WorldWideScience

Sample records for evolving cell models

  1. Modelling cell motility and chemotaxis with evolving surface finite elements.

    Science.gov (United States)

    Elliott, Charles M; Stinner, Björn; Venkataraman, Chandrasekhar

    2012-11-07

    We present a mathematical and a computational framework for the modelling of cell motility. The cell membrane is represented by an evolving surface, with the movement of the cell determined by the interaction of various forces that act normal to the surface. We consider external forces such as those that may arise owing to inhomogeneities in the medium and a pressure that constrains the enclosed volume, as well as internal forces that arise from the reaction of the cells' surface to stretching and bending. We also consider a protrusive force associated with a reaction-diffusion system (RDS) posed on the cell membrane, with cell polarization modelled by this surface RDS. The computational method is based on an evolving surface finite-element method. The general method can account for the large deformations that arise in cell motility and allows the simulation of cell migration in three dimensions. We illustrate applications of the proposed modelling framework and numerical method by reporting on numerical simulations of a model for eukaryotic chemotaxis and a model for the persistent movement of keratocytes in two and three space dimensions. Movies of the simulated cells can be obtained from http://homepages.warwick.ac.uk/∼maskae/CV_Warwick/Chemotaxis.html.

  2. Marshal: Maintaining Evolving Models Project

    Data.gov (United States)

    National Aeronautics and Space Administration — SIFT proposes to design and develop the Marshal system, a mixed-initiative tool for maintaining task models over the course of evolving missions. Marshal-enabled...

  3. EVOLVE

    CERN Document Server

    Deutz, André; Schütze, Oliver; Legrand, Pierrick; Tantar, Emilia; Tantar, Alexandru-Adrian

    2017-01-01

    This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.

  4. Synthesis of Evolving Cells for Reconfigurable Manufacturing Systems

    Science.gov (United States)

    Padayachee, J.; Bright, G.

    2014-07-01

    The concept of Reconfigurable Manufacturing Systems (RMSs) was formulated due to the global necessity for production systems that are able to economically evolve according to changes in markets and products. Technologies and design methods are under development to enable RMSs to exhibit transformable system layouts, reconfigurable processes, cells and machines. Existing factory design methods and software have not yet advanced to include reconfigurable manufacturing concepts. This paper presents the underlying group technology framework for the design of manufacturing cells that are able to evolve according to a changing product mix by mechanisms of reconfiguration. The framework is based on a Norton- Bass forecast and time variant BOM models. An adaptation of legacy group technology methods is presented for the synthesis of evolving cells and two optimization problems are presented within this context.

  5. Mesenchymal stromal cells: misconceptions and evolving concepts.

    Science.gov (United States)

    Phinney, Donald G; Sensebé, Luc

    2013-02-01

    Nearly half a century has passed since the publication of the first articles describing plastic-adherent cells from bone marrow, referred to initially as colony-forming unit fibroblasts, then marrow stromal cells, mesenchymal stem cells and most recently multipotent mesenchymal stromal cells (MSCs). As expected, our understanding of the nature and biologic functions of MSCs has undergone major paradigm shifts over this time. Despite significant advances made in deciphering their complex biology and therapeutic potential in both experimental animal models and human clinical trials, numerous misconceptions regarding the nature and function of MSCs have persisted in the field. Continued propagation of these misconceptions in some cases may significantly impede the advancement of MSC-based therapies in clinical medicine. We have identified six prevalent misconceptions about MSCs that we believe affect the field, and we attempt to rectify them based on current available data. Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  6. A local-world evolving hypernetwork model

    Science.gov (United States)

    Yang, Guang-Yong; Liu, Jian-Guo

    2014-01-01

    Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mechanisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is γ = 2 + 1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypernetwork model shares the scale-free and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems.

  7. An evolving model of online bipartite networks

    Science.gov (United States)

    Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang

    2013-12-01

    Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.

  8. How the social model of disability evolved.

    Science.gov (United States)

    Durell, Shirley

    The way nurses conceptualise disability influences their practice. Many use an individualised model, seeing disability as an individual problem arising from activity restriction and psychological loss. However, many disabled people are critical of this approach and instead promote a social way of thinking about disability. This article presents an overview of the individual and social models of disability so nurses can increase their understanding of these approaches.

  9. Modeling promoter grammars with evolving hidden Markov models

    DEFF Research Database (Denmark)

    Won, Kyoung-Jae; Sandelin, Albin; Marstrand, Troels Torben

    2008-01-01

    factors are involved in the regulation of a set of co-regulated genes. If so, promoters can be modeled with connected regulatory features, where the network of connections is characteristic for a particular mode of regulation. RESULTS: With the goal of automatically deciphering such regulatory structures......MOTIVATION: Describing and modeling biological features of eukaryotic promoters remains an important and challenging problem within computational biology. The promoters of higher eukaryotes in particular display a wide variation in regulatory features, which are difficult to model. Often several......, we present a method that iteratively evolves an ensemble of regulatory grammars using a hidden Markov Model (HMM) architecture composed of interconnected blocks representing transcription factor binding sites (TFBSs) and background regions of promoter sequences. The ensemble approach reduces the risk...

  10. Modeling and Understanding Time-Evolving Scenarios

    Directory of Open Access Journals (Sweden)

    Riccardo Melen

    2015-08-01

    Full Text Available In this paper, we consider the problem of modeling application scenarios characterized by variability over time and involving heterogeneous kinds of knowledge. The evolution of distributed technologies creates new and challenging possibilities of integrating different kinds of problem solving methods, obtaining many benefits from the user point of view. In particular, we propose here a multilayer modeling system and adopt the Knowledge Artifact concept to tie together statistical and Artificial Intelligence rule-based methods to tackle problems in ubiquitous and distributed scenarios.

  11. Conceptualizing Evolving Models of Educational Development

    Science.gov (United States)

    Fraser, Kym; Gosling, David; Sorcinelli, Mary Deane

    2010-01-01

    Educational development, which the authors use to refer to the field of professional and strategic development associated with university and college learning and teaching, can be described in many ways by referring to its different aspects. In this article the authors endeavor to categorize many of the models that have been used to describe…

  12. Evolving the structure of hidden Markov Models

    DEFF Research Database (Denmark)

    won, K. J.; Prugel-Bennett, A.; Krogh, A.

    2006-01-01

    A genetic algorithm (GA) is proposed for finding the structure of hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimization of the emission...

  13. Modeling and clustering users with evolving profiles in usage streams

    KAUST Repository

    Zhang, Chongsheng

    2012-09-01

    Today, there is an increasing need of data stream mining technology to discover important patterns on the fly. Existing data stream models and algorithms commonly assume that users\\' records or profiles in data streams will not be updated or revised once they arrive. Nevertheless, in various applications such asWeb usage, the records/profiles of the users can evolve along time. This kind of streaming data evolves in two forms, the streaming of tuples or transactions as in the case of traditional data streams, and more importantly, the evolving of user records/profiles inside the streams. Such data streams bring difficulties on modeling and clustering for exploring users\\' behaviors. In this paper, we propose three models to summarize this kind of data streams, which are the batch model, the Evolving Objects (EO) model and the Dynamic Data Stream (DDS) model. Through creating, updating and deleting user profiles, these models summarize the behaviors of each user as a profile object. Based upon these models, clustering algorithms are employed to discover interesting user groups from the profile objects. We have evaluated all the proposed models on a large real-world data set, showing that the DDS model summarizes the data streams with evolving tuples more efficiently and effectively, and provides better basis for clustering users than the other two models. © 2012 IEEE.

  14. Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism: network models, novel therapeutic target strategies, and the contributions of hypoxia, inflammation and cellular senescence.

    Science.gov (United States)

    Csermely, Peter; Hódsági, János; Korcsmáros, Tamás; Módos, Dezső; Perez-Lopez, Áron R; Szalay, Kristóf; Veres, Dániel V; Lenti, Katalin; Wu, Ling-Yun; Zhang, Xiang-Sun

    2015-02-01

    Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of plasticity at late stages of tumor development. The fluctuating intensity of stress factors, like hypoxia, inflammation and the either cooperative or hostile interactions of tumor inter-cellular networks, all increase the adaptation potential of cancer cells. This may lead to the bypass of cellular senescence, and to the development of cancer stem cells. We propose that the central tenet of cancer stem cell definition lies exactly in the indefinability of cancer stem cells. Actual properties of cancer stem cells depend on the individual "stress-history" of the given tumor. Cancer stem cells are characterized by an extremely large evolvability (i.e. a capacity to generate heritable phenotypic variation), which corresponds well with the defining hallmarks of cancer stem cells: the possession of the capacity to self-renew and to repeatedly re-build the heterogeneous lineages of cancer cells that comprise a tumor in new environments. Cancer stem cells represent a cell population, which is adapted to adapt. We argue that the high evolvability of cancer stem cells is helped by their repeated transitions between plastic (proliferative, symmetrically dividing) and rigid (quiescent, asymmetrically dividing, often more invasive) phenotypes having plastic and rigid networks. Thus, cancer stem cells reverse and replay cancer development multiple times. We describe network models potentially explaining cancer stem cell-like behavior. Finally, we propose novel strategies including combination therapies and multi-target drugs to overcome the Nietzschean dilemma of cancer stem cell targeting: "what does not kill me makes me stronger". Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Exploring, exploiting and evolving diversity of aquatic ecosystem models

    DEFF Research Database (Denmark)

    Janssen, Annette B. G.; Arhonditsis, George B.; Beusen, Arthur

    2015-01-01

    Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality...... management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity...... by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly...

  16. Cancer stem cells: constantly evolving and functionally heterogeneous therapeutic targets.

    Science.gov (United States)

    Yang, Tao; Rycaj, Kiera; Liu, Zhong-Min; Tang, Dean G

    2014-06-01

    Elucidating the origin of and dynamic interrelationship between intratumoral cell subpopulations has clear clinical significance in helping to understand the cellular basis of treatment response, therapeutic resistance, and tumor relapse. Cancer stem cells (CSC), together with clonal evolution driven by genetic alterations, generate cancer cell heterogeneity commonly observed in clinical samples. The 2013 Shanghai International Symposium on Cancer Stem Cells brought together leaders in the field to highlight the most recent progress in phenotyping, characterizing, and targeting CSCs and in elucidating the relationship between the cell-of-origin of cancer and CSCs. Discussions from the symposium emphasize the urgent need in developing novel therapeutics to target the constantly evolving CSCs. ©2014 American Association for Cancer Research.

  17. Exploring, exploiting and evolving diversity of aquatic ecosystem models

    NARCIS (Netherlands)

    Janssen, A.B.G.; Arhonditsis, G.B.; Beusen, Arthur; Bolding, Karsten; Bruce, Louise; Bruggeman, Jorn; Couture, Raoul Marie; Downing, Andrea S.; Alex Elliott, J.; Frassl, M.A.; Gal, Gideon; Gerla, Daan J.; Hipsey, M.R.; Hu, Fenjuan; Ives, S.C.; Janse, J.H.; Jeppesen, Erik; Jöhnk, K.D.; Kneis, David; Kong, Xiangzhen; Kuiper, J.J.; Lehmann, M.K.; Lemmen, Carsten; Özkundakci, Deniz; Petzoldt, Thomas; Rinke, Karsten; Robson, B.J.; Sachse, René; Schep, S.A.; Schmid, Martin; Scholten, Huub; Teurlincx, Sven; Trolle, Dennis; Troost, T.A.; Dam, Van A.A.; Gerven, Van L.P.A.; Weijerman, Mariska; Wells, S.A.; Mooij, W.M.

    2015-01-01

    Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality

  18. Extracellular Vesicles: Evolving Factors in Stem Cell Biology

    Directory of Open Access Journals (Sweden)

    Muhammad Nawaz

    2016-01-01

    Full Text Available Stem cells are proposed to continuously secrete trophic factors that potentially serve as mediators of autocrine and paracrine activities, associated with reprogramming of the tumor microenvironment, tissue regeneration, and repair. Hitherto, significant efforts have been made to understand the level of underlying paracrine activities influenced by stem cell secreted trophic factors, as little is known about these interactions. Recent findings, however, elucidate this role by reporting the effects of stem cell derived extracellular vesicles (EVs that mimic the phenotypes of the cells from which they originate. Exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell-EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations. This review therefore discusses stem cell-EVs as evolving communication factors in stem cell biology, focusing on how they regulate cell fates by inducing persistent and prolonged genetic reprogramming of resident cells in a paracrine fashion. In addition, we address the role of stem cell-secreted vesicles in shaping the tumor microenvironment and immunomodulation and in their ability to stimulate endogenous repair processes during tissue damage. Collectively, these functions ensure an enormous potential for future therapies.

  19. Extracellular Vesicles: Evolving Factors in Stem Cell Biology

    Science.gov (United States)

    Nawaz, Muhammad; Fatima, Farah; Vallabhaneni, Krishna C.; Penfornis, Patrice; Valadi, Hadi; Ekström, Karin; Kholia, Sharad; Whitt, Jason D.; Fernandes, Joseph D.; Pochampally, Radhika; Squire, Jeremy A.; Camussi, Giovanni

    2016-01-01

    Stem cells are proposed to continuously secrete trophic factors that potentially serve as mediators of autocrine and paracrine activities, associated with reprogramming of the tumor microenvironment, tissue regeneration, and repair. Hitherto, significant efforts have been made to understand the level of underlying paracrine activities influenced by stem cell secreted trophic factors, as little is known about these interactions. Recent findings, however, elucidate this role by reporting the effects of stem cell derived extracellular vesicles (EVs) that mimic the phenotypes of the cells from which they originate. Exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell-EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations. This review therefore discusses stem cell-EVs as evolving communication factors in stem cell biology, focusing on how they regulate cell fates by inducing persistent and prolonged genetic reprogramming of resident cells in a paracrine fashion. In addition, we address the role of stem cell-secreted vesicles in shaping the tumor microenvironment and immunomodulation and in their ability to stimulate endogenous repair processes during tissue damage. Collectively, these functions ensure an enormous potential for future therapies. PMID:26649044

  20. AUTOMOTIVE APPLICATIONS OF EVOLVING TAKAGI-SUGENO-KANG FUZZY MODELS

    Directory of Open Access Journals (Sweden)

    Radu-Emil Precup

    2017-08-01

    Full Text Available This paper presents theoretical and application results concerning the development of evolving Takagi-Sugeno-Kang fuzzy models for two dynamic systems, which will be viewed as controlled processes, in the field of automotive applications. The two dynamic systems models are nonlinear dynamics of the longitudinal slip in the Anti-lock Braking Systems (ABS and the vehicle speed in vehicles with the Continuously Variable Transmission (CVT systems. The evolving Takagi-Sugeno-Kang fuzzy models are obtained as discrete-time fuzzy models by incremental online identification algorithms. The fuzzy models are validated against experimental results in the case of the ABS and the first principles simulation results in the case of the vehicle with the CVT.

  1. The evolving cancer stem cell paradigm: implications in veterinary oncology.

    Science.gov (United States)

    Pang, Lisa Y; Argyle, David J

    2015-08-01

    The existence of subpopulations of cells in cancer with increased tumour-initiating ability, self-renewal potential, and intrinsic resistance to conventional therapeutics formed the basis of the cancer stem cell model. Some tumours have since been viewed as aberrant tissues with a unidirectional hierarchical structure consisting of cancer stem cells at the apex, driving tumour growth, metastasis and relapse after therapy. Here, recent developments in cancer stem cell research are reviewed with a focus on tumour heterogeneity, cellular plasticity and cancer stem cell reprogramming. The impact of these findings on the cancer stem cell model is discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Evolvable mathematical models: A new artificial Intelligence paradigm

    Science.gov (United States)

    Grouchy, Paul

    We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

  3. Evolving Microbial Communities in Cellulose-Fed Microbial Fuel Cell

    Directory of Open Access Journals (Sweden)

    Renata Toczyłowska-Mamińska

    2018-01-01

    Full Text Available The abundance of cellulosic wastes make them attractive source of energy for producing electricity in microbial fuel cells (MFCs. However, electricity production from cellulose requires obligate anaerobes that can degrade cellulose and transfer electrons to the electrode (exoelectrogens, and thus most previous MFC studies have been conducted using two-chamber systems to avoid oxygen contamination of the anode. Single-chamber, air-cathode MFCs typically produce higher power densities than aqueous catholyte MFCs and avoid energy input for the cathodic reaction. To better understand the bacterial communities that evolve in single-chamber air-cathode MFCs fed cellulose, we examined the changes in the bacterial consortium in an MFC fed cellulose over time. The most predominant bacteria shown to be capable electron generation was Firmicutes, with the fermenters decomposing cellulose Bacteroidetes. The main genera developed after extended operation of the cellulose-fed MFC were cellulolytic strains, fermenters and electrogens that included: Parabacteroides, Proteiniphilum, Catonella and Clostridium. These results demonstrate that different communities evolve in air-cathode MFCs fed cellulose than the previous two-chamber reactors.

  4. Evolving Concepts and Translational Relevance of Enteroendocrine Cell Biology.

    Science.gov (United States)

    Drucker, Daniel J

    2016-03-01

    Classical enteroenteroendocrine cell (EEC) biology evolved historically from identification of scattered hormone-producing endocrine cells within the epithelial mucosa of the stomach, small and large intestine. Purification of functional EEC hormones from intestinal extracts, coupled with molecular cloning of cDNAs and genes expressed within EECs has greatly expanded the complexity of EEC endocrinology, with implications for understanding the contribution of EECs to disease pathophysiology. Pubmed searches identified manuscripts highlighting new concepts illuminating the molecular biology, classification and functional role(s) of EECs and their hormonal products. Molecular interrogation of EECs has been transformed over the past decade, raising multiple new questions that challenge historical concepts of EEC biology. Evidence for evolution of the EEC from a unihormonal cell type with classical endocrine actions, to a complex plurihormonal dynamic cell with pleiotropic interactive functional networks within the gastrointestinal mucosa is critically assessed. We discuss gaps in understanding how EECs sense and respond to nutrients, cytokines, toxins, pathogens, the microbiota, and the microbial metabolome, and highlight the expanding translational relevance of EECs in the pathophysiology and therapy of metabolic and inflammatory disorders. The EEC system represents the largest specialized endocrine network in human physiology, integrating environmental and nutrient cues, enabling neural and hormonal control of metabolic homeostasis. Updating EEC classification systems will enable more accurate comparative analyses of EEC subpopulations and endocrine networks in multiple regions of the gastrointestinal tract.

  5. Duplication Detection When Evolving Feature Models of Software Product Lines

    Directory of Open Access Journals (Sweden)

    Amal Khtira

    2015-10-01

    Full Text Available After the derivation of specific applications from a software product line, the applications keep evolving with respect to new customer’s requirements. In general, evolutions in most industrial projects are expressed using natural language, because it is the easiest and the most flexible way for customers to express their needs. However, the use of this means of communication has shown its limits in detecting defects, such as inconsistency and duplication, when evolving the existing models of the software product line. The aim of this paper is to transform the natural language specifications of new evolutions into a more formal representation using natural language processing. Then, an algorithm is proposed to automatically detect duplication between these specifications and the existing product line feature models. In order to instantiate the proposed solution, a tool is developed to automatize the two operations.

  6. A weighted network evolving model with capacity constraints

    Science.gov (United States)

    Wu, XiaoHuan; Zhu, JinFu; Wu, WeiWei; Ge, Wei

    2013-09-01

    Most of existing works on complex network assumed that the nodes and edges were uncapacitated during the evolving process, and displayed "rich club" phenomenon. Here we will show that the "rich club" could be changed to "common rich" if we consider the node capacity. In this paper, we define the node and edge attractive index with node capacity, and propose a new evolving model on the base of BBV model, with evolving simulations of the networks. In the new model, an entering node is linked with an existing node according to the preferential attachment mechanism defined with the attractive index of the existing node. We give the theoretical approximation and simulation solutions. If node capacity is finite, the rich node may not be richer further when the node strength approaches or gets to the node capacity. This is confirmed by analyzing the passenger traffic and routes of Chinese main airports. Due to node strength being function of time t, we can use the theoretical approximation solution to forecast how node strength changes and the time when node strength reaches its maximum value.

  7. Evolving Four Part Harmony Using a Multiple Worlds Model

    DEFF Research Database (Denmark)

    Scirea, Marco; Brown, Joseph Alexander

    2015-01-01

    This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...... populations. We present the result of two experiments: the generation of compositions, given a static voice line, both in a constrained and unconstrained harmonic framework. The remaining three voices are evolved using this collaborative fitness function, which looks for a number of classical composition...

  8. Modeling the Chinese language as an evolving network

    Science.gov (United States)

    Liang, Wei; Shi, Yuming; Huang, Qiuling

    2014-01-01

    The evolution of Chinese language has three main features: the total number of characters is gradually increasing, new words are generated in the existing characters, and some old words are no longer used in daily-life language. Based on the features, we propose an evolving language network model. Finally, we use this model to simulate the character co-occurrence networks (nodes are characters, and two characters are connected by an edge if they are adjacent to each other) constructed from essays in 11 different periods of China, and find that characters that appear with high frequency in old words are likely to be reused when new words are formed.

  9. Evolving the Topology of Hidden Markov Models using Evolutionary Algorithms

    DEFF Research Database (Denmark)

    Thomsen, Réne

    2002-01-01

    Hidden Markov models (HMM) are widely used for speech recognition and have recently gained a lot of attention in the bioinformatics community, because of their ability to capture the information buried in biological sequences. Usually, heuristic algorithms such as Baum-Welch are used to estimate...... the model parameters. However, Baum-Welch has a tendency to stagnate on local optima. Furthermore, designing an optimal HMM topology usually requires a priori knowledge from a field expert and is usually found by trial-and-error. In this study, we present an evolutionary algorithm capable of evolving both...... the topology and the model parameters of HMMs. The applicability of the method is exemplified on a secondary structure prediction problem....

