoica

2016-01-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications. PMID:26820775

Biocompatibility effects of indirect exposure of base-metal dental casting alloys to a human-derived three-dimensional oral mucosal model.

PubMed

McGinley, Emma Louise; Moran, Gary P; Fleming, Garry J P

2013-11-01

The study employed a three-dimensional (3D) human-derived oral mucosal model to assess the biocompatibility of base-metal dental casting alloys ubiquitous in fixed prosthodontic and orthodontic dentistry. Oral mucosal models were generated using primary human oral keratinocyte and gingival fibroblast cells seeded onto human de-epidermidised dermal scaffolds. Nickel-chromium (Ni-Cr) and cobalt-chromium (Co-Cr) base-metal alloy immersion solutions were exposed to oral mucosal models for increasing time periods (2-72h). Analysis methodologies (histology, viable cell counts, oxidative stress, cytokine expression and toxicity) were performed following exposure. Ni-based alloy immersion solutions elicited significantly decreased cell viability (P<0.0004) with increased oxidative stress (P<0.0053), inflammatory cytokine expression (P<0.0077) and cellular toxicity levels (P<0.0001) compared with the controls. However, the Ni-free Co-Cr-based alloy immersion solutions did not elicit adverse oxidative stress (P>0.4755) or cellular toxicity (P<0.2339) responses compared with controls. Although the multiple analyses highlighted Ni-Cr base-metal alloy immersion solutions elicited significantly detrimental effects to the oral mucosal models, it was possible to distinguish between Ni-Cr alloys using the approach employed. The study employed a 3D human-derived full-thickness differentiated oral mucosal model suitable for biocompatibility assessment of base-metal dental casting alloys through discriminatory experimental parameters. Increasing incidences of Ni hypersensitivity in the general population warrants serious consideration from dental practitioners and patients alike where fixed prosthodontic/orthodontic dental treatments are the treatment modality involved. The novel and analytical oral mucosal model has the potential to significantly contribute to the advancement of reproducible dental medical device and dental material appraisals. Copyright © 2013 Elsevier Ltd. All rights reserved.

Probe molecules (PrM) approach in adverse outcome pathway (AOP) based high throughput screening (HTS): in vivo discovery for developing in vitro target methods

EPA Science Inventory

Efficient and accurate adverse outcome pathway (AOP) based high-throughput screening (HTS) methods use a systems biology based approach to computationally model in vitro cellular and molecular data for rapid chemical prioritization; however, not all HTS assays are grounded by rel...

In situ sensing and modeling of molecular events at the cellular level

NASA Astrophysics Data System (ADS)

Yang, Ruiguo

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior. To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the pathway map was delineated in detail while others were condensed into a single reaction. The model parameters were obtained by extracting the mechanical response from the experiment. The model refinements were conducted by testing a series of inhibition mechanisms and comparing the simulation data with the experimental data. The model was then used to predict the existences of certain reactions that are qualitatively reported in the literature.

Molecular counting of membrane receptor subunits with single-molecule localization microscopy

NASA Astrophysics Data System (ADS)

Krüger, Carmen; Fricke, Franziska; Karathanasis, Christos; Dietz, Marina S.; Malkusch, Sebastian; Hummer, Gerhard; Heilemann, Mike

2017-02-01

We report on quantitative single-molecule localization microscopy, a method that next to super-resolved images of cellular structures provides information on protein copy numbers in protein clusters. This approach is based on the analysis of blinking cycles of single fluorophores, and on a model-free description of the distribution of the number of blinking events. We describe the experimental and analytical procedures, present cellular data of plasma membrane proteins and discuss the applicability of this method.

A cellular automaton for the signed particle formulation of quantum mechanics

NASA Astrophysics Data System (ADS)

Sellier, J. M.; Kapanova, K. G.; Dimov, I.

2017-02-01

Recently, a new formulation of quantum mechanics, based on the concept of signed particles, has been suggested. In this paper, we introduce a cellular automaton which mimics the dynamics of quantum objects in the phase-space in a time-dependent fashion. This is twofold: it provides a simplified and accessible language to non-physicists who wants to simulate quantum mechanical systems, at the same time it enables a different way to explore the laws of Physics. Moreover, it opens the way towards hybrid simulations of quantum systems by combining full quantum models with cellular automata when the former fail. In order to show the validity of the suggested cellular automaton and its combination with the signed particle formalism, several numerical experiments are performed, showing very promising results. Being this article a preliminary study on quantum simulations in phase-space by means of cellular automata, some conclusions are drawn about the encouraging results obtained so far and the possible future developments.

A synthetic ion transporter that disrupts autophagy and induces apoptosis by perturbing cellular chloride concentrations

NASA Astrophysics Data System (ADS)

Busschaert, Nathalie; Park, Seong-Hyun; Baek, Kyung-Hwa; Choi, Yoon Pyo; Park, Jinhong; Howe, Ethan N. W.; Hiscock, Jennifer R.; Karagiannidis, Louise E.; Marques, Igor; Félix, Vítor; Namkung, Wan; Sessler, Jonathan L.; Gale, Philip A.; Shin, Injae

2017-07-01

Perturbations in cellular chloride concentrations can affect cellular pH and autophagy and lead to the onset of apoptosis. With this in mind, synthetic ion transporters have been used to disturb cellular ion homeostasis and thereby induce cell death; however, it is not clear whether synthetic ion transporters can also be used to disrupt autophagy. Here, we show that squaramide-based ion transporters enhance the transport of chloride anions in liposomal models and promote sodium chloride influx into the cytosol. Liposomal and cellular transport activity of the squaramides is shown to correlate with cell death activity, which is attributed to caspase-dependent apoptosis. One ion transporter was also shown to cause additional changes in lysosomal pH, which leads to impairment of lysosomal enzyme activity and disruption of autophagic processes. This disruption is independent of the initiation of apoptosis by the ion transporter. This study provides the first experimental evidence that synthetic ion transporters can disrupt both autophagy and induce apoptosis.

A Cellular High-Throughput Screening Approach for Therapeutic trans-Cleaving Ribozymes and RNAi against Arbitrary mRNA Disease Targets

PubMed Central

Yau, Edwin H.; Butler, Mark C.; Sullivan, Jack M.

2016-01-01

Major bottlenecks in development of therapeutic post transcriptional gene silencing (PTGS) agents (e.g. ribozymes, RNA interference, antisense) include the challenge of mapping rare accessible regions of the mRNA target that are open for annealing and cleavage, testing and optimization of agents in human cells to identify lead agents, testing for cellular toxicity, and preclinical evaluation in appropriate animal models of disease. Methods for rapid and reliable cellular testing of PTGS agents are needed to identify potent lead candidates for optimization. Our goal was to develop a means of rapid assessment of many RNA agents to identify a lead candidate for a given mRNA associated with a disease state. We developed a rapid human cell-based screening platform to test efficacy of hammerhead ribozyme (hhRz) or RNA interference (RNAi) constructs, using a model retinal degeneration target, human rod opsin (RHO) mRNA. The focus is on RNA Drug Discovery for diverse retinal degeneration targets. To validate the approach, candidate hhRzs were tested against NUH↓ cleavage sites (N=G,C,A,U; H=C,A,U) within the target mRNA of secreted alkaline phosphatase (SEAP), a model gene expression reporter, based upon in silico predictions of mRNA accessibility. HhRzs were embedded in a larger stable adenoviral VAI RNA scaffold for high cellular expression, cytoplasmic trafficking, and stability. Most hhRz expression plasmids exerted statistically significant knockdown of extracellular SEAP enzyme activity when readily assayed by a fluorescence enzyme assay intended for high throughput screening (HTS). Kinetics of PTGS knockdown of cellular targets is measureable in live cells with the SEAP reporter. The validated SEAP HTS platform was transposed to identify lead PTGS agents against a model hereditary retinal degeneration target, RHO mRNA. Two approaches were used to physically fuse the model retinal gene target mRNA to the SEAP reporter mRNA. The most expedient way to evaluate a large set of potential VAI-hhRz expression plasmids against diverse NUH↓ cleavage sites uses cultured human HEK293S cells stably expressing a dicistronic Target-IRES-SEAP target fusion mRNA. Broad utility of this rational RNA drug discovery approach is feasible for any ophthalmological disease-relevant mRNA targets and any disease mRNA targets in general. The approach will permit rank ordering of PTGS agents based on potency to identify a lead therapeutic compound for further optimization. PMID:27233447

A two-scale Weibull approach to the failure of porous ceramic structures made by robocasting: possibilities and limits

PubMed Central

Genet, Martin; Houmard, Manuel; Eslava, Salvador; Saiz, Eduardo; Tomsia, Antoni P.

2012-01-01

This paper introduces our approach to modeling the mechanical behavior of cellular ceramics, through the example of calcium phosphate scaffolds made by robocasting for bone-tissue engineering. The Weibull theory is used to deal with the scaffolds’ constitutive rods statistical failure, and the Sanchez-Palencia theory of periodic homogenization is used to link the rod- and scaffold-scales. Uniaxial compression of scaffolds and three-point bending of rods were performed to calibrate and validate the model. If calibration based on rod-scale data leads to over-conservative predictions of scaffold’s properties (as rods’ successive failures are not taken into account), we show that, for a given rod diameter, calibration based on scaffold-scale data leads to very satisfactory predictions for a wide range of rod spacing, i.e. of scaffold porosity, as well as for different loading conditions. This work establishes the proposed model as a reliable tool for understanding and optimizing cellular ceramics’ mechanical properties. PMID:23439936

Bioaccessibility and Cellular Uptake of β-Carotene Encapsulated in Model O/W Emulsions: Influence of Initial Droplet Size and Emulsifiers

PubMed Central

Kelly, Alan L.

2017-01-01

The effects of the initial emulsion structure (droplet size and emulsifier) on the properties of β-carotene-loaded emulsions and the bioavailability of β-carotene after passing through simulated gastrointestinal tract (GIT) digestion were investigated. Exposure to GIT significantly changed the droplet size, surface charge and composition of all emulsions, and these changes were dependent on their initial droplet size and the emulsifiers used. Whey protein isolate (WPI)-stabilized emulsion showed the highest β-carotene bioaccessibility, while sodium caseinate (SCN)-stabilized emulsion showed the highest cellular uptake of β-carotene. The bioavailability of emulsion-encapsulated β-carotene based on the results of bioaccessibility and cellular uptake showed the same order with the results of cellular uptake being SCN > TW80 > WPI. An inconsistency between the results of bioaccessibility and bioavailability was observed, indicating that the cellular uptake assay is necessary for a reliable evaluation of the bioavailability of emulsion-encapsulated compounds. The findings in this study contribute to a better understanding of the correlation between emulsion structure and the digestive fate of emulsion-encapsulated nutrients, which make it possible to achieve controlled or potential targeted delivery of nutrients by designing the structure of emulsion-based carriers. PMID:28930195

Biomimetic strategies for the glioblastoma microenvironment

NASA Astrophysics Data System (ADS)

Cha, Junghwa; Kim, Pilnam

2017-12-01

Glioblastoma multiforme (GBM) is a devastating type of tumor with high mortality, caused by extensive infiltration into adjacent tissue and rapid recurrence. Most therapies for GBM have focused on the cytotoxicity, and have not targeted GBM spread. However, there have been numerous attempts to improve therapy by addressing GBM invasion, through understanding and mimicking its behavior using three-dimensional (3D) experimental models. Compared with two-dimensional models and in vivo animal models, 3D GBM models can capture the invasive motility of glioma cells within a 3D environment comprising many cellular and non-cellular components. Based on tissue engineering techniques, GBM invasion has been investigated within a biologically relevant environment, from biophysical and biochemical perspectives, to clarify the pro-invasive factors of GBM. This review discusses the recent progress in techniques for modeling the microenvironments of GBM tissue and suggests future directions with respect to recreating the GBM microenvironment and preclinical applications.

Route Prediction on Tracking Data to Location-Based Services

NASA Astrophysics Data System (ADS)

Petróczi, Attila István; Gáspár-Papanek, Csaba

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Design and development of a layer-based additive manufacturing process for the realization of metal parts of designed mesostructure

NASA Astrophysics Data System (ADS)

Williams, Christopher Bryant

Low-density cellular materials, metallic bodies with gaseous voids, are a unique class of materials that are characterized by their high strength, low mass, good energy absorption characteristics, and good thermal and acoustic insulation properties. In an effort to take advantage of this entire suite of positive mechanical traits, designers are tailoring the cellular mesostructure for multiple design objectives. Unfortunately, existing cellular material manufacturing technologies limit the design space as they are limited to certain part mesostructure, material type, and macrostructure. The opportunity that exists to improve the design of existing products, and the ability to reap the benefits of cellular materials in new applications is the driving force behind this research. As such, the primary research goal of this work is to design, embody, and analyze a manufacturing process that provides a designer the ability to specify the material type, material composition, void morphology, and mesostructure topology for any conceivable part geometry. The accomplishment of this goal is achieved in three phases of research: (1) Design---Following a systematic design process and a rigorous selection exercise, a layer-based additive manufacturing process is designed that is capable of meeting the unique requirements of fabricating cellular material geometry. Specifically, metal parts of designed mesostructure are fabricated via three-dimensional printing of metal oxide ceramic powder followed by post-processing in a reducing atmosphere. (2) Embodiment ---The primary research hypothesis is verified through the use of the designed manufacturing process chain to successfully realize metal parts of designed mesostructure. (3) Modeling & Evaluation ---The designed manufacturing process is modeled in this final research phase so as to increase understanding of experimental results and to establish a foundation for future analytical modeling research. In addition to an analysis of the physics of primitive creation and an investigation of failure modes during the layered fabrication of thin trusses, build time and cost models are presented in order to verify claims of the process's economic benefits. The main contribution of this research is the embodiment of a novel manner for realizing metal parts of designed mesostructure.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

Driving mechanisms of passive and active transport across cellular membranes as the mechanisms of cell metabolism and development as well as the mechanisms of cellular distance reactions on hormonal expression and the immune response.

PubMed

Ponisovskiy, M R

2011-01-01

The article presents mechanisms of cell metabolism, cell development, cell activity, and maintenance of cellular stability. The literature is reviewed from the point of view of these concepts. The balance between anabolic and catabolic processes induces chemical potentials in the extracellular and intracellular media. The chemical potentials of these media are defined as the driving forces of both passive and active transport of substances across cellular membranes. The driving forces of substance transport across cellular membranes as in cellular metabolism and in immune responses and hormonal expressions are considered in the biochemical and biophysical models, reflecting the mechanisms for maintenance of stability of the internal medium and internal energy of an organism. The interactions of passive transport and active transport of substances across cellular walls promote cell proliferation, as well as the mechanism of cellular capacitors, promoting remote reactions across distance for hormonal expression and immune responses. The offered concept of cellular capacitors has given the possibility to explain the mechanism of remote responses of cells to new situations, resulting in the appearance of additional agents. The biophysical model develops an explanation of some cellular functions: cellular membrane action have been identified with capacitor action, based on the similarity of the structures and as well as on similarity of biophysical properties of electric data that confirm the action of the compound-specific interactions of cells within an organism, promoting hormonal expressions and immune responses to stabilize the thermodynamic system of an organism. Comparison of a cellular membrane action to a capacitor has given the possibility for the explanations of exocytosis and endocytosis mechanisms, internalization of the receptor-ligand complex, selection as a receptor reaction to a ligand by immune responses or hormonal effects, reflecting cellular distance reactions on the hormonal expressions, immune responses, and specificity of the mechanisms of immune reactions. Reviewing current research of cell activity, explanations are presented of mechanisms of apoptosis, autophagy, hormonal expression, and immune responses from the point of view of described cellular mechanisms. Thermodynamic laws are used to confirm the importance of the actions of these mechanisms for maintenance of stability of the internal medium and internal energy of an organism.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

Dynamical analysis of cellular ageing by modeling of gene regulatory network based attractor landscape.

PubMed

Chong, Ket Hing; Zhang, Xiaomeng; Zheng, Jie

2018-01-01

Ageing is a natural phenomenon that is inherently complex and remains a mystery. Conceptual model of cellular ageing landscape was proposed for computational studies of ageing. However, there is a lack of quantitative model of cellular ageing landscape. This study aims to investigate the mechanism of cellular ageing in a theoretical model using the framework of Waddington's epigenetic landscape. We construct an ageing gene regulatory network (GRN) consisting of the core cell cycle regulatory genes (including p53). A model parameter (activation rate) is used as a measure of the accumulation of DNA damage. Using the bifurcation diagrams to estimate the parameter values that lead to multi-stability, we obtained a conceptual model for capturing three distinct stable steady states (or attractors) corresponding to homeostasis, cell cycle arrest, and senescence or apoptosis. In addition, we applied a Monte Carlo computational method to quantify the potential landscape, which displays: I) one homeostasis attractor for low accumulation of DNA damage; II) two attractors for cell cycle arrest and senescence (or apoptosis) in response to high accumulation of DNA damage. Using the Waddington's epigenetic landscape framework, the process of ageing can be characterized by state transitions from landscape I to II. By in silico perturbations, we identified the potential landscape of a perturbed network (inactivation of p53), and thereby demonstrated the emergence of a cancer attractor. The simulated dynamics of the perturbed network displays a landscape with four basins of attraction: homeostasis, cell cycle arrest, senescence (or apoptosis) and cancer. Our analysis also showed that for the same perturbed network with low DNA damage, the landscape displays only the homeostasis attractor. The mechanistic model offers theoretical insights that can facilitate discovery of potential strategies for network medicine of ageing-related diseases such as cancer.

Toward micro-scale spatial modeling of gentrification

NASA Astrophysics Data System (ADS)

O'Sullivan, David

A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects.

Two dimensional finite element heat transfer models for softwood

Treesearch

Hongmei Gu; John F. Hunt

2004-01-01

The anisotropy of wood creates a complex problem for solving heat and mass transfer problems that require analyses be based on fundamental material properties of the wood structure. Most heat transfer models use average thermal properties across either the radial or tangential directions and have not differentiated the effects of cellular alignment, earlywood/latewood...

Mathematics, Thermodynamics, and Modeling to Address Ten Common Misconceptions about Protein Structure, Folding, and Stability

ERIC Educational Resources Information Center

Robic, Srebrenka

2010-01-01

To fully understand the roles proteins play in cellular processes, students need to grasp complex ideas about protein structure, folding, and stability. Our current understanding of these topics is based on mathematical models and experimental data. However, protein structure, folding, and stability are often introduced as descriptive, qualitative…

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

An implementation of cellular automaton model for single-line train working diagram

NASA Astrophysics Data System (ADS)

Hua, Wei; Liu, Jun

2006-04-01

According to the railway transportation system's characteristics, a new cellular automaton model for the single-line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train(s) pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

Simulation of root forms using cellular automata model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation usedmore » four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.« less

Active cell-matrix coupling regulates cellular force landscapes of cohesive epithelial monolayers

NASA Astrophysics Data System (ADS)

Zhao, Tiankai; Zhang, Yao; Wei, Qiong; Shi, Xuechen; Zhao, Peng; Chen, Long-Qing; Zhang, Sulin

2018-03-01

Epithelial cells can assemble into cohesive monolayers with rich morphologies on substrates due to competition between elastic, edge, and interfacial effects. Here we present a molecularly based thermodynamic model, integrating monolayer and substrate elasticity, and force-mediated focal adhesion formation, to elucidate the active biochemical regulation over the cellular force landscapes in cohesive epithelial monolayers, corroborated by microscopy and immunofluorescence studies. The predicted extracellular traction and intercellular tension are both monolayer size and substrate stiffness dependent, suggestive of cross-talks between intercellular and extracellular activities. Our model sets a firm ground toward a versatile computational framework to uncover the molecular origins of morphogenesis and disease in multicellular epithelia.

Mechanical behavior of regular open-cell porous biomaterials made of diamond lattice unit cells.

PubMed

Ahmadi, S M; Campoli, G; Amin Yavari, S; Sajadi, B; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

2014-06-01

Cellular structures with highly controlled micro-architectures are promising materials for orthopedic applications that require bone-substituting biomaterials or implants. The availability of additive manufacturing techniques has enabled manufacturing of biomaterials made of one or multiple types of unit cells. The diamond lattice unit cell is one of the relatively new types of unit cells that are used in manufacturing of regular porous biomaterials. As opposed to many other types of unit cells, there is currently no analytical solution that could be used for prediction of the mechanical properties of cellular structures made of the diamond lattice unit cells. In this paper, we present new analytical solutions and closed-form relationships for predicting the elastic modulus, Poisson׳s ratio, critical buckling load, and yield (plateau) stress of cellular structures made of the diamond lattice unit cell. The mechanical properties predicted using the analytical solutions are compared with those obtained using finite element models. A number of solid and porous titanium (Ti6Al4V) specimens were manufactured using selective laser melting. A series of experiments were then performed to determine the mechanical properties of the matrix material and cellular structures. The experimentally measured mechanical properties were compared with those obtained using analytical solutions and finite element (FE) models. It has been shown that, for small apparent density values, the mechanical properties obtained using analytical and numerical solutions are in agreement with each other and with experimental observations. The properties estimated using an analytical solution based on the Euler-Bernoulli theory markedly deviated from experimental results for large apparent density values. The mechanical properties estimated using FE models and another analytical solution based on the Timoshenko beam theory better matched the experimental observations. Copyright © 2014 Elsevier Ltd. All rights reserved.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

PubMed

Li, Fuhai; Zhou, Xiaobo; Zhu, Jinmin; Ma, Jinwen; Huang, Xudong; Wong, Stephen T C

2007-10-09

High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study. The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system. The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.

Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

PubMed

Nakajima, Kohei; Haruna, Taichi

2011-09-01

In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2013-01-01

The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.

Quantification of substrate and cellular strains in stretchable 3D cell cultures: an experimental and computational framework.

PubMed

González-Avalos, P; Mürnseer, M; Deeg, J; Bachmann, A; Spatz, J; Dooley, S; Eils, R; Gladilin, E

2017-05-01

The mechanical cell environment is a key regulator of biological processes . In living tissues, cells are embedded into the 3D extracellular matrix and permanently exposed to mechanical forces. Quantification of the cellular strain state in a 3D matrix is therefore the first step towards understanding how physical cues determine single cell and multicellular behaviour. The majority of cell assays are, however, based on 2D cell cultures that lack many essential features of the in vivo cellular environment. Furthermore, nondestructive measurement of substrate and cellular mechanics requires appropriate computational tools for microscopic image analysis and interpretation. Here, we present an experimental and computational framework for generation and quantification of the cellular strain state in 3D cell cultures using a combination of 3D substrate stretcher, multichannel microscopic imaging and computational image analysis. The 3D substrate stretcher enables deformation of living cells embedded in bead-labelled 3D collagen hydrogels. Local substrate and cell deformations are determined by tracking displacement of fluorescent beads with subsequent finite element interpolation of cell strains over a tetrahedral tessellation. In this feasibility study, we debate diverse aspects of deformable 3D culture construction, quantification and evaluation, and present an example of its application for quantitative analysis of a cellular model system based on primary mouse hepatocytes undergoing transforming growth factor (TGF-β) induced epithelial-to-mesenchymal transition. © 2017 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Model-based cell number quantification using online single-oxygen sensor data for tissue engineering perfusion bioreactors.

PubMed

Lambrechts, T; Papantoniou, I; Sonnaert, M; Schrooten, J; Aerts, J-M

2014-10-01

Online and non-invasive quantification of critical tissue engineering (TE) construct quality attributes in TE bioreactors is indispensable for the cost-effective up-scaling and automation of cellular construct manufacturing. However, appropriate monitoring techniques for cellular constructs in bioreactors are still lacking. This study presents a generic and robust approach to determine cell number and metabolic activity of cell-based TE constructs in perfusion bioreactors based on single oxygen sensor data in dynamic perfusion conditions. A data-based mechanistic modeling technique was used that is able to correlate the number of cells within the scaffold (R(2)  = 0.80) and the metabolic activity of the cells (R(2)  = 0.82) to the dynamics of the oxygen response to step changes in the perfusion rate. This generic non-destructive measurement technique is effective for a large range of cells, from as low as 1.0 × 10(5) cells to potentially multiple millions of cells, and can open-up new possibilities for effective bioprocess monitoring. © 2014 Wiley Periodicals, Inc.

Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

Cellular automata model for traffic flow at intersections in internet of vehicles

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

A Quantitative Study of Oxygen as a Metabolic Regulator

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabera, Marco E.

2000-01-01

An acute reduction in oxygen delivery to a tissue is associated with metabolic changes aimed at maintaining ATP homeostasis. However, given the complexity of the human bio-energetic system, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). In particular, we are interested in determining mechanisms relating cellular oxygen concentration to observed metabolic responses at the cellular, tissue, organ, and whole body levels and in quantifying how changes in tissue oxygen availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study; we extend a previously developed mathematical model of human bioenergetics, to provide a physicochemical framework that permits quantitative understanding of oxygen as a metabolic regulator. Specifically, the enhancement - sensitivity analysis - permits studying the effects of variations in tissue oxygenation and parameters controlling cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The analysis can distinguish between parameters that must be determined accurately and those that require less precision, based on their effects on model predictions. This capability may prove to be important in optimizing experimental design, thus reducing use of animals.

The use of real-time cell analyzer technology in drug discovery: defining optimal cell culture conditions and assay reproducibility with different adherent cellular models.