  10. How germinal centers evolve broadly neutralizing antibodies: the breadth of the follicular helper T cell response.

    Science.gov (United States)

    De Boer, Rob J; Perelson, Alan S

    2017-09-06

    Many HIV-1 infected patients evolve broadly neutralizing antibodies (bnAbs). This evolutionary process typically takes several years, and is poorly understood as selection taking place in germinal centers occurs on the basis of antibody affinity. B cells with the highest affinity receptors tend to acquire the most antigen from the FDC network, and present the highest density of cognate peptides to follicular helper T cells (Tfh), which provide survival signals to the B cell. BnAbs are therefore only expected to evolve when the B cell lineage evolving breadth is consistently capturing and presenting more peptides to Tfh cells than other lineages of more specific B cells. Here we develop mathematical models of Tfh in germinal centers to explicitly define the mechanisms of selection in this complex evolutionary process.Our results suggest that broadly reactive B cells presenting a high density of pMHC are readily outcompeted by B cells responding to lineages of HIV-1 that transiently dominate the within host viral population. Conversely, if broadly reactive B cells acquire a large variety of several HIV-1 proteins from the FDC network and present a high diversity of several pMHC, they be rescued by a large fraction of the Tfh repertoire in the germinal center. Under such circumstances the evolution of bnAbs is much more consistent. Increasing the magnitude of the Tfh response, or the breadth of the Tfh repertoire, both markedly facilitate the evolution of bnAbs. Because both can be increased by vaccination with several HIV-1 proteins, this calls for experiments testing.Importance Many HIV-infected patients slowly evolve antibodies that can neutralize a large variety of viruses. Such "broadly neutralizing antibodies" (bnAbs) could in the future become therapeutic agents. BnAbs appear very late and patients are typically not protected by them. At the moment we fail to understand why this takes so long, and how the immune system selects for broadly neutralizing capacity

  11. Beyond expressive writing: evolving models of developmental creative writing.

    Science.gov (United States)

    Nicholls, Sophie

    2009-03-01

    Pennebaker's expressive writing paradigm has helped to introduce the benefits of writing to health care. However, research in expressive writing has been largely dominated by an experimental and quantitative approach that does not take into account critical methodologies and approaches in health psychology, the increasingly complex ways in which creative writing is now being used in health care settings or recent research in the broader field of creative writing and personal development, health and well-being (developmental creative writing). This article contrasts expressive writing theories and methodologies with those evolving in the relatively new field of developmental creative writing. It investigates a number of theoretical and methodological problems with the expressive writing model and argues for a more critical approach to future research.

  12. A Markovian model of evolving world input-output network.

    Science.gov (United States)

    Moosavi, Vahid; Isacchini, Giulio

    2017-01-01

    The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

  13. The Evolving Roles of Memory Immune Cells in Transplantation.

    Science.gov (United States)

    Chen, Wenhao; Ghobrial, Rafik M; Li, Xian C

    2015-10-01

    Memory cells are the products of immune responses but also exert significant impact on subsequent immunity and immune tolerance, thus placing them in a unique position in transplant research. Memory cells are heterogeneous, including not only memory T cells but also memory B cells and innate memory cells. Memory cells are a critical component of protective immunity against invading pathogens, especially in immunosuppressed patients, but they also mediate graft loss and tolerance resistance. Recent studies suggest that some memory cells unexpectedly act as regulatory cells, promoting rather than hindering transplant survival. This functional diversity makes therapeutic targeting of memory cells a challenging task in transplantation. In this article, we highlight recent advances in our understanding of memory cells, focusing on diversity of memory cells and mechanisms involved in their induction and functions. We also provide a broad overview on the challenges and opportunities in targeting memory cells in the induction of transplant tolerance.

  14. Evolving Function and Potential of Pancreatic Alpha Cells

    Science.gov (United States)

    Stanojevic, Violeta; Habener, Joel F.

    2015-01-01

    The alpha cells that co-occupy the islets in association with beta cells have been long recognized as the source of glucagon, a hyperglycemia-producing and diabetogenic hormone. Although the mechanisms that control the functions of alpha cells, glucagon secretion, and the role of glucagon in diabetes have remained somewhat enigmatic over the fifty years since their discovery, seminal findings during the past few years have moved alpha cells into the spotlight of scientific discovery. These findings obtained largely from studies in mice are: Alpha cells have the capacity to trans-differentiate into insulin-producing beta cells. Alpha cells contain a GLP-1 generating system that produces GLP-1 locally for paracrine actions within the islets that likely promotes beta cell growth and survival and maintains beta cell mass. Impairment of glucagon signaling both prevents the occurrence of diabetes in conditions of the near absence of insulin and expands alpha cell mass. Alpha cells appear to serve as helper cells or guardians of beta cells to ensure their health and well-being. Of potential relevance to the possibility of promoting the transformation of alpha to beta cells is the observation that impairment of glucagon signaling leads to a marked increase in alpha cell mass in the islets. Such alpha cell hyperplasia provides an increased supply of alpha cells for their transdifferentiation into new beta cells. In this review we discuss these recent discoveries from the perspective of their potential relevance to the treatment of diabetes. PMID:26696515

  15. Effects of evolving quality of landfill leachate on microbial fuel cell performance.

    Science.gov (United States)

    Li, Simeng; Chen, Gang

    2018-01-01

    Microbial fuel cell (MFC) is a novel technology for landfill leachate treatment with simultaneous electric power generation. In recent years, more and more modern landfills are operating as bioreactors to shorten the time required for landfill stabilization and improve the leachate quality. For landfills to operate as biofilters, leachate is recirculated back to the landfill, during which time the organics of the leachate can be decomposed. Continuous recirculation typically results in evolving leachate quality, which chronologically corresponds to evolution stages such as hydrolysis, acidogenesis, acetogenesis, methanogenesis, and maturation. In this research, variable power generation (160 to 230 mW m-2) by MFC was observed when leachate of various evolutionary stages was used as the feed. The power density followed a Monod-type kinetic model with the chemical oxygen demand (COD) equivalent of the volatile fatty acids (VFAs) ( p < 0.001). The coulombic efficiency decreased from 20% to 14% as the leachate evolved towards maturation. The maximum power density linearly decreased with the increase of internal resistance, resulting from the change of the conductivity of the solution. The decreased conductivity boosted the internal resistance and consequently limited the power generation. COD removal as high as 90% could be achieved with leachate extracted from appropriate evolutionary stages, with a maximum energy yield of 0.9 kWh m-3 of leachate. This study demonstrated the importance of the evolving leachate quality in different evolutionary stages for the performance of leachate-fed MFCs. The leachate extracted from acidogenesis and acetogenesis were optimal for both COD reduction and energy production in MFCs.

  16. Genetic programming for evolving due-date assignment models in job shop environments.

    Science.gov (United States)

    Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

    2014-01-01

    Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

  17. [Evolvement of ecological footprint model representing ecological carrying capacity].

    Science.gov (United States)

    Cao, Shu-yan; Xie, Gao-di

    2007-06-01

    Ecological footprint (EF) is an important index of ecological carrying capacity. The original EF model is excellent in simplicity, aggregation, comparability, and lifelikeness in presenting results, but short in predictability, configuration, and applicability. To overcome these shortcomings, many researches were conducted to modify and promote the EF model, and developed it from static with single time scale to diversified ones, which included: 1) time series EF model, 2) input-output analysis based EF model, 3) integrated assessment incorporated EF model, 4) land disturbance degree based EF model, and 5) life cycle analysis based EF model, or component EF model. The function of EF as a measurement of ecological carrying capacity was significantly improved, but its accuracy and integrality still need to be advanced.

  18. Bayesian Mixed-Membership Models of Complex and Evolving Networks

    Science.gov (United States)

    2006-12-01

    are based on the stochastic block model (SBM) formalism for psychometric and sociological analysis pioneered 71 3.1. ADMIXTURE OF LATENT BLOCKS MODEL... Biotechnology , 23:1562–1567, 2005. T. Van Zandt. Decentralized information processing in the theory of organizations. In M. Ser- tel, editor, Contemporary

  19. Model for the Evolving Bed Surface around an Offshore Monopile

    DEFF Research Database (Denmark)

    Hartvig, Peres Akrawi

    2012-01-01

    This paper presents a model for the bed surface around an offshore monopile. The model has been designed from measured laboratory bed surfaces and is shown to reproduce these satisfactorily for both scouring and backfilling. The local rate of the bed elevation is assumed to satisfy a certain gene...

  20. An Evolving Asymmetric Game for Modeling Interdictor-Smuggler Problems

    Science.gov (United States)

    2016-06-01

    3–30. Morton D, Pan F, Saeger K (2007) Models for nuclear smuggling interdiction. IIE Transactions . 39(1): 3–14. Nehme M (2009) Two-person games...Twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Transactions on Modeling and Computer Simulation (TOMACS) 8(1

  1. Challenges for fuel cells as stationary power resource in the evolving energy enterprise

    Science.gov (United States)

    Rastler, Dan

    The primary market challenges for fuel cells as stationary power resources in evolving energy markets are reviewed. Fuel cell power systems have significant barriers to overcome in their anticipated role as decentralized energy power systems. Market segments for fuel cells include combined heat and power; low-cost energy, premium power; peak shaving; and load management and grid support. Understanding the role and fit of fuel cell systems in evolving energy markets and the highest value applications are a major challenge for developers and government funding organizations. The most likely adopters of fuel cell systems and the challenges facing each adopter in the target market segment are reviewed. Adopters include generation companies, utility distribution companies, retail energy service providers and end-users. Key challenges include: overcoming technology risk; achieving retail competitiveness; understanding high value markets and end-user needs; distribution and service channels; regulatory policy issues; and the integration of these decentralized resources within the electrical distribution system.

  2. Our evolving conceptual model of the coastal eutrophication problem

    Science.gov (United States)

    Cloern, James E.

    2001-01-01

    A primary focus of coastal science during the past 3 decades has been the question: How does anthropogenic nutrient enrichment cause change in the structure or function of nearshore coastal ecosystems? This theme of environmental science is recent, so our conceptual model of the coastal eutrophication problem continues to change rapidly. In this review, I suggest that the early (Phase I) conceptual model was strongly influenced by limnologists, who began intense study of lake eutrophication by the 1960s. The Phase I model emphasized changing nutrient input as a signal, and responses to that signal as increased phytoplankton biomass and primary production, decomposition of phytoplankton-derived organic matter, and enhanced depletion of oxygen from bottom waters. Coastal research in recent decades has identified key differences in the responses of lakes and coastal-estuarine ecosystems to nutrient enrichment. The contemporary (Phase II) conceptual model reflects those differences and includes explicit recognition of (1) system-specific attributes that act as a filter to modulate the responses to enrichment (leading to large differences among estuarine-coastal systems in their sensitivity to nutrient enrichment); and (2) a complex suite of direct and indirect responses including linked changes in: water transparency, distribution of vascular plants and biomass of macroalgae, sediment biogeochemistry and nutrient cycling, nutrient ratios and their regulation of phytoplankton community composition, frequency of toxic/harmful algal blooms, habitat quality for metazoans, reproduction/growth/survival of pelagic and benthic invertebrates, and subtle changes such as shifts in the seasonality of ecosystem functions. Each aspect of the Phase II model is illustrated here with examples from coastal ecosystems around the world. In the last section of this review I present one vision of the next (Phase III) stage in the evolution of our conceptual model, organized around 5

  3. Low-complexity stochastic modeling of spatially evolving flows

    Science.gov (United States)

    Zare, Armin; Ran, Wei; Hack, M. J. Philipp; Jovanovic, Mihailo

    2016-11-01

    Low-complexity approximations of the Navier-Stokes (NS) equations are commonly used for analysis and control of turbulent flows. In particular, stochastically-forced linearized models have been successfully employed to capture structural and statistical features observed in experiments and direct simulations. In this work, we utilize stochastically-forced linearized NS equations and their parabolized equivalents to study the dynamics of flow fluctuations in transitional and turbulent boundary layers. We exploit the streamwise causality of the parabolized model to efficiently propagate statistics of stochastic disturbances into statistics of velocity fluctuations. Our study provides insight into interactions of slowly-varying base flow with streamwise streaks, oblique modes, and Tollmien-Schlichting waves. It also offers a systematic, computationally efficient framework for quantifying the influence of stochastic excitation sources (e.g., free-stream turbulence and surface roughness) on velocity fluctuations in weakly non-parallel flows.

  4. An Evolving Model for Capacity Building with Earth Observation Imagery

    Science.gov (United States)

    Sylak-Glassman, E. J.

    2015-12-01

    For the first forty years of Earth observation satellite imagery, all imagery was collected by civilian or military governmental satellites. Over this timeframe, countries without observation satellite capabilities had very limited access to Earth observation data or imagery. In response to the limited access to Earth observation systems, capacity building efforts were focused on satellite manufacturing. Wood and Weigel (2012) describe the evolution of satellite programs in developing countries with a technology ladder. A country moves up the ladder as they move from producing satellites with training services to building satellites locally. While the ladder model may be appropriate if the goal is to develop autonomous satellite manufacturing capability, in the realm of Earth observation, the goal is generally to derive societal benefit from the use of Earth observation-derived information. In this case, the model for developing Earth observation capacity is more appropriately described by a hub-and-spoke model in which the use of Earth observation imagery is the "hub," and the "spokes" describe the various paths to achieving that imagery: the building of a satellite (either independently or with assistance), the purchase of a satellite, participation in a constellation of satellites, and the use of freely available or purchased satellite imagery. We discuss the different capacity-building activities that are conducted in each of these pathways, such as the "Know-How Transfer and Training" program developed by Surrey Satellite Technology Ltd. , Earth observation imagery training courses run by SERVIR in developing countries, and the use of national or regional remote sensing centers (such as those in Morocco, Malaysia, and Kenya) to disseminate imagery and training. In addition, we explore the factors that determine through which "spoke" a country arrives at the ability to use Earth observation imagery, and discuss best practices for achieving the capability to use

  5. Clinical coaching: Evolving the apprenticeship model for modern housestaff.

    Science.gov (United States)

    Rangachari, Deepa; Brown, Lorrel E; Kern, David E; Melia, Michael T

    2017-07-01

    Feedback is one of the core components of teaching in the clinical setting. Traditionally, this activity has emphasized observations made by senior physicians and delivered to medical trainees. However, the optimal approach to feedback remains uncertain, and the literature abounds with trainee-perceived inadequacies in feedback content, quality, and impact. Moreover, given the multiplicity of demands on trainees and their physician mentors, we propose that medical trainees themselves-specifically, medical residents-are poised to serve as unique adjunct effectors of feedback. We propose a model of "clinical coaching" for residents as teachers, with emphasis on the active roles of both the feedback "giver" and "recipient". We define "clinical coaching" as "a helping longitudinal relationship between coach and apprentice that provides continuing feedback on and assistance with improving performance." Here, "coach" is the more experienced trainee (e.g. supervising resident), and "apprentice" is the less experienced trainee (e.g. intern or medical student). By working to better recognize and prepare residents for this vital role, we propose to encourage efforts to optimize the structure, execution, and impact of feedback in the contemporary climate of medical education.

  6. Empirical Models of Social Learning in a Large, Evolving Network.

    Directory of Open Access Journals (Sweden)

    Ayşe Başar Bener

    Full Text Available This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1 attraction homophily causes individuals to form ties on the basis of attribute similarity, 2 aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3 social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  7. A quantum Bose-Hubbard model with evolving graph as toy model for emergent spacetime

    CERN Document Server

    Hamma, Alioscia; Lloyd, Seth; Caravelli, Francesco; Severini, Simone; Markstrom, Klas

    2009-01-01

    We present a toy model for interacting matter and geometry that explores quantum dynamics in a spin system as a precursor to a quantum theory of gravity. The model has no a priori geometric properties, instead, locality is inferred from the more fundamental notion of interaction between the matter degrees of freedom. The interaction terms are themselves quantum degrees of freedom so that the structure of interactions and hence the resulting local and causal structures are dynamical. The system is a Hubbard model where the graph of the interactions is a set of quantum evolving variables. We show entanglement between spatial and matter degrees of freedom. We study numerically the quantum system and analyze its entanglement dynamics. We analyze the asymptotic behavior of the classical model. Finally, we discuss analogues of trapped surfaces and gravitational attraction in this simple model.

  8. Analysing an Evolved Robotic Behaviour Using a Biological Model of Collegial Decision Making.

    OpenAIRE

    Francesca, Gianpiero; Brambilla, Manuele; Trianni, Vito; Dorigo, Marco; BIRATTARI, Mauro

    2012-01-01

    Evolutionary robotics can be a powerful tool in studies on the evolutionary origins of self-organising behaviours in biological systems. However, these studies are viable only when the behaviour of the evolved artificial system closely corresponds to the one observed in biology, as described by available models. In this paper, we compare the behaviour evolved in a robotic system with the collegial decision making displayed by cockroaches in selecting a resting shelter. We show that artificial...

  9. An evolving experience learned for modelling thermal dynamics of buildings from live experiments: the Flexhouse story

    DEFF Research Database (Denmark)

    Yu, Xingji; You, Shi; Jiang, Yuewen

    2017-01-01

    Abstract This paper shares an evolving experience learned for modelling the thermal dynamics of buildings from live experiments run in Flexhouse1 at Risø Campus of Technical University of Denmark (DTU). Among different trials, circuit based grey-box models approach have been developed and improved...... from time to time. Although the intension of modelling the thermal dynamics of Flexhouse1 remains unchanged, the details of experiments and applied modelling approach do evolve over time due to the increase of knowledge and the improvement made to the experimental platform. In addition to presenting...

  10. Introducing an Evolving Local Neuro-Fuzzy Model--Application to modeling of car-following behavior.

    Science.gov (United States)

    Kazemi, Reza; Abdollahzade, Majid

    2015-11-01

    This paper proposes an Evolving Local Linear Neuro-Fuzzy Model for modeling and identification of nonlinear time-variant systems which change their nature and character over time. The proposed approach evolves through time to follow the structural changes in the time-variant dynamic systems. The evolution process is managed by a distance-based extended hierarchical binary tree algorithm, which decides whether the proposed evolving model should be adapted to the system variations or evolution is necessary. To represent an interesting but challenging example of the systems with changing dynamics, the proposed evolving model is applied to model car-following process in a traffic flow, as an online identification problem. Results of simulations demonstrate effectiveness of the proposed approach in modeling of the time-variant systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Environmental noise, genetic diversity and the evolution of evolvability and robustness in model gene networks.

    Directory of Open Access Journals (Sweden)

    Christopher F Steiner

    Full Text Available The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or "evolvability" can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise compared to populations in stable or randomly varying (white noise environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions.

  12. Catalytic Oxygen Evolution by a Bioinorganic Model of the Photosystem II Oxygen-Evolving Complex

    Science.gov (United States)

    Howard, Derrick L.; Tinoco, Arthur D.; Brudvig, Gary W.; Vrettos, John S.; Allen, Bertha Connie

    2005-01-01

    Bioinorganic models of the manganese Mn4 cluster are important not only as aids in understanding the structure and function of the oxygen-evolving complex (OEC), but also in developing artificial water-oxidation catalysts. The mechanism of water oxidation by photosystem II (PSII) is thought to involve the formation of a high-valent terminal Mn-oxo…

  13. Evolvement law of a macroscopic traffic model accounting for density-dependent relaxation time

    Science.gov (United States)

    Wang, Yu-Qing; Chu, Xing-Jian; Zhou, Chao-Fan; Jia, Bin; Lin, Sen; Wu, Zi-Han; Zhu, Hua-Bing; Gao, Zi-You

    2017-11-01

    In this paper, a modified macroscopic traffic flow model is presented. The term of the density-dependent relaxation time is introduced here. The relation between the relaxation time and the density in traffic flow is presented quantitatively. Besides, a factor R depicting varied properties of traffic flow in different traffic states is also introduced in the formulation of the model. Furthermore, the evolvement law of traffic flow with distinctly initial density distribution and boundary perturbations is emphasized.

  14. PyEvolve: a toolkit for statistical modelling of molecular evolution.

    Science.gov (United States)

    Butterfield, Andrew; Vedagiri, Vivek; Lang, Edward; Lawrence, Cath; Wakefield, Matthew J; Isaev, Alexander; Huttley, Gavin A

    2004-01-05

    Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences - ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from approximately 10 days to approximately 6 hours. PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used

  15. PyEvolve: a toolkit for statistical modelling of molecular evolution

    Directory of Open Access Journals (Sweden)

    Wakefield Matthew J

    2004-01-01

    Full Text Available Abstract Background Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences – ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. Results Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from ~10 days to ~6 hours. Conclusion PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the

  16. Spatio-Temporal Data Model for Integrating Evolving Nation-Level Datasets

    Science.gov (United States)

    Sorokine, A.; Stewart, R. N.

    2017-10-01

    Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc.) and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets). Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

  17. SPATIO-TEMPORAL DATA MODEL FOR INTEGRATING EVOLVING NATION-LEVEL DATASETS

    Directory of Open Access Journals (Sweden)

    A. Sorokine

    2017-10-01

    Full Text Available Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc. and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets. Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

  18. An evolving new paradigm: endothelial cells--conditional innate immune cells.

    Science.gov (United States)

    Mai, Jietang; Virtue, Anthony; Shen, Jerry; Wang, Hong; Yang, Xiao-Feng

    2013-08-22

    Endothelial cells (ECs) are a heterogeneous population that fulfills many physiological processes. ECs also actively participate in both innate and adaptive immune responses. ECs are one of the first cell types to detect foreign pathogens and endogenous metabolite-related danger signals in the bloodstream, in which ECs function as danger signal sensors. Treatment with lipopolysaccharide activates ECs, causing the production of pro-inflammatory cytokines and chemokines, which amplify the immune response by recruiting immune cells. Thus, ECs function as immune/inflammation effectors and immune cell mobilizers. ECs also induce cytokine production by immune cells, in which ECs function as immune regulators either by activating or suppressing immune cell function. In addition, under certain conditions, ECs can serve as antigen presenting cells (antigen presenters) by expressing both MHC I and II molecules and presenting endothelial antigens to T cells. These facts along with the new concept of endothelial plasticity suggest that ECs are dynamic cells that respond to extracellular environmental changes and play a meaningful role in immune system function. Based on these novel EC functions, we propose a new paradigm that ECs are conditional innate immune cells. This paradigm provides a novel insight into the functions of ECs in inflammatory/immune pathologies.

  19. An evolving new paradigm: endothelial cells – conditional innate immune cells

    Science.gov (United States)

    2013-01-01

    Endothelial cells (ECs) are a heterogeneous population that fulfills many physiological processes. ECs also actively participate in both innate and adaptive immune responses. ECs are one of the first cell types to detect foreign pathogens and endogenous metabolite-related danger signals in the bloodstream, in which ECs function as danger signal sensors. Treatment with lipopolysaccharide activates ECs, causing the production of pro-inflammatory cytokines and chemokines, which amplify the immune response by recruiting immune cells. Thus, ECs function as immune/inflammation effectors and immune cell mobilizers. ECs also induce cytokine production by immune cells, in which ECs function as immune regulators either by activating or suppressing immune cell function. In addition, under certain conditions, ECs can serve as antigen presenting cells (antigen presenters) by expressing both MHC I and II molecules and presenting endothelial antigens to T cells. These facts along with the new concept of endothelial plasticity suggest that ECs are dynamic cells that respond to extracellular environmental changes and play a meaningful role in immune system function. Based on these novel EC functions, we propose a new paradigm that ECs are conditional innate immune cells. This paradigm provides a novel insight into the functions of ECs in inflammatory/immune pathologies. PMID:23965413

  20. Application of allogeneic bone marrow cells in view of residual alloreactivity: sirolimus but not cyclosporine evolves tolerogenic properties.

    Directory of Open Access Journals (Sweden)

    Kai Timrott

    Full Text Available Application of bone marrow cells (BMC is a promising strategy for tolerance induction, but usually requires strong depletion of the host immune system. This study evaluates the ability of immunosuppressants to evolve tolerogenic properties of BMC in view of residual alloreactivity.The rat model used a major histocompatibility complex (MHC class II disparate bone marrow transplantation (BMT setting (LEW.1AR1 (RT1auu → LEW.1AR2 (RT1aau. Heart grafts (LEW.1WR1 (RT1uua were disparate for the complete MHC to recipients and for MHC class I to BMC donors. Limited conditioning was performed by total body irradiation of 6 Gy. Cyclosporine (CsA or Sirolimus (Srl were administered for 14 or 28 days. Transplantation of heart grafts (HTx was performed at day 16 or at day 100 after BMT. Chimerism and changes in the T cell pool were detected by flow cytometry.Mixed chimeras accepted HTx indefinitely, although the composition of the regenerated T cell pool was not changed to a basically donor MHC class II haplotype. Non-chimeric animals rejected HTx spontaneously. BMC recipients, who received HTx during T cell recovery at day 16, accepted HTx only after pre-treatment with Srl, although chimerism was lost. CsA pre-treatment led to accelerated HTx rejection as did isolated application of BMC.Srl evolves tolerogenic properties of allogeneic BMC to achieve indefinite acceptance of partly MHC disparate HTx despite residual alloreactivity and in particular loss of chimerism.

  1. The evolving concepts of cancer stem cells in head and neck squamous cell carcinoma.

    Science.gov (United States)

    Shah, Amit; Patel, Shilpa; Pathak, Jigna; Swain, Niharika; Kumar, Shwetha

    2014-01-01

    There is increasing evidence that the growth and spread of cancers is driven by a small subpopulation of cancer stem cells (CSCs)--the only cells that are capable of long-term self-renewal and generation of the phenotypically diverse tumor cell population. CSCs have been identified and isolated in a variety of human cancers including head and neck squamous cell carcinoma (HNSCC). The concept of cancer stem cells may have profound implications for our understanding of tumor biology and for the design of novel treatments targeted toward these cells. The present review is an attempt to conceptualize the role of CSCs in HNSCC--its implication in tumorigenesis and the possible additional approach in current treatment strategies.

  2. Renal cell carcinoma: evolving approaches to advanced non-clear cell carcinoma

    Directory of Open Access Journals (Sweden)

    Daniel Y.C. Heng

    2011-12-01

    Full Text Available The treatment of metastatic renal cell carcinoma (RCC has changed dramatically with the introduction of targeted therapies including sunitinib, sorafenib, and temsirolimus. Because patients with conventional clear cell histology account for 75- 80% of all patients with RCC, there has been little accumulated evidence on the treatment of patients with non-clear cell histologies. Most clinical trials have excluded them from enrolment, except for randomized studies investigating temsirolimus. Many retrospective studies on the use of all three of these targeted therapies in patients with non-clear cell histology have demonstrated response rates ranging from 3.7%–16%. Although response rates may not be as high compared to patients with clear cell histologies, targeted therapy does provide a clinically meaningful response.

  3. Evolving T-cell vaccine strategies for HIV, the virus with a thousand faces

    Energy Technology Data Exchange (ETDEWEB)

    Korber, Bette [Los Alamos National Laboratory

    2009-01-01

    HIV's rapid global spread and the human suffering it has left in its wake have made AIDS a global heath priority for the 25 years since its discovery. Yet its capacity to rapidly evolve has made combating this virus a tremendous challenge. The obstacles to creating an effective HIV vaccine are formidable, but there are advances in the field on many fronts, in terms of novel vectors, adjuvants, and antigen design strategies. SIV live attenuated vaccine models are able to confer protection against heterologous challenge, and this continues to provide opportunities to explore the biological underpinnings of a protective effect (9). More indirect, but equally important, is new understanding regarding the biology of acute infection (43), the role of immune response in long-term non-progression (6,62, 81), and defining characteristics of broadly neutralizing antibodies (4). In this review we will focus on summarizing strategies directed towards a single issue, that of contending with HIV variation in terms of designing aT-cell vaccine. The strategies that prove most effective in this area can ultimately be combined with the best strategies under development in other areas, with the hope of ultimately converging on a viable vaccine candidate. Only two large HIV vaccine efficacy trials have been completed and both have failed to prevent infection or confer a benefit to infected individual (23,34), but there is ample reason to continue our efforts. A historic breakthrough came in 1996, when it was realized that although the virus could escape from a single antiretroviral (ARV) therapy, it could be thwarted by a combination of medications that simultaneously targeted different parts of the virus (HAART) (38). This revelation came after 15 years of research, thought, and clinical testing; to enable that vital progress the research and clinical communities had to first define and understand, then develop a strategy to counter, the remarkable evolutionary potential of the

  4. Statistical models for brain signals with properties that evolve across trials

    KAUST Repository

    Ombao, Hernando

    2017-12-07

    Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability.

  5. Tumorigenic Heterogeneity in Cancer Stem Cells Evolved from Long-term Cultures of Telomerase-Immortalized

    DEFF Research Database (Denmark)

    Burns, Jorge S; Abdallah, Basem M; Guldberg, Per

    2005-01-01

    tumorigenicity correlated with good viability plus capillary morphogenesis on serum starvation and high cyclin D1 expression. Thus, hMSC-TERT20 clones represent cancer stem cells with hierarchical tumorigenicity, providing new models to explore the stem cell hypothesis for cancer....... or if the stem cell origin allowed most cells to behave as cancer stem cells. Cultures of the hMSC-TERT20 strain at population doubling 440 were highly clonogenic (94%). From 110 single-cell clones expanded by 20 population doublings, 6 underwent detailed comparison. Like the parental population, each clone had...... approximately 1.2 days doubling time with loss of contact inhibition. All retained 1,25-(OH)(2) vitamin D(3)-induced expression of osteoblastic markers: collagen type I, alkaline phosphatase, and osteocalcin. All shared INK4a/ARF gene locus deletion and epigenetic silencing of the DBCCR1 tumor suppressor gene...

  6. Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

    Science.gov (United States)

    Lane, Peter C. R.; Gobet, Fernand

    2013-03-01

    Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

  7. Modeling Slump of Ready Mix Concrete Using Genetically Evolved Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Vinay Chandwani

    2014-01-01

    Full Text Available Artificial neural networks (ANNs have been the preferred choice for modeling the complex and nonlinear material behavior where conventional mathematical approaches do not yield the desired accuracy and predictability. Despite their popularity as a universal function approximator and wide range of applications, no specific rules for deciding the architecture of neural networks catering to a specific modeling task have been formulated. The research paper presents a methodology for automated design of neural network architecture, replacing the conventional trial and error technique of finding the optimal neural network. The genetic algorithms (GA stochastic search has been harnessed for evolving the optimum number of hidden layer neurons, transfer function, learning rate, and momentum coefficient for backpropagation ANN. The methodology has been applied for modeling slump of ready mix concrete based on its design mix constituents, namely, cement, fly ash, sand, coarse aggregates, admixture, and water-binder ratio. Six different statistical performance measures have been used for evaluating the performance of the trained neural networks. The study showed that, in comparison to conventional trial and error technique of deciding the neural network architecture and training parameters, the neural network architecture evolved through GA was of reduced complexity and provided better prediction performance.

  8. From sprouting angiogenesis to erythrocytes generation by cancer stem cells: evolving concepts in tumor microcirculation.

    Science.gov (United States)

    Alameddine, Raafat S; Hamieh, Lana; Shamseddine, Ali

    2014-01-01

    Angiogenesis is essential for tumor growth and metastasis. Over the last decades, a substantial progress has been achieved in defining different patterns of tumor microcirculation. Sprouting angiogenesis, the oldest model of microcirculation, is the de novo vessel formation from preexisting blood vessels. Vessel splitting and hijacking, also known, respectively, as intussusception and cooption, are alternative models that account for tumor resistance to antiangiogenic therapy. In addition to remodeling the microenvironment, the tumor cell can undergo intrinsic changes and survive hypoxic conditions by acquiring stem cell properties. In line with the concept of pluripotency, tumor cells can form vascular mimicry structures creating their own microcirculation despite a latent vessel growth. The recent identification of the polyploid giant cancer cells and tumor-derived erythrocytes is the most innovative survival mechanism in hypoxia and provides a potential target for more effective therapies.

  9. A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

    Directory of Open Access Journals (Sweden)

    C. K. Kwong

    2013-01-01

    Full Text Available Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1 the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS failed to run due to a large number of inputs; (2 the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  10. A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

    Science.gov (United States)

    Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

    2013-01-01

    Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  11. Emerging trends in evolving networks: Recent behaviour dominant and non-dominant model

    Science.gov (United States)

    Abbas, Khushnood; Shang, Mingsheng; Luo, Xin; Abbasi, Alireza

    2017-10-01

    Novel phenomenon receives similar attention as popular one. Therefore predicting novelty is as important as popularity. Emergence is the side effect of competition and ageing in evolving systems. Recent behaviour or recent link gain in networks plays an important role in emergence. We exploited this wisdom and came up with two models considering different scenarios and systems. Where recent behaviour dominates over total behaviour (total link gain) in the first one, and recent behaviour is as important as total behaviour for future link gain in the second one. It supposes that random walker walks on a network and can jump to any node, the probability of jumping or making a connection to other node is based on which node is recently more active or receiving more links. In our assumption, the random walker can also jump to the node which is already popular but recently not popular. We are able to predict emerging nodes which are generally suppressed under preferential attachment effect. To show the performance of our model we have conducted experiments on four real data sets namely, MovieLens, Netflix, Facebook and Arxiv High Energy Physics paper citation. For testing our model we used four information retrieval indices namely Precision, Novelty, Area Under Receiving Operating Characteristic (AUC) and Kendal's rank correlation coefficient. We have used four benchmark models for validating our proposed models. Although our model does not perform better in all the cases but, it has theoretical significance in working better for recent behaviour dominated systems.

  12. Spatio-temporal modeling of connectome-scale brain network interactions via time-evolving graphs.

    Science.gov (United States)

    Yuan, Jing; Li, Xiang; Zhang, Jinhe; Luo, Liao; Dong, Qinglin; Lv, Jinglei; Zhao, Yu; Jiang, Xi; Zhang, Shu; Zhang, Wei; Liu, Tianming

    2017-11-09

    Many recent literature studies have revealed interesting dynamics patterns of functional brain networks derived from fMRI data. However, it has been rarely explored how functional networks spatially overlap (or interact) and how such connectome-scale network interactions temporally evolve. To explore these unanswered questions, this paper presents a novel framework for spatio-temporal modeling of connectome-scale functional brain network interactions via two main effective computational methodologies. First, to integrate, pool and compare brain networks across individuals and their cognitive states under task performances, we designed a novel group-wise dictionary learning scheme to derive connectome-scale consistent brain network templates that can be used to define the common reference space of brain network interactions. Second, the temporal dynamics of spatial network interactions is modeled by a weighted time-evolving graph, and then a data-driven unsupervised learning algorithm based on the dynamic behavioral mixed-membership model (DBMM) is adopted to identify behavioral patterns of brain networks during the temporal evolution process of spatial overlaps/interactions. Experimental results on the Human Connectome Project (HCP) task fMRI data showed that our methods can reveal meaningful, diverse behavior patterns of connectome-scale network interactions. In particular, those networks' behavior patterns are distinct across HCP tasks such as motor, working memory, language and social tasks, and their dynamics well correspond to the temporal changes of specific task designs. In general, our framework offers a new approach to characterizing human brain function by quantitative description for the temporal evolution of spatial overlaps/interactions of connectome-scale brain networks in a standard reference space. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. How Preclinical Models Evolved to Resemble the Diagnostic Criteria of Drug Addiction.

    Science.gov (United States)

    Belin-Rauscent, Aude; Fouyssac, Maxime; Bonci, Antonello; Belin, David

    2016-01-01

    Drug addiction is a complex neuropsychiatric disorder that affects a subset of the individuals who take drugs. It is characterized by maladaptive drug-seeking habits that are maintained despite adverse consequences and intense drug craving. The pathophysiology and etiology of addiction is only partially understood despite extensive research because of the gap between current preclinical models of addiction and the clinical criteria of the disorder. This review presents a brief overview, based on selected methodologies, of how behavioral models have evolved over the last 50 years to the development of recent preclinical models of addiction that more closely mimic diagnostic criteria of addiction. It is hoped that these new models will increase our understanding of the complex neurobiological mechanisms whereby some individuals switch from controlled drug use to compulsive drug-seeking habits and relapse to these maladaptive habits. Additionally, by paving the way to bridge the gap that exists between biobehavioral research on addiction and the human situation, these models may provide new perspectives for the development of novel and effective therapeutic strategies for drug addiction. Published by Elsevier Inc.

  14. Universe in the theoretical model «Evolving matter»

    Directory of Open Access Journals (Sweden)

    Bazaluk Oleg

    2013-04-01

    Full Text Available The article critically examines modern model of the Universe evolution constructed by efforts of a group of scientists (mathematicians, physicists and cosmologists from the world's leading universities (Oxford and Cambridge Universities, Yale, Columbia, New York, Rutgers and the UC Santa Cruz. The author notes its strengths, but also points to shortcomings. Author believes that this model does not take into account the most important achievements in the field of biochemistry and biology (molecular, physical, developmental, etc., as well as neuroscience and psychology. Author believes that in the construction of model of the Universe evolution, scientists must take into account (with great reservations the impact of living and intelligent matter on space processes. As an example, the author gives his theoretical model "Evolving matter". In this model, he shows not only the general dependence of the interaction of cosmic processes with inert, living and intelligent matter, but also he attempts to show the direct influence of systems of living and intelligent matter on the acceleration of the Universe's expansion.

  15. Cell-Mediated Immunity to AAV Vectors, Evolving Concepts and Potential Solutions.

    Science.gov (United States)

    Basner-Tschakarjan, Etiena; Mingozzi, Federico

    2014-01-01

    Adeno-associated virus (AAV) vectors are one of the most efficient in vivo gene delivery platforms. Over the past decade, clinical trials of AAV vector-mediated gene transfer led to some of the most exciting results in the field of gene therapy and, recently, to the market approval of an AAV-based drug in Europe. With clinical development, however, it became obvious that the host immune system represents an important obstacle to successful gene transfer with AAV vectors. In this review article, we will discuss the issue of cytotoxic T cell responses directed against the AAV capsid encountered on human studies. While over the past several years the field has acquired a tremendous amount of information on the interactions of AAV vectors with the immune system, a lot of questions are still unanswered. Novel concepts are emerging, such as the relationship between the total capsid dose and the T cell-mediated clearance of transduced cells, the potential role of innate immunity in vector immunogenicity highlighted in preclinical studies, and the cross talk between regulatory and effector T cells in the determination of the outcome of gene transfer. There is still a lot to learn about immune responses in AAV gene transfer, for example, it is not well understood what are the determinants of the kinetics of activation of T cells in response to vector administration, why not all subjects develop detrimental T cell responses following gene transfer, and whether the intervention strategies currently in use to block T cell-mediated clearance of transduced cells will be safe and effective for all gene therapy indications. Results from novel preclinical models and clinical studies will help to address these points and to reach the important goal of developing safe and effective gene therapy protocols to treat human diseases.

  16. Can We Recognize an Innovation? Perspective from an Evolving Network Model

    Science.gov (United States)

    Jain, Sanjay; Krishna, Sandeep

    "Innovations" are central to the evolution of societies and the evolution of life. But what constitutes an innovation? We can often agree after the event, when its consequences and impact over a long term are known, whether something was an innovation, and whether it was a "big" innovation or a "minor" one. But can we recognize an innovation "on the fly" as it appears? Successful entrepreneurs often can. Is it possible to formalize that intuition? We discuss this question in the setting of a mathematical model of evolving networks. The model exhibits self-organization , growth, stasis, and collapse of a complex system with many interacting components, reminiscent of real-world phenomena. A notion of "innovation" is formulated in terms of graph-theoretic constructs and other dynamical variables of the model. A new node in the graph gives rise to an innovation, provided it links up "appropriately" with existing nodes; in this view innovation necessarily depends upon the existing context. We show that innovations, as defined by us, play a major role in the birth, growth, and destruction of organizational structures. Furthermore, innovations can be categorized in terms of their graph-theoretic structure as they appear. Different structural classes of innovation have potentially different qualitative consequences for the future evolution of the system, some minor and some major. Possible general lessons from this specific model are briefly discussed.

  17. An evolving model for the lodging-service network in a tourism destination

    Science.gov (United States)

    Hernández, Juan M.; González-Martel, Christian

    2017-09-01

    Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing model that explains how part of the supply components in a tourism system forms a social network. Specifically, the lodgings and services in a destination are the network nodes and a link between them appears if a representative tourist hosted in the lodging visits/consumes the service during his/her stay. The specific link between both categories are determined by a random and preferential attachment rule. The analytic results show that the long-term degree distribution of services follows a shifted power-law distribution. The numerical simulations show slight disagreements with the theoretical results in the case of the one-mode degree distribution of services, due to the low order of convergence to zero of X-motifs. The model predictions are compared with real data coming from a popular tourist destination in Gran Canaria, Spain, showing a good agreement between analytical and empirical data for the degree distribution of services. The theoretical model was validated assuming four type of perturbations in the real data.

  18. A Reproductive Threat-Based Model of Evolved Sex Differences in Jealousy

    Directory of Open Access Journals (Sweden)

    Brad J. Sagarin

    2012-07-01

    Full Text Available Although heterosexual women and men consistently demonstrate sex differences in jealousy, these differences disappear among lesbians and gay men as well as among heterosexual women and men contemplating same-sex infidelities (infidelities in which the partner and rival are the same sex. Synthesizing these past findings, the present paper offers a reproductive threat-based model of evolved sex differences in jealousy that predicts that the sexes will differ only when the jealous perceivers' reproductive outcomes are differentially at risk. This model is supported by data from a web-based study in which lesbians, gay men, bisexual women and men, and heterosexual women and men responded to a hypothetical infidelity scenario with the sex of the rival randomly determined. After reading the scenario, participants indicated which type of infidelity (sexual versus emotional would cause greater distress. Consistent with predictions, heterosexual women and men showed a sex difference when contemplating opposite-sex infidelities but not when contemplating same-sex infidelities, whereas lesbians and gay men showed no sex difference regardless of whether the infidelity was opposite-sex or same-sex.

  19. An evolving model for the supply network in a tourism destination

    CERN Document Server

    Hernández, Juan M

    2016-01-01

    Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing bipartite network model that explains the rise of the supply network in a tourism destination from the beginning phases of development. The nodes are the lodgings and services in a destination and a link between them appears if a representative tourist hosted in the lodging visits/consumes the service during his/her stay. The specific link between both categories are determined by a random and preferential attachment rule. The analytic results show that the long-term degree distribution of services follows a shifted power-law distribution. The numerical simulations show slight disagreements with the theoretical results in the case of the one-mode degree distribution of services, due to the low order of convergence to zero of X-motifs. The model predictions are compared with real data coming from a popular tourist destination in Gran Canaria, Spain, show...

  20. Evolving towards a human-cell based and multiscale approach to drug discovery for CNS disorders

    Directory of Open Access Journals (Sweden)

    Eric eSchadt

    2014-12-01

    Full Text Available A disruptive approach to therapeutic discovery and development is required in order to significantly improve the success rate of drug discovery for central nervous system (CNS disorders. In this review, we first assess the key factors contributing to the frequent clinical failures for novel drugs. Second, we discuss cancer translational research paradigms that addressed key issues in drug discovery and development and have resulted in delivering drugs with significantly improved outcomes for patients. Finally, we discuss two emerging technologies that could improve the success rate of CNS therapies: human induced pluripotent stem cell (hiPSC-based studies and multiscale biology models. Coincident with advances in cellular technologies that enable the generation of hiPSCs directly from patient blood or skin cells, together with methods to differentiate these hiPSC lines into specific neural cell types relevant to neurological disease, it is also now possible to combine data from large-scale forward genetics and post-mortem global epigenetic and expression studies in order to generate novel predictive models. The application of systems biology approaches to account for the multiscale nature of different data types, from genetic to molecular and cellular to clinical, can lead to new insights into human diseases that are emergent properties of biological networks, not the result of changes to single genes. Such studies have demonstrated the heterogeneity in etiological pathways and the need for studies on model systems that are patient-derived and thereby recapitulate neurological disease pathways with higher fidelity. In the context of two common and presumably representative neurological diseases, the neurodegenerative disease Alzheimer’s Disease (AD, and the psychiatric disorder schizophrenia (SZ, we propose the need for, and exemplify the impact of, a multiscale biology approach that can integrate panomic, clinical, imaging, and literature

  1. The basic postulates of the universal evolution model «Evolving matter»

    Directory of Open Access Journals (Sweden)

    Bazaluk Oleg

    2015-02-01

    Full Text Available The author reveals the features of construction of the universal evolution model, which he called «Evolving matter». According to the author, the material world, which is perceived in scales of the Earth and near space, consists of visually and empirically easily detectable states of matter, with different complexity of the internal organisation: inert, living and intelligent matter. The transition from one («parent» state of matter to another («daughter» state is caused by three main factors and two reasons of evolution. The author has carried the following factors of evolution as a complication: a Continuity of self-complication structures, types of interaction and environments of existence of any state of matter, which is supplemented by: – Block of continuous self-complication; – Principle of block of continuous self-complication of dominance; b Nonlinear complication of structure, types of interactions and environments of existence of any state of matter, which is specified by factors: – Hierarchical nonlinear complication; – Orientation of nonlinear hierarchical complication; c Complication isolation. The author carries complications to the evolution reasons: a Active principle, which is inherently the basis for the initial elements of any state of matter, and which forms a self-complication; b Natural selection as the environment influence.

  2. The Cardiovascular Intensive Care Unit-An Evolving Model for Health Care Delivery.

    Science.gov (United States)

    Loughran, John; Puthawala, Tauqir; Sutton, Brad S; Brown, Lorrel E; Pronovost, Peter J; DeFilippis, Andrew P

    2017-02-01

    Prior to the advent of the coronary care unit (CCU), patients having an acute myocardial infarction (AMI) were managed on the general medicine wards with reported mortality rates of greater than 30%. The first CCUs are believed to be responsible for reducing mortality attributed to AMI by as much as 40%. This drastic improvement can be attributed to both advances in medical technology and in the process of health care delivery. Evolving considerably since the 1960s, the CCU is now more appropriately labeled as a cardiac intensive care unit (CICU) and represents a comprehensive system designed for the care of patients with an array of advanced cardiovascular disease, an entity that reaches far beyond its early association with AMI. Grouping of patients by diagnosis to a common physical space, dedicated teams of health care providers, as well as the development and implementation of evidence-based treatment algorithms have resulted in the delivery of safer, more efficient care, and most importantly better patient outcomes. The CICU serves as a platform for an integrated, team-based patient care delivery system that addresses a broad spectrum of patient needs. Lessons learned from this model can be broadly applied to address the urgent need to improve outcomes and efficiency in a variety of health care settings.