PubMed

Atienzar, Franck A; Tilmant, Karen; Gerets, Helga H; Toussaint, Gaelle; Speeckaert, Sebastien; Hanon, Etienne; Depelchin, Olympe; Dhalluin, Stephane

2011-07-01

The use of impedance-based label-free technology applied to drug discovery is nowadays receiving more and more attention. Indeed, such a simple and noninvasive assay that interferes minimally with cell morphology and function allows one to perform kinetic measurements and to obtain information on proliferation, migration, cytotoxicity, and receptor-mediated signaling. The objective of the study was to further assess the usefulness of a real-time cell analyzer (RTCA) platform based on impedance in the context of quality control and data reproducibility. The data indicate that this technology is useful to determine the best coating and cellular density conditions for different adherent cellular models including hepatocytes, cardiomyocytes, fibroblasts, and hybrid neuroblastoma/neuronal cells. Based on 31 independent experiments, the reproducibility of cell index data generated from HepG2 cells exposed to DMSO and to Triton X-100 was satisfactory, with a coefficient of variation close to 10%. Cell index data were also well reproduced when cardiomyocytes and fibroblasts were exposed to 21 compounds three times (correlation >0.91, p < 0.0001). The data also show that a cell index decrease is not always associated with cytotoxicity effects and that there are some confounding factors that can affect the analysis. Finally, another drawback is that the correlation analysis between cellular impedance measurements and classical toxicity endpoints has been performed on a limited number of compounds. Overall, despite some limitations, the RTCA technology appears to be a powerful and reliable tool in drug discovery because of the reasonable throughput, rapid and efficient performance, technical optimization, and cell quality control.

Autophagy capacity and sub-mitochondrial heterogeneity shape Bnip3-induced mitophagy regulation of apoptosis.

PubMed

Choe, Sehyo Charley; Hamacher-Brady, Anne; Brady, Nathan Ryan

2015-08-08

Mitochondria are key regulators of apoptosis. In response to stress, BH3-only proteins activate pro-apoptotic Bcl2 family proteins Bax and Bak, which induce mitochondrial outer membrane permeabilization (MOMP). While the large-scale mitochondrial release of pro-apoptotic proteins activates caspase-dependent cell death, a limited release results in sub-lethal caspase activation which promotes tumorigenesis. Mitochondrial autophagy (mitophagy) targets dysfunctional mitochondria for degradation by lysosomes, and undergoes extensive crosstalk with apoptosis signaling, but its influence on apoptosis remains undetermined. The BH3-only protein Bnip3 integrates apoptosis and mitophagy signaling at different signaling domains. Bnip3 inhibits pro-survival Bcl2 members via its BH3 domain and activates mitophagy through its LC3 Interacting Region (LIR), which is responsible for binding to autophagosomes. Previously, we have shown that Bnip3-activated mitophagy prior to apoptosis induction can reduce mitochondrial activation of caspases, suggesting that a reduction to mitochondrial levels may be pro-survival. An outstanding question is whether organelle dynamics and/or recently discovered subcellular variations of protein levels responsible for both MOMP sensitivity and crosstalk between apoptosis and mitophagy can influence the cellular apoptosis decision event. To that end, here we undertook a systems biology analysis of mitophagy-apoptosis crosstalk at the level of cellular mitochondrial populations. Based on experimental findings, we developed a multi-scale, hybrid model with an individually adaptive mitochondrial population, whose actions are determined by protein levels, embedded in an agent-based model (ABM) for simulating subcellular dynamics and local feedback via reactive oxygen species signaling. Our model, supported by experimental evidence, identified an emergent regulatory structure within canonical apoptosis signaling. We show that the extent of mitophagy is determined by levels and spatial localization of autophagy capacity, and subcellular mitochondrial protein heterogeneities. Our model identifies mechanisms and conditions that alter the mitophagy decision within mitochondrial subpopulations to an extent sufficient to shape cellular outcome to apoptotic stimuli. Overall, our modeling approach provides means to suggest new experiments and implement findings at multiple scales in order to understand how network topologies and subcellular heterogeneities can influence signaling events at individual organelle level, and hence, determine the emergence of heterogeneity in cellular decisions due the actions of the collective intra-cellular population.

Integrated experimental and model-based analysis reveals the spatial aspects of EGFR activation dynamics

PubMed Central

Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. Steven; Resat, Haluk

2012-01-01

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks. PMID:22952062

A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

USGS Publications Warehouse

Clarke, K.C.; Hoppen, S.; Gaydos, L.

1997-01-01

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

Using a cellular model to explore human-facilitated spread of risk of EAB in Minnesota

Treesearch

Anantha Prasad; Louis Iverson; Matthew Peters; Steve Matthews

2011-01-01

The Emerald Ash Borer has made inroads to Minnesota in the past two years, killing ash trees. We use our spatially explicit cell based model called EAB-SHIFT to calculate the risk of infestation owing to flight characteristics and short distance movement of the insect (insect flight model, IFM), and the human facilitated agents like roads, campgrounds etc. (insect ride...

Space-time dynamics of Stem Cell Niches: a unified approach for Plants.

PubMed

Pérez, Maria Del Carmen; López, Alejandro; Padilla, Pablo

2013-06-01

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Space-time dynamics of stem cell niches: a unified approach for plants.

PubMed

Pérez, Maria del Carmen; López, Alejandro; Padilla, Pablo

2013-04-02

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Comparative evaluation of transmembrane ion transport due to monopolar and bipolar nanosecond, high-intensity electroporation pulses based on full three-dimensional analyses

NASA Astrophysics Data System (ADS)

Hu, Q.; Joshi, R. P.

2017-07-01

Electric pulse driven membrane poration finds applications in the fields of biomedical engineering and drug/gene delivery. Here we focus on nanosecond, high-intensity electroporation and probe the role of pulse shape (e.g., monopolar-vs-bipolar), multiple electrode scenarios, and serial-versus-simultaneous pulsing, based on a three-dimensional time-dependent continuum model in a systematic fashion. Our results indicate that monopolar pulsing always leads to higher and stronger cellular uptake. This prediction is in agreement with experimental reports and observations. It is also demonstrated that multi-pronged electrode configurations influence and increase the degree of cellular uptake.

The third dimension bridges the gap between cell culture and live tissue.

PubMed

Pampaloni, Francesco; Reynaud, Emmanuel G; Stelzer, Ernst H K

2007-10-01

Moving from cell monolayers to three-dimensional (3D) cultures is motivated by the need to work with cellular models that mimic the functions of living tissues. Essential cellular functions that are present in tissues are missed by 'petri dish'-based cell cultures. This limits their potential to predict the cellular responses of real organisms. However, establishing 3D cultures as a mainstream approach requires the development of standard protocols, new cell lines and quantitative analysis methods, which include well-suited three-dimensional imaging techniques. We believe that 3D cultures will have a strong impact on drug screening and will also decrease the use of laboratory animals, for example, in the context of toxicity assays.

Optogenetic Approaches to Drug Discovery in Neuroscience and Beyond.

PubMed

Zhang, Hongkang; Cohen, Adam E

2017-07-01

Recent advances in optogenetics have opened new routes to drug discovery, particularly in neuroscience. Physiological cellular assays probe functional phenotypes that connect genomic data to patient health. Optogenetic tools, in particular tools for all-optical electrophysiology, now provide a means to probe cellular disease models with unprecedented throughput and information content. These techniques promise to identify functional phenotypes associated with disease states and to identify compounds that improve cellular function regardless of whether the compound acts directly on a target or through a bypass mechanism. This review discusses opportunities and unresolved challenges in applying optogenetic techniques throughout the discovery pipeline - from target identification and validation, to target-based and phenotypic screens, to clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

A Multiplex Enzymatic Machinery for Cellular Protein S-nitrosylation.

PubMed

Seth, Divya; Hess, Douglas T; Hausladen, Alfred; Wang, Liwen; Wang, Ya-Juan; Stamler, Jonathan S

2018-02-01

S-nitrosylation, the oxidative modification of Cys residues by nitric oxide (NO) to form S-nitrosothiols (SNOs), modifies all main classes of proteins and provides a fundamental redox-based cellular signaling mechanism. However, in contrast to other post-translational protein modifications, S-nitrosylation is generally considered to be non-enzymatic, involving multiple chemical routes. We report here that endogenous protein S-nitrosylation in the model organism E. coli depends principally upon the enzymatic activity of the hybrid cluster protein Hcp, employing NO produced by nitrate reductase. Anaerobiosis on nitrate induces both Hcp and nitrate reductase, thereby resulting in the S-nitrosylation-dependent assembly of a large interactome including enzymes that generate NO (NO synthase), synthesize SNO-proteins (SNO synthase), and propagate SNO-based signaling (trans-nitrosylases) to regulate cell motility and metabolism. Thus, protein S-nitrosylation by NO in E. coli is essentially enzymatic, and the potential generality of the multiplex enzymatic mechanism that we describe may support a re-conceptualization of NO-based cellular signaling. Copyright © 2017 Elsevier Inc. All rights reserved.

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

PubMed

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

Repeated exposure of mouse dermal fibroblasts at a sub-cytotoxic dose of UVB leads to premature senescence: a robust model of cellular photoaging.

PubMed

Zeng, Ji-ping; Bi, Bo; Chen, Liang; Yang, Ping; Guo, Yu; Zhou, Yi-qun; Liu, Tian-yi

2014-01-01

Photoaging skin is due to accumulative effect of UV irradiation that mainly imposes its damage on dermal fibroblasts. To mimic the specific cellular responses invoked by long term effect of UVB, it is preferable to develop a photo-damaged model in vitro based on repeated UVB exposure instead of a single exposure. To develop a photo-damaged model of fibroblasts by repeated UVB exposure allowing for investigation of molecular mechanism underlying premature senescence and testing of potential anti-photoaging compounds. Mouse dermal fibroblasts (MDFs) at early passages (passages 1-3) were exposed to a series of 4 sub-cytotoxic dose of UVB. The senescent phenotypes were detected at 24 or 48h after the last irradiation including cell viability, ROS generation, mitochondrial membrane potential, cell cycle, production and degradation of extracellular matrix. Repeated exposure of UVB resulted in remarkable features of senescence. It effectively avoided the disadvantages of single dose such as induction of cell death rather than senescence, inadequate stress resulting in cellular self-rehabilitation. Our work confirms the possibility of detecting cellular machinery that mediates UVB damage to fibroblasts in vitro by repeated exposure, while the potential molecular mechanisms including cell surface receptors, protein kinase signal transduction pathways, and transcription factors remain to be further evaluated. Copyright © 2013 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Elastic force restricts growth of the murine utricle

PubMed Central

Gnedeva, Ksenia; Jacobo, Adrian; Salvi, Joshua D; Petelski, Aleksandra A; Hudspeth, A J

2017-01-01

Dysfunctions of hearing and balance are often irreversible in mammals owing to the inability of cells in the inner ear to proliferate and replace lost sensory receptors. To determine the molecular basis of this deficiency we have investigated the dynamics of growth and cellular proliferation in a murine vestibular organ, the utricle. Based on this analysis, we have created a theoretical model that captures the key features of the organ’s morphogenesis. Our experimental data and model demonstrate that an elastic force opposes growth of the utricular sensory epithelium during development, confines cellular proliferation to the organ’s periphery, and eventually arrests its growth. We find that an increase in cellular density and the subsequent degradation of the transcriptional cofactor Yap underlie this process. A reduction in mechanical constraints results in accumulation and nuclear translocation of Yap, which triggers proliferation and restores the utricle’s growth; interfering with Yap’s activity reverses this effect. DOI: http://dx.doi.org/10.7554/eLife.25681.001 PMID:28742024

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

On the combined gradient-stochastic plasticity model: Application to Mo-micropillar compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konstantinidis, A. A., E-mail: akonsta@civil.auth.gr; Zhang, X., E-mail: zhangxu26@126.com; Aifantis, E. C., E-mail: mom@mom.gen.auth.gr

2015-02-17

A formulation for addressing heterogeneous material deformation is proposed. It is based on the use of a stochasticity-enhanced gradient plasticity model implemented through a cellular automaton. The specific application is on Mo-micropillar compression, for which the irregularities of the strain bursts observed have been experimentally measured and theoretically interpreted through Tsallis' q-statistics.

Two-dimensional finite element heat transfer model of softwood. Part I, Effective thermal conductivity

Treesearch

John F. Hunt; Hongmei Gu

2006-01-01

The anisotropy of wood complicates solution of heat and mass transfer problems that require analyses be based on fundamental material properties of the wood structure. Most heat transfer models use average thermal properties across either the radial or tangential direction and do not differentiate the effects of cellular alignment, earlywood/latewood differences, or...

Numerically exploring habitat fragmentation effects on populations using cell-based coupled map lattices

Treesearch

Michael Bevers; Curtis H. Flather

1999-01-01

We examine habitat size, shape, and arrangement effects on populations using a discrete reaction-diffusion model. Diffusion is modeled passively and applied to a cellular grid of territories forming a coupled map lattice. Dispersal mortality is proportional to the amount of nonhabitat and fully occupied habitat surrounding a given cell, with distance decay. After...

A multi-model approach to nucleic acid-based drug development.

PubMed

Gautherot, Isabelle; Sodoyer, Regís

2004-01-01

With the advent of functional genomics and the shift of interest towards sequence-based therapeutics, the past decades have witnessed intense research efforts on nucleic acid-mediated gene regulation technologies. Today, RNA interference is emerging as a groundbreaking discovery, holding promise for development of genetic modulators of unprecedented potency. Twenty-five years after the discovery of antisense RNA and ribozymes, gene control therapeutics are still facing developmental difficulties, with only one US FDA-approved antisense drug currently available in the clinic. Limited predictability of target site selection models is recognized as one major stumbling block that is shared by all of the so-called complementary technologies, slowing the progress towards a commercial product. Currently employed in vitro systems for target site selection include RNAse H-based mapping, antisense oligonucleotide microarrays, and functional screening approaches using libraries of catalysts with randomized target-binding arms to identify optimal ribozyme/DNAzyme cleavage sites. Individually, each strategy has its drawbacks from a drug development perspective. Utilization of message-modulating sequences as therapeutic agents requires that their action on a given target transcript meets criteria of potency and selectivity in the natural physiological environment. In addition to sequence-dependent characteristics, other factors will influence annealing reactions and duplex stability, as well as nucleic acid-mediated catalysis. Parallel consideration of physiological selection systems thus appears essential for screening for nucleic acid compounds proposed for therapeutic applications. Cellular message-targeting studies face issues relating to efficient nucleic acid delivery and appropriate analysis of response. For reliability and simplicity, prokaryotic systems can provide a rapid and cost-effective means of studying message targeting under pseudo-cellular conditions, but such approaches also have limitations. To streamline nucleic acid drug discovery, we propose a multi-model strategy integrating high-throughput-adapted bacterial screening, followed by reporter-based and/or natural cellular models and potentially also in vitro assays for characterization of the most promising candidate sequences, before final in vivo testing.

A Cybrid Cell Model for the Assessment of the Link Between Mitochondrial Deficits and Sporadic Parkinson’s Disease

PubMed Central

Arduíno, Daniela M.; Esteves, A. Raquel; Swerdlow, Russell H.; Cardoso, Sandra M.

2015-01-01

Parkinson’s disease (PD) is a multifactorial and clinically complex age-related movement disorder. The cause of its most common form (sporadic PD, sPD) is unknown, but one prominent causal factor is mitochondrial dysfunction. Although several genetic- and toxin-based models have been developed along the last decades to mimic the pathological cascade of PD, cellular models that reliably recapitulate the pathological features of the neurons that degenerate in PD are scarce. We describe here the generation of cytoplasmic hybrid cells (or cybrids) as a cellular model of sPD. This approach consists on the fusion of platelets harboring mtDNA from sPD patients with cells in which the endogenous mtDNA has been depleted (Rho0 cells). The sPD cybrid model has been successful in recapitulating most of the hallmarks of sPD, constituting now a validated model for addressing the link between mitochondrial dysfunction and sPD pathology. PMID:25634293

A cybrid cell model for the assessment of the link between mitochondrial deficits and sporadic Parkinson's disease.

PubMed

Arduíno, Daniela M; Esteves, A Raquel; Swerdlow, Russell H; Cardoso, Sandra M

2015-01-01

Parkinson's disease (PD) is a multifactorial and clinically complex age-related movement disorder. The cause of its most common form (sporadic PD, sPD) is unknown, but one prominent causal factor is mitochondrial dysfunction. Although several genetic- and toxin-based models have been developed along the last decades to mimic the pathological cascade of PD, cellular models that reliably recapitulate the pathological features of the neurons that degenerate in PD are scarce.We describe here the generation of cytoplasmic hybrid cells (or cybrids) as a cellular model of sPD. This approach consists on the fusion of platelets harboring mtDNA from sPD patients with cells in which the endogenous mtDNA has been depleted (Rho0 cells).The sPD cybrid model has been successful in recapitulating most of the hallmarks of sPD, constituting now a validated model for addressing the link between mitochondrial dysfunction and sPD pathology.

Accurate reliability analysis method for quantum-dot cellular automata circuits

NASA Astrophysics Data System (ADS)

Cui, Huanqing; Cai, Li; Wang, Sen; Liu, Xiaoqiang; Yang, Xiaokuo

2015-10-01

Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.

Investigation of tissue cellularity at the tip of the core biopsy needle with optical coherence tomography.

PubMed

Iftimia, Nicusor; Park, Jesung; Maguluri, Gopi; Krishnamurthy, Savitri; McWatters, Amanda; Sabir, Sharjeel H

2018-02-01

We report the development and the pre-clinical testing of a new technology based on optical coherence tomography (OCT) for investigating tissue composition at the tip of the core biopsy needle. While ultrasound, computed tomography, and magnetic resonance imaging are routinely used to guide needle placement within a tumor, they still do not provide the resolution needed to investigate tissue cellularity (ratio between viable tumor and benign stroma) at the needle tip prior to taking a biopsy core. High resolution OCT imaging, however, can be used to investigate tissue morphology at the micron scale, and thus to determine if the biopsy core would likely have the expected composition. Therefore, we implemented this capability within a custom-made biopsy gun and evaluated its capability for a correct estimation of tumor tissue cellularity. A pilot study on a rabbit model of soft tissue cancer has shown the capability of this technique to provide correct evaluation of tumor tissue cellularity in over 85% of the cases. These initial results indicate the potential benefit of the OCT-based approach for improving the success of the core biopsy procedures.

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical simulation of dendrite growth in nickel-based superalloy and validated by in-situ observation using high temperature confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Xu, Qingyan; Liu, Baicheng

2017-12-01

Dendritic structures are the predominant microstructural constituents of nickel-based superalloys, an understanding of the dendrite growth is required in order to obtain the desirable microstructure and improve the performance of castings. For this reason, numerical simulation method and an in-situ observation technology by employing high temperature confocal laser scanning microscopy (HT-CLSM) were used to investigate dendrite growth during solidification process. A combined cellular automaton-finite difference (CA-FD) model allowing for the prediction of dendrite growth of binary alloys was developed. The algorithm of cells capture was modified, and a deterministic cellular automaton (DCA) model was proposed to describe neighborhood tracking. The dendrite and detail morphology, especially hundreds of dendrites distribution at a large scale and three-dimensional (3-D) polycrystalline growth, were successfully simulated based on this model. The dendritic morphologies of samples before and after HT-CLSM were both observed by optical microscope (OM) and scanning electron microscope (SEM). The experimental observations presented a reasonable agreement with the simulation results. It was also found that primary or secondary dendrite arm spacing, and segregation pattern were significantly influenced by dendrite growth. Furthermore, the directional solidification (DS) dendritic evolution behavior and detail morphology were also simulated based on the proposed model, and the simulation results also agree well with experimental results.

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

Crowd evacuation model based on bacterial foraging algorithm

NASA Astrophysics Data System (ADS)

Shibiao, Mu; Zhijun, Chen

To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model can effectively describe a real evacuation.

Systems metabolic engineering: genome-scale models and beyond.

PubMed

Blazeck, John; Alper, Hal

2010-07-01

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.

A density distribution algorithm for bone incorporating local orthotropy, modal analysis and theories of cellular solids.

PubMed

Impelluso, Thomas J

2003-06-01

An algorithm for bone remodeling is presented which allows for both a redistribution of density and a continuous change of principal material directions for the orthotropic material properties of bone. It employs a modal analysis to add density for growth and a local effective strain based analysis to redistribute density. General re-distribution functions are presented. The model utilizes theories of cellular solids to relate density and strength. The code predicts the same general density distributions and local orthotropy as observed in reality.

Analysis of peristaltic waves and their role in migrating Physarum plasmodia

NASA Astrophysics Data System (ADS)

Lewis, Owen L.; Guy, Robert D.

2017-07-01

The true slime mold Physarum polycephalum exhibits a vast array of sophisticated manipulations of its intracellular cytoplasm. Growing microplasmodia of Physarum have been observed to adopt an elongated tadpole shape, then contract in a rhythmic, traveling wave pattern that resembles peristaltic pumping. This contraction drives a fast flow of non-gelated cytoplasm along the cell longitudinal axis. It has been hypothesized that this flow of cytoplasm is a driving factor in generating motility of the plasmodium. In this work, we use two different mathematical models to investigate how peristaltic pumping within Physarum may be used to drive cellular motility. We compare the relative phase of flow and deformation waves predicted by both models to similar phase data collected from in vivo experiments using Physarum plasmodia. The first is a PDE model based on a dimensional reduction of peristaltic pumping within a finite length chamber. The second is a more sophisticated computational model which accounts for more general shape changes, more complex cellular mechanics, and dynamically modulated adhesion to the underlying substrate. This model allows us to directly compute cell crawling speed. Both models suggest that a mechanical asymmetry in the cell is required to reproduce the experimental observations. Such a mechanical asymmetry is also shown to increase the potential for cellular migration, as measured by both stress generation and migration velocity.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

ERIC Educational Resources Information Center

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do…

An Evaluation of the Efficacy of a Laboratory Exercise on Cellular Respiration

ERIC Educational Resources Information Center

Scholer, Anne-Marie; Hatton, Mary

2008-01-01

This study is an analysis of the effectiveness of a faculty-designed laboratory experience about a difficult topic, cellular respiration. The activity involves a hands-on model of the cellular-respiration process, making use of wooden ball-and-stick chemistry models and small toy trucks on a table top model of the mitochondrion. Students…

Cell mechanics in biomedical cavitation

PubMed Central

Wang, Qianxi; Manmi, Kawa; Liu, Kuo-Kang

2015-01-01

Studies on the deformation behaviours of cellular entities, such as coated microbubbles and liposomes subject to a cavitation flow, become increasingly important for the advancement of ultrasonic imaging and drug delivery. Numerical simulations for bubble dynamics of ultrasound contrast agents based on the boundary integral method are presented in this work. The effects of the encapsulating shell are estimated by adapting Hoff's model used for thin-shell contrast agents. The viscosity effects are estimated by including the normal viscous stress in the boundary condition. In parallel, mechanical models of cell membranes and liposomes as well as state-of-the-art techniques for quantitative measurement of viscoelasticity for a single cell or coated microbubbles are reviewed. The future developments regarding modelling and measurement of the material properties of the cellular entities for cutting-edge biomedical applications are also discussed. PMID:26442142

PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction.

PubMed

Krallinger, Martin; Rodriguez-Penagos, Carlos; Tendulkar, Ashish; Valencia, Alfonso

2009-07-01

There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l.

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

19F-perfluorocarbon-labeled human peripheral blood mononuclear cells can be detected in vivo using clinical MRI parameters in a therapeutic cell setting.

PubMed

Fink, Corby; Gaudet, Jeffrey M; Fox, Matthew S; Bhatt, Shashank; Viswanathan, Sowmya; Smith, Michael; Chin, Joseph; Foster, Paula J; Dekaban, Gregory A

2018-01-12

A 19 Fluorine ( 19 F) perfluorocarbon cell labeling agent, when employed with an appropriate cellular MRI protocol, allows for in vivo cell tracking. 19 F cellular MRI can be used to non-invasively assess the location and persistence of cell-based cancer vaccines and other cell-based therapies. This study was designed to determine the feasibility of labeling and tracking peripheral blood mononuclear cells (PBMC), a heterogeneous cell population. Under GMP-compliant conditions human PBMC were labeled with a 19 F-based MRI cell-labeling agent in a manner safe for autologous re-injection. Greater than 99% of PBMC labeled with the 19 F cell-labeling agent without affecting functionality or affecting viability. The 19 F-labeled PBMC were detected in vivo in a mouse model at the injection site and in a draining lymph node. A clinical cellular MR protocol was optimized for the detection of PBMC injected both at the surface of a porcine shank and at a depth of 1.2 cm, equivalent to depth of a human lymph node, using a dual 1 H/ 19 F dual switchable surface radio frequency coil. This study demonstrates it is feasible to label and track 19 F-labeled PBMC using clinical MRI protocols. Thus, 19 F cellular MRI represents a non-invasive imaging technique suitable to assess the effectiveness of cell-based cancer vaccines.

Cellular senescence in the Penna model of aging

NASA Astrophysics Data System (ADS)

Periwal, Avikar

2013-11-01

Cellular senescence is thought to play a major role in age-related diseases, which cause nearly 67% of all human deaths worldwide. Recent research in mice showed that exercising mice had higher levels of telomerase, an enzyme that helps maintain telomere length, than nonexercising mice. A commonly used model for biological aging was proposed by Penna. I propose a modification of the Penna model that incorporates cellular senescence and find an analytical steady-state solution following Coe, Mao, and Cates [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.89.288103 89, 288103 (2002)]. I find that models corresponding to delayed cellular senescence have younger populations that live longer. I fit the model to the United Kingdom's death distribution, which the original Penna model cannot do.

Second-harmonic generation and fluorescence lifetime imaging microscopy through a rodent mammary imaging window

NASA Astrophysics Data System (ADS)

Young, Pamela A.; Nazir, Muhammad; Szulczewski, Michael J.; Keely, Patricia J.; Eliceiri, Kevin W.