  3. Evolving a Simulation Model Product Line Software Architecture from Heterogeneous Model Representations

    Science.gov (United States)

    2003-09-01

    Crouching Dragon , Hidden Software: Software in DoD Weapon Systems,” IEEE Software, Vol. 18, No. 4, July-August 2001, pp. 105-107. [FG99...objects hidden , Generalization is a form of abstraction establishing an is-a relationship between the specialized and generic object, when similar...concept, [CGG98] explained the JSIMS Military Modeling Framework initiative, a De- partment enterprise-wide Tiger Team initiative to develop Mission

  4. Evolving models for medical physics education and training: a global perspective.

    Science.gov (United States)

    Sprawls, P

    2008-01-01

    There is a significant need for high-quality medical physics education and training in all countries to support effective and safe use of modern medical technology for both diagnostic and treatment purposes. This is, and will continue to be, achieved using appropriate technology to increase both the effectiveness and efficiency of educational activities everywhere in the world. While the applications of technology to education and training are relatively new, the successful applications are based on theories and principles of the learning process developed by two pioneers in the field, Robert Gagne and Edgar Dale.The work of Gagne defines the different levels of learning that can occur and is used to show the types and levels of learning that are required for the application of physics and engineering principles to achieve appropriate diagnostic and therapeutic results from modern technology. The learning outcomes are determined by the effectiveness of the learning activity or experience. The extensive work of Dale as formulated in his Cone of Experience relates the effectiveness to the efficiency of educational activities. A major challenge in education is the development and conduction of learning activities (classroom discussions, laboratory and applied experiences, individual study, etc) that provide an optimum balance between effectiveness and efficiency. New and evolving models of the educational process use technology as the infrastructure to support education that is both more effective and efficient.The goal is to use technology to enhance human performance for both learners (students) and learning facilitators (teachers). A major contribution to global education is the trend in the development of shared educational resources. Two models of programs to support this effort with open and free shared resources are Physical Principles of Medical Imaging Online (http://www.sprawls.org/resources) and AAPM Continuing Education Courses (http://www.aapm.org/international).

  5. Evolvement of cell-substrate interaction over time for cells cultivated on a 3-aminopropyltriethoxysilane ({gamma}-APTES) modified silicon dioxide (SiO{sub 2}) surface

    Energy Technology Data Exchange (ETDEWEB)

    Hsu, Chung-Ping [Division of Thoracic Surgery, Department of Surgery, Taichung Veterans General Hospital, Taichung, 40705, Taiwan, ROC (China); School of Medicine, National Yang Ming University, Taipei, 11221, Taiwan, ROC (China); Hsu, Po-Yen [Department of Electrical Engineering, National Chi Nan University, Puli, Nantou, 54561, Taiwan, ROC (China); Wu, You-Lin, E-mail: ylwu@ncnu.edu.tw [Department of Electrical Engineering, National Chi Nan University, Puli, Nantou, 54561, Taiwan, ROC (China); Hsu, Wan-Yun [Comprehensive Cancer Center, Taichung Veterans General Hospital, Taichung, 40705, Taiwan, ROC (China); Lin, Jing-Jenn [Department of Applied Materials and Optoelectronic Engineering, National Chi Nan University, Puli, Nantou, 54561, Taiwan, ROC (China)

    2012-09-01

    Highlights: Black-Right-Pointing-Pointer Cell-substrate interaction of single cells was observed directly from the post-cell-removal imprint left on {gamma}-APTES soft substrate surface. Black-Right-Pointing-Pointer The time evolvement of the cell-substrate interaction can be obtained by cultivating cells on the {gamma}-APTES surface for different periods of time. Black-Right-Pointing-Pointer The cell-substrate interaction property can be found from the post-cell-removal surface morphology profiles determined by AFM. Black-Right-Pointing-Pointer It was found that the cancer cells tend to form deeper trenches along the circumference of the imprints, while the normal cells do not. - Abstract: Since cell-substrate interaction is directly related to the traction force of the cell, the cell property can be judged from the imprint it leaves on the soft substrate surface onto which the cell is cultured. In this letter, the evolvement of the cell-substrate interaction over time was observed by cultivating cells on a 3-aminopropyltriethoxysilane ({gamma}-APTES) modified silicon dioxide (SiO{sub 2}) surface for different periods of time. The cell-substrate interaction property as a function of time can then be found from the post-cell-removal surface morphology profiles determined by atomic force microscopy (AFM). Different surface morphology profiles were found between normal cells and cancer cells. It was found that the cancer cells tend to form deeper trenches along the circumference of the imprints, while the normal cells do not. In addition, our results indicated that normal cells involve cell-substrate interaction mechanisms that are different from those for cancer cells.

  6. Generational dermatology: model for prevention and multi decade approach toward the evolving, aging patient.

    Science.gov (United States)

    Roberts, Wendy E

    2013-12-01

    The proposed terminology Generational Dermatology encompasses prevention and involves medical, cosmetic, surgical and oncologic strategies over the decades to optimize skin performance throughout the course of a lifetime. Organ failure is the inability of the organ to perform its determined function as a part of normal physiology and it may be possible to take a Generational preventive approach toward reducing morbidities associated with the failure of our largest organ, the skin. Outside of skin cancer prevention efforts we have as a specialty primarily worked on the tertiary prevention realm. I advocate that we can increase our focus on the primary and secondary tiers where we as Dermatologists have the training and education to identify risk factors and detect early symptoms of skin disease. I appeal to the house of Dermatology to embrace this concept of Generational Dermatology as preventive medicine for the evolving aging patient. The practice of Generational Dermatology will decrease patient morbidity and bring down the cost of healthcare. Our global increased longevity increases the number of elderly worldwide. Longer lifespan means dermatologic needs will increase as the skin must perform its basic function longer. There are also new unknowns and skin issues which arise from large numbers of people in the 9th and 10th decades. Generational Dermatology is well suited to be a model for prevention as our patient's age and we can intervene at any decade. I believe the specialty will increasingly focus on how the skin can optimally perform for a longer period. Lastly, the practice of Generational Dermatology unifies the house of Dermatology as we need the innovations and input of every subspecialty to contribute to the health of the people we serve.

  7. Cell therapy for multiple sclerosis: an evolving concept with implications for other neurodegenerative diseases.

    Science.gov (United States)

    Rice, Claire M; Kemp, Kevin; Wilkins, Alastair; Scolding, Neil J

    2013-10-05

    Multiple sclerosis is a major cause of neurological disability, and particularly occurs in young adults. It is characterised by conspicuous patches of damage throughout the brain and spinal cord, with loss of myelin and myelinating cells (oligodendrocytes), and damage to neurons and axons. Multiple sclerosis is incurable, but stem-cell therapy might offer valuable therapeutic potential. Efforts to develop stem-cell therapies for multiple sclerosis have been conventionally built on the principle of direct implantation of cells to replace oligodendrocytes, and therefore to regenerate myelin. Recent progress in understanding of disease processes in multiple sclerosis include observations that spontaneous myelin repair is far more widespread and successful than was previously believed, that loss of axons and neurons is more closely associated with progressive disability than is myelin loss, and that damage occurs diffusely throughout the CNS in grey and white matter, not just in discrete, isolated patches or lesions. These findings have introduced new and serious challenges that stem-cell therapy needs to overcome; the practical challenges to achieve cell replacement alone are difficult enough, but, to be useful, cell therapy for multiple sclerosis must achieve substantially more than the replacement of lost oligodendrocytes. However, parallel advances in understanding of the reparative properties of stem cells--including their distinct immunomodulatory and neuroprotective properties, interactions with resident or tissue-based stem cells, cell fusion, and neurotrophin elaboration--offer renewed hope for development of cell-based therapies. Additionally, these advances suggest avenues for translation of this approach not only for multiple sclerosis, but also for other common neurological and neurodegenerative diseases. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Cell Surface Properties of Lactococcus lactis Reveal Milk Protein Binding Specifically Evolved in Dairy Isolates

    NARCIS (Netherlands)

    Tarazanova, Mariya; Huppertz, Thom; Beerthuyzen, Marke; van Schalkwijk, Saskia; Janssen, Patrick; Wels, Michiel; Kok, Jan; Bachmann, Herwig

    2017-01-01

    Surface properties of bacteria are determined by the molecular composition of the cell wall and they are important for interactions of cells with their environment. Well-known examples of bacterial interactions with surfaces are biofilm formation and the fermentation of solid materials like food and

  9. Evolving Small-Cell Communications towards Mobile-over-FTTx Networks

    OpenAIRE

    Zhang, Jian A.; Collings, Iain B.; Chen, Chung Shue; Laurent, Roullet; Luo, Lin; Siu-Wai, Ho; Yuan, Jinhong

    2013-01-01

    International audience; Small cell techniques are recognized as the best way to deliver high capacity for broadband cellular communications. Femtocell and distributed antenna systems (DAS) are important components in the overall small cell story, but are not the complete solution. They have major disadvantages of very limited cooperation capability and expensive deployment cost, respectively. In this article, we propose a novel mobile-over-FTTx (MoF) network architecture, where a fiber-to-the...

  10. Generation of predictive price and trading volume patterns in a model of dynamically evolving free market supply and demand

    Directory of Open Access Journals (Sweden)

    J. K. Wang

    2001-01-01

    Full Text Available I present a model of stock market price fluctuations incorporating effects of share supply as a history-dependent function of previous purchases and share demand as a function of price deviation from moving averages. Price charts generated show intervals of oscillations switching amplitude and frequency suddenly in time, forming price and trading volume patterns well-known in market technical analysis. Ultimate price trends agree with traditional predictions for specific patterns. The consideration of dynamically evolving supply and demand in this model resolves the apparent contradiction with the Efficient Market Hypothesis: perceptions of imprecise equity values by a world of investors evolve over non-negligible periods of time, with dependence on price history.

  11. DNA aptamer evolved by cell-SELEX for recognition of prostate cancer.

    Directory of Open Access Journals (Sweden)

    Yuanyuan Wang

    Full Text Available Morbidity and mortality of prostate cancer (PCa have increased in recent years worldwide. Currently existing methods for diagnosis and treatment do not make the situation improve, especially for hormone refractory prostate cancer (HRPC. The lack of molecular probes for PCa hindered the early diagnosis of metastasis and accurate staging for PCa. In this work, we have developed a new aptamer probe Wy-5a against PCa cell line PC-3 by cell-SELEX technique. Wy-5a shows high specificity to the target cells with dissociation constants in the nanomolar range, and does not recognize other tested PCa cell lines and other tested tumor cell lines. The staining of clinical tissue sections with fluorescent dye labeled Wy-5a shows that sections from high risk group with metastasis exhibited stronger fluorescence and sections from Benign Prostatic Hyperplasia (BPH did not exhibit notable fluorescence, which suggests that aptamer Wy-5a may bind to protein related to the progression of PCa. The high affinity and specificity of Wy-5a makes this aptamer hold potential for application in diagnosis and target therapy of PCa.

  12. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    Science.gov (United States)

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould.

  13. Fatal Metastatic Cutaneous Squamous Cell Carcinoma Evolving from a Localized Verrucous Epidermal Nevus

    Directory of Open Access Journals (Sweden)

    Hassan Riad

    2013-10-01

    Full Text Available A malignant transformation is known to occur in many nevi such as a sebaceous nevus or a basal cell nevus, but a verrucous epidermal nevus has only rarely been associated with neoplastic changes. Keratoacanthoma, multifocal papillary apocrine adenoma, multiple malignant eccrine poroma, basal cell carcinoma and cutaneous squamous cell carcinoma (CSCC have all been reported to develop from a verrucous epidermal nevus. CSCC has also been reported to arise from other nevoid lesions like a nevus comedonicus, porokeratosis, a sebaceous nevus, an oral sponge nevus and an ichthyosiform nevus with CHILD syndrome. Here we report a case of progressive poorly differentiated CSCC arising from a localized verrucous epidermal nevus, which caused both spinal cord and brain metastasis.

  14. The Evolving Landscape of Neurotoxicity by Unconjugated Bilirubin: Role of Glial Cells and Inflammation

    Directory of Open Access Journals (Sweden)

    Dora eBrites

    2012-05-01

    Full Text Available Unconjugated hyperbilirubinemia is a common condition in the first week of postnatal life. Although generally harmless, some neonates may develop very high levels of unconjugated bilirubin (UCB, which may surpass the protective mechanisms of the brain at preventing UCB accumulation. In this case, both short-term and long-term neurodevelopmental disabilities, such as acute and chronic UCB encephalopathy, known as kernicterus, or more subtle alterations designed as bilirubin-induced neurological dysfunction (BIND may be produced. There is a tremendous variability in babies’ vulnerability towards UCB for reasons not yet explained, but preterm birth, sepsis, hypoxia and haemolytic disease are comprised as risk factors. Therefore, UCB levels and neurological abnormalities are not strictly correlated. Even nowadays, the mechanisms of UCB neurotoxicity are still unclear, as are specific biomarkers, and little is known about lasting sequelae attributable to hyperbilirubinemia. On autopsy, UCB was shown to be within neurons, neuronal processes and microglia, and to produce loss of neurons, demyelination and gliosis. In isolated cell cultures, UCB was shown to impair neuronal arborization and to induce the release of proinflammatory cytokines from microglia and astrocytes. However, cell dependent-sensitivity to UCB toxicity and the role of each nerve cell type remain understood. This review provides a comprehensive insight into cell susceptibilities and molecular targets of UCB in neurons, astrocytes, and oligodendrocytes, and on phenotypic and functional responses of microglia to UCB. Interplay among glia elements and cross-talk with neurons, with a special emphasis in the UCB-induced immunostimulation, and the role of sepsis in BIND pathogenesis are highlighted. New and interesting data on the anti-inflammatory and antioxidant activities of different pharmacological agents are also presented, as novel and promising additional therapeutic approaches to

  15. Cell Surface Properties of Lactococcus lactis Reveal Milk Protein Binding Specifically Evolved in Dairy Isolates

    Directory of Open Access Journals (Sweden)

    Mariya Tarazanova

    2017-09-01

    Full Text Available Surface properties of bacteria are determined by the molecular composition of the cell wall and they are important for interactions of cells with their environment. Well-known examples of bacterial interactions with surfaces are biofilm formation and the fermentation of solid materials like food and feed. Lactococcus lactis is broadly used for the fermentation of cheese and buttermilk and it is primarily isolated from either plant material or the dairy environment. In this study, we characterized surface hydrophobicity, charge, emulsification properties, and the attachment to milk proteins of 55 L. lactis strains in stationary and exponential growth phases. The attachment to milk protein was assessed through a newly developed flow cytometry-based protocol. Besides finding a high degree of biodiversity, phenotype-genotype matching allowed the identification of candidate genes involved in the modification of the cell surface. Overexpression and gene deletion analysis allowed to verify the predictions for three identified proteins that altered surface hydrophobicity and attachment of milk proteins. The data also showed that lactococci isolated from a dairy environment bind higher amounts of milk proteins when compared to plant isolates. It remains to be determined whether the alteration of surface properties also has potential to alter starter culture functionalities.

  16. Evolving radiological features of hypothalamo-pituitary lesions in adult patients with Langerhans cell histiocytosis (LCH)

    Energy Technology Data Exchange (ETDEWEB)

    Makras, P. [Athens General Hospital, Department of Endocrinology and Diabetes, Athens (Greece); Athens General Hospital, Department of Radiology, Athens (Greece); Samara, C.; Antoniou, M.; Nikolakopoulou, Z. [Athens Hospital, 9. Pulmonary Department, Athens (Greece); Zetos, A. [General Hospital, Department of Pathology, Athens (Greece); Papadogias, D.; Piaditis, G.; Kaltsas, G.A. [Athens General Hospital, Department of Endocrinology and Diabetes, Athens (Greece); Toloumis, G. [Athens General Hospital, Department of Radiology, Athens (Greece); Andreakos, E.; Kontogeorgos, G.

    2006-01-01

    Langerhans cell histiocytosis (LCH) is a rare, systemic disease caused by monoclonal expansion of dendritic cells that shows a particular predilection for the hypothalamic-pituitary system (HPS). We studied the function (anterior and posterior pituitary hormonal secretion) and morphology using magnetic resonance imaging (MRI) of the HPS in 17 adult patients (seven males, median age 35 years, range 18-59 years) with multisystem LCH. We also evaluated the evolution of structural HPS abnormalities in relation to pituitary function and response to treatment in 12 of these patients during a median follow-up period of 3.75 years (range 1.5-10 years). Of the 17 patients, 14 (82%) had abnormal HPS imaging, and 12 (70%) had more than one area involved. Lack of the bright spot of the posterior pituitary lobe was typically found in all patients with the diagnosis of diabetes insipidus (DI). Eight patients (47%) had infundibular enlargement, six (35%) pituitary infiltration, four (24%) partially or completely empty sella, three (18%) hypothalamic involvement, and two (12%) infundibular atrophy. DI was found in 16 patients (94%) and anterior pituitary hormonal deficiency (APHD) in 10 patients (59%); two patients had single (12%) and 8 (47%) multiple APHD. During the follow-up period there was improvement of the initially demonstrated HPS pathology in seven (47%) patients, and five (33%) of them had received at least one form of treatment. APHD and DI persisted in all patients except in one in whom established gonadotrophin deficiency recovered. In summary, DI and APHD are very common in patients with multisystem LCH and are almost always associated with abnormal HPS imaging. (orig.)

  17. Hematopoietic cell crisis: An early stage of evolving myeloid leukemia following radiation exposure

    Energy Technology Data Exchange (ETDEWEB)

    Seed, T.M.

    1990-01-01

    Under select radiological conditions, chronic radiation exposure elicits a high incidence of myeloproliferative disease, principally myeloid leukemia (ML), in beagles. Previously we demonstrated that for full ML expression, a four-stage preclinical sequence is required, namely (1) suppression, (2) recovery, (3) accommodation, and (4) preleukemic transition. Within this pathological sequence, a critical early event has been identified as the acquisition of radioresistance by hematopoietic progenitors that serves to mediate a newfound regenerative hematopoietic capacity. As such, this event sets the stage'' for preleukemic progression by initiating progression from preclinical phase 1 to 2. Due to the nature of target cell suppression, the induction of crisis, and the outgrowth of progenitors with altered phenotypes, this preleukemic event resembles the immortalization'' step of the in vitro transformation sequence following induction with either physical and chemical carcinogens. The radiological, temporal, and biological dictates governing this event have been extensively evaluated and will be discussed in light of their role in the induction and progression of chronic radiation leukemia. 35 refs., 2 tabs.

  18. Mentoring: An Evolving Relationship.

    Science.gov (United States)

    Block, Michelle; Florczak, Kristine L

    2017-04-01

    The column concerns itself with mentoring as an evolving relationship between mentor and mentee. The collegiate mentoring model, the transformational transcendence model, and the humanbecoming mentoring model are considered in light of a dialogue with mentors at a Midwest university and conclusions are drawn.

  19. Maintaining evolvability.

    Science.gov (United States)

    Crow, James F

    2008-12-01

    Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy

  20. Numerically modelling the Cygnus Loop as a remnant evolved in an anisotropic cavity

    Science.gov (United States)

    Fang, Jun; Yu, Huan; Zhang, Li

    2017-01-01

    The morphology of the middle-aged supernova remnant, Cygnus Loop, seen in X-rays, is peculiar, with a blowout in the south region and other irregular features, such as a bump in the west, a limb with a planar morphology in the east and asymmetry between the east and the west shock profiles of the blowout. The detailed process of the formation of the peculiar profile of the shock is still unclear. We perform three-dimensional hydrodynamical simulations for the remnant to revisit its evolution. In the simulations, the progenitor ejects an anisotropic, latitude-dependent wind, and travels in a direction that is not aligned with the symmetry axis of the wind. As a result, a cavity with a fringed structure is produced. The remnant has evolved in the cavity for about 104 yr. In the north-east, the shock has first encountered the bow shock, and this part corresponds to the bright north-eastern region. The south blowout is formed due to the shock travelling into the undisturbed wind, and the interaction of the shock with the cavity leads to the other peculiar features of the shock structure. The resulting profile of the remnant is consistent with that indicated in X-rays. It can be concluded that the supernova explosion occurred in the cavity produced by an anisotropic stellar wind experiencing two main phases with different wind velocities.