2012-03-01

Tumor-Associated Collagen Signatures (TACS) have been identified that manifest in specific ways during breast tumor progression and that correspond to patient outcome. There are also compelling metabolic changes associated with carcinoma invasion and progression. We have characterized the difference in the autofluorescent properties of metabolic co-factors, NADH and FAD, between normal and carcinoma breast cell lines. Also, we have shown in vitro that increased collagen density alters metabolic genes which are associated with glycolysis and leads to a more invasive phenotype. Establishing the relationship between collagen density, cellular metabolism, and metastasis in physiologically relevant cancer models is crucial for developing cancer therapies. To study cellular metabolism with respect to collagen density in vivo, we use multiphoton fluorescence excitation microscopy (MPM) in conjunction with a rodent mammary imaging window implanted in defined mouse cancer models. These models are ideal for the study of collagen changes in vivo, allowing determination of corresponding metabolic changes in breast cancer invasion and progression. To measure cellular metabolism, we collect fluorescence lifetime (FLIM) signatures of NADH and FAD, which are known to change based on the microenvironment of the cells. Additionally, MPM systems are capable of collecting second harmonic generation (SHG) signals which are a nonlinear optical property of collagen. Therefore, MPM, SHG, and FLIM are powerful tools with great potential for characterizing key features of breast carcinoma in vivo. Below we present the current efforts of our collaborative group to develop intravital approaches based on these imaging techniques to look at defined mouse mammary models.

Electoral surveys’ influence on the voting processes: a cellular automata model

NASA Astrophysics Data System (ADS)

Alves, S. G.; Oliveira Neto, N. M.; Martins, M. L.

2002-12-01

Nowadays, in societies threatened by atomization, selfishness, short-term thinking, and alienation from political life, there is a renewed debate about classical questions concerning the quality of democratic decision making. In this work a cellular automata model for the dynamics of free elections, based on the social impact theory is proposed. By using computer simulations, power-law distributions for the size of electoral clusters and decision time have been obtained. The major role of broadcasted electoral surveys in guiding opinion formation and stabilizing the “status quo” was demonstrated. Furthermore, it was shown that in societies where these surveys are manipulated within the universally accepted statistical error bars, even a majoritary opposition could be hindered from reaching power through the electoral path.

Comparison between reflectance confocal microscopy and two-photon microscopy in early detection of cutaneous radiation injury in a mouse model in-vivo.

PubMed

Jang, Won Hyuk; Kwon, Soonjae; Shim, Sehwan; Jang, Won-Suk; Myung, Jae Kyung; Yang, Sejung; Park, Sunhoo; Kim, Ki Hean

2018-05-12

Cutaneous radiation injury (CRI) is a skin injury caused by high dose exposure of ionizing radiation (IR). For proper treatment, early detection of CRI before clinical symptoms is important. Optical microscopic techniques such as reflectance confocal microscopy (RCM) and two-photon microscopy (TPM) have been tested as the early diagnosis method by detecting cellular changes. In this study, RCM and TPM were compared in the detection of cellular changes caused by CRI in an in-vivo mouse model. CRI was induced on the mouse hindlimb skin with various IR doses and the injured skin regions were imaged longitudinally by both modalities until the onset of clinical symptoms. Both RCM and TPM detected the changes of epidermal cells and sebaceous glands before clinical symptoms in different optical contrasts. RCM detected changes of cell morphology and scattering property based on light reflection. TPM detected detail changes of cellular structures based on autofluorescence of cells. Since both RCM and TPM were sensitive to the early-stage CRI by using different contrasts, the optimal method for clinical CRI diagnosis could be either individual methods or their combination. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Laser-based direct-write techniques for cell printing

PubMed Central

Schiele, Nathan R; Corr, David T; Huang, Yong; Raof, Nurazhani Abdul; Xie, Yubing; Chrisey, Douglas B

2016-01-01

Fabrication of cellular constructs with spatial control of cell location (±5 μm) is essential to the advancement of a wide range of applications including tissue engineering, stem cell and cancer research. Precise cell placement, especially of multiple cell types in co- or multi-cultures and in three dimensions, can enable research possibilities otherwise impossible, such as the cell-by-cell assembly of complex cellular constructs. Laser-based direct writing, a printing technique first utilized in electronics applications, has been adapted to transfer living cells and other biological materials (e.g., enzymes, proteins and bioceramics). Many different cell types have been printed using laser-based direct writing, and this technique offers significant improvements when compared to conventional cell patterning techniques. The predominance of work to date has not been in application of the technique, but rather focused on demonstrating the ability of direct writing to pattern living cells, in a spatially precise manner, while maintaining cellular viability. This paper reviews laser-based additive direct-write techniques for cell printing, and the various cell types successfully laser direct-written that have applications in tissue engineering, stem cell and cancer research are highlighted. A particular focus is paid to process dynamics modeling and process-induced cell injury during laser-based cell direct writing. PMID:20814088

Macro-architectured cellular materials: Properties, characteristic modes, and prediction methods

NASA Astrophysics Data System (ADS)

Ma, Zheng-Dong

2017-12-01

Macro-architectured cellular (MAC) material is defined as a class of engineered materials having configurable cells of relatively large (i.e., visible) size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson's ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

PubMed Central

Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed. PMID:29487626

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review.

PubMed

Savio, Gianpaolo; Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed.

DIGE Proteome Analysis Reveals Suitability of Ischemic Cardiac In Vitro Model for Studying Cellular Response to Acute Ischemia and Regeneration

PubMed Central

Haas, Sina; Jahnke, Heinz-Georg; Moerbt, Nora; von Bergen, Martin; Aharinejad, Seyedhossein; Andrukhova, Olena; Robitzki, Andrea A.

2012-01-01

Proteomic analysis of myocardial tissue from patient population is suited to yield insights into cellular and molecular mechanisms taking place in cardiovascular diseases. However, it has been limited by small sized biopsies and complicated by high variances between patients. Therefore, there is a high demand for suitable model systems with the capability to simulate ischemic and cardiotoxic effects in vitro, under defined conditions. In this context, we established an in vitro ischemia/reperfusion cardiac disease model based on the contractile HL-1 cell line. To identify pathways involved in the cellular alterations induced by ischemia and thereby defining disease-specific biomarkers and potential target structures for new drug candidates we used fluorescence 2D-difference gel electrophoresis. By comparing spot density changes in ischemic and reperfusion samples we detected several protein spots that were differentially abundant. Using MALDI-TOF/TOF-MS and ESI-MS the proteins were identified and subsequently grouped by functionality. Most prominent were changes in apoptosis signalling, cell structure and energy-metabolism. Alterations were confirmed by analysis of human biopsies from patients with ischemic cardiomyopathy. With the establishment of our in vitro disease model for ischemia injury target identification via proteomic research becomes independent from rare human material and will create new possibilities in cardiac research. PMID:22384053

Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model.

PubMed

Chai, Chen; Wong, Yiik Diew; Wang, Xuesong

2017-07-01

This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computer modeling describes gravity-related adaptation in cell cultures.

PubMed

Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny

2009-12-16

Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool

PubMed Central

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-01-01

Background It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. Results This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. Conclusion SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes. PMID:18706080

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.

PubMed

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-08-15

It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes.

Membrane-Based Functions in the Origin of Cellular Life

NASA Technical Reports Server (NTRS)

Chipot, Christophe; New, Michael H.; Schweighofer, Karl; Pohorille, Andrew; Wilson, Michael A.

1999-01-01

Our objective is to help explain how the earliest ancestors of contemporary cells (protocells) performed their essential functions employing only the molecules available in the protobiological milieu. Our hypothesis is that vesicles, built of amphiphilic, membrane-forming materials, emerged early in protobiological evolution and served as precursors to protocells. We further assume that the cellular functions associated with contemporary membranes, such as capturing and, transducing of energy, signaling, or sequestering organic molecules and ions, evolved in these membrane environments. An alternative hypothesis is that these functions evolved in different environments and were incorporated into membrane-bound structures at some later stage of evolution. We focus on the application of the fundamental principles of physics and chemistry to determine how they apply to the formation of a primitive, functional cell. Rather than attempting to develop specific models for cellular functions and to identify the origin of the molecules which perform these functions, our goal is to define the structural and energetic conditions that any successful model must fulfill, therefore providing physico-chemical boundaries for these models. We do this by carrying out large-scale, molecular level computer simulations on systems of interest.

Modeling Land Use/Cover Changes in an African Rural Landscape

NASA Astrophysics Data System (ADS)

Kamusoko, C.; Aniya, M.

2006-12-01

Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata

Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information.

PubMed

Tack, Ignace L M M; Nimmegeers, Philippe; Akkermans, Simen; Hashem, Ihab; Van Impe, Jan F M

2017-01-01

Clustered microbial communities are omnipresent in the food industry, e.g., as colonies of microbial pathogens in/on food media or as biofilms on food processing surfaces. These clustered communities are often characterized by metabolic differentiation among their constituting cells as a result of heterogeneous environmental conditions in the cellular surroundings. This paper focuses on the role of metabolic differentiation due to oxygen gradients in the development of Escherichia coli cell communities, whereby low local oxygen concentrations lead to cellular secretion of weak acid products. For this reason, a metabolic model has been developed for the facultative anaerobe E. coli covering the range of aerobic, microaerobic, and anaerobic environmental conditions. This metabolic model is expressed as a multiparametric programming problem, in which the influence of low extracellular pH values and the presence of undissociated acid cell products in the environment has been taken into account. Furthermore, the developed metabolic model is incorporated in MICRODIMS, an in-house developed individual-based modeling framework to simulate microbial colony and biofilm dynamics. Two case studies have been elaborated using the MICRODIMS simulator: (i) biofilm growth on a substratum surface and (ii) submerged colony growth in a semi-solid mixed food product. In the first case study, the acidification of the biofilm environment and the emergence of typical biofilm morphologies have been observed, such as the mushroom-shaped structure of mature biofilms and the formation of cellular chains at the exterior surface of the biofilm. The simulations show that these morphological phenomena are respectively dependent on the initial affinity of pioneer cells for the substratum surface and the cell detachment process at the outer surface of the biofilm. In the second case study, a no-growth zone emerges in the colony center due to a local decline of the environmental pH. As a result, cellular growth in the submerged colony is limited to the colony periphery, implying a linear increase of the colony radius over time. MICRODIMS has been successfully used to reproduce complex dynamics of clustered microbial communities.

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Computation Modeling of Limb-bud Dysmorphogenesis: Predicting Cellular Dynamics and Key Events in Developmental Toxicity with a Multicellular Systems Model (FutureToxII)

EPA Science Inventory

Congenital limb malformations are among the most frequent malformation occurs in humans, with a frequency of about 1 in 500 to 1 in 1000 human live births. ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput (HTS) and computational methods that...

Metabolic modeling of energy balances in Mycoplasma hyopneumoniae shows that pyruvate addition increases growth rate.

PubMed

Kamminga, Tjerko; Slagman, Simen-Jan; Bijlsma, Jetta J E; Martins Dos Santos, Vitor A P; Suarez-Diez, Maria; Schaap, Peter J

2017-10-01

Mycoplasma hyopneumoniae is cultured on large-scale to produce antigen for inactivated whole-cell vaccines against respiratory disease in pigs. However, the fastidious nutrient requirements of this minimal bacterium and the low growth rate make it challenging to reach sufficient biomass yield for antigen production. In this study, we sequenced the genome of M. hyopneumoniae strain 11 and constructed a high quality constraint-based genome-scale metabolic model of 284 chemical reactions and 298 metabolites. We validated the model with time-series data of duplicate fermentation cultures to aim for an integrated model describing the dynamic profiles measured in fermentations. The model predicted that 84% of cellular energy in a standard M. hyopneumoniae cultivation was used for non-growth associated maintenance and only 16% of cellular energy was used for growth and growth associated maintenance. Following a cycle of model-driven experimentation in dedicated fermentation experiments, we were able to increase the fraction of cellular energy used for growth through pyruvate addition to the medium. This increase in turn led to an increase in growth rate and a 2.3 times increase in the total biomass concentration reached after 3-4 days of fermentation, enhancing the productivity of the overall process. The model presented provides a solid basis to understand and further improve M. hyopneumoniae fermentation processes. Biotechnol. Bioeng. 2017;114: 2339-2347. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Safety impacts of red light cameras at signalized intersections based on cellular automata models.

PubMed

Chai, C; Wong, Y D; Lum, K M

2015-01-01

This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

The role of autophagy in Parkinson's disease: rotenone-based modeling

PubMed Central

2013-01-01

Background Autophagy-mediated self-digestion of cytoplasmic inclusions may be protective against neurodegenerative diseases such as Parkinson’s disease (PD). However, excessive autophagic activation evokes autophagic programmed cell death. Methods In this study, we aimed at exploring the role of autophagy in the pathogenesis of rotenone-induced cellular and animal models for PD. Results Reactive oxygen species over-generation, mitochondrial membrane potential reduction or apoptosis rate elevation occurred in a dose-dependent fashion in rotenone-treated human neuroblastoma cell line SH-SY5Y. The time- and dose-dependent increases in autophagic marker microtubule-associated protein1 light chain 3 (LC3) expression and decreases in autophagic adaptor protein P62 were observed in this cellular model. LC3-positive autophagic vacuoles were colocalized with alpha-synuclein-overexpressed aggregations. Moreover, the number of autophagic vacuoles was increased in rotenone-based PD models in vitro and in vivo. Conclusions These data, along with our previous finding showing rotenone-induced toxicity was prevented by the autophagy enhancers and was aggravated by the autophagy inhibitors in SH-SY5Y, suggest that autophagy contributes to the pathogenesis of PD, attenuates the rotenone toxicity and possibly represents a new subcellular target for treating PD. PMID:23497442

SYMPOSIUM SESSION PROPOSAL: INCORPORATION OF MODE OF ACTION INTO MECHANISTICALLY-BASED QUANTITATIVE MODELS

EPA Science Inventory

The biological processes by which environmental pollutants induce adverse health effects is most likely regulated by complex interactions dependent upon the route of exposure, dose, kinetics of distribution, and multiple cellular responses. To further complicate deciphering thes...

Virtual Embryo: Cell-Agent Based Modeling of Developmental Processes and Toxicities (CSS BOSC)

EPA Science Inventory

Spatial regulation of cellular dynamics is fundamental to morphological development. As such, chemical disruption of spatial dynamics is a determinant of developmental toxicity. Incorporating spatial dynamics into AOPs for developmental toxicity is desired but constrained by the ...

A simple 2D biofilm model yields a variety of morphological features.

PubMed

Hermanowicz, S W

2001-01-01

A two-dimensional biofilm model was developed based on the concept of cellular automata. Three simple, generic processes were included in the model: cell growth, internal and external mass transport and cell detachment (erosion). The model generated a diverse range of biofilm morphologies (from dense layers to open, mushroom-like forms) similar to those observed in real biofilm systems. Bulk nutrient concentration and external mass transfer resistance had a large influence on the biofilm structure.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

PubMed Central

Westermark, Stefanie; Steuer, Ralf

2016-01-01

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes. PMID:28083530

Theoretical aspects and modelling of cellular decision making, cell killing and information-processing in photodynamic therapy of cancer.

PubMed

Gkigkitzis, Ioannis

2013-01-01

The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

A propagating ATPase gradient drives transport of surface-confined cellular cargo

NASA Astrophysics Data System (ADS)

Vecchiarelli, Anthony; Neuman, Keir; Mizuuchi, Kiyoshi

2014-03-01

The process of DNA segregation is of central importance for all organisms. Although eukaryotic mitosis is relatively well established, the most common mechanism employed for bacterial DNA segregation has been unclear. ParA ATPases form dynamic patterns on the bacterial nucleoid, to spatially organize plasmids, chromosomes and other large cellular cargo, but the force generating mechanism has been a source of controversy and debate. A dominant view proposes that ParA-mediated transport and cargo positioning occurs via a filament-based mechanism that resembles eukaryotic mitosis. Here we present direct evidence against such models. Our cell-free reconstitution supports a non-filament-based mode of transport that may be as widely found in nature as actin filaments and microtubules.

On the complex relationship between energy expenditure and longevity: Reconciling the contradictory empirical results with a simple theoretical model.

PubMed

Hou, Chen; Amunugama, Kaushalya

2015-07-01

The relationship between energy expenditure and longevity has been a central theme in aging studies. Empirical studies have yielded controversial results, which cannot be reconciled by existing theories. In this paper, we present a simple theoretical model based on first principles of energy conservation and allometric scaling laws. The model takes into considerations the energy tradeoffs between life history traits and the efficiency of the energy utilization, and offers quantitative and qualitative explanations for a set of seemingly contradictory empirical results. We show that oxidative metabolism can affect cellular damage and longevity in different ways in animals with different life histories and under different experimental conditions. Qualitative data and the linearity between energy expenditure, cellular damage, and lifespan assumed in previous studies are not sufficient to understand the complexity of the relationships. Our model provides a theoretical framework for quantitative analyses and predictions. The model is supported by a variety of empirical studies, including studies on the cellular damage profile during ontogeny; the intra- and inter-specific correlations between body mass, metabolic rate, and lifespan; and the effects on lifespan of (1) diet restriction and genetic modification of growth hormone, (2) the cold and exercise stresses, and (3) manipulations of antioxidant. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Assessment of radiofrequency exposure from cellular telephone daily use in an epidemiological study: German Validation study of the international case-control study of cancers of the brain--INTERPHONE-Study.

PubMed

Berg, Gabriele; Schüz, Joachim; Samkange-Zeeb, Florence; Blettner, Maria

2005-05-01

The objective of the study is to validate self-reported cellular phone use information by comparing it with the cumulative emitted power and duration of calls measured by software-modified cellular phones (SMP). The information was obtained using a questionnaire developed for the international case-control study on the risk of the use of mobile phones in tumours of the brain or salivary gland (INTERPHONE-study). The study was conducted in Bielefeld, Germany. Volunteers were asked to use SMPs instead of their own cellular phones for a period of 1 month. The SMP recorded the power emitted by the mobile phone handset during each base station contact. Information on cellular phone use for the same time period from traffic records of the network providers and from face-to-face interviews with the participants 3 months after the SMP use was assessed. Pearson's correlation coefficients and linear regression models were used to analyse the association between information from the interview and from the SMP. In total, 1757 personal mobile phone calls were recorded for 45 persons by SMP and traffic records. The correlation between the self-reported information about the number and the duration of calls with the cumulative power of calls was 0.50 (P<0.01) and 0.48 (P<0.01), respectively. Almost 23% of the variance of the cumulative power was explained by either the number or the cumulative duration of calls. After inclusion of possible confounding factors in the regression model, the variance increased to 26%. Minor confounding factors were "network provider", "contract form", and "cellular phone model". The number of calls alone is a sufficient parameter to estimate the cumulative power emitted by the handset of a cellular telephone. The cumulative power emitted by these phones is only associated with number of calls but not with possible confounding factors. Using the mobile phone while driving, mainly in cities, or mainly in rural areas is not associated with the recorded cumulative power in the SMP.

Three dimensional multi-cellular muscle-like tissue engineering in perfusion-based bioreactors.

PubMed

Cerino, Giulia; Gaudiello, Emanuele; Grussenmeyer, Thomas; Melly, Ludovic; Massai, Diana; Banfi, Andrea; Martin, Ivan; Eckstein, Friedrich; Grapow, Martin; Marsano, Anna

2016-01-01

Conventional tissue engineering strategies often rely on the use of a single progenitor cell source to engineer in vitro biological models; however, multi-cellular environments can better resemble the complexity of native tissues. Previous described co-culture models used skeletal myoblasts, as parenchymal cell source, and mesenchymal or endothelial cells, as stromal component. Here, we propose instead the use of adipose tissue-derived stromal vascular fraction cells, which include both mesenchymal and endothelial cells, to better resemble the native stroma. Percentage of serum supplementation is one of the crucial parameters to steer skeletal myoblasts toward either proliferation (20%) or differentiation (5%) in two-dimensional culture conditions. On the contrary, three-dimensional (3D) skeletal myoblast culture often simply adopts the serum content used in monolayer, without taking into account the new cell environment. When considering 3D cultures of mm-thick engineered tissues, homogeneous and sufficient oxygen supply is paramount to avoid formation of necrotic cores. Perfusion-based bioreactor culture can significantly improve the oxygen access to the cells, enhancing the viability and the contractility of the engineered tissues. In this study, we first investigated the influence of different serum supplementations on the skeletal myoblast ability to proliferate and differentiate during 3D perfusion-based culture. We tested percentages of serum promoting monolayer skeletal myoblast-proliferation (20%) and differentiation (5%) and suitable for stromal cell culture (10%) with a view to identify the most suitable condition for the subsequent co-culture. The 10% serum medium composition resulted in the highest number of mature myotubes and construct functionality. Co-culture with stromal vascular fraction cells at 10% serum also supported the skeletal myoblast differentiation and maturation, hence providing a functional engineered 3D muscle model that resembles the native multi-cellular environment. © 2015 Wiley Periodicals, Inc.

Synchrotron IR microspectroscopy for protein structure analysis: Potential and questions

DOE PAGES

Yu, Peiqiang

2006-01-01

Synchrotron radiation-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced technique to the study of pure protein inherent structure at a cellular level in biological tissues. In this review, a novel approach was introduced to show the potential of the newly developed, advancedmore » synchrotron-based analytical technology, which can be used to localize relatively “pure“ protein in the plant tissues and relatively reveal protein inherent structure and protein molecular chemical make-up within intact tissue at cellular and subcellular levels. Several complex protein IR spectra data analytical techniques (Gaussian and Lorentzian multi-component peak modeling, univariate and multivariate analysis, principal component analysis (PCA), and hierarchical cluster analysis (CLA) are employed to relatively reveal features of protein inherent structure and distinguish protein inherent structure differences between varieties/species and treatments in plant tissues. By using a multi-peak modeling procedure, RELATIVE estimates (but not EXACT determinations) for protein secondary structure analysis can be made for comparison purpose. The issues of pro- and anti-multi-peaking modeling/fitting procedure for relative estimation of protein structure were discussed. By using the PCA and CLA analyses, the plant molecular structure can be qualitatively separate one group from another, statistically, even though the spectral assignments are not known. The synchrotron-based technology provides a new approach for protein structure research in biological tissues at ultraspatial resolutions.« less

Harnessing cellular differentiation to improve ALA-based photodynamic therapy in an artificial skin model

NASA Astrophysics Data System (ADS)

Maytin, Edward; Anand, Sanjay; Sato, Nobuyuki; Mack, Judith; Ortel, Bernhard

2005-04-01

During ALA-based photodynamic therapy (PDT), a pro-drug (aminolevulinic acid; ALA) is taken up by tumor cells and metabolically converted to a photosensitizing intermediate (protoporphyrin IX; PpIX). ALA-based PDT, while an emerging treatment modality, remains suboptimal for most cancers (e.g. squamous cell carcinoma of the skin). Many treatment failures may be largely due to insufficient conversion of ALA to PpIX within cells. We discovered a novel way to increase the conversion of ALA to PpIX, by administering agents that can drive terminal differentiation (i.e., accelerate cellular maturation). Terminally-differentiated epithelial cells show higher levels of intracellular PpIX, apparently via increased levels of a rate-limiting enzyme, coproporphyrinogen oxidase (CPO). To study these mechanisms in a three-dimensional tissue, we developed an organotypic model that mimics true epidermal physiology in a majority of respects. A line of rat epidermal keratinocytes (REKs), when grown in raft cultures, displays all the features of a fully-differentiated epidermis. Addition of ALA to the culture medium results in ALA uptake and PpIX synthesis, with subsequent death of keratinocytes upon exposure to blue light. Using this model, we can manipulate cellular differentiation via three different approaches. (1) Vitamin D, a hormone that enhances keratinocyte differentiation; (2) Hoxb13, a nuclear transcription factor that affects the genetically-controlled differentiation program of stratifying cells (3) Hyaluronan, an abundant extracellular matrix molecule that regulates epidermal differentiation. Because the raft cultures contain only a single cell type (no blood, fibroblasts, etc.) the effects of terminal differentiation upon CPO, PpIX, and keratinocyte cell death can be specifically defined.

Estimating Primary Production of Picophytoplankton Using the Carbon-Based Ocean Productivity Model: A Preliminary Study

PubMed Central

Liang, Yantao; Zhang, Yongyu; Wang, Nannan; Luo, Tingwei; Zhang, Yao; Rivkin, Richard B.

2017-01-01

Picophytoplankton are acknowledged to contribute significantly to primary production (PP) in the ocean while now the method to measure PP of picophytoplankton (PPPico) at large scales is not yet well established. Although the traditional 14C method and new technologies based on the use of stable isotopes (e.g., 13C) can be employed to accurately measure in situ PPPico, the time-consuming and labor-intensive shortage of these methods constrain their application in a survey on large spatiotemporal scales. To overcome this shortage, a modified carbon-based ocean productivity model (CbPM) is proposed for estimating the PPPico whose principle is based on the group-specific abundance, cellular carbon conversion factor (CCF), and temperature-derived growth rate of picophytoplankton. Comparative analysis showed that the estimated PPPico using CbPM method is significantly and positively related (r2 = 0.53, P < 0.001, n = 171) to the measured 14C uptake. This significant relationship suggests that CbPM has the potential to estimate the PPPico over large spatial and temporal scales. Currently this model application may be limited by the use of invariant cellular CCF and the relatively small data sets to validate the model which may introduce some uncertainties and biases. Model performance will be improved by the use of variable conversion factors and the larger data sets representing diverse growth conditions. Finally, we apply the CbPM-based model on the collected data during four cruises in the Bohai Sea in 2005. Model-estimated PPPico ranged from 0.1 to 11.9, 29.9 to 432.8, 5.5 to 214.9, and 2.4 to 65.8 mg C m-2 d-1 during March, June, September, and December, respectively. This study shed light on the estimation of global PPPico using carbon-based production model. PMID:29051755

Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

PubMed Central

de la Fuente, Ildefonso Martínez

2010-01-01

One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

A cellular reporter to evaluate CRM1 nuclear export activity: functional analysis of the cancer-related mutant E571K.

PubMed

García-Santisteban, Iraia; Arregi, Igor; Alonso-Mariño, Marián; Urbaneja, María A; Garcia-Vallejo, Juan J; Bañuelos, Sonia; Rodríguez, Jose A

2016-12-01

The exportin CRM1 binds nuclear export signals (NESs), and mediates active transport of NES-bearing proteins from the nucleus to the cytoplasm. Structural and biochemical analyses have uncovered the molecular mechanisms underlying CRM1/NES interaction. CRM1 binds NESs through a hydrophobic cleft, whose open or closed conformation facilitates NES binding and release. Several cofactors allosterically modulate the conformation of the NES-binding cleft through intramolecular interactions involving an acidic loop and a C-terminal helix in CRM1. This current model of CRM1-mediated nuclear export has not yet been evaluated in a cellular setting. Here, we describe SRV100, a cellular reporter to interrogate CRM1 nuclear export activity. Using this novel tool, we provide evidence further validating the model of NES binding and release by CRM1. Furthermore, using both SRV100-based cellular assays and in vitro biochemical analyses, we investigate the functional consequences of a recurrent cancer-related mutation, which targets a residue near CRM1 NES-binding cleft. Our data indicate that this mutation does not necessarily abrogate the nuclear export activity of CRM1, but may increase its affinity for NES sequences bearing a more negatively charged C-terminal end.

Physical biology of human brain development.

PubMed

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2015-01-01

Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view toward surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level toward form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

ISDD: A computational model of particle sedimentation, diffusion and target cell dosimetry for in vitro toxicity studies

PubMed Central

2010-01-01

Background The difficulty of directly measuring cellular dose is a significant obstacle to application of target tissue dosimetry for nanoparticle and microparticle toxicity assessment, particularly for in vitro systems. As a consequence, the target tissue paradigm for dosimetry and hazard assessment of nanoparticles has largely been ignored in favor of using metrics of exposure (e.g. μg particle/mL culture medium, particle surface area/mL, particle number/mL). We have developed a computational model of solution particokinetics (sedimentation, diffusion) and dosimetry for non-interacting spherical particles and their agglomerates in monolayer cell culture systems. Particle transport to cells is calculated by simultaneous solution of Stokes Law (sedimentation) and the Stokes-Einstein equation (diffusion). Results The In vitro Sedimentation, Diffusion and Dosimetry model (ISDD) was tested against measured transport rates or cellular doses for multiple sizes of polystyrene spheres (20-1100 nm), 35 nm amorphous silica, and large agglomerates of 30 nm iron oxide particles. Overall, without adjusting any parameters, model predicted cellular doses were in close agreement with the experimental data, differing from as little as 5% to as much as three-fold, but in most cases approximately two-fold, within the limits of the accuracy of the measurement systems. Applying the model, we generalize the effects of particle size, particle density, agglomeration state and agglomerate characteristics on target cell dosimetry in vitro. Conclusions Our results confirm our hypothesis that for liquid-based in vitro systems, the dose-rates and target cell doses for all particles are not equal; they can vary significantly, in direct contrast to the assumption of dose-equivalency implicit in the use of mass-based media concentrations as metrics of exposure for dose-response assessment. The difference between equivalent nominal media concentration exposures on a μg/mL basis and target cell doses on a particle surface area or number basis can be as high as three to six orders of magnitude. As a consequence, in vitro hazard assessments utilizing mass-based exposure metrics have inherently high errors where particle number or surface areas target cells doses are believed to drive response. The gold standard for particle dosimetry for in vitro nanotoxicology studies should be direct experimental measurement of the cellular content of the studied particle. However, where such measurements are impractical, unfeasible, and before such measurements become common, particle dosimetry models such as ISDD provide a valuable, immediately useful alternative, and eventually, an adjunct to such measurements. PMID:21118529

Under the Microscope: Single-Domain Antibodies for Live-Cell Imaging and Super-Resolution Microscopy.

PubMed

Traenkle, Bjoern; Rothbauer, Ulrich

2017-01-01

Single-domain antibodies (sdAbs) have substantially expanded the possibilities of advanced cellular imaging such as live-cell or super-resolution microscopy to visualize cellular antigens and their dynamics. In addition to their unique properties including small size, high stability, and solubility in many environments, sdAbs can be efficiently functionalized according to the needs of the respective imaging approach. Genetically encoded intrabodies fused to fluorescent proteins (chromobodies) have become versatile tools to study dynamics of endogenous proteins in living cells. Additionally, sdAbs conjugated to organic dyes were shown to label cellular structures with high density and minimal fluorophore displacement making them highly attractive probes for super-resolution microscopy. Here, we review recent advances of the chromobody technology to visualize localization and dynamics of cellular targets and the application of chromobody-based cell models for compound screening. Acknowledging the emerging importance of super-resolution microscopy in cell biology, we further discuss advantages and challenges of sdAbs for this technology.

Subcutaneous administration CpG-ODNs acts as a potent adjuvant for an HIV-1-tat-based vaccine candidate to elicit cellular immunity in BALB/c mice.

PubMed

Panahi, Zeinab; Abdoli, Asghar; Mosayebi, Ghasem; Mahdavi, Mehdi; Bahrami, Fariborz

2018-03-01

To evaluate the combined effects of CpG oligodeoxynucleotides (CpG-ODNs) adjuvant and subcutaneous injection route on efficacy of a HIV-1-tat DNA vaccine candidate using BALB/c mice as an animal model. Evaluation of cellular and humoral immunity of mice injected subcutaneously with HIV-1-tat gene cloned into a pcDNA3.1 vector indicated that significant levels of IFN-γ cytokine secretion (900 pg/ml), lymphocyte proliferation (2.5 stimulation index) and IgG 2a (1.45 absorbance 450 nm) production could be achieved. These indicators of stimulated cellular immunity were elicited 2 weeks after the last injection (P < 0.05). Formulation of HIV-1-tat DNA vaccine candidate with CpG-ODNs as an adjuvant while administrated subcutaneously are a promising approach to induce effective cellular immunity responses against HIV-1 infection.

Regulation, cell differentiation and protein-based inheritance.

PubMed

Malagnac, Fabienne; Silar, Philippe

2006-11-01

Recent research using fungi as models provide new insight into the ability of regulatory networks to generate cellular states that are sufficiently stable to be faithfully transmitted to daughter cells, thereby generating epigenetic inheritance. Such protein-based inheritance is driven by infectious factors endowed with properties usually displayed by prions. We emphasize the contribution of regulatory networks to the emerging properties displayed by cells.

Searching for Order Within Chaos: Complexity Theorys Implications to Intelligence Support During Joint Operational Planning

DTIC Science & Technology

2017-06-09

structures constantly arise in firefights and skirmishes on the battlefield. Source: Andrew Ilachinski, Artificial War: Multiagent- Based Simulation of...Alternative Methods of Analysis and Innovative Organizational Structures .” Conference, Rome, Italy March 31-April 2. ...Intelligence Analysis, Joint Operational Planning, Cellular Automata, Agent- Based Modeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Researches on the behaviour of cellular antiballistic composites based on AlMg-SiC alloys

NASA Astrophysics Data System (ADS)

Bălţătescu, O.; Florea, R. M.; Rusu, I.; Carcea, I.

2015-11-01

The researches presented in this paper refers basically to the impact of a small/medium caliber bullet shot on a light armor built on the base of a AlMg-SiC metallic composite cellular/foam. Thus, we study the antiballistic behavior and protection properties of the armor, based on the effects that occur at the impact zone of the bullet with the composite surface. We performed an antiballistic behavior modeling by means of a finite element analysis, based on a "multi grid" Fast Finite Element (FFE) system. We used for this purpose the DYNA 2D software package. The obtained samples show after the impact the occurrence of concentration / deformation pores effect and intercellular cracks development to the interior of the composite. Those effects, depending on speed, mass and length of the projectile ballistic trajectory, reduce zonal tensions due to the effect of cell walls deformation. It was obtained a good correlation between modeling results and the electron microscope analyse of the impact area. It is worth mentioning that almost all values for impact energy absorbed by the composite armor are in the protection active zone provided by it.

Optical scatter imaging of cellular and mitochondrial swelling in brain tissue models of stroke

NASA Astrophysics Data System (ADS)

Johnson, Lee James

2001-08-01

The severity of brain edema resulting from a stroke can determine a patient's survival and the extent of their recovery. Cellular swelling is the microscopic source of a significant part of brain edema. Mitochondrial swelling also appears to be a determining event in the death or survival of the cells that are injured during a stroke. Therapies for reducing brain edema are not effective in many cases and current treatments of stroke do not address mitochondrial swelling at all. This dissertation is motivated by the lack of a complete understanding of cellular swelling resulting from stroke and the lack of a good method to begin to study mitochondrial swelling resulting from stroke in living brain tissue. In this dissertation, a novel method of detecting mitochondrial and cellular swelling in living hippocampal slices is developed and validated. The system is used to obtain spatial and temporal information about cellular and mitochondrial swelling resulting from various models of stroke. The effect of changes in water content on light scatter and absorption are examined in two models of brain edema. The results of this study demonstrate that optical techniques can be used to detect changes in water content. Mie scatter theory, the theoretical basis of the dual- angle scatter ratio imaging system, is presented. Computer simulations based on Mie scatter theory are used to determine the optimal angles for imaging. A detailed account of the early systems is presented to explain the motivations for the system design, especially polarization, wavelength and light path. Mitochondrial sized latex particles are used to determine the system response to changes in scattering particle size and concentration. The dual-angle scatter ratio imaging system is used to distinguish between osmotic and excitotoxic models of stroke injury. Such distinction cannot be achieved using the current techniques to study cellular swelling in hippocampal slices. The change in the scatter ratio is then shown to correlate to mitochondrial swelling, as observed with electron microscopy. The system is finally used to study mitochondrial and cellular swelling. Evidence of the susceptibility of certain hippocampal regions, CA1 and the dentate gyrus, to exhibit mitochondrial swelling as the result of oxygen and glucose deprivation is presented. In addition, for the first time, the time course of mitochondrial swelling is seen. Finally, experiments with scatter imaging and measurement of nitric oxide with carbon fiber electrodes demonstrate a clear link between nitric oxide and cellular swelling. A potential mechanism of the action of nitric oxide is evaluated. Nitric oxide appears to act to cause cellular swelling without the release of glutamate. The use of targeted nitric oxide inhibitors may be useful for the reduction of edema.

Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Zhang, Yi; Chrisler, William B.

2012-10-02

The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerizationmore » and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.« less

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804

Designing synthetic RNA for delivery by nanoparticles

NASA Astrophysics Data System (ADS)

Jedrzejczyk, Dominika; Gendaszewska-Darmach, Edyta; Pawlowska, Roza; Chworos, Arkadiusz

2017-03-01

The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid’s nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided.

Study on queueing behavior in pedestrian evacuation by extended cellular automata model

NASA Astrophysics Data System (ADS)

Hu, Jun; You, Lei; Zhang, Hong; Wei, Juan; Guo, Yangyong

2018-01-01

This paper proposes a pedestrian evacuation model for effective simulation of evacuation efficiency based on extended cellular automata. In the model, pedestrians' momentary transition probability to a target position is defined in terms of the floor field and queueing time, and the critical time is defined as the waiting time threshold in a queue. Queueing time and critical time are derived using Fractal Brownian Motion through analysis of pedestrian arrival characteristics. Simulations using the platform and actual evacuations were conducted to study the relationships among system evacuation time, average system velocity, pedestrian density, flow rate, and critical time. The results demonstrate that at low pedestrian density, evacuation efficiency can be improved through adoption of the shortest route strategy, and critical time has an inverse relationship with average system velocity. Conversely, at higher pedestrian densities, it is better to adopt the shortest queueing time strategy, and critical time is inversely related to flow rate.

Space biosynthesis systems

NASA Technical Reports Server (NTRS)

Nyiri, L. K.; Toth, G. M.

1976-01-01

Model reactions based on chemical, enzymatic or cellular conversion of D glucose into d gluconic acid are designed to unequivocally define the advantages of microgravity on reaction mechanisms, mass-transfers and separation of organic chemicals and to serve as procedures to test the performance characteristics of space bioprocessing equipment.

Biomaterials for integration with 3-D bioprinting.

PubMed

Skardal, Aleksander; Atala, Anthony

2015-03-01

Bioprinting has emerged in recent years as an attractive method for creating 3-D tissues and organs in the laboratory, and therefore is a promising technology in a number of regenerative medicine applications. It has the potential to (i) create fully functional replacements for damaged tissues in patients, and (ii) rapidly fabricate small-sized human-based tissue models, or organoids, for diagnostics, pathology modeling, and drug development. A number of bioprinting modalities have been explored, including cellular inkjet printing, extrusion-based technologies, soft lithography, and laser-induced forward transfer. Despite the innovation of each of these technologies, successful implementation of bioprinting relies heavily on integration with compatible biomaterials that are responsible for supporting the cellular components during and after biofabrication, and that are compatible with the bioprinting device requirements. In this review, we will evaluate a variety of biomaterials, such as curable synthetic polymers, synthetic gels, and naturally derived hydrogels. Specifically we will describe how they are integrated with the bioprinting technologies above to generate bioprinted constructs with practical application in medicine.

Phase averaging method for the modeling of the multiprobe and cutaneous cryosurgery

NASA Astrophysics Data System (ADS)

E Shilnikov, K.; Kudryashov, N. A.; Y Gaiur, I.

2017-12-01

In this paper we consider the problem of planning and optimization of the cutaneous and multiprobe cryosurgery operations. An explicit scheme based on the finite volume approximation of phase averaged Pennes bioheat transfer model is applied. The flux relaxation method is used for the stability improvement of scheme. Skin tissue is considered as strongly inhomogeneous media. Computerized planning tool is tested on model cryotip-based and cutaneous cryosurgery problems. For the case of cutaneous cryosurgery the method of an additional freezing element mounting is studied as an approach to optimize the cellular necrosis front propagation.

Perspectives for the treatment of sensorineural hearing loss by cellular regeneration of the inner ear.

PubMed

Almeida-Branco, Mario S; Cabrera, Sonia; Lopez-Escamez, Jose A

2015-01-01

Sensorineural hearing loss is a caused by the loss of the cochlear hair cells with the consequent deafferentation of spiral ganglion neurons. Humans do not show endogenous cellular regeneration in the inner ear and there is no exogenous therapy that allows the replacement of the damaged hair cells. Currently, treatment is based on the use of hearing aids and cochlear implants that present different outcomes, some difficulties in auditory discrimination and a limited useful life. More advanced technology is hindered by the functional capacity of the remaining spiral ganglion neurons. The latest advances with stem cell therapy and cellular reprogramming have developed several possibilities to induce endogenous regeneration or stem cell transplantation to replace damaged inner ear hair cells and restore hearing function. With further knowledge of the cellular and molecular biology of the inner ear and its embryonic development, it will be possible to use induced stem cells as in vitro models of disease and as replacement cellular therapy. Investigation in this area is focused on generating cellular therapy with clinical use for the treatment of profound sensorineural hearing loss. Copyright © 2014 Elsevier España, S.L.U. and Sociedad Española de Otorrinolaringología y Patología Cérvico-Facial. All rights reserved.

Anti-oxidative cellular protection effect of fasting-induced autophagy as a mechanism for hormesis.

PubMed

Moore, Michael N; Shaw, Jennifer P; Ferrar Adams, Dawn R; Viarengo, Aldo

2015-06-01

The aim of this investigation was to test the hypothesis that fasting-induced augmented lysosomal autophagic turnover of cellular proteins and organelles will reduce potentially harmful lipofuscin (age-pigment) formation in cells by more effectively removing oxidatively damaged proteins. An animal model (marine snail--common periwinkle, Littorina littorea) was used to experimentally test this hypothesis. Snails were deprived of algal food for 7 days to induce an augmented autophagic response in their hepatopancreatic digestive cells (hepatocyte analogues). This treatment resulted in a 25% reduction in the cellular content of lipofuscin in the digestive cells of the fasting animals in comparison with snails fed ad libitum on green alga (Ulva lactuca). Similar findings have previously been observed in the digestive cells of marine mussels subjected to copper-induced oxidative stress. Additional measurements showed that fasting significantly increased cellular health based on lysosomal membrane stability, and reduced lipid peroxidation and lysosomal/cellular triglyceride. These findings support the hypothesis that fasting-induced augmented autophagic turnover of cellular proteins has an anti-oxidative cytoprotective effect by more effectively removing damaged proteins, resulting in a reduction in the formation of potentially harmful proteinaceous aggregates such as lipofuscin. The inference from this study is that autophagy is important in mediating hormesis. An increase was demonstrated in physiological complexity with fasting, using graph theory in a directed cell physiology network (digraph) model to integrate the various biomarkers. This was commensurate with increased health status, and supportive of the hormesis hypothesis. The potential role of enhanced autophagic lysosomal removal of damaged proteins in the evolutionary acquisition of stress tolerance in intertidal molluscs is discussed and parallels are drawn with the growing evidence for the involvement of autophagy in hormesis and anti-ageing processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Generation and detection of broadband airborne ultrasound with cellular polymer ferroelectrets

NASA Astrophysics Data System (ADS)

Dansachmüller, Mario; Minev, Ivan; Bartu, Petr; Graz, Ingrid; Arnold, Nikita; Bauer, Siegfried

2007-11-01

Cellular polypropylene ferroelectrets are useful for broadband airborne ultrasound generation and detection up to the fundamental thickness extension resonance. The authors show that the coupling of ferroelectrets to air alters the electromechanical resonance of the foam. In an acoustical cavity, Fabry-Perot resonances are obtained, which is in excellent agreement with the plane wave model calculations. For material assessment in airborne ultrasound applications, a figure of merit is used based on the electromechanical coupling factor and acoustical impedance of the material. The good coupling of ferroelectrets to gases results from the small acoustical impedance of the material.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts

PubMed Central

Iskandar, Anita R.; Xiang, Yang; Frentzel, Stefan; Talikka, Marja; Leroy, Patrice; Kuehn, Diana; Guedj, Emmanuel; Martin, Florian; Mathis, Carole; Ivanov, Nikolai V.; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

Organotypic 3D cultures of epithelial cells are grown at the air–liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model. PMID:26085348

Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts.

PubMed

Iskandar, Anita R; Xiang, Yang; Frentzel, Stefan; Talikka, Marja; Leroy, Patrice; Kuehn, Diana; Guedj, Emmanuel; Martin, Florian; Mathis, Carole; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2015-09-01

Organotypic 3D cultures of epithelial cells are grown at the air-liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.

A Computational Model Predicting Disruption of Blood Vessel Development

PubMed Central

Kleinstreuer, Nicole; Dix, David; Rountree, Michael; Baker, Nancy; Sipes, Nisha; Reif, David; Spencer, Richard; Knudsen, Thomas

2013-01-01

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. PMID:23592958

Overexpression of the human DEK oncogene reprograms cellular metabolism and promotes glycolysis

PubMed Central

Watanabe, Miki; Muraleedharan, Ranjithmenon; Lambert, Paul F.; Lane, Andrew N.; Romick-Rosendale, Lindsey E.; Wells, Susanne I.

2017-01-01

The DEK oncogene is overexpressed in many human malignancies including at early tumor stages. Our reported in vitro and in vivo models of squamous cell carcinoma have demonstrated that DEK contributes functionally to cellular and tumor survival and to proliferation. However, the underlying molecular mechanisms remain poorly understood. Based on recent RNA sequencing experiments, DEK expression was necessary for the transcription of several metabolic enzymes involved in anabolic pathways. This identified a possible mechanism whereby DEK may drive cellular metabolism to enable cell proliferation. Functional metabolic Seahorse analysis demonstrated increased baseline and maximum extracellular acidification rates, a readout of glycolysis, in DEK-overexpressing keratinocytes and squamous cell carcinoma cells. DEK overexpression also increased the maximum rate of oxygen consumption and therefore increased the potential for oxidative phosphorylation (OxPhos). To detect small metabolites that participate in glycolysis and the tricarboxylic acid cycle (TCA) that supplies substrate for OxPhos, we carried out NMR-based metabolomics studies. We found that high levels of DEK significantly reprogrammed cellular metabolism and altered the abundances of amino acids, TCA cycle intermediates and the glycolytic end products lactate, alanine and NAD+. Taken together, these data support a scenario whereby overexpression of the human DEK oncogene reprograms keratinocyte metabolism to fulfill energy and macromolecule demands required to enable and sustain cancer cell growth. PMID:28558019

Overexpression of the human DEK oncogene reprograms cellular metabolism and promotes glycolysis.

PubMed

Matrka, Marie C; Watanabe, Miki; Muraleedharan, Ranjithmenon; Lambert, Paul F; Lane, Andrew N; Romick-Rosendale, Lindsey E; Wells, Susanne I

2017-01-01

The DEK oncogene is overexpressed in many human malignancies including at early tumor stages. Our reported in vitro and in vivo models of squamous cell carcinoma have demonstrated that DEK contributes functionally to cellular and tumor survival and to proliferation. However, the underlying molecular mechanisms remain poorly understood. Based on recent RNA sequencing experiments, DEK expression was necessary for the transcription of several metabolic enzymes involved in anabolic pathways. This identified a possible mechanism whereby DEK may drive cellular metabolism to enable cell proliferation. Functional metabolic Seahorse analysis demonstrated increased baseline and maximum extracellular acidification rates, a readout of glycolysis, in DEK-overexpressing keratinocytes and squamous cell carcinoma cells. DEK overexpression also increased the maximum rate of oxygen consumption and therefore increased the potential for oxidative phosphorylation (OxPhos). To detect small metabolites that participate in glycolysis and the tricarboxylic acid cycle (TCA) that supplies substrate for OxPhos, we carried out NMR-based metabolomics studies. We found that high levels of DEK significantly reprogrammed cellular metabolism and altered the abundances of amino acids, TCA cycle intermediates and the glycolytic end products lactate, alanine and NAD+. Taken together, these data support a scenario whereby overexpression of the human DEK oncogene reprograms keratinocyte metabolism to fulfill energy and macromolecule demands required to enable and sustain cancer cell growth.

Crystallization of isotactic polypropylene in different shear regimes

NASA Astrophysics Data System (ADS)

Spina, Roberto; Spekowius, Marcel; Hopmann, Christian

2017-10-01

The investigation of the shear-induced crystallization of isotactic polypropylene in isothermal conditions in different shear regimes is the aim of the present research. A multiscale framework is developed and implemented to compute the nucleation and growth of spherulites, based on material parameters needed to connect crystallization kinetics to the molecular material properties. The framework consists of a macro-model based on a Finite Element Method linked to a micro-model based on Cellular Automata. The main results are the evolution of the crystallization degree and spherulite space filling as a function of imposed temperature ash shear rate.

In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy.

PubMed

Jiang, Xiaoyu; Li, Hua; Xie, Jingping; McKinley, Eliot T; Zhao, Ping; Gore, John C; Xu, Junzhong

2017-07-01

A temporal diffusion MRI spectroscopy based approach has been developed to quantify cancer cell size and density in vivo. A novel imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method selects a specific limited diffusion spectral window for an accurate quantification of cell sizes ranging from 10 to 20 μm in common solid tumors. In practice, it is achieved by a combination of a single long diffusion time pulsed gradient spin echo (PGSE) and three low-frequency oscillating gradient spin echo (OGSE) acquisitions. To validate our approach, hematoxylin and eosin staining and immunostaining of cell membranes, in concert with whole slide imaging, were used to visualize nuclei and cell boundaries, and hence, enabled accurate estimates of cell size and cellularity. Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes were obtained in vivo for three types of human colon cancers. The IMPULSED-derived apparent cellularities showed a stronger correlation (r = 0.81; P < 0.0001) with histology-derived cellularities than conventional ADCs (r = -0.69; P < 0.03). The IMPULSED approach samples a specific region of temporal diffusion spectra with enhanced sensitivity to length scales of 10-20 μm, and enables measurements of cell sizes and cellularities in solid tumors in vivo. Magn Reson Med 78:156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Modeling and simulating industrial land-use evolution in Shanghai, China

NASA Astrophysics Data System (ADS)

Qiu, Rongxu; Xu, Wei; Zhang, John; Staenz, Karl

2018-01-01

This study proposes a cellular automata-based Industrial and Residential Land Use Competition Model to simulate the dynamic spatial transformation of industrial land use in Shanghai, China. In the proposed model, land development activities in a city are delineated as competitions among different land-use types. The Hedonic Land Pricing Model is adopted to implement the competition framework. To improve simulation results, the Land Price Agglomeration Model was devised to simulate and adjust classic land price theory. A new evolutionary algorithm-based parameter estimation method was devised in place of traditional methods. Simulation results show that the proposed model closely resembles actual land transformation patterns and the model can not only simulate land development, but also redevelopment processes in metropolitan areas.

Two-dimensional finite element heat transfer model of softwood. Part III, Effect of moisture content on thermal conductivity

Treesearch

Hongmei Gu; John F. Hunt

2007-01-01

The anisotropy of wood creates a complex problem for solving heat and mass transfer problems that require analyses be based on fundamental material properties of the wood structure. Most heat transfer models for softwood use average thermal properties across either the radial or tangential direction and do not differentiate the effects of cellular alignment or...

Serum-free keloid fibroblast cell culture: an in vitro model for the study of aberrant wound healing.

PubMed

Koch, R J; Goode, R L; Simpson, G T

1997-04-01

The purpose of this study was to develop an in vitro serum-free keloid fibroblast model. Keloid formation remains a problem for every surgeon. Prior evaluations of fibroblast characteristics in vitro, especially those of growth factor measurement, have been confounded by the presence of serum-containing tissue culture media. The serum itself contains growth factors, yet has been a "necessary evil" to sustain cell growth. The design of this study is laboratory-based and uses keloid fibroblasts obtained from five patients undergoing facial (ear lobule) keloid removal in a university-affiliated clinic. Keloid fibroblasts were established in primary cell culture and then propagated in a serum-free environment. The main outcome measures included sustained keloid fibroblast growth and viability, which was comparable to serum-based models. The keloid fibroblast cell cultures exhibited logarithmic growth, sustained a high cellular viability, maintained a monolayer, and displayed contact inhibition. Demonstrating model consistency, there was no statistically significant difference between the mean cell counts of the five keloid fibroblast cell lines at each experimental time point. The in vitro growth of keloid fibroblasts in a serum-free model has not been done previous to this study. The results of this study indicate that the proliferative characteristics described are comparable to those of serum-based models. The described model will facilitate the evaluation of potential wound healing modulators, and cellular effects and collagen modifications of laser resurfacing techniques, and may serve as a harvest source for contaminant-free fibroblast autoimplants. Perhaps its greatest utility will be in the evaluation of endogenous and exogenous growth factors.