  1. A genetic polymorphism evolving in parallel in two cell compartments and in two clades

    Directory of Open Access Journals (Sweden)

    Watt Ward B

    2013-01-01

    Full Text Available Abstract Background The enzyme phosphoenolpyruvate carboxykinase, PEPCK, occurs in its guanosine-nucleotide-using form in animals and a few prokaryotes. We study its natural genetic variation in Colias (Lepidoptera, Pieridae. PEPCK offers a route, alternative to pyruvate kinase, for carbon skeletons to move between cytosolic glycolysis and mitochondrial Krebs cycle reactions. Results PEPCK is expressed in both cytosol and mitochondrion, but differently in diverse animal clades. In vertebrates and independently in Drosophila, compartment-specific paralogous genes occur. In a contrasting expression strategy, compartment-specific PEPCKs of Colias and of the silkmoth, Bombyx, differ only in their first, 5′, exons; these are alternatively spliced onto a common series of following exons. In two Colias species from distinct clades, PEPCK sequence is highly variable at nonsynonymous and synonymous sites, mainly in its common exons. Three major amino acid polymorphisms, Gly 335 ↔ Ser, Asp 503 ↔ Glu, and Ile 629 ↔ Val occur in both species, and in the first two cases are similar in frequency between species. Homology-based structural modelling shows that the variants can alter hydrogen bonding, salt bridging, or van der Waals interactions of amino acid side chains, locally or at one another′s sites which are distant in PEPCK′s structure, and thus may affect its enzyme function. We ask, using coalescent simulations, if these polymorphisms′ cross-species similarities are compatible with neutral evolution by genetic drift, but find the probability of this null hypothesis is 0.001 ≤ P ≤ 0.006 under differing scenarios. Conclusion Our results make the null hypothesis of neutrality of these PEPCK polymorphisms quite unlikely, but support an alternative hypothesis that they are maintained by natural selection in parallel in the two species. This alternative can now be justifiably tested further via studies of PEPCK genotypes′ effects

  2. Scalable geocomputation: evolving an environmental model building platform from single-core to supercomputers

    Science.gov (United States)

    Schmitz, Oliver; de Jong, Kor; Karssenberg, Derek

    2017-04-01

    There is an increasing demand to run environmental models on a big scale: simulations over large areas at high resolution. The heterogeneity of available computing hardware such as multi-core CPUs, GPUs or supercomputer potentially provides significant computing power to fulfil this demand. However, this requires detailed knowledge of the underlying hardware, parallel algorithm design and the implementation thereof in an efficient system programming language. Domain scientists such as hydrologists or ecologists often lack this specific software engineering knowledge, their emphasis is (and should be) on exploratory building and analysis of simulation models. As a result, models constructed by domain specialists mostly do not take full advantage of the available hardware. A promising solution is to separate the model building activity from software engineering by offering domain specialists a model building framework with pre-programmed building blocks that they combine to construct a model. The model building framework, consequently, needs to have built-in capabilities to make full usage of the available hardware. Developing such a framework providing understandable code for domain scientists and being runtime efficient at the same time poses several challenges on developers of such a framework. For example, optimisations can be performed on individual operations or the whole model, or tasks need to be generated for a well-balanced execution without explicitly knowing the complexity of the domain problem provided by the modeller. Ideally, a modelling framework supports the optimal use of available hardware whichsoever combination of model building blocks scientists use. We demonstrate our ongoing work on developing parallel algorithms for spatio-temporal modelling and demonstrate 1) PCRaster, an environmental software framework (http://www.pcraster.eu) providing spatio-temporal model building blocks and 2) parallelisation of about 50 of these building blocks using

  3. Characteristics of evolving models of care for arthritis: A key informant study

    Directory of Open Access Journals (Sweden)

    Veinot Paula

    2008-07-01

    Full Text Available Abstract Background The burden of arthritis is increasing in the face of diminishing health human resources to deliver care. In response, innovative models of care delivery are developing to facilitate access to quality care. Most models have developed in response to local needs with limited evaluation. The primary objective of this study is to a examine the range of models of care that deliver specialist services using a medical/surgical specialist and at least one other health care provider and b document the strengths and challenges of the identified models. A secondary objective is to identify key elements of best practice models of care for arthritis. Methods Semi-structured interviews were conducted with a sample of key informants with expertise in arthritis from jurisdictions with primarily publicly-funded health care systems. Qualitative data were analyzed using a constant comparative approach to identify common types of models of care, strengths and challenges of models, and key components of arthritis care. Results Seventy-four key informants were interviewed from six countries. Five main types of models of care emerged. 1 Specialized arthritis programs deliver comprehensive, multidisciplinary team care for arthritis. Two models were identified using health care providers (e.g. nurses or physiotherapists in expanded clinical roles: 2 triage of patients with musculoskeletal conditions to the appropriate services including specialists; and 3 ongoing management in collaboration with a specialist. Two models promoting rural access were 4 rural consultation support and 5 telemedicine. Key informants described important components of models of care including knowledgeable health professionals and patients. Conclusion A range of models of care for arthritis have been developed. This classification can be used as a framework for discussing care delivery. Areas for development include integration of care across the continuum, including primary

  4. Beyond Dyadic Interdependence: Actor-Oriented Models for Co-Evolving Social Networks and Individual Behaviors

    Science.gov (United States)

    Burk, William J.; Steglich, Christian E. G.; Snijders, Tom A. B.

    2007-01-01

    Actor-oriented models are described as a longitudinal strategy for examining the co-evolution of social networks and individual behaviors. We argue that these models provide advantages over conventional approaches due to their ability to account for inherent dependencies between individuals embedded in a social network (i.e., reciprocity,…

  5. Evolving Models of Pavlovian Conditioning: Cerebellar Cortical Dynamics in Awake Behaving Mice

    Directory of Open Access Journals (Sweden)

    Michiel M. ten Brinke

    2015-12-01

    Full Text Available Three decades of electrophysiological research on cerebellar cortical activity underlying Pavlovian conditioning have expanded our understanding of motor learning in the brain. Purkinje cell simple spike suppression is considered to be crucial in the expression of conditional blink responses (CRs. However, trial-by-trial quantification of this link in awake behaving animals is lacking, and current hypotheses regarding the underlying plasticity mechanisms have diverged from the classical parallel fiber one to the Purkinje cell synapse LTD hypothesis. Here, we establish that acquired simple spike suppression, acquired conditioned stimulus (CS-related complex spike responses, and molecular layer interneuron (MLI activity predict the expression of CRs on a trial-by-trial basis using awake behaving mice. Additionally, we show that two independent transgenic mouse mutants with impaired MLI function exhibit motor learning deficits. Our findings suggest multiple cerebellar cortical plasticity mechanisms underlying simple spike suppression, and they implicate the broader involvement of the olivocerebellar module within the interstimulus interval.

  6. Opsins have evolved under the permanent heterozygote model: insights from phylotranscriptomics of Odonata.

    Science.gov (United States)

    Suvorov, Anton; Jensen, Nicholas O; Sharkey, Camilla R; Fujimoto, M Stanley; Bodily, Paul; Wightman, Haley M Cahill; Ogden, T Heath; Clement, Mark J; Bybee, Seth M

    2017-03-01

    Gene duplication plays a central role in adaptation to novel environments by providing new genetic material for functional divergence and evolution of biological complexity. Several evolutionary models have been proposed for gene duplication to explain how new gene copies are preserved by natural selection, but these models have rarely been tested using empirical data. Opsin proteins, when combined with a chromophore, form a photopigment that is responsible for the absorption of light, the first step in the phototransduction cascade. Adaptive gene duplications have occurred many times within the animal opsins' gene family, leading to novel wavelength sensitivities. Consequently, opsins are an attractive choice for the study of gene duplication evolutionary models. Odonata (dragonflies and damselflies) have the largest opsin repertoire of any insect currently known. Additionally, there is tremendous variation in opsin copy number between species, particularly in the long-wavelength-sensitive (LWS) class. Using comprehensive phylotranscriptomic and statistical approaches, we tested various evolutionary models of gene duplication. Our results suggest that both the blue-sensitive (BS) and LWS opsin classes were subjected to strong positive selection that greatly weakens after multiple duplication events, a pattern that is consistent with the permanent heterozygote model. Due to the immense interspecific variation and duplicability potential of opsin genes among odonates, they represent a unique model system to test hypotheses regarding opsin gene duplication and diversification at the molecular level. © 2016 John Wiley & Sons Ltd.

  7. A Plate Tectonic Model for the Neoproterozoic with Evolving Plate Boundaries

    Science.gov (United States)

    Merdith, Andrew; Collins, Alan; Williams, Simon; Pisarevsky, Sergei; Müller, Dietmar

    2017-04-01

    The Neoproterozoic was dominated by the formation of the supercontinent Rodinia, its break-up and the subsequent amalgamation of Gondwana, during which, the planet experienced large climatic variations and the emergence of complex life. Here we present a topological plate model of the Neoproterozoic based on a synthesis of available geological and palaeomagnetic data. Subduction zones, which are well preserved in the geological record, are used as a proxy for convergent margins; evidence for mid-ocean ridges and transform motion is less clearly preserved, though passive margins are used as a proxy for spreading centres, and evidence for strike-slip motions are used to model transform boundaries. We find that the model presented here only predicts 70% of the total length of subduction active today, though it models similar lengths of both transform and divergent boundaries, suggesting that we have produced a conservative model and are probably underestimating the amount of subduction. Where evidence for convergent, divergent or transform motion is not preserved, we interpret the locations of plate boundaries based on the relative motions of cratonic crust as suggested through either palaeomagnetic data or the geological record. Using GPlates, we tie these boundaries together to generate a plate model that depicts the motion of tectonic plates through the Neoproterozoic. We omit India and South China from Rodinia completely, due to long-lived subduction preserved on margins of India and conflicting palaeomagnetic data for the Cryogenian, but tie them together due to similar Tonian aged accretionary patterns along their respective (present-day) north-western and northern margins, such that these two cratons act as a "lonely wanderer" for much of the Neoproterozoic, and form their own tectonic plate. We also introduce a Tonian-Cryogenian aged rotation of the Congo-São Francisco Craton relative to Rodinia to better fit palaeomagnetic data and account for thick passive

  8. Direct numerical simulations and modeling of a spatially-evolving turbulent wake

    Science.gov (United States)

    Cimbala, John M.

    1994-12-01

    Understanding of turbulent free shear flows (wakes, jets, and mixing layers) is important, not only for scientific interest, but also because of their appearance in numerous practical applications. Turbulent wakes, in particular, have recently received increased attention by researchers at NASA Langley. The turbulent wake generated by a two-dimensional airfoil has been selected as the test-case for detailed high-resolution particle image velocimetry (PIV) experiments. This same wake has also been chosen to enhance NASA's turbulence modeling efforts. Over the past year, the author has completed several wake computations, while visiting NASA through the 1993 and 1994 ASEE summer programs, and also while on sabbatical leave during the 1993-94 academic year. These calculations have included two-equation (K-omega and K-epsilon) models, algebraic stress models (ASM), full Reynolds stress closure models, and direct numerical simulations (DNS). Recently, there has been mutually beneficial collaboration of the experimental and computational efforts. In fact, these projects have been chosen for joint presentation at the NASA Turbulence Peer Review, scheduled for September 1994. DNS calculations are presently underway for a turbulent wake at Re(sub theta) = 1000 and at a Mach number of 0.20. (Theta is the momentum thickness, which remains constant in the wake of a two dimensional body.) These calculations utilize a compressible DNS code written by M. M. Rai of NASA Ames, and modified for the wake by J. Cimbala. The code employs fifth-order accurate upwind-biased finite differencing for the convective terms, fourth-order accurate central differencing for the viscous terms, and an iterative-implicit time-integration scheme. The computational domain for these calculations starts at x/theta = 10, and extends to x/theta = 610. Fully developed turbulent wake profiles, obtained from experimental data from several wake generators, are supplied at the computational inlet, along with

  9. A model study of mixing and entrainment in the horizontally evolving atmospheric convective boundary layer

    Energy Technology Data Exchange (ETDEWEB)

    Fedorovich, E.; Kaiser, R. [Univ. Karlsruhe, Inst. fuer Hydrologie und Wasserwirtschaft (Germany)

    1997-10-01

    We present results from a parallel wind-tunnel/large-eddy simulation (LES) model study of mixing and entrainment in the atmospheric convective boundary layer (CBL) longitudinally developing over a heated surface. The advection-type entrainment of warmer air from upper turbulence-free layers into the growing CBL has been investigated. Most of numerical and laboratory model studies of the CBL carried out so far dealt with another type of entrainment, namely the non-steady one, regarding the CBL growth as a non-stationary process. In the atmosphere, both types of the CBL development can take place, often being superimposed. (au)

  10. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun

    2016-02-02

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  11. Time-Evolving Acoustic Propagation Modeling in a Complex Ocean Environment

    NARCIS (Netherlands)

    Colin, M.E.G.G.; Duda, T.F.; Raa, L.A. te; Zon, T. van; Haley Jr., P.J., P. F. J.; Lermusiaux, P.F.J.; Leslie, W.G.; Mirabito, C.; Lam, F.P.A.; Newhall, A.E.; Lin, Y.T.; Lynch, J.F.

    2013-01-01

    During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried out in challenging and dynamic environments. This makes acoustic propagation

  12. Evolving dynamical regimes during secular cooling of terrestrial planets : insights and inferences from numerical models

    NARCIS (Netherlands)

    Thienen, Peter van

    2003-01-01

    Although plate tectonics is the present-day mode of geodynamics on Earth, it is not so on Mars and Venus, and probably also not during the early history of the Earth. In this thesis, the conditions under which plate tectonics may operate on terrestrial planets are investigated. Numerical model

  13. Evolving Approaches and Technologies to Enhance the Role of Ecological Modeling in Decision Making

    Science.gov (United States)

    Eric Gustafson; John Nestler; Louis Gross; Keith M. Reynolds; Daniel Yaussy; Thomas P. Maxwell; Virginia H. Dale

    2002-01-01

    Understanding the effects of management activities is difficult for natural resource managers and decision makers because ecological systems are highly complex and their behavior is difficult to predict. Furthermore, the empirical studies necessary to illuminate all management questions quickly become logistically complicated and cost prohibitive. Ecological models...

  14. Global Evolving Models of Photospheric Flux as Driven by Electric Fields

    Science.gov (United States)

    DeRosa, Marc L.; Cheung, Mark; Kazachenko, Maria D.; Fisher, George H.

    2017-08-01

    We present a novel method for modeling the global radial magnetic field that is based on the incorporation of time series of photospheric electric fields. The determination of the electric fields is the result of a recently developed method that uses as input various data products from SDO/HMI, namely vector magnetic fields and line-of-sight Doppler images. For locations on the sphere where electric field data are unavailable, we instead use electric fields that are consistent with measurements of the mean differential rotation, meridional flow, and flux dispersal profiles. By combining these electric fields, a full-Sun model of the photospheric radial magnetic field can be advanced forward in time via Faraday's Law.

  15. An updated conceptual model of Delta Smelt biology: Our evolving understanding of an estuarine fish

    Science.gov (United States)

    Baxter, Randy; Brown, Larry R.; Castillo, Gonzalo; Conrad, Louise; Culberson, Steven D.; Dekar, Matthew P.; Dekar, Melissa; Feyrer, Frederick; Hunt, Thaddeus; Jones, Kristopher; Kirsch, Joseph; Mueller-Solger, Anke; Nobriga, Matthew; Slater, Steven B.; Sommer, Ted; Souza, Kelly; Erickson, Gregg; Fong, Stephanie; Gehrts, Karen; Grimaldo, Lenny; Herbold, Bruce

    2015-01-01

    The main purpose of this report is to provide an up-to-date assessment and conceptual model of factors affecting Delta Smelt (Hypomesus transpacificus) throughout its primarily annual life cycle and to demonstrate how this conceptual model can be used for scientific and management purposes. The Delta Smelt is a small estuarine fish that only occurs in the San Francisco Estuary. Once abundant, it is now rare and has been protected under the federal and California Endangered Species Acts since 1993. The Delta Smelt listing was related to a step decline in the early 1980s; however, population abundance decreased even further with the onset of the “pelagic organism decline” (POD) around 2002. A substantial, albeit short-lived, increase in abundance of all life stages in 2011 showed that the Delta Smelt population can still rebound when conditions are favorable for spawning, growth, and survival. In this report, we update previous conceptual models for Delta Smelt to reflect new data and information since the release of the last synthesis report about the POD by the Interagency Ecological Program for the San Francisco Estuary (IEP) in 2010. Specific objectives include:

  16. An existential model of oral health from evolving views on health, function and disability.

    Science.gov (United States)

    MacEntee, Michael I

    2006-03-01

    This study explores the evolution of conceptual frameworks and models of health and disability to construct an explanatory model of oral health. The International Classification of Impairments, Disabilities, and Handicaps adopted by the WHO is based largely on social role theory and a utilitarian tradition portraying disablement as a negative and socially unacceptable consequence of impairment. It has been the major conceptual influence on the construction of psychometric tools for dentistry. However current views of chronic disease are refocused on the influence of coping strategies used by people to prevent or limit disability and handicap. Consequently, the WHO adopted the International Classification of Functioning, Disability and Health (ICF) as an alternative description of health and health-related states based on an existentialist view of the body, the person and society. In addition, an ethnographic exploration has identified three major domains of oral health--oral hygiene, comfort and general health--that dominate the opinions of people with oral impairments. Application of the framework and language of the ICF to the major domains of oral health provides the basis for a new biopsychosocial model of oral health, function and disablement.

  17. Integrating Spanish language training across a Doctor of Physical Therapy curriculum: a case report of one program's evolving model.

    Science.gov (United States)

    Pechak, Celia; Diaz, Deborah; Dillon, Loretta

    2014-12-01

    As the Hispanic population continues to expand in the United States, health professionals increasingly may encounter people who speak Spanish and have limited English proficiency. Responding to these changes, various health profession educators have incorporated Spanish language training into their curricula. Of 12 doctor of physical therapy (DPT) programs identified as including elective or required Spanish courses, the program at The University of Texas at El Paso is the only one integrating required Spanish language training across the curriculum. The purpose of this case report is to describe the development, implementation, and preliminary outcomes of the evolving educational model at The University of Texas at El Paso. The University of Texas at El Paso is situated immediately across the border from Mexico. Responding to the large population with limited English proficiency in the community, faculty began to integrate required Spanish language training during a transition from a master-level to a DPT curriculum. The Spanish language curriculum pillar includes a Spanish medical terminology course, language learning opportunities threaded throughout the clinical courses, clinical education courses, and service-learning. Forty-five DPT students have completed the curriculum. Assessment methods were limited for early cohorts. Clinically relevant Spanish verbal proficiency was assessed with a practical examination in the Spanish course, a clinical instructor-rated instrument, and student feedback. Preliminary data suggested that the model is improving Spanish language proficiency. The model still is evolving. Spanish language learning opportunities in the curriculum are being expanded. Also, problems with the clinical outcome measure have been recognized. Better definition of intended outcomes and validation of a revised tool are needed. This report should promote opportunities for collaboration with others who are interested in linguistic competence. © 2014

  18. NOAA Ship Okeanos Explorer: Evolving Models Enabling Remote Science Participation via Telepresence

    Science.gov (United States)

    Elliott, K.; Potter, J.; Martinez, C.; Pinner, W.; Russell, C. W.; Verplanck, N.

    2014-12-01

    Since 2005 NOAA's Office of Ocean Exploration and Research (OER) and partners have tested and developed uses of telepresence to extend ocean exploration expeditions to shore-based scientists and students in real-time. Telepresence increases the potential pace and scope of ocean exploration by enabling experts to join an expedition from anywhere, providing unlimited access to intellectual capital, while simultaneously expanding the reach of ocean science expeditions to public audiences worldwide. "America's Ship for Ocean Exploration", NOAA Ship Okeanos Explorer, is the first and only federal vessel purpose-outfitted for conducting telepresence-enabled ocean exploration. As a platform for testing new technologies and methodologies, her primary operating paradigm focuses on using telepresence to enable the majority of expedition scientists to participate and guide explorations from shore in real-time. Between 2010-2014, NOAA and partners implemented different models to conduct telepresence-enabled ocean exploration on NOAA Ship Okeanos Explorer, all with the majority of the participating expedition scientists located on shore. These expeditions tested different scientist participation models, communication technologies, operating procedures, internet video streams, data distribution methods, and internet-based collaboration tools, and provided varying levels of real-time access to ongoing expeditions. Each expedition provided new insights into what makes remote science participation "work", and identified challenges that remain to be overcome. This presentation will provide an overview of the different methods and tools used by NOAA's Okeanos Explorer Program to enable remote science participation in expeditions over the last five years, highlighting successes, lessons learned, and challenges for the future.

  19. General synthesis of di-mu-oxo dimanganese complexes as functional models for the oxygen evolving complex of photosystem II.

    Science.gov (United States)

    Chen, Hongyu; Tagore, Ranitendranath; Das, Siddhartha; Incarvito, Christopher; Faller, J W; Crabtree, Robert H; Brudvig, Gary W

    2005-10-17

    A series of complexes with the formula [Mn(III/IV)2(mu-O)2(L)2(X)2]3+ have been prepared in situ from Mn(II)LCl2 precursors by a general preparative method (L = terpy, Cl-terpy, Br-terpy, Ph-terpy, tolyl-terpy, mesityl-terpy, t Bu3-terpy, EtO-terpy, py-phen, dpya, Me2N-terpy, or HO-terpy, and X = a labile ligand such as water, chloride, or sulfate). The parent complex, where L = terpy and X = water, is a functional model for the oxygen-evolving complex of photosystem II (Limburg, et al. J. Am. Chem. Soc. 2001, 123, 423-430). Crystals of Mn(II)(dpya)Cl2, Mn(II)(Ph-terpy)Cl2, Mn(II)(mesityl-terpy)Cl2, and an organic-soluble di-mu-oxo di-aqua dimanganese complex, [Mn(III/)(IV)2(mu-O)2(mesityl-terpy)2(OH2)2](NO3)3, were obtained and characterized by X-ray crystallography. Solutions of the in situ-formed di-mu-oxo dimanganese complexes were characterized by electrospray mass spectrometry, EPR spectroscopy, and UV-visible spectroscopy, and the rates of catalytic oxygen-evolving activity were assayed. The use of Mn(II)LCl2 precursors leads to higher product purity of the Mn dimers while achieving the 1:1 ligand to Mn stoichiometry appropriate for catalytic activity assay. These methods can be used to screen the catalytic activity of other di-mu-oxo dimanganese complexes generated by using a ligand library.

  20. Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

    Science.gov (United States)

    Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

    2017-03-23

    Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. An evolved ribosome-inactivating protein targets and kills human melanoma cells in vitro and in vivo

    Directory of Open Access Journals (Sweden)

    Green David E

    2010-02-01

    Full Text Available Abstract Background Few treatment options exist for patients with metastatic melanoma, resulting in poor prognosis. One standard treatment, dacarbazine (DTIC, shows low response rates ranging from 15 to 25 percent with an 8-month median survival time. The development of targeted therapeutics with novel mechanisms of action may improve patient outcome. Ribosome-inactivating proteins (RIPs such as Shiga-like Toxin 1 (SLT-1 represent powerful scaffolds for developing selective anticancer agents. Here we report the discovery and properties of a single chain ribosome-inactivating protein (scRIP derived from the cytotoxic A subunit of SLT-1 (SLT-1A, harboring the 7-amino acid peptide insertion IYSNKLM (termed SLT-1AIYSNKLM allowing the toxin variant to selectively target and kill human melanoma cells. Results SLT-1AIYSNKLM was able to kill 7 of 8 human melanoma cell lines. This scRIP binds to 518-A2 human melanoma cells with a dissociation constant of 18 nM, resulting in the blockage of protein synthesis and apoptosis in such cells. Biodistribution and imaging studies of radiolabeled SLT-1AIYSNKLM administered intravenously into SCID mice bearing a human melanoma xenograft indicate that SLT-1AIYSNKLM readily accumulates at the tumor site as opposed to non-target tissues. Furthermore, the co-administration of SLT-1AIYSNKLM with DTIC resulted in tumor regression and greatly increased survival in this mouse xenograft model in comparison to DTIC or SLT-1AIYSNKLM treatment alone (115 day median survival versus 46 and 47 days respectively; P values IYSNKLM is stable in serum and its intravenous administration resulted in modest immune responses following repeated injections in CD1 mice. Conclusions These results demonstrate that the evolution of a scRIP template can lead to the discovery of novel cancer cell-targeted compounds and in the case of SLT-1AIYSNKLM can specifically kill human melanoma cells in vitro and in vivo.

  2. Evolving power grids with self-organized intermittent strain releases: An analogy with sandpile models and earthquakes

    Science.gov (United States)

    Po, Ho Fai; Yeung, Chi Ho; Zeng, An; Wong, K. Y. Michael

    2017-11-01

    The stability of powergrid is crucial since its disruption affects systems ranging from street lightings to hospital life-support systems. While short-term dynamics of single-event cascading failures have been extensively studied, less is understood on the long-term evolution and self-organization of powergrids. In this paper, we introduce a simple model of evolving powergrid and establish its connection with the sandpile model and earthquakes, i.e., self-organized systems with intermittent strain releases. Various aspects during its self-organization are examined, including blackout magnitudes, their interevent waiting time, the predictability of large blackouts, as well as the spatiotemporal rescaling of blackout data. We examined the self-organized strain releases on simulated networks as well as the IEEE 118-bus system, and we show that both simulated and empirical blackout waiting times can be rescaled in space and time similarly to those observed between earthquakes. Finally, we suggested proactive maintenance strategies to drive the powergrids away from self-organization to suppress large blackouts.