Selective visualization of fluorescent sterols in Caenorhabditis elegans by bleach-rate-based image segmentation.

PubMed

Wüstner, Daniel; Landt Larsen, Ane; Faergeman, Nils J; Brewer, Jonathan R; Sage, Daniel

2010-04-01

The nematode Caenorhabditis elegans is a genetically tractable model organism to investigate sterol transport. In vivo imaging of the fluorescent sterol, dehydroergosterol (DHE), is challenged by C. elegans' high autofluorescence in the same spectral region as emission of DHE. We present a method to detect DHE selectively, based on its rapid bleaching kinetics compared to cellular autofluorescence. Worms were repeatedly imaged on an ultraviolet-sensitive wide field (UV-WF) microscope, and bleaching kinetics of DHE were fitted on a pixel-basis to mathematical models describing the intensity decay. Bleach-rate constants were determined for DHE in vivo and confirmed in model membranes. Using this method, we could detect enrichment of DHE in specific tissues like the nerve ring, the spermateca and oocytes. We confirm these results in C. elegans gut-granule-loss (glo) mutants with reduced autofluorescence and compare our method with three-photon excitation microscopy of sterol in selected tissues. Bleach-rate-based UV-WF imaging is a useful tool for genetic screening experiments on sterol transport, as exemplified by RNA interference against the rme-2 gene coding for the yolk receptor and for worm homologues of Niemann-Pick C disease proteins. Our approach is generally useful for identifying fluorescent probes in the presence of high cellular autofluorescence.

Development of a pluripotent stem cell derived neuronal model to identify chemically induced pathway perturbations in relation to neurotoxicity: Effects of CREB pathway inhibition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pistollato, Francesca; Louisse, Jochem; Scelfo, Bibiana

2014-10-15

According to the advocated paradigm shift in toxicology, acquisition of knowledge on the mechanisms underlying the toxicity of chemicals, such as perturbations of biological pathways, is of primary interest. Pluripotent stem cells (PSCs), such as human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs), offer a unique opportunity to derive physiologically relevant human cell types to measure molecular and cellular effects of such pathway modulations. Here we compared the neuronal differentiation propensity of hESCs and hiPSCs with the aim to develop novel hiPSC-based tools for measuring pathway perturbation in relation to molecular and cellular effects in vitro.more » Among other fundamental pathways, also, the cAMP responsive element binding protein (CREB) pathway was activated in our neuronal models and gave us the opportunity to study time-dependent effects elicited by chemical perturbations of the CREB pathway in relation to cellular effects. We show that the inhibition of the CREB pathway, using 2-naphthol-AS-E-phosphate (KG-501), induced an inhibition of neurite outgrowth and synaptogenesis, as well as a decrease of MAP2{sup +} neuronal cells. These data indicate that a CREB pathway inhibition can be related to molecular and cellular effects that may be relevant for neurotoxicity testing, and, thus, qualify the use of our hiPSC-derived neuronal model for studying chemical-induced neurotoxicity resulting from pathway perturbations. - Highlights: • HESCs derived neuronal cells serve as benchmark for iPSC based neuronal toxicity test development. • Comparisons between hESCs and hiPSCs demonstrated variability of the epigenetic state • CREB pathway modulation have been explored in relation to the neurotoxicant exposure KG-501 • hiPSC might be promising tools to translate theoretical AoPs into toxicological in vitro tests.« less

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

D'Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

2013-01-01

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

NASA Astrophysics Data System (ADS)

Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

2015-11-01

The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Generation and precise control of dynamic biochemical gradients for cellular assays

NASA Astrophysics Data System (ADS)

Saka, Yasushi; MacPherson, Murray; Giuraniuc, Claudiu V.

2017-03-01

Spatial gradients of diffusible signalling molecules play crucial roles in controlling diverse cellular behaviour such as cell differentiation, tissue patterning and chemotaxis. In this paper, we report the design and testing of a microfluidic device for diffusion-based gradient generation for cellular assays. A unique channel design of the device eliminates cross-flow between the source and sink channels, thereby stabilizing gradients by passive diffusion. The platform also enables quick and flexible control of chemical concentration that makes highly dynamic gradients in diffusion chambers. A model with the first approximation of diffusion and surface adsorption of molecules recapitulates the experimentally observed gradients. Budding yeast cells cultured in a gradient of a chemical inducer expressed a reporter fluorescence protein in a concentration-dependent manner. This microfluidic platform serves as a versatile prototype applicable to a broad range of biomedical investigations.

Theory of Epithelial Cell Shape Transitions Induced by Mechanoactive Chemical Gradients.

PubMed

Dasbiswas, Kinjal; Hannezo, Edouard; Gov, Nir S

2018-02-27

Cell shape is determined by a balance of intrinsic properties of the cell as well as its mechanochemical environment. Inhomogeneous shape changes underlie many morphogenetic events and involve spatial gradients in active cellular forces induced by complex chemical signaling. Here, we introduce a mechanochemical model based on the notion that cell shape changes may be induced by external diffusible biomolecules that influence cellular contractility (or equivalently, adhesions) in a concentration-dependent manner-and whose spatial profile in turn is affected by cell shape. We map out theoretically the possible interplay between chemical concentration and cellular structure. Besides providing a direct route to spatial gradients in cell shape profiles in tissues, we show that the dependence on cell shape helps create robust mechanochemical gradients. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Molecular Signaling Network Motifs Provide a Mechanistic Basis for Cellular Threshold Responses

PubMed Central

Bhattacharya, Sudin; Conolly, Rory B.; Clewell, Harvey J.; Kaminski, Norbert E.; Andersen, Melvin E.

2014-01-01

Background: Increasingly, there is a move toward using in vitro toxicity testing to assess human health risk due to chemical exposure. As with in vivo toxicity testing, an important question for in vitro results is whether there are thresholds for adverse cellular responses. Empirical evaluations may show consistency with thresholds, but the main evidence has to come from mechanistic considerations. Objectives: Cellular response behaviors depend on the molecular pathway and circuitry in the cell and the manner in which chemicals perturb these circuits. Understanding circuit structures that are inherently capable of resisting small perturbations and producing threshold responses is an important step towards mechanistically interpreting in vitro testing data. Methods: Here we have examined dose–response characteristics for several biochemical network motifs. These network motifs are basic building blocks of molecular circuits underpinning a variety of cellular functions, including adaptation, homeostasis, proliferation, differentiation, and apoptosis. For each motif, we present biological examples and models to illustrate how thresholds arise from specific network structures. Discussion and Conclusion: Integral feedback, feedforward, and transcritical bifurcation motifs can generate thresholds. Other motifs (e.g., proportional feedback and ultrasensitivity)produce responses where the slope in the low-dose region is small and stays close to the baseline. Feedforward control may lead to nonmonotonic or hormetic responses. We conclude that network motifs provide a basis for understanding thresholds for cellular responses. Computational pathway modeling of these motifs and their combinations occurring in molecular signaling networks will be a key element in new risk assessment approaches based on in vitro cellular assays. Citation: Zhang Q, Bhattacharya S, Conolly RB, Clewell HJ III, Kaminski NE, Andersen ME. 2014. Molecular signaling network motifs provide a mechanistic basis for cellular threshold responses. Environ Health Perspect 122:1261–1270; http://dx.doi.org/10.1289/ehp.1408244 PMID:25117432

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

47 CFR 22.923 - Cellular system configuration.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 22.923 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.923 Cellular system configuration. Mobile stations communicate with and through base transmitters only. Base transmitters communicate with mobile stations...

Predicting cancer rates in astronauts from animal carcinogenesis studies and cellular markers

NASA Technical Reports Server (NTRS)

Williams, J. R.; Zhang, Y.; Zhou, H.; Osman, M.; Cha, D.; Kavet, R.; Cuccinotta, F.; Dicello, J. F.; Dillehay, L. E.

1999-01-01

The radiation space environment includes particles such as protons and multiple species of heavy ions, with much of the exposure to these radiations occurring at extremely low average dose-rates. Limitations in databases needed to predict cancer hazards in human beings from such radiations are significant and currently do not provide confidence that such predictions are acceptably precise or accurate. In this article, we outline the need for animal carcinogenesis data based on a more sophisticated understanding of the dose-response relationship for induction of cancer and correlative cellular endpoints by representative space radiations. We stress the need for a model that can interrelate human and animal carcinogenesis data with cellular mechanisms. Using a broad model for dose-response patterns which we term the "subalpha-alpha-omega (SAO) model", we explore examples in the literature for radiation-induced cancer and for radiation-induced cellular events to illustrate the need for data that define the dose-response patterns more precisely over specific dose ranges, with special attention to low dose, low dose-rate exposure. We present data for multiple endpoints in cells, which vary in their radiosensitivity, that also support the proposed model. We have measured induction of complex chromosome aberrations in multiple cell types by two space radiations, Fe-ions and protons, and compared these to photons delivered at high dose-rate or low dose-rate. Our data demonstrate that at least three factors modulate the relative efficacy of Fe-ions compared to photons: (i) intrinsic radiosensitivity of irradiated cells; (ii) dose-rate; and (iii) another unspecified effect perhaps related to reparability of DNA lesions. These factors can produce respectively up to at least 7-, 6- and 3-fold variability. These data demonstrate the need to understand better the role of intrinsic radiosensitivity and dose-rate effects in mammalian cell response to ionizing radiation. Such understanding is critical in extrapolating databases between cellular response, animal carcinogenesis and human carcinogenesis, and we suggest that the SAO model is a useful tool for such extrapolation.

Protein subcellular location pattern classification in cellular images using latent discriminative models.

PubMed

Li, Jieyue; Xiong, Liang; Schneider, Jeff; Murphy, Robert F

2012-06-15

Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization. http://murphylab.web.cmu.edu/software/.

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

PubMed Central

Sibole, Scott C.; Erdemir, Ahmet

2012-01-01

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems. PMID:22649535

A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

NASA Astrophysics Data System (ADS)

Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

2018-02-01

In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

Marine traffic model based on cellular automaton: Considering the change of the ship's velocity under the influence of the weather and sea

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-10-01

It was found that the ships' velocity change, which is impacted by the weather and sea, e.g., wind, sea wave, sea current, tide, etc., is significant and must be considered in the marine traffic model. Therefore, a new marine traffic model based on cellular automaton (CA) was proposed in this paper. The characteristics of the ship's velocity change are taken into account in the model. First, the acceleration of a ship was divided into two components: regular component and random component. Second, the mathematical functions and statistical distribution parameters of the two components were confirmed by spectral analysis, curve fitting and auto-correlation analysis methods. Third, by combining the two components, the acceleration was regenerated in the update rules for ships' movement. To test the performance of the model, the ship traffic flows in the Dover Strait, the Changshan Channel and the Qiongzhou Strait were studied and simulated. The results show that the characteristics of ships' velocities in the simulations are consistent with the measured data by Automatic Identification System (AIS). Although the characteristics of the traffic flow in different areas are different, the velocities of ships can be simulated correctly. It proves that the velocities of ships under the influence of weather and sea can be simulated successfully using the proposed model.

Synchrotron based infrared imaging and spectroscopy via focal plane array on live fibroblasts in D2O enriched medium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quaroni, Luca; Zlateva, Theodora; Sarafimov, Blagoj

2014-03-26

We tested the viability of using synchrotron based infrared imaging to study biochemical processes inside living cells. As a model system, we studied fibroblast cells exposed to a medium highly enriched with D2O. We could show that the experimental technique allows us to reproduce at the cellular level measurements that are normally performed on purified biological molecules. We can obtain information about lipid conformation and distribution, kinetics of hydrogen/deuterium exchange, and the formation of concentration gradients of H and O isotopes in water that are associated with cell metabolism. The implementation of the full field technique in a sequential imagingmore » format gives a description of cellular biochemistry and biophysics that contains both spatial and temporal information.« less

Radiation induced pulmonary fibrosis as a model of progressive fibrosis: Contributions of DNA damage, inflammatory response and cellular senescence genes.

PubMed

Beach, Tyler A; Johnston, Carl J; Groves, Angela M; Williams, Jacqueline P; Finkelstein, Jacob N

2017-04-01

Purpose/Aim of Study: Studies of pulmonary fibrosis (PF) have resulted in DNA damage, inflammatory response, and cellular senescence being widely hypothesized to play a role in the progression of the disease. Utilizing these aforementioned terms, genomics databases were interrogated along with the term, "pulmonary fibrosis," to identify genes common among all 4 search terms. Findings were compared to data derived from a model of radiation-induced progressive pulmonary fibrosis (RIPF) to verify that these genes are similarly expressed, supporting the use of radiation as a model for diseases involving PF, such as human idiopathic pulmonary fibrosis (IPF). In an established model of RIPF, C57BL/6J mice were exposed to 12.5 Gy thorax irradiation and sacrificed at 24 hours, 1, 4, 12, and 32 weeks following exposure, and lung tissue was compared to age-matched controls by RNA sequencing. Of 176 PF associated gene transcripts identified by database interrogation, 146 (>82%) were present in our experimental model, throughout the progression of RIPF. Analysis revealed that nearly 85% of PF gene transcripts were associated with at least 1 other search term. Furthermore, of 22 genes common to all four terms, 16 were present experimentally in RIPF. This illustrates the validity of RIPF as a model of progressive PF/IPF based on the numbers of transcripts reported in both literature and observed experimentally. Well characterized genes and proteins are implicated in this model, supporting the hypotheses that DNA damage, inflammatory response and cellular senescence are associated with the pathogenesis of PF.

A structured approach to the study of metabolic control principles in intact and impaired mitochondria.

PubMed

Huber, Heinrich J; Connolly, Niamh M C; Dussmann, Heiko; Prehn, Jochen H M

2012-03-01

We devised an approach to extract control principles of cellular bioenergetics for intact and impaired mitochondria from ODE-based models and applied it to a recently established bioenergetic model of cancer cells. The approach used two methods for varying ODE model parameters to determine those model components that, either alone or in combination with other components, most decisively regulated bioenergetic state variables. We found that, while polarisation of the mitochondrial membrane potential (ΔΨ(m)) and, therefore, the protomotive force were critically determined by respiratory complex I activity in healthy mitochondria, complex III activity was dominant for ΔΨ(m) during conditions of cytochrome-c deficiency. As a further important result, cellular bioenergetics in healthy, ATP-producing mitochondria was regulated by three parameter clusters that describe (1) mitochondrial respiration, (2) ATP production and consumption and (3) coupling of ATP-production and respiration. These parameter clusters resembled metabolic blocks and their intermediaries from top-down control analyses. However, parameter clusters changed significantly when cells changed from low to high ATP levels or when mitochondria were considered to be impaired by loss of cytochrome-c. This change suggests that the assumption of static metabolic blocks by conventional top-down control analyses is not valid under these conditions. Our approach is complementary to both ODE and top-down control analysis approaches and allows a better insight into cellular bioenergetics and its pathological alterations.

Simulation of land use change in the three gorges reservoir area based on CART-CA

NASA Astrophysics Data System (ADS)

Yuan, Min

2018-05-01

This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

The 3-dimensional cellular automata for HIV infection

NASA Astrophysics Data System (ADS)

Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei

2014-04-01

The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.

Immortalized pathological human myoblasts: towards a universal tool for the study of neuromuscular disorders

PubMed Central

2011-01-01

Background Investigations into both the pathophysiology and therapeutic targets in muscle dystrophies have been hampered by the limited proliferative capacity of human myoblasts. Isolation of reliable and stable immortalized cell lines from patient biopsies is a powerful tool for investigating pathological mechanisms, including those associated with muscle aging, and for developing innovative gene-based, cell-based or pharmacological biotherapies. Methods Using transduction with both telomerase-expressing and cyclin-dependent kinase 4-expressing vectors, we were able to generate a battery of immortalized human muscle stem-cell lines from patients with various neuromuscular disorders. Results The immortalized human cell lines from patients with Duchenne muscular dystrophy, facioscapulohumeral muscular dystrophy, oculopharyngeal muscular dystrophy, congenital muscular dystrophy, and limb-girdle muscular dystrophy type 2B had greatly increased proliferative capacity, and maintained their potential to differentiate both in vitro and in vivo after transplantation into regenerating muscle of immunodeficient mice. Conclusions Dystrophic cellular models are required as a supplement to animal models to assess cellular mechanisms, such as signaling defects, or to perform high-throughput screening for therapeutic molecules. These investigations have been conducted for many years on cells derived from animals, and would greatly benefit from having human cell models with prolonged proliferative capacity. Furthermore, the possibility to assess in vivo the regenerative capacity of these cells extends their potential use. The innovative cellular tools derived from several different neuromuscular diseases as described in this report will allow investigation of the pathophysiology of these disorders and assessment of new therapeutic strategies. PMID:22040608

In silico modeling for tumor growth visualization.

PubMed

Jeanquartier, Fleur; Jean-Quartier, Claire; Cemernek, David; Holzinger, Andreas

2016-08-08

Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ . In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.

LAND USE CHANGE DUE TO URBANIZATION FOR THE NEUSE RIVER BASIN

EPA Science Inventory

The Urban Growth Model (UGM) was applied to analysis of land use change in the Neuse River Basin as part of a larger project for estimating the regional and broader impact of urbanization. UGM is based on cellular automation (CA) simulation techniques developed at the University...

Computational Systems Biology and Dose Response Modeling Workshop, September 22-26, 2008

EPA Science Inventory

The recently published National Academy of Sciences (NAS) report “Toxicity Testing in the 21st Century” recommends a new approach to toxicity testing, based on evaluating cellular responses in a suite of toxicity pathway assays in human cells or cells lines in vitro. Such a parad...

The New Curricula: How Media Literacy Education Transforms Teaching and Learning

ERIC Educational Resources Information Center

Jolls, Tessa

2015-01-01

As new online and cellular technologies advance, the implications for the traditional textbook model of curricular instruction are profound. The ability to construct, share, collaborate on and publish new instructional materials marks the beginning of a global revolution in curricula development. Research-based media literacy frameworks can be…

21 CFR 830.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... identification and data capture (AIDC) means any technology that conveys the unique device identifier or the... use. Human cell, tissue, or cellular or tissue-based product (HCT/P) regulated as a device means an... device or more that consist of a single type, model, class, size, composition, or software version that...

The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

NASA Astrophysics Data System (ADS)

Guan, Yujuan; Zhang, Liquan

2006-10-01

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

The mechanics of cellular compartmentalization as a model for tumor spreading

NASA Astrophysics Data System (ADS)

Fritsch, Anatol; Pawlizak, Steve; Zink, Mareike; Kaes, Josef A.

2012-02-01

Based on a recently developed surgical method of Michael H"ockel, which makes use of cellular confinement to compartments in the human body, we study the mechanics of the process of cell segregation. Compartmentalization is a fundamental process of cellular organization and occurs during embryonic development. A simple model system can demonstrate the process of compartmentalization: When two populations of suspended cells are mixed, this mixture will eventually segregate into two phases, whereas mixtures of the same cell type will not. In the 1960s, Malcolm S. Steinberg formulated the so-called differential adhesion hypothesis which explains the segregation in the model system and the process of compartmentalization by differences in surface tension and adhesiveness of the interacting cells. We are interested in to which extend the same physical principles affect tumor growth and spreading between compartments. For our studies, we use healthy and cancerous breast cell lines of different malignancy as well as primary cells from human cervix carcinoma. We apply a set of techniques to study their mechanical properties and interactions. The Optical Stretcher is used for whole cell rheology, while Cell-cell-adhesion forces are directly measured with a modified AFM. In combination with 3D segregation experiments in droplet cultures we try to clarify the role of surface tension in tumor spreading.

Progesterone-induced Neuroprotection: Factors that may predict therapeutic efficacy

PubMed Central

Singh, Meharvan; Su, Chang

2013-01-01

Both progesterone and estradiol have well-described neuroprotective effects against numerous insults in a variety of cell culture models, animal models and in humans. However, the efficacy of these hormones may depend on a variety of factors, including the type of hormone used (ex. progesterone versus medroxyprogesterone acetate), the duration of the postmenopausal period prior to initiating the hormone intervention, and potentially, the age of the subject. The latter two factors relate to the proposed existence of a “window of therapeutic opportunity” for steroid hormones in the brain. While such a window of opportunity has been described for estrogen, there is a paucity of information to address whether such a window of opportunity exists for progesterone and its related progestins. Here, we review known cellular mechanisms likely to underlie the protective effects of progesterone and furthermore, describe key differences in the neurobiology of progesterone and the synthetic progestin, medroxyprogesterone acetate (MPA). Based on the latter, we offer a model that defines some of the key cellular and molecular players that predict the neuroprotective efficacy of progesterone. Accordingly, we suggest how changes in the expression or function of these cellular and molecular targets of progesterone with age or prolonged duration of hormone withdrawal (such as following surgical or natural menopause) may impact the efficacy of progesterone. PMID:23340161

Predicting multicellular function through multi-layer tissue networks

PubMed Central

Zitnik, Marinka; Leskovec, Jure

2017-01-01

Abstract Motivation: Understanding functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Results: Here, we present OhmNet, a hierarchy-aware unsupervised node feature learning approach for multi-layer networks. We build a multi-layer network, where each layer represents molecular interactions in a different human tissue. OhmNet then automatically learns a mapping of proteins, represented as nodes, to a neural embedding-based low-dimensional space of features. OhmNet encourages sharing of similar features among proteins with similar network neighborhoods and among proteins activated in similar tissues. The algorithm generalizes prior work, which generally ignores relationships between tissues, by modeling tissue organization with a rich multiscale tissue hierarchy. We use OhmNet to study multicellular function in a multi-layer protein interaction network of 107 human tissues. In 48 tissues with known tissue-specific cellular functions, OhmNet provides more accurate predictions of cellular function than alternative approaches, and also generates more accurate hypotheses about tissue-specific protein actions. We show that taking into account the tissue hierarchy leads to improved predictive power. Remarkably, we also demonstrate that it is possible to leverage the tissue hierarchy in order to effectively transfer cellular functions to a functionally uncharacterized tissue. Overall, OhmNet moves from flat networks to multiscale models able to predict a range of phenotypes spanning cellular subsystems. Availability and implementation: Source code and datasets are available at http://snap.stanford.edu/ohmnet. Contact: jure@cs.stanford.edu PMID:28881986

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Multiscale Modeling of Virus Entry via Receptor-Mediated Endocytosis

NASA Astrophysics Data System (ADS)

Liu, Jin

2012-11-01

Virus infections are ubiquitous and remain major threats to human health worldwide. Viruses are intracellular parasites and must enter host cells to initiate infection. Receptor-mediated endocytosis is the most common entry pathway taken by viruses, the whole process is highly complex and dictated by various events, such as virus motions, membrane deformations, receptor diffusion and ligand-receptor reactions, occurring at multiple length and time scales. We develop a multiscale model for virus entry through receptor-mediated endocytosis. The binding of virus to cell surface is based on a mesoscale three dimensional stochastic adhesion model, the internalization (endocytosis) of virus and cellular membrane deformation is based on the discretization of Helfrich Hamiltonian in a curvilinear space using Monte Carlo method. The multiscale model is based on the combination of these two models. We will implement this model to study the herpes simplex virus entry into B78 cells and compare the model predictions with experimental measurements.

In Vitro Modeling of Repetitive Motion Injury and Myofascial Release

PubMed Central

Meltzer, Kate R.; Cao, Thanh V.; Schad, Joseph F.; King, Hollis; Stoll, Scott T.; Standley, Paul R.

2010-01-01

Objective In this study we modeled repetitive motion strain (RMS) and myofascial release (MFR) in vitro to investigate possible cellular and molecular mechanisms to potentially explain the immediate clinical outcomes associated with RMS and MFR. Method Cultured human fibroblasts were strained with 8 hours RMS, 60 seconds MFR and combined treatment; RMS+MFR. Fibroblasts were immediately sampled upon cessation of strain and evaluated for cell morphology, cytokine secretions, proliferation, apoptosis, and potential changes to intracellular signaling molecules. Results RMS induced fibroblast elongation of lameopodia, cellular decentralization, reduction of cell to cell contact and significant decreases in cell area to perimeter ratios compared to all other experimental groups (p<0.0001). Cellular proliferation indicated no change among any treatment group; however RMS resulted in a significant increase in apoptosis rate (p<0.05) along with increases in death-associated protein kinase (DAPK) and focal adhesion kinase (FAK) phosphorylation by 74% and 58% respectively, when compared to control. These responses were not observed in the MFR and RMS+MFR group. Of the twenty cytokines measured there was a significant increase in GRO secretion in the RMS+MFR group when compared to control and MFR alone. Conclusion Our modeled injury (RMS) appropriately displayed enhanced apoptosis activity and loss of intercellular integrity that is consistent with pro-apoptotic DAPK2 and FAK signaling. Treatment with MFR following RMS resulted in normalization in apoptotic rate and cell morphology both consistent with changes observed in DAPK2. These in vitro studies build upon the cellular evidence base needed to fully explain clinical efficacy of manual manipulative therapies. PMID:20226363

Biology Based Lung Cancer Model for Chronic Low Radon Exposures

NASA Astrophysics Data System (ADS)

TruÅ£ǎ-Popa, Lucia-Adina; Hofmann, Werner; Fakir, Hatim; Cosma, Constantin

2008-08-01

Low dose effects of alpha particles at the tissue level are characterized by the interaction of single alpha particles, affecting only a small fraction of the cells within that tissue. Alpha particle intersections of bronchial target cells during a given exposure period were simulated by an initiation-promotion model, formulated in terms of cellular hits within the cycle time of the cell (dose-rate) and then integrated over the whole exposure period (dose). For a given average number of cellular hits during the lifetime of bronchial cells, the actual number of single and multiple hits was selected from a Poisson distribution. While oncogenic transformation is interpreted as the primary initiation step, stimulated mitosis by killing adjacent cells is assumed to be the primary radiological promotion event. Analytical initiation and promotion functions were derived from experimental in vitro data on oncogenic transformation and cellular survival. To investigate the shape of the lung cancer risk function at chronic, low level exposures in more detail, additional biological factors describing the tissue response and operating specifically at low doses were incorporated into the initiation-promotion model. These mechanisms modifying the initial response at the cellular level were: adaptive response, genomic instability, induction of apoptosis by surrounding cells, and detrimental as well as protective bystander mechanisms. To quantify the effects of these mechanisms as functions of dose, analytical functions were derived from the experimental evidence presently available. Predictions of lung cancer risk, including these mechanisms, exhibit a distinct sublinear dose-response relationship at low exposures, particularly for very low exposure rates.

Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience.

PubMed

Hall, Catherine N; Howarth, Clare; Kurth-Nelson, Zebulun; Mishra, Anusha

2016-10-05

Cognitive neuroscience depends on the use of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to probe brain function. Although commonly used as a surrogate measure of neuronal activity, BOLD signals actually reflect changes in brain blood oxygenation. Understanding the mechanisms linking neuronal activity to vascular perfusion is, therefore, critical in interpreting BOLD. Advances in cellular neuroscience demonstrating differences in this neurovascular relationship in different brain regions, conditions or pathologies are often not accounted for when interpreting BOLD. Meanwhile, within cognitive neuroscience, the increasing use of high magnetic field strengths and the development of model-based tasks and analyses have broadened the capability of BOLD signals to inform us about the underlying neuronal activity, but these methods are less well understood by cellular neuroscientists. In 2016, a Royal Society Theo Murphy Meeting brought scientists from the two communities together to discuss these issues. Here, we consolidate the main conclusions arising from that meeting. We discuss areas of consensus about what BOLD fMRI can tell us about underlying neuronal activity, and how advanced modelling techniques have improved our ability to use and interpret BOLD. We also highlight areas of controversy in understanding BOLD and suggest research directions required to resolve these issues.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).

Predictive model to describe water migration in cellular solid foods during storage.

PubMed

Voogt, Juliën A; Hirte, Anita; Meinders, Marcel B J

2011-11-01

Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Water migration in cellular solid foods involves migration through both the air cells and the solid matrix. For systems in which the water migration distance is large compared with the cell wall thickness of the solid matrix, the overall water flux through the system is dominated by the flux through the air. For these systems, water migration can be approximated well by a Fickian diffusion model. The effective diffusion coefficient can be expressed in terms of the material properties of the solid matrix (i.e. the density, sorption isotherm and diffusion coefficient of water in the solid matrix) and the morphological properties of the cellular structure (i.e. water vapour permeability and volume fraction of the solid matrix). The water vapour permeability is estimated from finite element method modelling using a simplified model for the cellular structure. It is shown that experimentally observed dynamical water profiles of bread rolls that differ in crust permeability are predicted well by the Fickian diffusion model. Copyright © 2011 Society of Chemical Industry.

A bounding-based solution approach for the continuous arc covering problem

NASA Astrophysics Data System (ADS)

Wei, Ran; Murray, Alan T.; Batta, Rajan

2014-04-01

Road segments, telecommunication wiring, water and sewer pipelines, canals and the like are important features of the urban environment. They are often conceived of and represented as network-based arcs. As a result of the usefulness and significance of arc-based features, there is a need to site facilities along arcs to serve demand. Examples of such facilities include surveillance equipment, cellular towers, refueling centers and emergency response stations, with the intent of being economically efficient as well as providing good service along the arcs. While this amounts to a continuous location problem by nature, various discretizations are generally relied upon to solve such problems. The result is potential for representation errors that negatively impact analysis and decision making. This paper develops a solution approach for the continuous arc covering problem that theoretically eliminates representation errors. The developed approach is applied to optimally place acoustic sensors and cellular base stations along a road network. The results demonstrate the effectiveness of this approach for ameliorating any error and uncertainty in the modeling process.

Intracellular probes for imaging oxygen concentration: how good are they?

NASA Astrophysics Data System (ADS)

Dmitriev, Ruslan I.; Papkovsky, Dmitri B.

2015-09-01

In the last decade a number of cell-permeable phosphorescence based probes for imaging of (intra)cellular oxygen (icO2) have been described. These small molecule, supramolecular and nanoparticle structures, although allowing analysis of hypoxia, local gradients and fluctuations in O2, responses to stimulation and drug treatment at sub-cellular level with high spatial and temporal resolution, differ significantly in their operational performance and applicability to different cell and tissue models. Here we discuss and compare these probes with respect to their staining efficiency, brightness, photostability, toxicity, cell specificity, compatibility with different cell and tissue models, and analytical performance. Merits and limitations of particular probes are highlighted and strategies for development of new high-performance O2 imaging probes defined. Key application areas in hypoxia research, stem cells, cancer biology and tissue physiology are also discussed.

Recent Advances in Particulate Matter and Nanoparticle Toxicology: A Review of the In Vivo and In Vitro Studies

PubMed Central

Nemmar, Abderrahim; Holme, Jørn A.; Rosas, Irma; Schwarze, Per E.

2013-01-01

Epidemiological and clinical studies have linked exposure to particulate matter (PM) to adverse health effects, which may be registered as increased mortality and morbidity from various cardiopulmonary diseases. Despite the evidence relating PM to health effects, the physiological, cellular, and molecular mechanisms causing such effects are still not fully characterized. Two main approaches are used to elucidate the mechanisms of toxicity. One is the use of in vivo experimental models, where various effects of PM on respiratory, cardiovascular, and nervous systems can be evaluated. To more closely examine the molecular and cellular mechanisms behind the different physiological effects, the use of various in vitro models has proven to be valuable. In the present review, we discuss the current advances on the toxicology of particulate matter and nanoparticles based on these techniques. PMID:23865044

An Asynchronous Cellular Automata-Based Adaptive Illumination Facility

NASA Astrophysics Data System (ADS)

Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito

The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Traffic dynamics of an on-ramp system with a cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xin-Gang; Gao, Zi-You; Jia, Bin; Jiang, Rui

2010-06-01

This paper uses the cellular automaton model to study the dynamics of traffic flow around an on-ramp with an acceleration lane. It adopts a parameter, which can reflect different lane-changing behaviour, to represent the diversity of driving behaviour. The refined cellular automaton model is used to describe the lower acceleration rate of a vehicle. The phase diagram and the capacity of the on-ramp system are investigated. The simulation results show that in the single cell model, the capacity of the on-ramp system will stay at the highest flow of a one lane system when the driver is moderate and careful; it will be reduced when the driver is aggressive. In the refined cellular automaton model, the capacity is always reduced even when the driver is careful. It proposes that the capacity drop of the on-ramp system is caused by aggressive lane-changing behaviour and lower acceleration rate.

Identifying Flow Networks in a Karstified Aquifer by Application of the Cellular Automata-Based Deterministic Inversion Method (Lez Aquifer, France)

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Wang, X.; Jourde, H.; Lecoq, N.

2017-12-01

The distributed modeling of flow paths within karstic and fractured fields remains a complex task because of the high dependence of the hydraulic responses to the relative locations between observational boreholes and interconnected fractures and karstic conduits that control the main flow of the hydrosystem. The inverse problem in a distributed model is one alternative approach to interpret the hydraulic test data by mapping the karstic networks and fractured areas. In this work, we developed a Bayesian inversion approach, the Cellular Automata-based Deterministic Inversion (CADI) algorithm to infer the spatial distribution of hydraulic properties in a structurally constrained model. This method distributes hydraulic properties along linear structures (i.e., flow conduits) and iteratively modifies the structural geometry of this conduit network to progressively match the observed hydraulic data to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. The method is applied to invert a set of multiborehole hydraulic tests collected from a hydraulic tomography experiment conducted at the Terrieu field site in the Lez aquifer, Southern France. The emergent model shows a high consistency to field observation of hydraulic connections between boreholes. Furthermore, it provides a geologically realistic pattern of flow conduits. This method is therefore of considerable value toward an enhanced distributed modeling of the fractured and karstified aquifers.

Animal models to study microRNA function

PubMed Central

Pal, Arpita S.; Kasinski, Andrea L.

2018-01-01

The discovery of the microRNAs, lin-4 and let-7 as critical mediators of normal development in Caenorhabditis elegans and their conservation throughout evolution has spearheaded research towards identifying novel roles of microRNAs in other cellular processes. To accurately elucidate these fundamental functions, especially in the context of an intact organism various microRNA transgenic models have been generated and evaluated. Transgenic C. elegans (worms), Drosophila melanogaster (flies), Danio rerio (zebrafish), and Mus musculus (mouse) have contributed immensely towards uncovering the roles of multiple microRNAs in cellular processes such as proliferation, differentiation, and apoptosis, pathways that are severely altered in human diseases such as cancer. The simple model organisms, C. elegans, D. melanogaster and D. rerio do not develop cancers, but have proved to be convenient systesm in microRNA research, especially in characterizing the microRNA biogenesis machinery which is often dysregulated during human tumorigenesis. The microRNA-dependent events delineated via these simple in vivo systems have been further verified in vitro, and in more complex models of cancers, such as M. musculus. The focus of this review is to provide an overview of the important contributions made in the microRNA field using model organisms. The simple model systems provided the basis for the importance of microRNAs in normal cellular physiology, while the more complex animal systems provided evidence for the role of microRNAs dysregulation in cancers. Highlights include an overview of the various strategies used to generate transgenic organisms and a review of the use of transgenic mice for evaluating pre-clinical efficacy of microRNA-based cancer therapeutics. PMID:28882225

Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

NASA Astrophysics Data System (ADS)

Ellis, Michael; Dobrovolny, Hana

2014-03-01

One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

2013-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

1980-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Cellular and Molecular Mechanisms of Sexual Differentiation in the Mammalian Nervous System

PubMed Central

Forger, Nancy G.; Strahan, J. Alex; Castillo-Ruiz, Alexandra

2016-01-01

Neuroscientists are likely to discover new sex differences in the coming years, spurred by the National Institutes of Health initiative to include both sexes in preclinical studies. This review summarizes the current state of knowledge of the cellular and molecular mechanisms underlying sex differences in the mammalian nervous system, based primarily on work in rodents. Cellular mechanisms examined include neurogenesis, migration, the differentiation of neurochemical and morphological cell phenotype, and cell death. At the molecular level we discuss evolving roles for epigenetics, sex chromosome complement, the immune system, and newly identified cell signaling pathways. We review recent findings on the role of the environment, as well as genome-wide studies with some surprising results, causing us to rethink often-used models of sexual differentiation. We end by pointing to future directions, including an increased awareness of the important contributions of tissues outside of the nervous system to sexual differentiation of the brain. PMID:26790970

Three-dimensional microstructure simulation of Ni-based superalloy investment castings

NASA Astrophysics Data System (ADS)

Pan, Dong; Xu, Qingyan; Liu, Baicheng

2011-05-01

An integrated macro and micro multi-scale model for the three-dimensional microstructure simulation of Ni-based superalloy investment castings was developed, and applied to industrial castings to investigate grain evolution during solidification. A ray tracing method was used to deal with the complex heat radiation transfer. The microstructure evolution was simulated based on the Modified Cellular Automaton method, which was coupled with three-dimensional nested macro and micro grids. Experiments for Ni-based superalloy turbine wheel investment casting were carried out, which showed a good correspondence with the simulated results. It is indicated that the proposed model is able to predict the microstructure of the casting precisely, which provides a tool for the optimizing process.

Important cellular targets for antimicrobial photodynamic therapy.

PubMed

Awad, Mariam M; Tovmasyan, Artak; Craik, James D; Batinic-Haberle, Ines; Benov, Ludmil T

2016-09-01

The persistent problem of antibiotic resistance has created a strong demand for new methods for therapy and disinfection. Photodynamic inactivation (PDI) of microbes has demonstrated promising results for eradication of antibiotic-resistant strains. PDI is based on the use of a photosensitive compound (photosensitizer, PS), which upon illumination with visible light generates reactive species capable of damaging and killing microorganisms. Since photogenerated reactive species are short lived, damage is limited to close proximity of the PS. It is reasonable to expect that the larger the number of damaged targets is and the greater their variety is, the higher the efficiency of PDI is and the lower the chances for development of resistance are. Exact molecular mechanisms and specific targets whose damage is essential for microbial inactivation have not been unequivocally established. Two main cellular components, DNA and plasma membrane, are regarded as the most important PDI targets. Using Zn porphyrin-based PSs and Escherichia coli as a model Gram-negative microorganism, we demonstrate that efficient photoinactivation of bacteria can be achieved without detectable DNA modification. Among the cellular components which are modified early during illumination and constitute key PDI targets are cytosolic enzymes, membrane-bound protein complexes, and the plasma membrane. As a result, membrane barrier function is lost, and energy and reducing equivalent production is disrupted, which in turn compromises cell defense mechanisms, thus augmenting the photoinduced oxidative injury. In conclusion, high PDI antimicrobial effectiveness does not necessarily require impairment of a specific critical cellular component and can be achieved by inducing damage to multiple cellular targets.

Novel Texture-based Visualization Methods for High-dimensional Multi-field Data Sets

DTIC Science & Technology

2013-07-06

project: In standard format showing authors, title, journal, issue, pages, and date, for each category list the following: b) papers published...visual- isation [18]. Novel image acquisition and simulation tech- niques have made is possible to record a large number of co-located data fields...function, structure, anatomical changes, metabolic activity, blood perfusion, and cellular re- modelling. In this paper we investigate texture-based

Derivation of large-scale cellular regulatory networks from biological time series data.

PubMed

de Bivort, Benjamin L

2010-01-01

Pharmacological agents and other perturbants of cellular homeostasis appear to nearly universally affect the activity of many genes, proteins, and signaling pathways. While this is due in part to nonspecificity of action of the drug or cellular stress, the large-scale self-regulatory behavior of the cell may also be responsible, as this typically means that when a cell switches states, dozens or hundreds of genes will respond in concert. If many genes act collectively in the cell during state transitions, rather than every gene acting independently, models of the cell can be created that are comprehensive of the action of all genes, using existing data, provided that the functional units in the model are collections of genes. Techniques to develop these large-scale cellular-level models are provided in detail, along with methods of analyzing them, and a brief summary of major conclusions about large-scale cellular networks to date.

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

In vivo cell biology in zebrafish - providing insights into vertebrate development and disease.

PubMed

Vacaru, Ana M; Unlu, Gokhan; Spitzner, Marie; Mione, Marina; Knapik, Ela W; Sadler, Kirsten C

2014-02-01

Over the past decades, studies using zebrafish have significantly advanced our understanding of the cellular basis for development and human diseases. Zebrafish have rapidly developing transparent embryos that allow comprehensive imaging of embryogenesis combined with powerful genetic approaches. However, forward genetic screens in zebrafish have generated unanticipated findings that are mirrored by human genetic studies: disruption of genes implicated in basic cellular processes, such as protein secretion or cytoskeletal dynamics, causes discrete developmental or disease phenotypes. This is surprising because many processes that were assumed to be fundamental to the function and survival of all cell types appear instead to be regulated by cell-specific mechanisms. Such discoveries are facilitated by experiments in whole animals, where zebrafish provides an ideal model for visualization and manipulation of organelles and cellular processes in a live vertebrate. Here, we review well-characterized mutants and newly developed tools that underscore this notion. We focus on the secretory pathway and microtubule-based trafficking as illustrative examples of how studying cell biology in vivo using zebrafish has broadened our understanding of the role fundamental cellular processes play in embryogenesis and disease.

Configurable Cellular Automata for Pseudorandom Number Generation

NASA Astrophysics Data System (ADS)

Quieta, Marie Therese; Guan, Sheng-Uei

This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.

Simulation tools for particle-based reaction-diffusion dynamics in continuous space

PubMed Central

2014-01-01

Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics. PMID:25737778

A Monte Carlo study of macroscopic and microscopic dose descriptors for kilovoltage cellular dosimetry

NASA Astrophysics Data System (ADS)

Oliver, P. A. K.; Thomson, Rowan M.

2017-02-01

This work investigates how doses to cellular targets depend on cell morphology, as well as relations between cellular doses and doses to bulk tissues and water. Multicellular models of five healthy and cancerous soft tissues are developed based on typical values of cell compartment sizes, elemental compositions and number densities found in the literature. Cells are modelled as two concentric spheres with nucleus and cytoplasm compartments. Monte Carlo simulations are used to calculate the absorbed dose to the nucleus and cytoplasm for incident photon energies of 20-370 keV, relevant for brachytherapy, diagnostic radiology, and out-of-field radiation in higher-energy external beam radiotherapy. Simulations involving cell clusters, single cells and single nuclear cavities are carried out for cell radii between 5 and 10~μ m, and nuclear radii between 2 and 9~μ m. Seven nucleus and cytoplasm elemental compositions representative of animal cells are considered. The presence of a cytoplasm, extracellular matrix and surrounding cells can affect the nuclear dose by up to 13 % . Differences in cell and nucleus size can affect dose to the nucleus (cytoplasm) of the central cell in a cluster of 13 cells by up to 13 % (8 % ). Furthermore, the results of this study demonstrate that neither water nor bulk tissue are reliable substitutes for subcellular targets for incident photon energies  <50 keV: nuclear (cytoplasm) doses differ from dose-to-medium by up to 32 % (18 % ), and from dose-to-water by up to 21 % (8 % ). The largest differences between dose descriptors are seen for the lowest incident photon energies; differences are less than 3 % for energies ≥slant 90 keV. The sensitivity of results with regard to the parameters of the microscopic tissue structure model and cell model geometry, and the importance of the nucleus and cytoplasm as targets for radiation-induced cell death emphasize the importance of accurate models for cellular dosimetry studies.

State of the field: An informatics-based systematic review of the SOD1-G93A amyotrophic lateral sclerosis transgenic mouse model

PubMed Central

Kim, Renaid B.; Irvin, Cameron W.; Tilva, Keval R.; Mitchell, Cassie S.

2016-01-01

Numerous sub-cellular through system-level disturbances have been identified in over 1300 articles examining the superoxide dismutase-1 guanine 93 to alanine (SOD1-G93A) transgenic mouse amyotrophic lateral sclerosis (ALS) pathophysiology. Manual assessment of such a broad literature base is daunting. We performed a comprehensive informatics-based systematic review or ‘field analysis’ to agnostically compute and map the current state of the field. Text mining of recaptured articles was used to quantify published data topic breadth and frequency. We constructed a nine-category pathophysiological function-based ontology to systematically organize and quantify the field's primary data. Results demonstrated that the distribution of primary research belonging to each category is: systemic measures an motor function, 59%; inflammation, 46%; cellular energetics, 37%; proteomics, 31%; neural excitability, 22%; apoptosis, 20%; oxidative stress, 18%; aberrant cellular chemistry, 14%; axonal transport, 10%. We constructed a SOD1-G93A field map that visually illustrates and categorizes the 85% most frequently assessed sub-topics. Finally, we present the literature-cited significance of frequently published terms and uncover thinly investigated areas. In conclusion, most articles individually examine at least two categories, which is indicative of the numerous underlying pathophysiological interrelationships. An essential future path is examination of cross-category pathophysiological interrelationships and their co-correspondence to homeostatic regulation and disease progression. PMID:25998063

The proteasome of the differently-diverged eukaryote Giardia lamblia and its role in remodeling of the microtubule-based cytoskeleton.

PubMed

Ray, Atrayee; Sarkar, Srimonti

2017-08-01

Giardia lamblia is the causative agent of the diarrheal disease giardiasis, against which only a limited number of drugs are currently available. Increasing reports of resistance to these drugs makes it necessary to identify new cellular targets for designing the next generation of anti-giardial drugs. Towards this goal, therapeutic agents that target the parasitic cellular machinery involved in the functioning of the unique microtubule-based cytoskeleton of the Giardia trophozoites are likely to be effective as microtubule function is not only important for the survival of trophozoites within the host, but also their extensive remodeling is necessary during the transition from trophozoites to cysts. Thus, drugs that affect microtubule remodeling have the potential to not only kill the disease-causing trophozoites, but also inhibit transmission of cysts in the community. Recent studies in other model organisms have indicated that the proteasome plays an integral role in the formation and remodeling of the microtubule-based cytoskeleton. This review draws attention to the various processes by which the giardial proteasome may impact the functioning of its microtubule cytoskeleton and highlights the possible differences of the parasitic proteasome and some of other cellular machinery involved in microtubule remodeling, compared to that of the higher eukaryotic host.

Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening.

PubMed

O'Duibhir, Eoghan; Carragher, Neil O; Pollard, Steven M

2017-04-01

Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Amyotrophic lateral sclerosis: cell vulnerability or system vulnerability?

PubMed

Talbot, Kevin

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease with clinical, pathological and genetic overlap with frontotemporal dementia (FTD). No longer viewed as one disease with a single unified cause, ALS is now considered to be a clinicopathological syndrome resulting from a complex convergence of genetic susceptibility, age-related loss of cellular homeostasis, and possible environmental influences. The rapid increase in recent years of the number of genes in which mutations have been associated with ALS has led to in vitro and in vivo models that have generated a wealth of data indicating disruption of specific biochemical pathways and sub-cellular compartments. Data implicating pathways including protein misfolding, mRNA splicing, oxidative stress, proteosome and mitochondrial dysfunction in the pathogenesis of ALS reinforce a disease model based on selective age-dependent vulnerability of a specific population of cells. To the clinical neurologist, however, ALS presents as a disease of focal onset and contiguous spread. Characteristic regional patterns of involvement and progression suggest that the disease does not proceed randomly but via a restricted number of anatomical pathways. These clinical observations combined with electrophysiological and brain-imaging studies underpin the concept of ALS at the macroscopic level as a 'system degeneration'. This dichotomy between cellular and systems neurobiology raises the fundamental questions of what initiates the disease process in a specific anatomical site and how the disease is propagated. Is the essence of ALS a cell-to-cell transmission of pathology with, for example, a 'prion-like' mechanism, or does the cellular pathology follow degeneration of specific synaptic networks? Elucidating the interaction between cellular degeneration and system level degeneration will aid modeling of the disease in the earliest phases, improve the development of sensitive markers of disease progression and response to therapy, and expand our understanding of the biological basis of clinical and pathological heterogeneity. © 2013 Anatomical Society.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

PubMed

Brocklehurst, Paul; Ni, Haibo; Zhang, Henggui; Ye, Jianqiao

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue

PubMed Central

Zhang, Henggui

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation. PMID:28510575

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

Dissecting a new connection between cytokinin and jasmonic acid in control of leaf growth

USDA-ARS?s Scientific Manuscript database

Plant growth is mediated by two cellular processes: division and elongation. The maize leaf is an excellent model to study plant growth since these processes are spatially separated into discreet zones - a division zone (DZ), transition zone (TZ), and elongation zone (EZ) - at the base of the leaf. ...

Pacific Northwest Laboratory annual report for 1990 to the DOE Office of Energy Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toburen, L.H.; Stults, B.R.; Mahaffey, J.A.

Part four of the PNL Annual Report for 1990 includes research in physical sciences. Individual reports are processed separately for the data bases in the following areas: Dosimetry Research; Measurement Science; Radiological and Chemical Physics; Radiation Dosimetry; Radiation Biophysics; and Modelling Cellular Response to Genetic Damage. (FL)

Atrial Model Development and Prototype Simulations: CRADA Final Report on Tasks 3 and 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Hara, T.; Zhang, X.; Villongco, C.

2016-10-28

The goal of this CRADA was to develop essential tools needed to simulate human atrial electrophysiology in 3-dimensions using an anatomical image-based anatomy and physiologically detailed human cellular model. The atria were modeled as anisotropic, representing the preferentially longitudinal electrical coupling between myocytes. Across the entire anatomy, cellular electrophysiology was heterogeneous, with left and right atrial myocytes defined differently. Left and right cell types for the “control” case of sinus rhythm (SR) was compared with remodeled electrophysiology and calcium cycling characteristics of chronic atrial fibrillation (cAF). The effects of Isoproterenol (ISO), a beta-adrenergic agonist that represents the functional consequences ofmore » PKA phosphorylation of various ion channels and transporters, was also simulated in SR and cAF to represent atrial activity under physical or emotional stress. Results and findings from Tasks 3 & 4 are described. Tasks 3 and 4 are, respectively: Input parameters prepared for a Cardioid simulation; Report including recommendations for additional scenario development and post-processing analytic strategy.« less

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Imaging hypoxia using 3D photoacoustic spectroscopy

NASA Astrophysics Data System (ADS)

Stantz, Keith M.

2010-02-01

Purpose: The objective is to develop a multivariate in vivo hemodynamic model of tissue oxygenation (MiHMO2) based on 3D photoacoustic spectroscopy. Introduction: Low oxygen levels, or hypoxia, deprives cancer cells of oxygen and confers resistance to irradiation, some chemotherapeutic drugs, and oxygen-dependent therapies (phototherapy) leading to treatment failure and poor disease-free and overall survival. For example, clinical studies of patients with breast carcinomas, cervical cancer, and head and neck carcinomas (HNC) are more likely to suffer local reoccurrence and metastasis if their tumors are hypoxic. A novel method to non invasively measure tumor hypoxia, identify its type, and monitor its heterogeneity is devised by measuring tumor hemodynamics, MiHMO2. Material and Methods: Simulations are performed to compare tumor pO2 levels and hypoxia based on physiology - perfusion, fractional plasma volume, fractional cellular volume - and its hemoglobin status - oxygen saturation and hemoglobin concentration - based on in vivo measurements of breast, prostate, and ovarian tumors. Simulations of MiHMO2 are performed to assess the influence of scanner resolutions and different mathematic models of oxygen delivery. Results: Sensitivity of pO2 and hypoxic fraction to photoacoustic scanner resolution and dependencies on model complexity will be presented using hemodynamic parameters for different tumors. Conclusions: Photoacoustic CT spectroscopy provides a unique ability to monitor hemodynamic and cellular physiology in tissue, which can be used to longitudinally monitor tumor oxygenation and its response to anti-angiogenic therapies.