  3. Final Report for Award #0006731. Modeling, Patterning and Evolving Syntrophic Communities that Link Fermentation to Metal Reduction

    Energy Technology Data Exchange (ETDEWEB)

    Marx, Christopher J. [Harvard Univ., Cambridge, MA (United States)

    2015-07-17

    This project has developed and combined mathematical models, multi-species consortia, and spatially structured environments as an approach for studying metabolic exchange in communities like the ones between fermenters and metal reducers. We have developed novel, broadly-applicable tools for following community dynamics, come to a better understanding of both sugar and lactate-utilization in S. oneidensis, the interactions between carbon and mineral availability, and have a methodology for cell printing to match with spatiotemporal models of consortia metabolism.

  4. Simulations of Living Cell Origins Using a Cellular Automata Model

    Science.gov (United States)

    Ishida, Takeshi

    2014-04-01

    Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

  5. Simulations of living cell origins using a cellular automata model.

    Science.gov (United States)

    Ishida, Takeshi

    2014-04-01

    Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

  6. Human Endothelial Cell Models in Biomaterial Research.

    Science.gov (United States)

    Hauser, Sandra; Jung, Friedrich; Pietzsch, Jens

    2017-03-01

    Endothelial cell (EC) models have evolved as important tools in biomaterial research due to ubiquitously occurring interactions between implanted materials and the endothelium. However, screening the available literature has revealed a gap between material scientists and physiologists in terms of their understanding of these biomaterial-endothelium interactions and their relative importance. Consequently, EC models are often applied in nonphysiological experimental setups, or too extensive conclusions are drawn from their results. The question arises whether this might be one reason why, among the many potential biomaterials, only a few have found their way into the clinic. In this review, we provide an overview of established EC models and possible selection criteria to enable researchers to determine the most reliable and relevant EC model to use. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Evolution of evolvability in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Anton Crombach

    Full Text Available Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.

  8. Microscopic Colitis Evolved Into Inflammatory Bowel Diseases Is Characterized by Increased Th1/Tc1 Cells in Colonic Mucosal Lamina Propria.

    Science.gov (United States)

    Li, Ji; Yan, Yuchu; Meng, Ziran; Liu, Shuhong; Beck, Paul L; Ghosh, Subrata; Qian, Jiaming; Gui, Xianyong

    2017-10-01

    An association between microscopic colitis (MC), i.e., lymphocytic colitis (LC) and collagenous colitis (CC), and inflammatory bowel diseases (IBD) has been noticed. A subset of MC cases may evolve into IBD, and IBD in remission may present as MC in a histologic pattern. Moreover, MC and IBD may coexist in different regions of the bowel. A link between MC and IBD in their pathogenesis is, therefore, suggested. Abnormal mucosal immunity is likely the key. We reviewed 2324 MC cases in Calgary over 14 years and identified 20 cases evolved into IBD (IBD transformers). 13 of them were further investigated for colonic mucosal lamina propria mononuclear cells (LPMNCs), as opposed to 22 cases whose MC resolved. On their index colonic biopsy immunohistochemistry was performed to detect major T cell subsets characterized by key cytokines and master transcription factors (IFNγ and T-bet for Th1/Tc1, GATA-3 for Th2/Tc2, IL-17 and RORc for Th17/Tc17, FoxP3 for Treg/Tcreg) as well as TNFα+ cells (partly representing Th1). LPMNCs positive for each marker were counted (average number per high-power field). IBD transformers had increased IFNγ+, T-bet+, TNF-α+, and GATA-3+ LPMNCs compared to the MC-resolved cases. The LC-to-IBD subgroup had increased IFNγ+ and GATA-3+ cells compared to the LC-resolved subgroup. The CC-to-IBD subgroup had increased T-bet+, TNF-α+, and GATA-3+ cells compared to the CC-resolved subgroup. Among MC-resolved patients, more TNF-α+ and RORc+ cells were seen in LC than in CC. Th1/Tc1- and TNFα-producing cells, and likely a subset of Th2/Tc2 cells as well, may be involved in the MC-to-IBD transformation.

  9. Interaction of methanol with the oxygen-evolving complex: atomistic models, channel identification, species dependence, and mechanistic implications.

    Science.gov (United States)

    Retegan, Marius; Pantazis, Dimitrios A

    2016-10-01

    Methanol has long being used as a substrate analogue to probe access pathways and investigate water delivery at the oxygen-evolving complex (OEC) of photosystem-II. In this contribution we study the interaction of methanol with the OEC by assembling available spectroscopic data into a quantum mechanical treatment that takes into account the local channel architecture of the active site. The effect on the magnetic energy levels of the Mn4Ca cluster in the S2 state of the catalytic cycle can be explained equally well by two models that involve either methanol binding to the calcium ion of the cluster, or a second-sphere interaction in the vicinity of the "dangler" Mn4 ion. However, consideration of the latest 13C hyperfine interaction data shows that only one model is fully consistent with experiment. In contrast to previous hypotheses, methanol is not a direct ligand to the OEC, but is situated at the end-point of a water channel associated with the O4 bridge. Its effect on magnetic properties of plant PS-II results from disruption of hydrogen bonding between O4 and proximal channel water molecules, thus enhancing superexchange (antiferromagnetic coupling) between the Mn3 and Mn4 ions. The same interaction mode applies to the dark-stable S1 state and possibly to all other states of the complex. Comparison of protein sequences from cyanobacteria and plants reveals a channel-altering substitution (D1-Asn87 versus D1-Ala87) in the proximity of the methanol binding pocket, explaining the species-dependence of the methanol effect. The water channel established as the methanol access pathway is the same that delivers ammonia to the Mn4 ion, supporting the notion that this is the only directly solvent-accessible manganese site of the OEC. The results support the pivot mechanism for water binding at a component of the S3 state and would be consistent with partial inhibition of water delivery by methanol. Mechanistic implications for enzymatic regulation and catalytic

  10. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  11. The carrier of the "30" mu m emission feature in evolved stars - A simple model using magnesium sulfide

    NARCIS (Netherlands)

    Hony, S; Waters, LBFM; Tielens, AGGM

    We present 2-45 mum spectra of a large sample of carbon-rich evolved stars in order to study the "30" mum feature. We find the "30" mum feature in a wide range of sources: low mass loss carbon stars, extreme carbon-stars, post-AGB objects and planetary nebulae. We extract the profiles from the

  12. A PACS maturity model: a systematic meta-analytic review on maturation and evolvability of PACS in the hospital enterprise.

    NARCIS (Netherlands)

    Wetering, R. van de; Batenburg, R.

    2009-01-01

    INTRODUCTION: With PACS and medical imaging technology maturing, the importance of organizational maturity and effective deployment of PACS in the hospital enterprise are becoming significant. OBJECTIVE: The objective of this paper is twofold. Firstly, PACS literature on maturity and evolvability in

  13. A continuum mechanics approach to modeling and simulating engineering materials undergoing phase transformation using the evolving micro-structural model of inelasticity

    Science.gov (United States)

    Adedoyin, Adetokunbo Adelana

    Heat treatment for the purpose of material strengthening is accompanied by residual stresses and distortion. During these processing steps, steel alloys experience a phase change that in turn modify their overall mechanical response. To properly account for the cumulative composite behavior, the mechanical response, transformation kinetics and subsequent interaction of each phase have to be properly accounted for. Of interest to material designers and fabricators is modeling and simulating the evolutionary process a part undergoes for the sake of capturing the observable residual stress states and geometric distortion accumulated after processing. In an attempt to capture the aforementioned physical phenomena, this investigation is premised upon a consistent thermodynamic framework. Following this, the single phase Evolving Microstructural Model of Inelasticity state variable model is extended to accommodate the occurrence of multiphases, affirming that the interaction between coexisting phases is through an interfacial stress. Since the efficacy of a multiphase model is dependent on its ability to capture the behavior of constituents phases and their subsequent interaction, we introduce a physically based self-consistent strain partitioning algorithm. With synthesis of the aforementioned ideas, the additional transformation induced plasticity is numerically accounted for by modifying each phase's flowrule to accommodate an interfacial stress. In addition, for simulating the cohabitation of two phases, the mechanical multiphase model equations is coupled with a previously developed non-diffusional phase transformation kinetics model. A qualitative assessment of the material response based on a Taylor, Sachs and self-consistent polycrystalline approximation is carried out. Further analysis of the multiphase model and its interaction with transformation kinetics is evaluated.

  14. Defects in Mitochondrial Dynamics and Metabolomic Signatures of Evolving Energetic Stress in Mouse Models of Familial Alzheimer's Disease

    Science.gov (United States)

    Trushina, Eugenia; Nemutlu, Emirhan; Zhang, Song; Christensen, Trace; Camp, Jon; Mesa, Janny; Siddiqui, Ammar; Tamura, Yasushi; Sesaki, Hiromi; Wengenack, Thomas M.; Dzeja, Petras P.; Poduslo, Joseph F.

    2012-01-01

    Background The identification of early mechanisms underlying Alzheimer's Disease (AD) and associated biomarkers could advance development of new therapies and improve monitoring and predicting of AD progression. Mitochondrial dysfunction has been suggested to underlie AD pathophysiology, however, no comprehensive study exists that evaluates the effect of different familial AD (FAD) mutations on mitochondrial function, dynamics, and brain energetics. Methods and Findings We characterized early mitochondrial dysfunction and metabolomic signatures of energetic stress in three commonly used transgenic mouse models of FAD. Assessment of mitochondrial motility, distribution, dynamics, morphology, and metabolomic profiling revealed the specific effect of each FAD mutation on the development of mitochondrial stress and dysfunction. Inhibition of mitochondrial trafficking was characteristic for embryonic neurons from mice expressing mutant human presenilin 1, PS1(M146L) and the double mutation of human amyloid precursor protein APP(Tg2576) and PS1(M146L) contributing to the increased susceptibility of neurons to excitotoxic cell death. Significant changes in mitochondrial morphology were detected in APP and APP/PS1 mice. All three FAD models demonstrated a loss of the integrity of synaptic mitochondria and energy production. Metabolomic profiling revealed mutation-specific changes in the levels of metabolites reflecting altered energy metabolism and mitochondrial dysfunction in brains of FAD mice. Metabolic biomarkers adequately reflected gender differences similar to that reported for AD patients and correlated well with the biomarkers currently used for diagnosis in humans. Conclusions Mutation-specific alterations in mitochondrial dynamics, morphology and function in FAD mice occurred prior to the onset of memory and neurological phenotype and before the formation of amyloid deposits. Metabolomic signatures of mitochondrial stress and altered energy metabolism indicated

  15. Natural selection promotes antigenic evolvability.

    Science.gov (United States)

    Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin

    2013-01-01

    The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.

  16. Natural selection promotes antigenic evolvability.

    Directory of Open Access Journals (Sweden)

    Christopher J Graves

    Full Text Available The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish

  17. A H2-evolving photocathode based on direct sensitization of MoS3 with an organic photovoltaic cell

    Science.gov (United States)

    Bourgeteau, Tiphaine; Tondelier, Denis; Geffroy, Bernard; Brisse, Romain; Laberty-Robert, Christel; Campidelli, Stéphane; de Bettignies, Rémi; Artero, Vincent; Palacin, Serge; Jousselme, Bruno

    2013-01-01

    An organic solar cell based on a poly-3-hexylthiophene (P3HT): phenyl-C61-butyric acid (PCBM) bulk hetero-junction was directly coupled with molybdenum sulfide resulting in the design of a new type of photocathode for the production of hydrogen. Both the light-harvesting system and the catalyst were deposited by low-cost solution-processed methods, i.e. spin coating and spray coating respectively. Spray-coated MoS3 films are catalytically active in strongly acidic aqueous solutions with the best efficiencies for thicknesses of 40 to 90 nm. The photocathodes display photocurrents higher than reference samples, without catalyst or without coupling with a solar cell. Analysis by gas chromatography confirms the light-induced hydrogen evolution. The addition of titanium dioxide in the MoS3 film enhances electron transport and collection within thick films and therefore the performance of the photocathode. PMID:24404434

  18. Evolving role of 2B4/CD244 in T and NK cell responses during virus infection

    Directory of Open Access Journals (Sweden)

    Stephen Noel Waggoner

    2012-12-01

    Full Text Available The signaling lymphocyte activation molecule (SLAM family receptor, 2B4/CD244, was first implicated in anti-viral immunity by the discovery that mutations of the SLAM-associated protein, SAP/SH2D1A, impaired 2B4-dependent stimulation of T and natural killer (NK cell anti-viral functions in X-linked lymphoproliferative (XLP syndrome patients with uncontrolled Epstein-Barr virus (EBV infections. Engagement of 2B4 has been variably shown to either activate or inhibit lymphocytes which express this receptor. While SAP expression is required for stimulatory functions of 2B4 on lymphocytes, it remains unclear whether inhibitory signals derived from 2B4 can predominate even in the presence of SAP. Regardless, mounting evidence suggests that 2B4 expression by NK and CD8 T cells is altered by virus infection in mice as well as in humans, and 2B4-mediated signaling may be an important determinant of effective immune control of chronic virus infections. In this review, recent findings regarding the expression and function of 2B4 as well as SAP on T and NK cells during virus infection is discussed, with a focus on the role of 2B4-CD48 interactions in crosstalk between innate and adaptive immunity.

  19. Stochastic models of cell motility

    DEFF Research Database (Denmark)

    Gradinaru, Cristian

    2012-01-01

    Cell motility and migration are central to the development and maintenance of multicellular organisms, and errors during this process can lead to major diseases. Consequently, the mechanisms and phenomenology of cell motility are currently under intense study. In recent years, a new...... interdisciplinary field focusing on the study of biological processes at the nanoscale level, with a range of technological applications in medicine and biological research, has emerged. The work presented in this thesis is at the interface of cell biology, image processing, and stochastic modeling. The stochastic...... models introduced here are based on persistent random motion, which I apply to real-life studies of cell motility on flat and nanostructured surfaces. These models aim to predict the time-dependent position of cell centroids in a stochastic manner, and conversely determine directly from experimental...

  20. Cytokinesis-block micronucleus assay evolves into a 'cytome' assay of chromosomal instability, mitotic dysfunction and cell death

    Energy Technology Data Exchange (ETDEWEB)

    Fenech, Michael [CSIRO Human Nutrition, Genome Health Nutrigenomics Project, P.O. Box 10041, Adelaide BC, Adelaide, SA 5000 (Australia)]. E-mail: michael.fenech@csiro.au

    2006-08-30

    The cytokinesis-block micronucleus (CBMN) assay was originally developed as an ideal system for measuring micronuclei (MNi) however it can also be used to measure nucleoplasmic bridges (NPBs), nuclear buds (NBUDs), cell death (necrosis or apoptosis) and nuclear division rate. Current evidence suggests that (a) NPBs originate from dicentric chromosomes in which the centromeres have been pulled to the opposite poles of the cell at anaphase and are therefore indicative of DNA mis-repair, chromosome rearrangement or telomere end-fusions, (b) NPBs may break to form MNi, (c) the nuclear budding process is the mechanism by which cells remove amplified and/or excess DNA and is therefore a marker of gene amplification and/or altered gene dosage, (d) cell cycle checkpoint defects result in micronucleus formation and (e) hypomethylation of DNA, induced nutritionally or by inhibition of DNA methyl transferase can lead to micronucleus formation either via chromosome loss or chromosome breakage. The strong correlation between micronucleus formation, nuclear budding and NPBs (r = 0.75-0.77, P < 0.001) induced by either folic acid deficiency or exposure to ionising radiation is supportive of the hypothesis that folic acid deficiency and/or ionising radiation cause genomic instability and gene amplification by the initiation of breakage-fusion-bridge cycles. In its comprehensive mode, the CBMN assay measures all cells including necrotic and apoptotic cells as well as number of nuclei per cell to provide a measure of cytotoxicity and mitotic activity. The CBMN assay has in fact evolved into a 'cytome' method for measuring comprehensively chromosomal instability phenotype and altered cellular viability caused by genetic defects and/or nutrional deficiencies and/or exogenous genotoxins thus opening up an exciting future for the use of this methodology in the emerging fields of nutrigenomics and toxicogenomics and their combinations.

  1. Evolving stability and pH-dependent activity of the high redox potential Botrytis aclada laccase for enzymatic fuel cells.

    Science.gov (United States)

    Scheiblbrandner, Stefan; Breslmayr, Erik; Csarman, Florian; Paukner, Regina; Führer, Johannes; Herzog, Peter L; Shleev, Sergey V; Osipov, Evgeny M; Tikhonova, Tamara V; Popov, Vladimir O; Haltrich, Dietmar; Ludwig, Roland; Kittl, Roman

    2017-10-20

    Fungal high redox potential laccases are proposed as cathodic biocatalysts in implantable enzymatic fuel cells to generate high cell voltages. Their application is limited mainly through their acidic pH optimum and chloride inhibition. This work investigates evolutionary and engineering strategies to increase the pH optimum of a chloride-tolerant, high redox potential laccase from the ascomycete Botrytis aclada. The laccase was subjected to two rounds of directed evolution and the clones screened for increased stability and activity at pH 6.5. Beneficial mutation sites were investigated by semi-rational and combinatorial mutagenesis. Fourteen variants were characterised in detail to evaluate changes of the kinetic constants. Mutations increasing thermostability were distributed over the entire structure. Among them, T383I showed a 2.6-fold increased half-life by preventing the loss of the T2 copper through unfolding of a loop. Mutations affecting the pH-dependence cluster around the T1 copper and categorise in three types of altered pH profiles: pH-type I changes the monotonic decreasing pH profile into a bell-shaped profile, pH-type II describes increased specific activity below pH 6.5, and pH-type III increased specific activity above pH 6.5. Specific activities of the best variants were up to 5-fold higher (13 U mg-1) than BaL WT at pH 7.5.

  2. An ovarian mature cystic teratoma evolving in squamous cell carcinoma: A case report and review of the literature

    Directory of Open Access Journals (Sweden)

    C Goudeli

    2017-02-01

    Full Text Available Mature cystic teratomas (MCT, also known as dermoid cysts, are the most common ovarian germ cell tumors and the most common ovarian neoplasms in patients younger than 20 years. Malignant transformation (MT is a rare complication of MCTs which may occur in 1–2% of the cases. Squamous cell carcinoma (SCC is the most frequent histology arising from MCTs and its appearance depends on diverse risk factors such as patient's age, the size of the tumor and levels of serum tumor markers. Diagnosis and treatment constitute a big challenge due to the rarity and the aggressive course of this entity. Adjuvant chemotherapy has a leading role in the treatment of MCT-arising SCC, while the use of radiotherapy or chemoradiation is still under consideration. Herein, we report a case of a post-menopausal woman, presenting with mild symptoms and a large pelvic mass deriving from the left ovary occurring as dermoid cyst. Simultaneously, we review the literature stressing out the prognostic factors and the treatment options for MCT arising SCC according to traditional and new therapy-strategies.

  3. Modeling cell-in-cell structure into its biological significance.

    Science.gov (United States)

    He, M-f; Wang, S; Wang, Y; Wang, X-n

    2013-05-16

    Although cell-in-cell structure was noted 100 years ago, the molecular mechanisms of 'entering' and the destination of cell-in-cell remain largely unclear. It takes place among the same type of cells (homotypic cell-in-cell) or different types of cells (heterotypic cell-in-cell). Cell-in-cell formation affects both effector cells and their host cells in multiple aspects, while cell-in-cell death is under more intensive investigation. Given that cell-in-cell has an important role in maintaining homeostasis, aberrant cell-in-cell process contributes to the etiopathology in humans. Indeed, cell-in-cell is observed in many pathological processes of human diseases. In this review, we intend to discuss the biological models of cell-in-cell structures under physiological and pathological status.

  4. Model cell membranes

    DEFF Research Database (Denmark)

    Günther-Pomorski, Thomas; Nylander, Tommy; Cardenas Gomez, Marite

    2014-01-01

    The high complexity of biological membranes has motivated the development and application of a wide range of model membrane systems to study biochemical and biophysical aspects of membranes in situ under well defined conditions. The aim is to provide fundamental understanding of processes control...

  5. Physical models of cell motility

    CERN Document Server

    2016-01-01

    This book surveys the most recent advances in physics-inspired cell movement models. This synergetic, cross-disciplinary effort to increase the fidelity of computational algorithms will lead to a better understanding of the complex biomechanics of cell movement, and stimulate progress in research on related active matter systems, from suspensions of bacteria and synthetic swimmers to cell tissues and cytoskeleton.Cell motility and collective motion are among the most important themes in biology and statistical physics of out-of-equilibrium systems, and crucial for morphogenesis, wound healing, and immune response in eukaryotic organisms. It is also relevant for the development of effective treatment strategies for diseases such as cancer, and for the design of bioactive surfaces for cell sorting and manipulation. Substrate-based cell motility is, however, a very complex process as regulatory pathways and physical force generation mechanisms are intertwined. To understand the interplay between adhesion, force ...

  6. A modeling and control framework for operating large-scale electric power systems under present and newly evolving competitive industry structures

    Directory of Open Access Journals (Sweden)

    Marija D. Ilić

    1995-01-01

    Full Text Available This paper introduces a systematic, structure-based modeling framework for analysis and control of electric power systems for processes evolving over the mid-term and long-term time horizons. Much simpler models than the detailed dynamics specifically for control design at different hierarchical levels are obtained by applying both temporal and spatial separation. These simple models, or the aggregate models, represent the net effect of interactions among interconnected regions on specific hierarchical levels. They are exact, since no assumptions on weak interconnections among the subsystems are made. Moreover they are easily understood in terms of power flows among the regions. The approach is essential for improving present performance of the system. It is also potentially useful in a competitive utility environment in which it is critical to study the interplay between technical and economic processes.

  7. Distention of the Immature Left Ventricle Triggers Development of Endocardial Fibroelastosis: An Animal Model of Endocardial Fibroelastosis Introducing Morphopathological Features of Evolving Fetal Hypoplastic Left Heart Syndrome

    Directory of Open Access Journals (Sweden)

    Shogo Shimada

    2015-01-01

    Full Text Available Background. Endocardial fibroelastosis (EFE, characterized by a diffuse endocardial thickening through collagen and elastin fibers, develops in the human fetal heart restricting growth of the left ventricle (LV. Recent advances in fetal imaging indicate that EFE development is directly associated with a distended, poorly contractile LV in evolving hypoplastic left heart syndrome (HLHS. In this study, we developed an animal model of EFE by introducing this human fetal LV morphopathology to an immature rat heart. Methods and Results. A neonatal donor heart, in which aortic regurgitation (AR was created, was heterotopically transplanted into a recipient adult rat. AR successfully induced the LV morphology of evolving HLHS in the transplanted donor hearts, which resulted in the development of significant EFE covering the entire LV cavity within two weeks postoperatively. In contrast, posttransplants with a competent aortic valve displayed unloaded LVs with a trace of EFE. Conclusions. We could show that distention of the immature LV in combination with stagnant flow triggers EFE development in this animal model. This model would serve as a robust tool to develop therapeutic strategies to treat EFE while providing insight into its pathogenesis.