Establishing a Cell-based Assay for Assessment of Cellular Metabolism on Chemical Toxicity

EPA Science Inventory

A major drawback of current in vitro chemical testing is that many commonly used cell lines lack chemical metabolism. To help address this challenge, we are established a method for assessing the impact of cellular metabolism on chemical-based cellular toxicity. A commonly used h...

Characterizing viscoelastic properties of breast cancer tissue in a mouse model using indentation.

PubMed

Qiu, Suhao; Zhao, Xuefeng; Chen, Jiayao; Zeng, Jianfeng; Chen, Shuangqing; Chen, Lei; Meng, You; Liu, Biao; Shan, Hong; Gao, Mingyuan; Feng, Yuan

2018-03-01

Breast cancer is one of the leading cancer forms affecting females worldwide. Characterizing the mechanical properties of breast cancer tissue is important for diagnosis and uncovering the mechanobiology mechanism. Although most of the studies were based on human cancer tissue, an animal model is still describable for preclinical analysis. Using a custom-build indentation device, we measured the viscoelastic properties of breast cancer tissue from 4T1 and SKBR3 cell lines. A total of 7 samples were tested for each cancer tissue using a mouse model. We observed that a viscoelastic model with 2-term Prony series could best describe the ramp and stress relaxation of the tissue. For long-term responses, the SKBR3 tissues were stiffer in the strain levels of 4-10%, while no significant differences were found for the instantaneous elastic modulus. We also found tissues from both cell lines appeared to be strain-independent for the instantaneous elastic modulus and for the long-term elastic modulus in the strain level of 4-10%. In addition, by inspecting the cellular morphological structure of the two tissues, we found that SKBR3 tissues had a larger volume ratio of nuclei and a smaller volume ratio of extracellular matrix (ECM). Compared with prior cellular mechanics studies, our results indicated that ECM could contribute to the stiffening the tissue-level behavior. The viscoelastic characterization of the breast cancer tissue contributed to the scarce animal model data and provided support for the linear viscoelastic model used for in vivo elastography studies. Results also supplied helpful information for modeling of the breast cancer tissue in the tissue and cellular levels. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rational Targeting of Cellular Cholesterol in Diffuse Large B-Cell Lymphoma (DLBCL) Enabled by Functional Lipoprotein Nanoparticles: A Therapeutic Strategy Dependent on Cell of Origin.

PubMed

Rink, Jonathan S; Yang, Shuo; Cen, Osman; Taxter, Tim; McMahon, Kaylin M; Misener, Sol; Behdad, Amir; Longnecker, Richard; Gordon, Leo I; Thaxton, C Shad

2017-11-06

Cancer cells have altered metabolism and, in some cases, an increased demand for cholesterol. It is important to identify novel, rational treatments based on biology, and cellular cholesterol metabolism as a potential target for cancer is an innovative approach. Toward this end, we focused on diffuse large B-cell lymphoma (DLBCL) as a model because there is differential cholesterol biosynthesis driven by B-cell receptor (BCR) signaling in germinal center (GC) versus activated B-cell (ABC) DLBCL. To specifically target cellular cholesterol homeostasis, we employed high-density lipoprotein-like nanoparticles (HDL NP) that can generally reduce cellular cholesterol by targeting and blocking cholesterol uptake through the high-affinity HDL receptor, scavenger receptor type B-1 (SCARB1). As we previously reported, GC DLBCL are exquisitely sensitive to HDL NP as monotherapy, while ABC DLBCL are less sensitive. Herein, we report that enhanced BCR signaling and resultant de novo cholesterol synthesis in ABC DLBCL drastically reduces the ability of HDL NPs to reduce cellular cholesterol and induce cell death. Therefore, we combined HDL NP with the BCR signaling inhibitor ibrutinib and the SYK inhibitor R406. By targeting both cellular cholesterol uptake and BCR-associated de novo cholesterol synthesis, we achieved cellular cholesterol reduction and induced apoptosis in otherwise resistant ABC DLBCL cell lines. These results in lymphoma demonstrate that reduction of cellular cholesterol is a powerful mechanism to induce apoptosis. Cells rich in cholesterol require HDL NP therapy to reduce uptake and molecularly targeted agents that inhibit upstream pathways that stimulate de novo cholesterol synthesis, thus, providing a new paradigm for rationally targeting cholesterol metabolism as therapy for cancer.

Bioactive Polymeric Composites for Tooth Mineral Regeneration: Physicochemical and Cellular Aspects

PubMed Central

Skrtic, Drago; Antonucci, Joseph M.

2011-01-01

Our studies of amorphous calcium phosphate (ACP)-based dental materials are focused on the design of bioactive, non-degradable, biocompatible, polymeric composites derived from acrylic monomer systems and ACP by photochemical or chemically activated polymerization. Their intended uses include remineralizing bases/liners, orthodontic adhesives and/or endodontic sealers. The bioactivity of these materials originates from the propensity of ACP, once exposed to oral fluids, to release Ca and PO4 ions (building blocks of tooth and bone mineral) in a sustained manner while spontaneously converting to thermodynamically stable apatite. As a result of ACP's bioactivity, local Ca- and PO4-enriched environments are created with supersaturation conditions favorable for the regeneration of tooth mineral lost to decay or wear. Besides its applicative purpose, our research also seeks to expand the fundamental knowledge base of structure-composition-property relationships existing in these complex systems and identify the mechanisms that govern filler/polymer and composite/tooth interfacial phenomena. In addition to an extensive physicochemical evaluation, we also assess the leachability of the unreacted monomers and in vitro cellular responses to these types of dental materials. The systematic physicochemical and cellular assessments presented in this study typically provide model materials suitable for further animal and/or clinical testing. In addition to their potential dental clinical value, these studies suggest the future development of calcium phosphate-based biomaterials based on composite materials derived from biodegradable polymers and ACP, and designed primarily for general bone tissue regeneration. PMID:22102967

The effects of storage and sterilization on de-cellularized and re-cellularized whole lung.

PubMed

Bonenfant, Nicholas R; Sokocevic, Dino; Wagner, Darcy E; Borg, Zachary D; Lathrop, Melissa J; Lam, Ying Wai; Deng, Bin; Desarno, Michael J; Ashikaga, Taka; Loi, Roberto; Weiss, Daniel J

2013-04-01

Despite growing interest on the potential use of de-cellularized whole lungs as 3-dimensional scaffolds for ex vivo lung tissue generation, optimal processing including sterilization and storage conditions, are not well defined. Further, it is unclear whether lungs need to be obtained immediately or may be usable even if harvested several days post-mortem, a situation mimicking potential procurement of human lungs from autopsy. We therefore assessed effects of delayed necropsy, prolonged storage (3 and 6 months), and of two commonly utilized sterilization approaches: irradiation or final rinse with peracetic acid, on architecture and extracellular matrix (ECM) protein characteristics of de-cellularized mouse lungs. These different approaches resulted in significant differences in both histologic appearance and in retention of ECM and intracellular proteins as assessed by immunohistochemistry and mass spectrometry. Despite these differences, binding and proliferation of bone marrow-derived mesenchymal stromal cells (MSCs) over a one month period following intratracheal inoculation was similar between experimental conditions. In contrast, significant differences occurred with C10 mouse lung epithelial cells between the different conditions. Therefore, delayed necropsy, duration of scaffold storage, sterilization approach, and cell type used for re-cellularization may significantly impact the usefulness of this biological scaffold-based model of ex vivo lung tissue regeneration. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic Segmentation of High-Throughput RNAi Fluorescent Cellular Images

PubMed Central

Yan, Pingkum; Zhou, Xiaobo; Shah, Mubarak; Wong, Stephen T. C.

2010-01-01

High-throughput genome-wide RNA interference (RNAi) screening is emerging as an essential tool to assist biologists in understanding complex cellular processes. The large number of images produced in each study make manual analysis intractable; hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. In this paper, a fully automatic method for segmentation of cells from genome-wide RNAi screening images is proposed. Nuclei are first extracted from the DNA channel by using a modified watershed algorithm. Cells are then extracted by modeling the interaction between them as well as combining both gradient and region information in the Actin and Rac channels. A new energy functional is formulated based on a novel interaction model for segmenting tightly clustered cells with significant intensity variance and specific phenotypes. The energy functional is minimized by using a multiphase level set method, which leads to a highly effective cell segmentation method. Promising experimental results demonstrate that automatic segmentation of high-throughput genome-wide multichannel screening can be achieved by using the proposed method, which may also be extended to other multichannel image segmentation problems. PMID:18270043

Cellular automata models for diffusion of information and highway traffic flow

NASA Astrophysics Data System (ADS)

Fuks, Henryk

In the first part of this work we study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents degree of 'anticipatory driving'. We compare two driving strategies with identical maximum throughput: 'conservative' driving with high speed limit and 'anticipatory' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered. For rule 184, we present exact calculations of the order parameter in a transition from the moving phase to the jammed phase using the method of preimage counting, and use this result to construct a solution to the density classification problem. In the second part we propose a probabilistic cellular automaton model for the spread of innovations, rumors, news, etc., in a social system. We start from simple deterministic models, for which exact expressions for the density of adopters are derived. For a more realistic model, based on probabilistic cellular automata, we study the influence of a range of interaction R on the shape of the adoption curve. When the probability of adoption is proportional to the local density of adopters, and individuals can drop the innovation with some probability p, the system exhibits a second order phase transition. Critical line separating regions of parameter space in which asymptotic density of adopters is positive from the region where it is equal to zero converges toward the mean-field line when the range of the interaction increases. In a region between R=1 critical line and the mean-field line asymptotic density of adopters depends on R, becoming zero if R is too small (smaller than some critical value). This result demonstrates the importance of connectivity in diffusion of information. We also define a new class of automata networks which incorporates non-local interactions, and discuss its applicability in modeling of diffusion of innovations.

Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.

PubMed

Inoue, Yasuhiro; Adachi, Taiji

2011-07-01

Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.

A Semi-quantum Version of the Game of Life

NASA Astrophysics Data System (ADS)

Flitney, Adrian P.; Abbott, Derek

The following sections are included: * Background and Motivation * Classical cellular automata * Conway's game of life * Quantum cellular automata * Semi-quantum Life * The idea * A first model * A semi-quantum model * Discussion * Summary * References

ALC: automated reduction of rule-based models

PubMed Central

Koschorreck, Markus; Gilles, Ernst Dieter

2008-01-01

Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705

Human pluripotent stem cell models of autism spectrum disorder: emerging frontiers, opportunities, and challenges towards neuronal networks in a dish.

PubMed

Aigner, Stefan; Heckel, Tobias; Zhang, Jitao D; Andreae, Laura C; Jagasia, Ravi

2014-03-01

Autism spectrum disorder (ASD) is characterized by deficits in language development and social cognition and the manifestation of repetitive and restrictive behaviors. Despite recent major advances, our understanding of the pathophysiological mechanisms leading to ASD is limited. Although most ASD cases have unknown genetic underpinnings, animal and human cellular models of several rare, genetically defined syndromic forms of ASD have provided evidence for shared pathophysiological mechanisms that may extend to idiopathic cases. Here, we review our current knowledge of the genetic basis and molecular etiology of ASD and highlight how human pluripotent stem cell-based disease models have the potential to advance our understanding of molecular dysfunction. We summarize landmark studies in which neuronal cell populations generated from human embryonic stem cells and patient-derived induced pluripotent stem cells have served to model disease mechanisms, and we discuss recent technological advances that may ultimately allow in vitro modeling of specific human neuronal circuitry dysfunction in ASD. We propose that these advances now offer an unprecedented opportunity to help better understand ASD pathophysiology. This should ultimately enable the development of cellular models for ASD, allowing drug screening and the identification of molecular biomarkers for patient stratification.

Mouse Models in Bone Marrow Transplantation and Adoptive Cellular Therapy

PubMed Central

Arber, Caroline; Brenner, Malcolm K.; Reddy, Pavan

2014-01-01

Mouse models of transplantation have been indispensable to the development of bone marrow transplantation (BMT). Their role in the generation of basic science knowledge is invaluable and is subject to discussion below. However, this article focuses on the direct role and relevance of mouse models towards the clinical development and advances in BMT and adoptive T-cell therapy for human diseases. The authors aim to present a thoughtful perspective on the pros and cons of mouse models while noting that despite imperfections these models are obligatory for the development of science-based medicine. PMID:24216170

Multi-layer composite mechanical modeling for the inhomogeneous biofilm mechanical behavior.

PubMed

Wang, Xiaoling; Han, Jingshi; Li, Kui; Wang, Guoqing; Hao, Mudong

2016-08-01

Experiments showed that bacterial biofilms are heterogeneous, for example, the density, the diffusion coefficient, and mechanical properties of the biofilm are different along the biofilm thickness. In this paper, we establish a multi-layer composite model to describe the biofilm mechanical inhomogeneity based on unified multiple-component cellular automaton (UMCCA) model. By using our model, we develop finite element simulation procedure for biofilm tension experiment. The failure limit and biofilm extension displacement obtained from our model agree well with experimental measurements. This method provides an alternative theory to study the mechanical inhomogeneity in biological materials.

Post-traumatic stress disorder and beyond: an overview of rodent stress models.

PubMed

Schöner, Johanna; Heinz, Andreas; Endres, Matthias; Gertz, Karen; Kronenberg, Golo

2017-10-01

Post-traumatic stress disorder (PTSD) is a psychiatric disorder of high prevalence and major socioeconomic impact. Patients suffering from PTSD typically present intrusion and avoidance symptoms and alterations in arousal, mood and cognition that last for more than 1 month. Animal models are an indispensable tool to investigate underlying pathophysiological pathways and, in particular, the complex interplay of neuroendocrine, genetic and environmental factors that may be responsible for PTSD induction. Since the 1960s, numerous stress paradigms in rodents have been developed, based largely on Seligman's seminal formulation of 'learned helplessness' in canines. Rodent stress models make use of physiological or psychological stressors such as foot shock, underwater trauma, social defeat, early life stress or predator-based stress. Apart from the brief exposure to an acute stressor, chronic stress models combining a succession of different stressors for a period of several weeks have also been developed. Chronic stress models in rats and mice may elicit characteristic PTSD-like symptoms alongside, more broadly, depressive-like behaviours. In this review, the major existing rodent models of PTSD are reviewed in terms of validity, advantages and limitations; moreover, significant results and implications for future research-such as the role of FKBP5, a mediator of the glucocorticoid stress response and promising target for therapeutic interventions-are discussed. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

A Continuum Damage Mechanics Model for the Static and Cyclic Fatigue of Cellular Composites

PubMed Central

Huber, Otto

2017-01-01

The fatigue behavior of a cellular composite with an epoxy matrix and glass foam granules is analyzed and modeled by means of continuum damage mechanics. The investigated cellular composite is a particular type of composite foam, and is very similar to syntactic foams. In contrast to conventional syntactic foams constituted by hollow spherical particles (balloons), cellular glass, mineral, or metal place holders are combined with the matrix material (metal or polymer) in the case of cellular composites. A microstructural investigation of the damage behavior is performed using scanning electron microscopy. For the modeling of the fatigue behavior, the damage is separated into pure static and pure cyclic damage and described in terms of the stiffness loss of the material using damage models for cyclic and creep damage. Both models incorporate nonlinear accumulation and interaction of damage. A cycle jumping procedure is developed, which allows for a fast and accurate calculation of the damage evolution for constant load frequencies. The damage model is applied to examine the mean stress effect for cyclic fatigue and to investigate the frequency effect and the influence of the signal form in the case of static and cyclic damage interaction. The calculated lifetimes are in very good agreement with experimental results. PMID:28809806

Pericentrin in cellular function and disease

PubMed Central

Delaval, Benedicte

2010-01-01

Pericentrin is an integral component of the centrosome that serves as a multifunctional scaffold for anchoring numerous proteins and protein complexes. Through these interactions, pericentrin contributes to a diversity of fundamental cellular processes. Recent studies link pericentrin to a growing list of human disorders. Studies on pericentrin at the cellular, molecular, and, more recently, organismal level, provide a platform for generating models to elucidate the etiology of these disorders. Although the complexity of phenotypes associated with pericentrin-mediated disorders is somewhat daunting, insights into the cellular basis of disease are beginning to come into focus. In this review, we focus on human conditions associated with loss or elevation of pericentrin and propose cellular and molecular models that might explain them. PMID:19951897

Cellular Automata with Anticipation: Examples and Presumable Applications

NASA Astrophysics Data System (ADS)

Krushinsky, Dmitry; Makarenko, Alexander

2010-11-01

One of the most prospective new methodologies for modelling is the so-called cellular automata (CA) approach. According to this paradigm, the models are built from simple elements connected into regular structures with local interaction between neighbours. The patterns of connections usually have a simple geometry (lattices). As one of the classical examples of CA we mention the game `Life' by J. Conway. This paper presents two examples of CA with anticipation property. These examples include a modification of the game `Life' and a cellular model of crowd movement.

A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

PubMed

Sluka, James P; Fu, Xiao; Swat, Maciej; Belmonte, Julio M; Cosmanescu, Alin; Clendenon, Sherry G; Wambaugh, John F; Glazier, James A

2016-01-01

We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

A Liver-Centric Multiscale Modeling Framework for Xenobiotics

PubMed Central

Swat, Maciej; Cosmanescu, Alin; Clendenon, Sherry G.; Wambaugh, John F.; Glazier, James A.

2016-01-01

We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. PMID:27636091

Erythroid cell growth and differentiation in vitro in the simulated microgravity environment of the NASA rotating wall vessel bioreactor

NASA Technical Reports Server (NTRS)

Sytkowski, A. J.; Davis, K. L.

2001-01-01

Prolonged exposure of humans and experimental animals to the altered gravitational conditions of space flight has adverse effects on the lymphoid and erythroid hematopoietic systems. Although some information is available regarding the cellular and molecular changes in lymphocytes exposed to microgravity, little is known about the erythroid cellular changes that may underlie the reduction in erythropoiesis and resultant anemia. We now report a reduction in erythroid growth and a profound inhibition of erythropoietin (Epo)-induced differentiation in a ground-based simulated microgravity model system. Rauscher murine erythroleukemia cells were grown either in tissue culture vessels at 1 x g or in the simulated microgravity environment of the NASA-designed rotating wall vessel (RWV) bioreactor. Logarithmic growth was observed under both conditions; however, the doubling time in simulated microgravity was only one-half of that seen at 1 x g. No difference in apoptosis was detected. Induction with Epo at the initiation of the culture resulted in differentiation of approximately 25% of the cells at 1 x g, consistent with our previous observations. In contrast, induction with Epo at the initiation of simulated microgravity resulted in only one-half of this degree of differentiation. Significantly, the growth of cells in simulated microgravity for 24 h prior to Epo induction inhibited the differentiation almost completely. The results suggest that the NASA RWV bioreactor may serve as a suitable ground-based microgravity simulator to model the cellular and molecular changes in erythroid cells observed in true microgravity.

Biosensor Architectures for High-Fidelity Reporting of Cellular Signaling

PubMed Central

Dushek, Omer; Lellouch, Annemarie C.; Vaux, David J.; Shahrezaei, Vahid

2014-01-01

Understanding mechanisms of information processing in cellular signaling networks requires quantitative measurements of protein activities in living cells. Biosensors are molecular probes that have been developed to directly track the activity of specific signaling proteins and their use is revolutionizing our understanding of signal transduction. The use of biosensors relies on the assumption that their activity is linearly proportional to the activity of the signaling protein they have been engineered to track. We use mechanistic mathematical models of common biosensor architectures (single-chain FRET-based biosensors), which include both intramolecular and intermolecular reactions, to study the validity of the linearity assumption. As a result of the classic mechanism of zero-order ultrasensitivity, we find that biosensor activity can be highly nonlinear so that small changes in signaling protein activity can give rise to large changes in biosensor activity and vice versa. This nonlinearity is abolished in architectures that favor the formation of biosensor oligomers, but oligomeric biosensors produce complicated FRET states. Based on this finding, we show that high-fidelity reporting is possible when a single-chain intermolecular biosensor is used that cannot undergo intramolecular reactions and is restricted to forming dimers. We provide phase diagrams that compare various trade-offs, including observer effects, which further highlight the utility of biosensor architectures that favor intermolecular over intramolecular binding. We discuss challenges in calibrating and constructing biosensors and highlight the utility of mathematical models in designing novel probes for cellular signaling. PMID:25099816

Research on the comparison of extension mechanism of cellular automaton based on hexagon grid and rectangular grid

NASA Astrophysics Data System (ADS)

Zhai, Xiaofang; Zhu, Xinyan; Xiao, Zhifeng; Weng, Jie

2009-10-01

Historically, cellular automata (CA) is a discrete dynamical mathematical structure defined on spatial grid. Research on cellular automata system (CAS) has focused on rule sets and initial condition and has not discussed its adjacency. Thus, the main focus of our study is the effect of adjacency on CA behavior. This paper is to compare rectangular grids with hexagonal grids on their characteristics, strengths and weaknesses. They have great influence on modeling effects and other applications including the role of nearest neighborhood in experimental design. Our researches present that rectangular and hexagonal grids have different characteristics. They are adapted to distinct aspects, and the regular rectangular or square grid is used more often than the hexagonal grid. But their relative merits have not been widely discussed. The rectangular grid is generally preferred because of its symmetry, especially in orthogonal co-ordinate system and the frequent use of raster from Geographic Information System (GIS). However, in terms of complex terrain, uncertain and multidirectional region, we have preferred hexagonal grids and methods to facilitate and simplify the problem. Hexagonal grids can overcome directional warp and have some unique characteristics. For example, hexagonal grids have a simpler and more symmetric nearest neighborhood, which avoids the ambiguities of the rectangular grids. Movement paths or connectivity, the most compact arrangement of pixels, make hexagonal appear great dominance in the process of modeling and analysis. The selection of an appropriate grid should be based on the requirements and objectives of the application. We use rectangular and hexagonal grids respectively for developing city model. At the same time we make use of remote sensing images and acquire 2002 and 2005 land state of Wuhan. On the base of city land state in 2002, we make use of CA to simulate reasonable form of city in 2005. Hereby, these results provide a proof of concept for hexagonal which has great dominance.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

A unifying view of the broad-spectrum antiviral activity of RSAD2 (viperin) based on its radical-SAM chemistry.

PubMed

Honarmand Ebrahimi, Kourosh

2018-04-25

RSAD2 (cig-5), also known as viperin (virus inhibitory protein, endoplasmic reticulum associated, interferon inducible), is a member of the radical S-adenosylmethionine (SAM) superfamily of enzymes. Since the discovery of this enzyme more than a decade ago, numerous studies have shown that it exhibits antiviral activity against a wide range of viruses. However, there is no clear picture demonstrating the mechanism by which RSAD2 restricts the replication process of different viruses, largely because there is no direct evidence describing its in vivo enzymatic activity. As a result, a multifunctionality model has emerged. According to this model the mechanism by which RSAD2 restricts replication of different viruses varies and in many cases is not dependent on the radical-SAM chemistry of RSAD2. If the radical-SAM activity of RSAD2 is not required for its antiviral function, the question worth asking is: why does the cellular defence mechanism induce the expression of the radical-SAM enzyme RSAD2, which is metabolically expensive due to the requirement for a [4Fe-4S] cluster and usage of SAM? Here, in contrast to the multifunctionality view, I put forward a unifying model. I postulate that the radical-SAM activity of RSAD2 modulates cellular metabolic pathways essential for viral replication and/or cell proliferation and survival. As a result, its catalytic activity restricts the replication of a wide range of viruses via a common cellular function. This view is based on recent discoveries hinting towards possible substrates of RSAD2, re-evaluation of previous studies regarding the antiviral activity of RSAD2, and accumulating evidence suggesting a role of human RSAD2 in the metabolic reprogramming of cells.

Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages

PubMed Central

Pradervand, Sylvain; Maurya, Mano R; Subramaniam, Shankar

2006-01-01

Background Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling pathways. However, using specific markers of signaling pathways, such as signaling proteins, it is possible to develop a 'coarse-grained network' map that can help understand common regulatory modules for various cytokine responses and help differentiate between the causes of their release. Results Using a systematic profiling of signaling responses and cytokine release in RAW 264.7 macrophages made available by the Alliance for Cellular Signaling, an analysis strategy is presented that integrates principal component regression and exhaustive search-based model reduction to identify required signaling factors necessary and sufficient to predict the release of seven cytokines (G-CSF, IL-1α, IL-6, IL-10, MIP-1α, RANTES, and TNFα) in response to selected ligands. This study provides a model-based quantitative estimate of cytokine release and identifies ten signaling components involved in cytokine production. The models identified capture many of the known signaling pathways involved in cytokine release and predict potentially important novel signaling components, like p38 MAPK for G-CSF release, IFNγ- and IL-4-specific pathways for IL-1a release, and an M-CSF-specific pathway for TNFα release. Conclusion Using an integrative approach, we have identified the pathways responsible for the differential regulation of cytokine release in RAW 264.7 macrophages. Our results demonstrate the power of using heterogeneous cellular data to qualitatively and quantitatively map intermediate cellular phenotypes. PMID:16507166

CNNEDGEPOT: CNN based edge detection of 2D near surface potential field data

NASA Astrophysics Data System (ADS)

Aydogan, D.