  8. Using Stem Cells to Model Diseases of the Outer Retina

    Directory of Open Access Journals (Sweden)

    Camille Yvon

    2015-01-01

    Full Text Available Retinal degeneration arises from the loss of photoreceptors or retinal pigment epithelium (RPE. It is one of the leading causes of irreversible blindness worldwide with limited effective treatment options. Generation of induced pluripotent stem cell (IPSC-derived retinal cells and tissues from individuals with retinal degeneration is a rapidly evolving technology that holds a great potential for its use in disease modelling. IPSCs provide an ideal platform to investigate normal and pathological retinogenesis, but also deliver a valuable source of retinal cell types for drug screening and cell therapy. In this review, we will provide some examples of the ways in which IPSCs have been used to model diseases of the outer retina including retinitis pigmentosa (RP, Usher syndrome (USH, Leber congenital amaurosis (LCA, gyrate atrophy (GA, juvenile neuronal ceroid lipofuscinosis (NCL, Best vitelliform macular dystrophy (BVMD and age related macular degeneration (AMD.

  9. Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

    CERN Document Server

    Knabe, Johannes F

    2013-01-01

    Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

  10. Targeted disruption in mice of a neural stem cell-maintaining, KRAB-Zn finger-encoding gene that has rapidly evolved in the human lineage.

    Directory of Open Access Journals (Sweden)

    Huan-Chieh Chien

    Full Text Available Understanding the genetic basis of the physical and behavioral traits that separate humans from other primates is a challenging but intriguing topic. The adaptive functions of the expansion and/or reduction in human brain size have long been explored. From a brain transcriptome project we have identified a KRAB-Zn finger protein-encoding gene (M003-A06 that has rapidly evolved since the human-chimpanzee separation. Quantitative RT-PCR analysis of different human tissues indicates that M003-A06 expression is enriched in the human fetal brain in addition to the fetal heart. Furthermore, analysis with use of immunofluorescence staining, neurosphere culturing and Western blotting indicates that the mouse ortholog of M003-A06, Zfp568, is expressed mainly in the embryonic stem (ES cells and fetal as well as adult neural stem cells (NSCs. Conditional gene knockout experiments in mice demonstrates that Zfp568 is both an NSC maintaining- and a brain size-regulating gene. Significantly, molecular genetic analyses show that human M003-A06 consists of 2 equilibrated allelic types, H and C, one of which (H is human-specific. Combined contemporary genotyping and database mining have revealed interesting genetic associations between the different genotypes of M003-A06 and the human head sizes. We propose that M003-A06 is likely one of the genes contributing to the uniqueness of the human brain in comparison to other higher primates.

  11. Asymmetric evolving random networks

    Science.gov (United States)

    Coulomb, S.; Bauer, M.

    2003-10-01

    We generalize the Poissonian evolving random graph model of M. Bauer and D. Bernard (2003), to deal with arbitrary degree distributions. The motivation comes from biological networks, which are well-known to exhibit non Poissonian degree distributions. A node is added at each time step and is connected to the rest of the graph by oriented edges emerging from older nodes. This leads to a statistical asymmetry between incoming and outgoing edges. The law for the number of new edges at each time step is fixed but arbitrary. Thermodynamical behavior is expected when this law has a large time limit. Although (by construction) the incoming degree distributions depend on this law, this is not the case for most qualitative features concerning the size distribution of connected components, as long as the law has a finite variance. As the variance grows above 1/4, the average being < 1/2, a giant component emerges, which connects a finite fraction of the vertices. Below this threshold, the distribution of component sizes decreases algebraically with a continuously varying exponent. The transition is of infinite order, in sharp contrast with the case of static graphs. The local-in-time profiles for the components of finite size allow to give a refined description of the system.

  12. Functional imaging studies of emotion regulation: A synthetic review and evolving model of the cognitive control of emotion

    Science.gov (United States)

    Ochsner, Kevin N.; Silvers, Jennifer A.; Buhle, Jason T.

    2014-01-01

    This paper reviews and synthesizes functional imaging research that over the past decade has begun to offer new insights into the brain mechanisms underlying emotion regulation. Towards that end, the first section of the paper outlines a model of the processes and neural systems involved in emotion generation and regulation. The second section surveys recent research supporting and elaborating the model, focusing primarily on studies of the most commonly investigated strategy, which is known as reappraisal. At its core, the model specifies how prefrontal and cingulate control systems modulate activity in perceptual, semantic and affect systems as a function of one's regulatory goals, tactics, and the nature of the stimuli and emotions being regulated. This section also shows how the model can be generalized to understand the brain mechanisms underlying other emotion regulation strategies as well as a range of other allied phenomena. The third and last section considers directions for future research, including how basic models of emotion regulation can be translated to understand changes in emotion across the lifespan and in clinical disorders. PMID:23025352

  13. Evolving MCDM Applications Using Hybrid Expert-Based ISM and DEMATEL Models: An Example of Sustainable Ecotourism

    Directory of Open Access Journals (Sweden)

    Huan-Ming Chuang

    2013-01-01

    Full Text Available Ecological degradation is an escalating global threat. Increasingly, people are expressing awareness and priority for concerns about environmental problems surrounding them. Environmental protection issues are highlighted. An appropriate information technology tool, the growing popular social network system (virtual community, VC, facilitates public education and engagement with applications for existent problems effectively. Particularly, the exploration of related involvement behavior of VC member engagement is an interesting topic. Nevertheless, member engagement processes comprise interrelated sub-processes that reflect an interactive experience within VCs as well as the value co-creation model. To address the top-focused ecotourism VCs, this study presents an application of a hybrid expert-based ISM model and DEMATEL model based on multi-criteria decision making tools to investigate the complex multidimensional and dynamic nature of member engagement. Our research findings provide insightful managerial implications and suggest that the viral marketing of ecotourism protection is concerned with practitioners and academicians alike.

  14. Evolving MCDM applications using hybrid expert-based ISM and DEMATEL models: an example of sustainable ecotourism.

    Science.gov (United States)

    Chuang, Huan-Ming; Lin, Chien-Ku; Chen, Da-Ren; Chen, You-Shyang

    2013-01-01

    Ecological degradation is an escalating global threat. Increasingly, people are expressing awareness and priority for concerns about environmental problems surrounding them. Environmental protection issues are highlighted. An appropriate information technology tool, the growing popular social network system (virtual community, VC), facilitates public education and engagement with applications for existent problems effectively. Particularly, the exploration of related involvement behavior of VC member engagement is an interesting topic. Nevertheless, member engagement processes comprise interrelated sub-processes that reflect an interactive experience within VCs as well as the value co-creation model. To address the top-focused ecotourism VCs, this study presents an application of a hybrid expert-based ISM model and DEMATEL model based on multi-criteria decision making tools to investigate the complex multidimensional and dynamic nature of member engagement. Our research findings provide insightful managerial implications and suggest that the viral marketing of ecotourism protection is concerned with practitioners and academicians alike.

  15. Evolving digital ecological networks.

    Directory of Open Access Journals (Sweden)

    Miguel A Fortuna

    Full Text Available "It is hard to realize that the living world as we know it is just one among many possibilities" [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism. Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved.

  16. A depth-averaged debris-flow model that includes the effects of evolving dilatancy. I. physical basis

    Science.gov (United States)

    Iverson, Richard M.; George, David L.

    2014-01-01

    To simulate debris-flow behaviour from initiation to deposition, we derive a depth-averaged, two-phase model that combines concepts of critical-state soil mechanics, grain-flow mechanics and fluid mechanics. The model's balance equations describe coupled evolution of the solid volume fraction, m, basal pore-fluid pressure, flow thickness and two components of flow velocity. Basal friction is evaluated using a generalized Coulomb rule, and fluid motion is evaluated in a frame of reference that translates with the velocity of the granular phase, vs. Source terms in each of the depth-averaged balance equations account for the influence of the granular dilation rate, defined as the depth integral of ∇⋅vs. Calculation of the dilation rate involves the effects of an elastic compressibility and an inelastic dilatancy angle proportional to m−meq, where meq is the value of m in equilibrium with the ambient stress state and flow rate. Normalization of the model equations shows that predicted debris-flow behaviour depends principally on the initial value of m−meq and on the ratio of two fundamental timescales. One of these timescales governs downslope debris-flow motion, and the other governs pore-pressure relaxation that modifies Coulomb friction and regulates evolution of m. A companion paper presents a suite of model predictions and tests.

  17. Beyond anaemia management: evolving role of erythropoietin therapy in neurological disorders, multiple myeloma and tumour hypoxia models.

    Science.gov (United States)

    Boogaerts, Marc; Mittelman, Moshe; Vaupel, Peter

    2005-01-01

    Recombinant human erythropoietin (epoetin) has become the standard of care in the treatment of anaemia resulting from cancer and its treatment, and chronic kidney disease. The discovery that erythropoietin and its receptor are located in regions outside the erythropoietic system has led to interest in the potential role of epoetin in other tissues, such as the central nervous system. Animal studies have shown that systemically applied epoetin can cross the blood-brain barrier, where it reduces tissue injury associated with stroke, blunt trauma and experimental autoimmune encephalomyelitis. Pilot studies in humans have shown that epoetin treatment given within 8 h of stroke reduces infarct size and results in a significantly better outcome when compared with placebo treatment. Studies also suggest that epoetin has the potential to improve cognitive impairment associated with adjuvant chemotherapy in patients with cancer. Anaemia is a major factor causing tumour hypoxia, a condition that can promote changes within neoplastic cells that further tumour survival and malignant progression and also reduces the effectiveness of several anticancer therapies including radiotherapy and oxygen-dependent cytotoxic agents. Use of epoetin to prevent or correct anaemia has the potential to reduce tumour hypoxia and improve treatment outcome. Several therapeutic studies in anaemic animals with experimental tumours have shown a beneficial effect of epoetin on delaying tumour growth. Furthermore, clinical observations in patients with multiple myeloma and animal studies have suggested that epoetin has an antimyeloma effect, mediated via the immune system through activation of CD8+ T cells. Therefore, the role of epoetin may go well beyond that of increasing haemoglobin levels in anaemic patients, although additional studies are required to confirm these promising results. Copyright 2005 S. Karger AG, Basel.

  18. The Battlefield Health and Trauma Research Institute Scientific Ethics Committee: An Evolving Model for Fostering a Culture of Integrity

    Science.gov (United States)

    2012-01-01

    grants and contracts.8 The ORI defines research misconduct as ‘‘fabrication, falsification, or plagiarism in proposing, performing, or reviewing research...fabrication, falsification, or plagiarism (FFP) is only 1% to 2%, based on self-reporting.10,11 However, approx- imately 33% of scientists admitted...provide investigators training and guidance? THE ACADEMIC MODEL Just as regulations governing the ethical use of human and animal research subjects grew

  19. The Evolving role of Tier2s in ATLAS with the new Computing and Data Distribution Model

    CERN Document Server

    Gonzalez de la Hoz, S; The ATLAS collaboration

    2012-01-01

    Originally the ATLAS computing model assumed that the Tier2s of each of the 10 clouds should keep on disk collectively at least one copy of all "active" AOD and DPD datasets. Evolution of ATLAS computing and data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. Tier2 operations take place completely asynchronously with respect to data taking. Tier2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier1s but will progressively move to Tier2s as well. The availability of disk space at Tier2s is extremely important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used mo...

  20. The evolving role of Tier2s in ATLAS with the new Computing and Data Distribution model

    CERN Document Server

    Gonzalez de la Hoz, S

    2012-01-01

    Originally the ATLAS computing model assumed that the Tier2s of each of the 10 clouds should keep on disk collectively at least one copy of all "active" AOD and DPD datasets. Evolution of ATLAS computing and data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. Tier2 operations take place completely asynchronously with respect to data taking. Tier2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier1s but will progressively move to Tier2s as well. The availability of disk space at Tier2s is extremely important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used mo...

  1. MATRIX-VBS (v1.0): implementing an evolving organic aerosol volatility in an aerosol microphysics model

    Science.gov (United States)

    Gao, Chloe Y.; Tsigaridis, Kostas; Bauer, Susanne E.

    2017-02-01

    The gas-particle partitioning and chemical aging of semi-volatile organic aerosol are presented in a newly developed box model scheme, where its effect on the growth, composition, and mixing state of particles is examined. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often also with an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish forest, and a southeastern US forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the intermediate-volatility range, while they remain in the particle phase in the low-volatility range. Their volatility distribution at any point in time depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensed-phase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases.

  2. MATRIX-VBS (v1.0): Implementing an Evolving Organic Aerosol Volatility in an Aerosol Microphysics Model

    Science.gov (United States)

    Gao, Chloe Y.; Tsigaridis, Kostas; Bauer, Susanne E.

    2017-01-01

    The gas-particle partitioning and chemical aging of semi-volatile organic aerosol are presented in a newly developed box model scheme, where its effect on the growth, composition, and mixing state of particles is examined. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often also with an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish forest, and a southeastern US forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the intermediate-volatility range, while they remain in the particle phase in the low-volatility range. Their volatility distribution at any point in time depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensed-phase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases.

  3. CADUCEUS, SCIPIO, ALCADIA: Cell therapy trials using cardiac-°©‐derived cells for patients with post myocardial infarction LV dysfunction, still evolving

    Directory of Open Access Journals (Sweden)

    Magdi H Yacoub

    2012-03-01

    Full Text Available The early results of the CArdiosphere-Derived aUtologous stem CElls to reverse ventricUlar dySfunction study were recently published in the Lancet [1]. This study is a phase 1 prospective randomised study, performed at two centres. The study was designed to test the hypothesis that intracoronary infusion of autologous cardiac-derived cells following myocardial infarction can reduce the size of the infarct and increase the amount of viable myocardium. The eligible patients were randomised in a 2:1 ratio to receive CDCs or standard care. In all, 17 patients were randomised to cell therapy and 8 to standard care. The cell therapy consisted of an infusion of 25 million cells into the infarct related artery, 1.5–3 months after successful primary angioplasty in patients who developed LV dysfunction (EF less than 37 per cent. The cells were derived from RV endomyocardial biopsies performed within the previous 37 days. The number of cells was determined from previous experimental studies of the maximum number of cells which can be injected without inducing infarction. The study was not blinded because of ethical considerations regarding performing right ventricular biopsy on the controls. The exclusion criteria included patients who had evidence of right ventricular infarction, or could not have an MRI examination because of claustrophobia or prior insertion of devices. There was no death, myocardial infarction or serious arrhythmia reported in either group during the period of follow up, which was between 6-12 months. Serious adverse events were observed in 24 percent of the intervention group versus 12 per cent in the controls (p not significant.

  4. The evolving market structures of gambling: case studies modelling the socioeconomic assignment of gaming machines in Melbourne and Sydney, Australia.

    Science.gov (United States)

    Marshall, David C; Baker, Robert G V

    2002-01-01

    The expansion of gambling industries worldwide is intertwined with the growing government dependence on gambling revenue for fiscal assignments. In Australia, electronic gaming machines (EGMs) have dominated recent gambling industry growth. As EGMs have proliferated, growing recognition has emerged that EGM distribution closely reflects levels of socioeconomic disadvantage. More machines are located in less advantaged regions. This paper analyses time-series socioeconomic distributions of EGMs in Melbourne, Australia, an immature EGM market, and then compares the findings with the mature market in Sydney. Similar findings in both cities suggest that market assignment of EGMs transcends differences in historical and legislative environments. This indicates that similar underlying structures are evident in both markets. Modelling the spatial structures of gambling markets provides an opportunity to identify regions most at risk of gambling related problems. Subsequently, policies can be formulated which ensure fiscal revenue from gambling can be better targeted towards regions likely to be most afflicted by excessive gambling-related problems.

  5. PEM Fuel Cells - Fundamentals, Modeling and Applications

    OpenAIRE

    Maher A.R. Sadiq Al-Baghdadi

    2013-01-01

    Part I: Fundamentals Chapter 1: Introduction. Chapter 2: PEM fuel cell thermodynamics, electrochemistry, and performance. Chapter 3: PEM fuel cell components. Chapter 4: PEM fuel cell failure modes. Part II: Modeling and Simulation Chapter 5: PEM fuel cell models based on semi-empirical simulation. Chapter 6: PEM fuel cell models based on computational fluid dynamics. Part III: Applications Chapter 7: PEM fuel cell system design and applications.

  6. Age-associated DNA methylation changes in naive CD4+T cells suggest an evolving autoimmune epigenotype in aging T cells.

    Science.gov (United States)

    Dozmorov, Mikhail G; Coit, Patrick; Maksimowicz-McKinnon, Kathleen; Sawalha, Amr H

    2017-04-01

    We sought to define age-associated DNA methylation changes in naive CD4 + T cells. Naive CD4 + T cells were collected from 74 healthy individuals (age 19-66 years), and age-related DNA methylation changes were characterized. We identified 11,431 age-associated CpG sites, 57% of which were hypermethylated with age. Hypermethylated sites were enriched in CpG islands and repressive transcription factor binding sites, while hypomethylated sites showed T cell specific enrichment in active enhancers marked by H3K27ac and H3K4me1. Our data emphasize cancer-related DNA methylation changes with age, and also reveal age-associated hypomethylation in immune-related pathways, such as T cell receptor signaling, FCγR-mediated phagocytosis, apoptosis and the mammalian target of rapamycin signaling pathway. The MAPK signaling pathway was hypermethylated with age, consistent with a defective MAPK signaling in aging T cells. Age-associated DNA methylation changes may alter regulatory mechanisms and signaling pathways that predispose to autoimmunity.

  7. Genomic, RNAseq, and Molecular Modeling Evidence Suggests That the Major Allergen Domain in Insects Evolved from a Homodimeric Origin

    Science.gov (United States)

    Randall, Thomas A.; Perera, Lalith; London, Robert E.; Mueller, Geoffrey A.

    2013-01-01

    The major allergen domain (MA) is widely distributed in insects. The crystal structure of a single Bla g 1 MA revealed a novel protein fold in which the fundamental structure was a duplex of two subsequences (monomers), which had diverged over time. This suggested that the evolutionary origin of the MA structure may have been a homodimer of this smaller subsequence. Using publicly available genomic data, the distribution of the basic unit of this class of proteins was determined to better understand its evolutionary history. The duplication and divergence is examined at three distinct levels of resolution: 1) within the orders Diptera and Hymenoptera, 2) within one genus Drosophila, and 3) within one species Aedes aegypti. Within the family Culicidae, we have found two separate occurrences of monomers as independent genes. The organization of the gene family in A. aegypti shows a common evolutionary origin for its monomer and several closely related MAs. Molecular modeling of the A. aegypti monomer with the unique Bla g 1 fold confirms the distant evolutionary relationship and supports the feasibility of homodimer formation from a single monomer. RNAseq data for A. aegypti confirms that the monomer is expressed in the mosquito similar to other A. aegypti MAs after a blood meal. Together, these data support the contention that the detected monomer shares similar functional characteristics to related MAs in other insects. An extensive search for this domain outside of Insecta confirms that the MAs are restricted to insects. PMID:24253356

  8. SU-B-BRF-01: Professional Council Symposium: The Evolving US Healthcare Delivery Model, How Will the Medical Physics Profession Be Impacted and How Should We Respond?

    Energy Technology Data Exchange (ETDEWEB)

    Halvorsen, P [Lahey Clinic, Burlington, MA (United States); Shine, K [Austin, TX (United States); White, G [Colorado Associates in Medical Phys, Colorado Springs, CO (United States)

    2014-06-15

    The United States' healthcare delivery model is undergoing significant change. Insurance and reimbursement models are rapidly evolving, federal allocations are shifting from specialty services to preventive and generalpractice services, and Accountable Care Organizations are gaining in prominence. One area of focus is on the perceived over-utilization of expensive services such as advanced imaging and, in some cases, radiation therapy. Reimbursement incentives are increasingly aimed at quality metrics, leading to an increased interest in the core concepts of High Reliability Organizations. With the shift in federal resources away from specialty services and the increasing prominence of Accountable Care Organizations, we will likely be challenged to re-assess our traditional model for delivering medical physics services. Medical physicists have a unique combination of education and training in physics principles, radiation physics applications in medicine, human anatomy, as well as safety analysis and quality control methods. An effective medical physicist recognizes that to advance the institution's mission, the medical physicist must join other professional leaders within the institution to provide clear direction and perspective for the entire team. To do that, we must first recognize the macro changes in our healthcare delivery system and candidly assess how the medical physics practice model can evolve in a prudent way to support the institution's objectives while maintaining the traditionally high level of quality and safety. This year's Professional Council Symposium will explore the many facets of the changing healthcare system and its potential impact on medical physics. Dr. Shine will provide an overview of the developing healthcare delivery and reimbursement models, with a focus on how the physician community has adapted to the changing objectives. Mr. White will describe recent changes in the reimbursement patterns for both imaging

  9. Mental models vs cell schemes

    Directory of Open Access Journals (Sweden)

    Mª Luz Rodríguez Palmero

    2002-01-01

    Full Text Available Student's mental representations of cell are examined from the perspectives of Johnson-Laird's mental models theory five years after instruction. The observed identity and stability of such representations are then interpreted under the framework of Vergnaud's conceptual fields theory. From the findings of these analyses some connections between these theories which might help in understanding the cognitive processes in learning scientific concepts, are established.

  10. Measurably evolving populations

    DEFF Research Database (Denmark)

    Drummond, Alexei James; Pybus, Oliver George; Rambaut, Andrew

    2003-01-01

    processes through time. Populations for which such studies are possible � measurably evolving populations (MEPs) � are characterized by sufficiently long or numerous sampled sequences and a fast mutation rate relative to the available range of sequence sampling times. The impact of sequences sampled through...... understanding of evolutionary processes in diverse organisms, from viruses to vertebrates....

  11. Electron spin-lattice relaxation of the S0 state of the oxygen-evolving complex in photosystem II and of dinuclear manganese model complexes.