2012-09-01

All anomalies are important in the interpretation of gravity and magnetic data because they indicate some important structural features. One of the advantages of using gravity or magnetic data for searching contacts is to be detected buried structures whose signs could not be seen on the surface. In this paper, a general view of the cellular neural network (CNN) method with a large scale nonlinear circuit is presented focusing on its image processing applications. The proposed CNN model is used consecutively in order to extract body and body edges. The algorithm is a stochastic image processing method based on close neighborhood relationship of the cells and optimization of A, B and I matrices entitled as cloning template operators. Setting up a CNN (continues time cellular neural network (CTCNN) or discrete time cellular neural network (DTCNN)) for a particular task needs a proper selection of cloning templates which determine the dynamics of the method. The proposed algorithm is used for image enhancement and edge detection. The proposed method is applied on synthetic and field data generated for edge detection of near-surface geological bodies that mask each other in various depths and dimensions. The program named as CNNEDGEPOT is a set of functions written in MATLAB software. The GUI helps the user to easily change all the required CNN model parameters. A visual evaluation of the outputs due to DTCNN and CTCNN are carried out and the results are compared with each other. These examples demonstrate that in detecting the geological features the CNN model can be used for visual interpretation of near surface gravity or magnetic anomaly maps.

Predicting cell viability within tissue scaffolds under equiaxial strain: multi-scale finite element model of collagen-cardiomyocytes constructs.

PubMed

Elsaadany, Mostafa; Yan, Karen Chang; Yildirim-Ayan, Eda

2017-06-01

Successful tissue engineering and regenerative therapy necessitate having extensive knowledge about mechanical milieu in engineered tissues and the resident cells. In this study, we have merged two powerful analysis tools, namely finite element analysis and stochastic analysis, to understand the mechanical strain within the tissue scaffold and residing cells and to predict the cell viability upon applying mechanical strains. A continuum-based multi-length scale finite element model (FEM) was created to simulate the physiologically relevant equiaxial strain exposure on cell-embedded tissue scaffold and to calculate strain transferred to the tissue scaffold (macro-scale) and residing cells (micro-scale) upon various equiaxial strains. The data from FEM were used to predict cell viability under various equiaxial strain magnitudes using stochastic damage criterion analysis. The model validation was conducted through mechanically straining the cardiomyocyte-encapsulated collagen constructs using a custom-built mechanical loading platform (EQUicycler). FEM quantified the strain gradients over the radial and longitudinal direction of the scaffolds and the cells residing in different areas of interest. With the use of the experimental viability data, stochastic damage criterion, and the average cellular strains obtained from multi-length scale models, cellular viability was predicted and successfully validated. This methodology can provide a great tool to characterize the mechanical stimulation of bioreactors used in tissue engineering applications in providing quantification of mechanical strain and predicting cellular viability variations due to applied mechanical strain.

Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range.

PubMed

Bachmann, Julie; Raue, Andreas; Schilling, Marcel; Böhm, Martin E; Kreutz, Clemens; Kaschek, Daniel; Busch, Hauke; Gretz, Norbert; Lehmann, Wolf D; Timmer, Jens; Klingmüller, Ursula

2011-07-19

Cellular signal transduction is governed by multiple feedback mechanisms to elicit robust cellular decisions. The specific contributions of individual feedback regulators, however, remain unclear. Based on extensive time-resolved data sets in primary erythroid progenitor cells, we established a dynamic pathway model to dissect the roles of the two transcriptional negative feedback regulators of the suppressor of cytokine signaling (SOCS) family, CIS and SOCS3, in JAK2/STAT5 signaling. Facilitated by the model, we calculated the STAT5 response for experimentally unobservable Epo concentrations and provide a quantitative link between cell survival and the integrated response of STAT5 in the nucleus. Model predictions show that the two feedbacks CIS and SOCS3 are most effective at different ligand concentration ranges due to their distinct inhibitory mechanisms. This divided function of dual feedback regulation enables control of STAT5 responses for Epo concentrations that can vary 1000-fold in vivo. Our modeling approach reveals dose-dependent feedback control as key property to regulate STAT5-mediated survival decisions over a broad range of ligand concentrations.

Glycolysis Is Governed by Growth Regime and Simple Enzyme Regulation in Adherent MDCK Cells

PubMed Central

Rehberg, Markus; Ritter, Joachim B.; Reichl, Udo

2014-01-01

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses. PMID:25329309

Glycolysis is governed by growth regime and simple enzyme regulation in adherent MDCK cells.

PubMed

Rehberg, Markus; Ritter, Joachim B; Reichl, Udo

2014-10-01

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses.

A cellular model for sporadic ALS using patient-derived induced pluripotent stem cells

PubMed Central

Burkhardt, Matthew F; Martinez, Fernando J; Wright, Sarah; Ramos, Carla; Volfson, Dmitri; Mason, Michael; Garnes, Jeff; Dang, Vu; Lievers, Jeffery; Shoukat-Mumtaz, Uzma; Martinez, Rita; Gai, Hui; Blake, Robert; Vaisberg, Eugeni; Grskovic, Marica; Johnson, Charles; Irion, Stefan; Bright, Jessica; Cooper, Bonnie; Nguyen, Leane; Griswold-Prenner, Irene; Javaherian, Ashkan

2016-01-01

Development of therapeutics for genetically complex neurodegenerative diseases such as sporadic amyotrophic lateral sclerosis (ALS) has largely been hampered by lack of relevant disease models. Reprogramming of sporadic ALS patients’ fibroblasts into induced pluripotent stem cells (iPSC) and differentiation into affected neurons that show a disease phenotype could provide a cellular model for disease mechanism studies and drug discovery. Here we report the reprogramming to pluripotency of fibroblasts from a large cohort of healthy controls and ALS patients and their differentiation into motor neurons. We demonstrate that motor neurons derived from three sALS patients show de novo TDP-43 aggregation and that the aggregates recapitulate pathology in postmortem tissue from one of the same patients from which the iPSC were derived. We configured a high-content chemical screen using the TDP-43 aggregate endpoint both in lower motor neurons and upper motor neuron like cells and identified FDA-approved small molecule modulators including Digoxin demonstrating the feasibility of patient-derived iPSC-based disease modelling for drug screening. PMID:23891805

Models for discovery of targeted therapy in genetic epileptic encephalopathies.

PubMed

Maljevic, Snezana; Reid, Christopher A; Petrou, Steven

2017-10-01

Epileptic encephalopathies are severe disorders emerging in the first days to years of life that commonly include refractory seizures, various types of movement disorders, and different levels of developmental delay. In recent years, many de novo occurring variants have been identified in individuals with these devastating disorders. To unravel disease mechanisms, the functional impact of detected variants associated with epileptic encephalopathies is investigated in a range of cellular and animal models. This review addresses efforts to advance and use such models to identify specific molecular and cellular targets for the development of novel therapies. We focus on ion channels as the best-studied group of epilepsy genes. Given the clinical and genetic heterogeneity of epileptic encephalopathy disorders, experimental models that can reflect this complexity are critical for the development of disease mechanisms-based targeted therapy. The convergence of technological advances in gene sequencing, stem cell biology, genome editing, and high throughput functional screening together with massive unmet clinical needs provides unprecedented opportunities and imperatives for precision medicine in epileptic encephalopathies. © 2017 International Society for Neurochemistry.

Physical Model of the Dynamic Instability in an Expanding Cell Culture

PubMed Central

Mark, Shirley; Shlomovitz, Roie; Gov, Nir S.; Poujade, Mathieu; Grasland-Mongrain, Erwan; Silberzan, Pascal

2010-01-01

Abstract Collective cell migration is of great significance in many biological processes. The goal of this work is to give a physical model for the dynamics of cell migration during the wound healing response. Experiments demonstrate that an initially uniform cell-culture monolayer expands in a nonuniform manner, developing fingerlike shapes. These fingerlike shapes of the cell culture front are composed of columns of cells that move collectively. We propose a physical model to explain this phenomenon, based on the notion of dynamic instability. In this model, we treat the first layers of cells at the front of the moving cell culture as a continuous one-dimensional membrane (contour), with the usual elasticity of a membrane: curvature and surface-tension. This membrane is active, due to the forces of cellular motility of the cells, and we propose that this motility is related to the local curvature of the culture interface; larger convex curvature correlates with a stronger cellular motility force. This shape-force relation gives rise to a dynamic instability, which we then compare to the patterns observed in the wound healing experiments. PMID:20141748

A model of aging as accumulated damage matches observed mortality patterns and predicts the life-extending effects of prospective interventions

PubMed Central

Phoenix, Chris

2007-01-01

The relative insensitivity of lifespan to environmental factors constitutes compelling evidence that the physiological decline associated with aging derives primarily from the accumulation of intrinsic molecular and cellular side-effects of metabolism. Here we model that accumulation starting from a biologically based interpretation of the way in which those side-effects interact. We first validate this model by showing that it very accurately reproduces the distribution of ages at death seen in typical populations that are well protected from age-independent causes of death. We then exploit the mechanistic basis of this model to explore the impact on lifespans of interventions that combat aging, with an emphasis on interventions that repair (rather than merely retard) the direct molecular or cellular consequences of metabolism and thus prevent them from accumulating to pathogenic levels. Our results strengthen the case that an indefinite extension of healthy and total life expectancy can be achieved by a plausible rate of progress in the development of such therapies, once a threshold level of efficacy of those therapies has been reached. PMID:19424837

Cellular Model of Atherogenesis Based on Pluripotent Vascular Wall Pericytes.

PubMed

Ivanova, Ekaterina A; Orekhov, Alexander N

2016-01-01

Pericytes are pluripotent cells that can be found in the vascular wall of both microvessels and large arteries and veins. They have distinct morphology with long branching processes and form numerous contacts with each other and with endothelial cells, organizing the vascular wall cells into a three-dimensional network. Accumulating evidence demonstrates that pericytes may play a key role in the pathogenesis of vascular disorders, including atherosclerosis. Macrovascular pericytes are able to accumulate lipids and contribute to growth and vascularization of the atherosclerotic plaque. Moreover, they participate in the local inflammatory process and thrombosis, which can lead to fatal consequences. At the same time, pericytes can represent a useful model for studying the atherosclerotic process and for the development of novel therapeutic approaches. In particular, they are suitable for testing various substances' potential for decreasing lipid accumulation induced by the incubation of cells with atherogenic low-density lipoprotein. In this review we will discuss the application of cellular models for studying atherosclerosis and provide several examples of successful application of these models to drug research.

A cellular automaton model of wildfire propagation and extinction

Treesearch

Keith C. Clarke; James A. Brass; Phillip J. Riggan

1994-01-01

We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

Computational study on cortical spreading depression based on a generalized cellular automaton model

NASA Astrophysics Data System (ADS)

Chen, Shangbin; Hu, Lele; Li, Bing; Xu, Changcheng; Liu, Qian

2009-02-01

Cortical spreading depression (CSD) is an important neurophysiological phenomenon correlating with some neural disorders, such as migraine, cerebral ischemia and epilepsy. By now, we are still not clear about the mechanisms of CSD's initiation and propagation, also the relevance between CSD and those neural diseases. Nevertheless, characterization of CSD, especially the spatiotemporal evolution, will promote the understanding of the CSD's nature and mechanisms. Besides the previous experimental work on charactering the spatiotemporal evolution of CSD in rats by optical intrinsic signal imaging, a computational study based on a generalized cellular automaton (CA) model was proposed here. In the model, we exploited a generalized neighborhood connection rule: a central CA cell is related with a group of surrounding CA cells with different weight coefficients. By selecting special parameters, the generalized CA model could be transformed to the traditional CA models with von Neumann, Moore and hexagon neighborhood connection means. Hence, the new model covered several properties of CSD simulated in traditional CA models: 1) expanding from the origin site like a circular wave; 2) annihilation of two waves traveling in opposite directions after colliding; 3) wavefront of CSD breaking and recovering when and after encountering an obstacle. By setting different refractory period in the different CA lattice field, different connection coefficient in different direction within the defined neighborhood, inhomogeneous propagation of CSD was simulated with high fidelity. The computational results were analogous to the reported time-varying CSD waves by optical imaging. So, the generalized CA model would be useful to study CSD because of its intuitive appeal and computational efficiency.

Induction of humoural and cellular immunity by immunisation with HCV particle vaccine in a non-human primate model.

PubMed

Yokokawa, Hiroshi; Higashino, Atsunori; Suzuki, Saori; Moriyama, Masaki; Nakamura, Noriko; Suzuki, Tomohiko; Suzuki, Ryosuke; Ishii, Koji; Kobiyama, Kouji; Ishii, Ken J; Wakita, Takaji; Akari, Hirofumi; Kato, Takanobu

2018-02-01

Although HCV is a major cause of chronic liver disease worldwide, there is currently no prophylactic vaccine for this virus. Thus, the development of an HCV vaccine that can induce both humoural and cellular immunity is urgently needed. To create an effective HCV vaccine, we evaluated neutralising antibody induction and cellular immune responses following the immunisation of a non-human primate model with cell culture-generated HCV (HCVcc). To accomplish this, 10 common marmosets were immunised with purified, inactivated HCVcc in combination with two different adjuvants: the classically used aluminum hydroxide (Alum) and the recently established adjuvant: CpG oligodeoxynucleotide (ODN) wrapped by schizophyllan (K3-SPG). The coadministration of HCVcc with K3-SPG efficiently induced immune responses against HCV, as demonstrated by the production of antibodies with specific neutralising activity against chimaeric HCVcc with structural proteins from multiple HCV genotypes (1a, 1b, 2a and 3a). The induction of cellular immunity was also demonstrated by the production of interferon-γ mRNA in spleen cells following stimulation with the HCV core protein. These changes were not observed following immunisation with HCVcc/Alum preparation. No vaccination-related abnormalities were detected in any of the immunised animals. The current preclinical study demonstrated that a vaccine included both HCVcc and K3-SPG induced humoural and cellular immunity in marmosets. Vaccination with this combination resulted in the production of antibodies exhibiting cross-neutralising activity against multiple HCV genotypes. Based on these findings, the vaccine created in this study represents a promising, potent and safe prophylactic option against HCV. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Nanotopographical Cues for Modulating Fibrosis and Drug Delivery

NASA Astrophysics Data System (ADS)

Walsh, Laura Aiko Michelle

Nanotopography in the cellular microenvironment provides biological cues and therefore has potential to be a useful tool for directing cellular behavior. Fibrotic encapsulation of implanted devices and materials can wall off and eventually cause functional failure of the implant. Drug delivery requires penetrating the epithelium, which encapsulates the body and provides a barrier to separate the body from its external environment. Both of these challenges could be elegantly surmounted using nanotopography, which would harness innate cellular responses to topographic cues to elicit desired cellular behavior. To this end, we fabricated high and low aspect ratio nanotopographically patterned thin films. Using scanning electron microscopy, real time polymerase chain reaction, immunofluorescence microscopy, in vitro drug delivery assays, transmission electron microscopy, inhibitor studies, and rabbit and rat in vivo drug delivery studies, we investigated cellular response to our nanotopographic thin films. We determined that high aspect ratio topography altered fibroblast morphology and decreased proliferation, possibly due to decreased protein adsorption. The fibroblasts also down regulated expression of mRNA of key factors associated with fibrosis, such as collagens 1 and 3. Low aspect ratio nanotopography increased drug delivery in vitro across an intestinal epithelial model monolayer by increasing paracellular permeability and remodeling the tight junction. This increase in drug delivery required integrin engagement and MLCK activity, and is consistent with the increased focal adhesion formation. Tight junction remodeling was also observed in a multilayered keratinocyte model, showing this mechanism can be generalized to multiple epithelium types. By facilitating direct contact of nanotopography with the viable epidermis using microneedles to pierce the stratum corneum, we are able to transdermally deliver a 150 kiloDalton, IgG-based therapeutic in vivo..

Transparent metal model study of the use of a cellular growth front to form aligned monotectic composite materials

NASA Technical Reports Server (NTRS)

Kaukler, William F.

1988-01-01

The purpose of this work was to resolve a scientific controversy in the understanding of how second phase particles become aligned during unidirectional growth of a monotectic alloy. A second aspect was to make the first systematic observations of the solidification behavior of a monotectic alloy during cellular growth in-situ. This research provides the first systematic transparent model study of cellular solidification. An interface stability diagram was developed for the planar to cellular transition of the succinonitrile glycerol (SNG) system. A method was developed utilizing Fourier Transform Infrared Spectroscopy which allows quantitative compositional analysis of directionally solidified SNG along the growth axis. To determine the influence of cellular growth front on alignment for directionally solidified monotectic alloys, the planar and cellular growth morphology was observed in-situ for SNG between 8 and 17 percent glycerol and for a range of over two orders of magnitude G/R.

Kinetic memory based on the enzyme-limited competition.

PubMed

Hatakeyama, Tetsuhiro S; Kaneko, Kunihiko

2014-08-01

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed, including dynamic modifications of calcium-calmodulin kinase II and cAMP-response element-binding protein essential for synaptic plasticity.

3D surface reconstruction and visualization of the Drosophila wing imaginal disc at cellular resolution

NASA Astrophysics Data System (ADS)

Bai, Linge; Widmann, Thomas; Jülicher, Frank; Dahmann, Christian; Breen, David

2013-01-01

Quantifying and visualizing the shape of developing biological tissues provide information about the morphogenetic processes in multicellular organisms. The size and shape of biological tissues depend on the number, size, shape, and arrangement of the constituting cells. To better understand the mechanisms that guide tissues into their final shape, it is important to investigate the cellular arrangement within tissues. Here we present a data processing pipeline to generate 3D volumetric surface models of epithelial tissues, as well as geometric descriptions of the tissues' apical cell cross-sections. The data processing pipeline includes image acquisition, editing, processing and analysis, 2D cell mesh generation, 3D contourbased surface reconstruction, cell mesh projection, followed by geometric calculations and color-based visualization of morphological parameters. In their first utilization we have applied these procedures to construct a 3D volumetric surface model at cellular resolution of the wing imaginal disc of Drosophila melanogaster. The ultimate goal of the reported effort is to produce tools for the creation of detailed 3D geometric models of the individual cells in epithelial tissues. To date, 3D volumetric surface models of the whole wing imaginal disc have been created, and the apicolateral cell boundaries have been identified, allowing for the calculation and visualization of cell parameters, e.g. apical cross-sectional area of cells. The calculation and visualization of morphological parameters show position-dependent patterns of cell shape in the wing imaginal disc. Our procedures should offer a general data processing pipeline for the construction of 3D volumetric surface models of a wide variety of epithelial tissues.

Application of Transfer Matrix Approach to Modeling and Decentralized Control of Lattice-Based Structures

NASA Technical Reports Server (NTRS)

Cramer, Nick; Swei, Sean Shan-Min; Cheung, Kenny; Teodorescu, Mircea

2015-01-01

This paper presents a modeling and control of aerostructure developed by lattice-based cellular materials/components. The proposed aerostructure concept leverages a building block strategy for lattice-based components which provide great adaptability to varying ight scenarios, the needs of which are essential for in- ight wing shaping control. A decentralized structural control design is proposed that utilizes discrete-time lumped mass transfer matrix method (DT-LM-TMM). The objective is to develop an e ective reduced order model through DT-LM-TMM that can be used to design a decentralized controller for the structural control of a wing. The proposed approach developed in this paper shows that, as far as the performance of overall structural system is concerned, the reduced order model can be as e ective as the full order model in designing an optimal stabilizing controller.

Changes in lipid membranes may trigger amyloid toxicity in Alzheimer's disease

PubMed Central

Drolle, Elizabeth; Negoda, Alexander; Hammond, Keely; Pavlov, Evgeny

2017-01-01

Amyloid-beta peptides (Aβ), implicated in Alzheimer’s disease (AD), interact with the cellular membrane and induce amyloid toxicity. The composition of cellular membranes changes in aging and AD. We designed multi-component lipid models to mimic healthy and diseased states of the neuronal membrane. Using atomic force microscopy (AFM), Kelvin probe force microscopy (KPFM) and black lipid membrane (BLM) techniques, we demonstrated that these model membranes differ in their nanoscale structure and physical properties, and interact differently with Aβ1–42. Based on our data, we propose a new hypothesis that changes in lipid membrane due to aging and AD may trigger amyloid toxicity through electrostatic mechanisms, similar to the accepted mechanism of antimicrobial peptide action. Understanding the role of the membrane changes as a key activating amyloid toxicity may aid in the development of a new avenue for the prevention and treatment of AD. PMID:28767712

Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

NASA Astrophysics Data System (ADS)

Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

2015-03-01

Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

Anomalous transport in cellular flows: The role of initial conditions and aging

NASA Astrophysics Data System (ADS)

Pöschke, Patrick; Sokolov, Igor M.; Nepomnyashchy, Alexander A.; Zaks, Michael A.

2016-09-01

We consider the diffusion-advection problem in two simple cellular flow models (often invoked as examples of subdiffusive tracer motion) and concentrate on the intermediate time range, in which the tracer motion indeed may show subdiffusion. We perform extensive numerical simulations of the systems under different initial conditions and show that the pure intermediate-time subdiffusion regime is only evident when the particles start at the border between different cells, i.e., at the separatrix, and is less pronounced or absent for other initial conditions. The motion moreover shows quite peculiar aging properties, which are also mirrored in the behavior of the time-averaged mean squared displacement for single trajectories. This kind of behavior is due to the complex motion of tracers trapped inside the cell and is absent in classical models based on continuous-time random walks with no dynamics in the trapped state.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Analysis And Augmentation Of Timing Advance Based Geolocation In Lte Cellular Networks

DTIC Science & Technology

2016-12-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA DISSERTATION ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCATION IN LTE CELLULAR NETWORKS by...estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the...AND SUBTITLE ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCA- TION IN LTE CELLULAR NETWORKS 5. FUNDING NUMBERS 6. AUTHOR(S) John D. Roth 7

Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja

Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features. These results show how the static landscape features can be controlled by adjusting the correlations between patterns. Finally, I explore the dynamical features of landscapes generated using neural network models such as the stability of minima and the transition rates between minima. The results from this project show that the stability depends on the correlations between patterns. It is also found that the transition rates between minima strongly depend on the type of bias applied and the correlation between patterns. The results from this part of the dissertation can be useful in engineering an energy landscape without even having the complete information about the associated minima of the landscape.

Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering.

PubMed

Ando, David; Garcia Martin, Hector

2018-01-01

Accelerating the Design-Build-Test-Learn (DBTL) cycle in synthetic biology is critical to achieving rapid and facile bioengineering of organisms for the production of, e.g., biofuels and other chemicals. The Learn phase involves using data obtained from the Test phase to inform the next Design phase. As part of the Learn phase, mathematical models of metabolic fluxes give a mechanistic level of comprehension to cellular metabolism, isolating the principle drivers of metabolic behavior from the peripheral ones, and directing future experimental designs and engineering methodologies. Furthermore, the measurement of intracellular metabolic fluxes is specifically noteworthy as providing a rapid and easy-to-understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis in the Learn phase of the DBTL cycle, where we show how one can take the isotope labeling data from a 13 C labeling experiment and immediately turn it into a determination of cellular fluxes that points in the direction of genetic engineering strategies that will advance the metabolic engineering process.For our modeling purposes we use the Joint BioEnergy Institute (JBEI) Quantitative Metabolic Modeling (jQMM) library, which provides an open-source, python-based framework for modeling internal metabolic fluxes and making actionable predictions on how to modify cellular metabolism for specific bioengineering goals. It presents a complete toolbox for performing different types of flux analysis such as Flux Balance Analysis, 13 C Metabolic Flux Analysis, and it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) [1]. In addition to several other capabilities, the jQMM is also able to predict the effects of knockouts using the MoMA and ROOM methodologies. The use of the jQMM library is illustrated through a step-by-step demonstration, which is also contained in a digital Jupyter Notebook format that enhances reproducibility and provides the capability to be adopted to the user's specific needs. As an open-source software project, users can modify and extend the code base and make improvements at will, providing a base for future modeling efforts.

Virtual tissues in toxicology.

PubMed

Shah, Imran; Wambaugh, John

2010-02-01

New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects across chemicals, dose, time, and species remains challenging. Technological advances in multiresolution imaging and multiscale simulation are making it feasible to reconstruct tissues in silico. In toxicology, these "virtual" tissues (VT) aim to predict histopathological outcomes from alterations of cellular phenotypes that are controlled by chemical-induced perturbations in molecular pathways. The behaviors of thousands of heterogeneous cells in tissues are simulated discretely using agent-based modeling (ABM), in which computational "agents" mimic cell interactions and cellular responses to the microenvironment. The behavior of agents is constrained by physical laws and biological rules derived from experimental evidence. VT extend compartmental physiologic models to simulate both acute insults as well as the chronic effects of low-dose exposure. Furthermore, agent behavior can encode the logic of signaling and genetic regulatory networks to evaluate the role of different pathways in chemical-induced injury. To extrapolate toxicity across species, chemicals, and doses, VT require four main components: (a) organization of prior knowledge on physiologic events to define the mechanistic rules for agent behavior, (b) knowledge on key chemical-induced molecular effects, including activation of stress sensors and changes in molecular pathways that alter the cellular phenotype, (c) multiresolution quantitative and qualitative analysis of histologic data to characterize and measure chemical-, dose-, and time-dependent physiologic events, and (d) multiscale, spatiotemporal simulation frameworks to effectively calibrate and evaluate VT using experimental data. This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis.

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches.

PubMed

Arazi, Arnon; Pendergraft, William F; Ribeiro, Ruy M; Perelson, Alan S; Hacohen, Nir

2013-10-31

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Physical model of protein cluster positioning in growing bacteria

NASA Astrophysics Data System (ADS)

Wasnik, Vaibhav; Wang, Hui; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2017-10-01

Chemotaxic receptors in bacteria form clusters at cell poles and also laterally, and this clustering plays an important role in signal transduction. These clusters were found to be periodically arranged on the surface of the bacterium Escherichia coli, independent of any known positioning mechanism. In this work we extend a model based on diffusion and aggregation to more realistic geometries and present a means based on ‘bursty’ protein production to distinguish spontaneous positioning from an independently existing positioning mechanism. We also consider the case of isotropic cellular growth and characterize the degree of order arising spontaneously. Our model could also be relevant for other examples of periodically positioned protein clusters in bacteria.