    Science.gov (United States)

    Kulik, L V; Lubitz, W; Messinger, J

    2005-07-05

    The temperature dependence of the electron spin-lattice relaxation time T1 was measured for the S0 state of the oxygen-evolving complex (OEC) in photosystem II and for two dinuclear manganese model complexes by pulse EPR using the inversion-recovery method. For [Mn(III)Mn(IV)(mu-O)2 bipy4]ClO4, the Raman relaxation process dominates at temperatures below 50 K. In contrast, Orbach type relaxation was found for [Mn(II)Mn(III)(mu-OH)(mu-piv)2(Me3 tacn)2](ClO4)2 between 4.3 and 9 K. For the latter complex, an energy separation of 24.7-28.0 cm(-1) between the ground and the first excited electronic state was determined. In the S0 state of photosystem II, the T1 relaxation times were measured in the range of 4.3-6.5 K. A comparison with the relaxation data (rate and pre-exponential factor) of the two model complexes and of the S2 state of photosystem II indicates that the Orbach relaxation process is dominant for the S0 state and that its first excited state lies 21.7 +/- 0.4 cm(-1) above its ground state. The results are discussed with respect to the structure of the OEC in photosystem II.

  12. Fractionation and current time trends of PCB congeners: evolvement of distributions 1950–2010 studied using a global atmosphere-ocean general circulation model

    Directory of Open Access Journals (Sweden)

    G. Lammel

    2012-08-01

    Full Text Available PCBs are ubiquitous environmental pollutants expected to decline in abiotic environmental media in response to decreasing primary emissions since the 1970s. A coupled atmosphere-ocean general circulation model with embedded dynamic sub-models for atmospheric aerosols and the marine biogeochemistry and air-surface exchange processes with soils, vegetation and the cryosphere is used to study the transport and fate of four PCB congeners covering a range of 3–7 chlorine atoms.

    The change of the geographic distribution of the PCB mixture reflects the sources and sinks' evolvement over time. Globally, secondary emissions (re-volatilisation from surfaces are on the long term increasingly gaining importance over primary emissions. Secondary emissions are most important for the congeners with 5–6 chlorine atoms. Correspondingly, the levels of these congeners are predicted to decrease slowest. Changes in congener mixture composition (fractionation are characterized both geographically and temporally. In high latitudes enrichment of the lighter, less persistent congeners and more delayed decreasing levels in response to decreasing emissions are found. The delivery of the contaminants to high latitudes is predicted to be more efficient than previously suggested. The results suggest furthermore that the effectiveness of emission control measures may significantly vary among substances. The trends of decline of organic contaminant levels in the abiotic environmental media do not only vary with latitude (slow in high latitudes, but do also show longitudinal gradients.

  13. EVOLVE 2014 International Conference

    CERN Document Server

    Tantar, Emilia; Sun, Jian-Qiao; Zhang, Wei; Ding, Qian; Schütze, Oliver; Emmerich, Michael; Legrand, Pierrick; Moral, Pierre; Coello, Carlos

    2014-01-01

    This volume encloses research articles that were presented at the EVOLVE 2014 International Conference in Beijing, China, July 1–4, 2014.The book gathers contributions that emerged from the conference tracks, ranging from probability to set oriented numerics and evolutionary computation; all complemented by the bridging purpose of the conference, e.g. Complex Networks and Landscape Analysis, or by the more application oriented perspective. The novelty of the volume, when considering the EVOLVE series, comes from targeting also the practitioner’s view. This is supported by the Machine Learning Applied to Networks and Practical Aspects of Evolutionary Algorithms tracks, providing surveys on new application areas, as in the networking area and useful insights in the development of evolutionary techniques, from a practitioner’s perspective. Complementary to these directions, the conference tracks supporting the volume, follow on the individual advancements of the subareas constituting the scope of the confe...

  14. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  15. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  16. EVOLVE : International Conference

    CERN Document Server

    Deutz, Andre; Schuetze, Oliver; Bäck, Thomas; Tantar, Emilia; Tantar, Alexandru-Adrian; Moral, Pierre; Legrand, Pierrick; Bouvry, Pascal; Coello, Carlos

    2013-01-01

    Numerical and computational methods are nowadays used in a wide range of contexts in complex systems research, biology, physics, and engineering.  Over the last decades different methodological schools have emerged with emphasis on different aspects of computation, such as nature-inspired algorithms, set oriented numerics, probabilistic systems and Monte Carlo methods. Due to the use of different terminologies and emphasis on different aspects of algorithmic performance there is a strong need for a more integrated view and opportunities for cross-fertilization across particular disciplines. These proceedings feature 20 original publications from distinguished authors in the cross-section of computational sciences, such as machine learning algorithms and probabilistic models, complex networks and fitness landscape analysis, set oriented numerics and cell mapping, evolutionary multiobjective optimization, diversity-oriented search, and the foundations of genetic programming algorithms. By presenting cutting ed...

  17. [Studies of the origin of malignant rhabdoid tumor(MRT)--experimental researches on the MRT evolving in nude mice inoculated with violently variable HeLa cells].

    Science.gov (United States)

    Zhang, D L; Huang, G S; Li, L J; He, X Y; Xia, G T; Gao, B X; Bai, X H; Liu, S G

    2000-01-01

    of one test group inoculated subcutaneously with 0.17 ml cell-cultures of super-high density containing 12.75 x 10(7) HeLa cells of KB strain on passages 10-11(with the rate of chromosome aberration high to 20% on passages 10-11 including 18% dicentric chromosome and 2% breakage chromosome). Although the incidence of MRT in nude mice inoculated subcutaneously with violently variable HeLa cells of NM20/X strain on passage 11, HeLa cells of KB strain on passages 10-11 reaches 100%(5/5) & 100%(4/4) respectively, yet it is requested that the inoculated live cell number is huge (5-12 x 10(7) cells per nude mouse), the tumor emerges immediately, develops violently, grows very fast, and has an extremely aggressive malignancy, the tumor is rich in the blood vessel giving a full supply of blood for it, and the mean value of major diameter X minor diameter of the tumor is essentially up to the standard of 30 mm x 20 mm in 16-22 days after the inoculation of the cells into the nude mice. The first finding of MRT in model animals provides an opportunity for answering the origin problem of MRT. Based on this reason, human uterus vertical epithelium may be an original tissue of MRT, thus opening up a new era for the research of MRT origin. It is also concluded as follows: 1. Cellular tumorigenicity is different among differently-karyotypic cells. 2. Highly variable strain of tumor cell line can be selected quickly and successfully in nude mouse. 3. Cellular tumorigenicity may be increased if chromosome aberration is very high. 4. The genetic characteristics of chromosomes of HeLa cells determines their tumorigenicity, chromosome number variation of HeLa cells has positive relationship with their carcinogenesis or tumorigenicity, and the turn of HeLa cells concerning their tumorigenicity from weak to strong is KB, X and NM20/X strains (excluding H strain, in which tumorigenicity remains to be determined by further experiments) respectively.

  18. Single-cell model of prokaryotic cell cycle.

    Science.gov (United States)

    Abner, Kristo; Aaviksaar, Tõnis; Adamberg, Kaarel; Vilu, Raivo

    2014-01-21

    One of the recognized prokaryotic cell cycle theories is Cooper-Helmstetter (CH) theory which relates start of DNA replication to particular (initiation) cell mass, cell growth and division. Different aspects of this theory have been extensively studied in the past. In the present study CH theory was applied at single cell level. Universal equations were derived for different cell parameters (cell mass and volume, surface area, DNA amount and content) depending on constructivist cell cycle parameters (unit mass, replication and division times, cell age, cell cycle duration) based on selected growth laws of cell mass (linear, exponential). The equations derived can be integrated into single-cell models for the analysis and design of bacterial cells. © 2013 Published by Elsevier Ltd.

  19. Analyzing Evolving Social Network 2 (EVOLVE2)

    Science.gov (United States)

    2015-04-01

    social media. We have demonstrated recently that information spread cannot be modeled as an epidemic diffusion. Instead, cognitive constraints, such as...respond to any one stimulus. Cognitive constraints the nature of social interactions and therefore, how central nodes are identified. Now a node’s...link prediction task and their properties. network nodes edges missing density social networks dolphins 62 159 16 0.084 email 1133 5452 545 0.0085

  20. In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

    Science.gov (United States)

    Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun

    2017-07-14

    Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 104 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

  1. Regolith Evolved Gas Analyzer

    Science.gov (United States)

    Hoffman, John H.; Hedgecock, Jud; Nienaber, Terry; Cooper, Bonnie; Allen, Carlton; Ming, Doug

    2000-01-01

    The Regolith Evolved Gas Analyzer (REGA) is a high-temperature furnace and mass spectrometer instrument for determining the mineralogical composition and reactivity of soil samples. REGA provides key mineralogical and reactivity data that is needed to understand the soil chemistry of an asteroid, which then aids in determining in-situ which materials should be selected for return to earth. REGA is capable of conducting a number of direct soil measurements that are unique to this instrument. These experimental measurements include: (1) Mass spectrum analysis of evolved gases from soil samples as they are heated from ambient temperature to 900 C; and (2) Identification of liberated chemicals, e.g., water, oxygen, sulfur, chlorine, and fluorine. REGA would be placed on the surface of a near earth asteroid. It is an autonomous instrument that is controlled from earth but does the analysis of regolith materials automatically. The REGA instrument consists of four primary components: (1) a flight-proven mass spectrometer, (2) a high-temperature furnace, (3) a soil handling system, and (4) a microcontroller. An external arm containing a scoop or drill gathers regolith samples. A sample is placed in the inlet orifice where the finest-grained particles are sifted into a metering volume and subsequently moved into a crucible. A movable arm then places the crucible in the furnace. The furnace is closed, thereby sealing the inner volume to collect the evolved gases for analysis. Owing to the very low g forces on an asteroid compared to Mars or the moon, the sample must be moved from inlet to crucible by mechanical means rather than by gravity. As the soil sample is heated through a programmed pattern, the gases evolved at each temperature are passed through a transfer tube to the mass spectrometer for analysis and identification. Return data from the instrument will lead to new insights and discoveries including: (1) Identification of the molecular masses of all of the gases

  2. Modeling population dynamics of mitochondria in mammalian cells

    Science.gov (United States)

    Kornick, Kellianne; Das, Moumita

    Mitochondria are organelles located inside eukaryotic cells and are essential for several key cellular processes such as energy (ATP) production, cell signaling, differentiation, and apoptosis. All organisms are believed to have low levels of variation in mitochondrial DNA (mtDNA), and alterations in mtDNA are connected to a range of human health conditions, including epilepsy, heart failure, Parkinsons disease, diabetes, and multiple sclerosis. Therefore, understanding how changes in mtDNA accumulate over time and are correlated to changes in mitochondrial function and cell properties can have a profound impact on our understanding of cell physiology and the origins of some diseases. Motivated by this, we develop and study a mathematical model to determine which cellular parameters have the largest impact on mtDNA population dynamics. The model consists of coupled ODEs to describe subpopulations of healthy and dysfunctional mitochondria subject to mitochondrial fission, fusion, autophagy, and mutation. We study the time evolution and stability of each sub-population under specific selection biases and pressures by tuning specific terms in our model. Our results may provide insights into how sub-populations of mitochondria survive and evolve under different selection pressures. This work was supported by a Grant from the Moore Foundation.

  3. Primordial evolvability: Impasses and challenges.

    Science.gov (United States)

    Vasas, Vera; Fernando, Chrisantha; Szilágyi, András; Zachár, István; Santos, Mauro; Szathmáry, Eörs

    2015-09-21

    While it is generally agreed that some kind of replicating non-living compounds were the precursors of life, there is much debate over their possible chemical nature. Metabolism-first approaches propose that mutually catalytic sets of simple organic molecules could be capable of self-replication and rudimentary chemical evolution. In particular, the graded autocatalysis replication domain (GARD) model, depicting assemblies of amphiphilic molecules, has received considerable interest. The system propagates compositional information across generations and is suggested to be a target of natural selection. However, evolutionary simulations indicate that the system lacks selectability (i.e. selection has negligible effect on the equilibrium concentrations). We elaborate on the lessons learnt from the example of the GARD model and, more widely, on the issue of evolvability, and discuss the implications for similar metabolism-first scenarios. We found that simple incorporation-type chemistry based on non-covalent bonds, as assumed in GARD, is unlikely to result in alternative autocatalytic cycles when catalytic interactions are randomly distributed. An even more serious problem stems from the lognormal distribution of catalytic factors, causing inherent kinetic instability of such loops, due to the dominance of efficiently catalyzed components that fail to return catalytic aid. Accordingly, the dynamics of the GARD model is dominated by strongly catalytic, but not auto-catalytic, molecules. Without effective autocatalysis, stable hereditary propagation is not possible. Many repetitions and different scaling of the model come to no rescue. Despite all attempts to show the contrary, the GARD model is not evolvable, in contrast to reflexively autocatalytic networks, complemented by rare uncatalyzed reactions and compartmentation. The latter networks, resting on the creation and breakage of chemical bonds, can generate novel ('mutant') autocatalytic loops from a given set of

  4. Modeling the Shapes of Cells

    Science.gov (United States)

    Garimella, Umadevi I.; Robertson, Belinda M.

    2015-01-01

    A solid understanding of the structure and function of cells can help establish the foundation for learning advanced concepts in the biological sciences. The concept of the cell is introduced in middle school life science courses and is continued at the undergraduate level in college (NRC 2012; Reece et al. 2014). Cells are introduced to students…

  5. Before the endless forms: embodied model of transition from single cells to aggregates to ecosystem engineering.

    Science.gov (United States)

    Solé, Ricard V; Valverde, Sergi

    2013-01-01

    The emergence of complex multicellular systems and their associated developmental programs is one of the major problems of evolutionary biology. The advantages of cooperation over individuality seem well known but it is not clear yet how such increase of complexity emerged from unicellular life forms. Current multicellular systems display a complex cell-cell communication machinery, often tied to large-scale controls of body size or tissue homeostasis. Some unicellular life forms are simpler and involve groups of cells cooperating in a tissue-like fashion, as it occurs with biofilms. However, before true gene regulatory interactions were widespread and allowed for controlled changes in cell phenotypes, simple cellular colonies displaying adhesion and interacting with their environments were in place. In this context, models often ignore the physical embedding of evolving cells, thus leaving aside a key component. The potential for evolving pre-developmental patterns is a relevant issue: how far a colony of evolving cells can go? Here we study these pre-conditions for morphogenesis by using CHIMERA, a physically embodied computational model of evolving virtual organisms in a pre-Mendelian world. Starting from a population of identical, independent cells moving in a fluid, the system undergoes a series of changes, from spatial segregation, increased adhesion and the development of generalism. Eventually, a major transition occurs where a change in the flow of nutrients is triggered by a sub-population. This ecosystem engineering phenomenon leads to a subsequent separation of the ecological network into two well defined compartments. The relevance of these results for evodevo and its potential ecological triggers is discussed.

  6. Before the endless forms: embodied model of transition from single cells to aggregates to ecosystem engineering.

    Directory of Open Access Journals (Sweden)

    Ricard V Solé

    Full Text Available The emergence of complex multicellular systems and their associated developmental programs is one of the major problems of evolutionary biology. The advantages of cooperation over individuality seem well known but it is not clear yet how such increase of complexity emerged from unicellular life forms. Current multicellular systems display a complex cell-cell communication machinery, often tied to large-scale controls of body size or tissue homeostasis. Some unicellular life forms are simpler and involve groups of cells cooperating in a tissue-like fashion, as it occurs with biofilms. However, before true gene regulatory interactions were widespread and allowed for controlled changes in cell phenotypes, simple cellular colonies displaying adhesion and interacting with their environments were in place. In this context, models often ignore the physical embedding of evolving cells, thus leaving aside a key component. The potential for evolving pre-developmental patterns is a relevant issue: how far a colony of evolving cells can go? Here we study these pre-conditions for morphogenesis by using CHIMERA, a physically embodied computational model of evolving virtual organisms in a pre-Mendelian world. Starting from a population of identical, independent cells moving in a fluid, the system undergoes a series of changes, from spatial segregation, increased adhesion and the development of generalism. Eventually, a major transition occurs where a change in the flow of nutrients is triggered by a sub-population. This ecosystem engineering phenomenon leads to a subsequent separation of the ecological network into two well defined compartments. The relevance of these results for evodevo and its potential ecological triggers is discussed.

  7. Thinking Through Computational Exposure as an Evolving Paradign Shift for Exposure Science: Development and Application of Predictive Models from Big Data

    Science.gov (United States)

    Symposium Abstract: Exposure science has evolved from a time when the primary focus was on measurements of environmental and biological media and the development of enabling field and laboratory methods. The Total Exposure Assessment Method (TEAM) studies of the 1980s were class...

  8. Fat: an evolving issue

    Directory of Open Access Journals (Sweden)

    John R. Speakman

    2012-09-01

    Work on obesity is evolving, and obesity is a consequence of our evolutionary history. In the space of 50 years, we have become an obese species. The reasons why can be addressed at a number of different levels. These include separating between whether the primary cause lies on the food intake or energy expenditure side of the energy balance equation, and determining how genetic and environmental effects contribute to weight variation between individuals. Opinion on whether increased food intake or decreased energy expenditure drives the obesity epidemic is still divided, but recent evidence favours the idea that food intake, rather than altered expenditure, is most important. There is more of a consensus that genetics explains most (probably around 65% of weight variation between individuals. Recent advances in genome-wide association studies have identified many polymorphisms that are linked to obesity, yet much of the genetic variance remains unexplained. Finding the causes of this unexplained variation will be an impetus of genetic and epigenetic research on obesity over the next decade. Many environmental factors – including gut microbiota, stress and endocrine disruptors – have been linked to the risk of developing obesity. A better understanding of gene-by-environment interactions will also be key to understanding obesity in the years to come.

  9. Evolving Concepts of Asthma

    Science.gov (United States)

    Ray, Anuradha; Wenzel, Sally E.

    2015-01-01

    Our understanding of asthma has evolved over time from a singular disease to a complex of various phenotypes, with varied natural histories, physiologies, and responses to treatment. Early therapies treated most patients with asthma similarly, with bronchodilators and corticosteroids, but these therapies had varying degrees of success. Similarly, despite initial studies that identified an underlying type 2 inflammation in the airways of patients with asthma, biologic therapies targeted toward these type 2 pathways were unsuccessful in all patients. These observations led to increased interest in phenotyping asthma. Clinical approaches, both biased and later unbiased/statistical approaches to large asthma patient cohorts, identified a variety of patient characteristics, but they also consistently identified the importance of age of onset of disease and the presence of eosinophils in determining clinically relevant phenotypes. These paralleled molecular approaches to phenotyping that developed an understanding that not all patients share a type 2 inflammatory pattern. Using biomarkers to select patients with type 2 inflammation, repeated trials of biologics directed toward type 2 cytokine pathways saw newfound success, confirming the importance of phenotyping in asthma. Further research is needed to clarify additional clinical and molecular phenotypes, validate predictive biomarkers, and identify new areas for possible interventions. PMID:26161792

  10. Evolving endoscopic surgery.

    Science.gov (United States)

    Sakai, Paulo; Faintuch, Joel

    2014-06-01

    Since the days of Albukasim in medieval Spain, natural orifices have been regarded not only as a rather repugnant source of bodily odors, fluids and excreta, but also as a convenient invitation to explore and treat the inner passages of the organism. However, surgical ingenuity needed to be matched by appropriate tools and devices. Lack of technologically advanced instrumentation was a strong deterrent during almost a millennium until recent decades when a quantum jump materialized. Endoscopic surgery is currently a vibrant and growing subspecialty, which successfully handles millions of patients every year. Additional opportunities lie ahead which might benefit millions more, however, requiring even more sophisticated apparatuses, particularly in the field of robotics, artificial intelligence, and tissue repair (surgical suturing). This is a particularly exciting and worthwhile challenge, namely of larger and safer endoscopic interventions, followed by seamless and scarless recovery. In synthesis, the future is widely open for those who use together intelligence and creativity to develop new prototypes, new accessories and new techniques. Yet there are many challenges in the path of endoscopic surgery. In this new era of robotic endoscopy, one will likely need a virtual simulator to train and assess the performance of younger doctors. More evidence will be essential in multiple evolving fields, particularly to elucidate whether more ambitious and complex pathways, such as intrathoracic and intraperitoneal surgery via natural orifice transluminal endoscopic surgery (NOTES), are superior or not to conventional techniques. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

  11. Evolving a photosynthetic organelle

    Directory of Open Access Journals (Sweden)

    Nakayama Takuro

    2012-04-01

    Full Text Available Abstract The evolution of plastids from cyanobacteria is believed to represent a singularity in the history of life. The enigmatic amoeba Paulinella and its 'recently' acquired photosynthetic inclusions provide a fascinating system through which to gain fresh insight into how endosymbionts become organelles. The plastids, or chloroplasts, of algae and plants evolved from cyanobacteria by endosymbiosis. This landmark event conferred on eukaryotes the benefits of photosynthesis - the conversion of solar energy into chemical energy - and in so doing had a huge impact on the course of evolution and the climate of Earth 1. From the present state of plastids, however, it is difficult to trace the evolutionary steps involved in this momentous development, because all modern-day plastids have fully integrated into their hosts. Paulinella chromatophora is a unicellular eukaryote that bears photosynthetic entities called chromatophores that are derived from cyanobacteria and has thus received much attention as a possible example of an organism in the early stages of organellogenesis. Recent studies have unlocked the genomic secrets of its chromatophore 23 and provided concrete evidence that the Paulinella chromatophore is a bona fide photosynthetic organelle 4. The question is how Paulinella can help us to understand the process by which an endosymbiont is converted into an organelle.

  12. Stem cells and models of astrocytomas.

    Science.gov (United States)

    Kamnasaran, Deepak

    2009-04-01

    To provide a critical assessment of current stem-cell based pre-clinical models of astrocytomas (gliomas). Data were archived from MEDLINE using Boolean formatted keyword queries. Top articles were selected for critical analyses depending on the qualitative assessment of the citation index, novelty of the findings, reputation of the research group and relevance to stem-cell based pre-clinical models of astrocytomas. The emergence of stem-cell based pre-clinical models of gliomas offers advantages for cellular transformation studies over other current in-vitro cell cultured based models. Cells utilized in these stem-cell based pre-clinical models are easier to transform, with the induced tumours demonstrating very high molecular and pathological recapitulations of astrocytomas that are derived from humans. These stem-cell based models fall into two categories. In the first, synthetic astrocytes can be differentiated from various stem cell sources such as the nervous system and embryos, and utilized in elegant forward genetic strategies to develop novel astrocytoma pre-clinical models. The second category represents a cancer stem cell pre-clinical model. In this model, glioma stem cells exhibit very high pathological recapitulations of the human tumours, and can be very informative to comprehend the basis of radio-chemoresistance among patients. The quest to develop robust pre-clinical models of astrocytomas is on an ongoing basis. The models are of clinical importance for the discovery of effective treatment modalities that can considerably improve the health of patients with this deadly disease.

  13. Stochastic biophysical modeling of irradiated cells

    CERN Document Server

    Fornalski, Krzysztof Wojciech

    2014-01-01

    The paper presents a computational stochastic model of virtual cells irradiation, based on Quasi-Markov Chain Monte Carlo method and using biophysical input. The model is based on a stochastic tree of probabilities for each cell of the entire colony. Biophysics of the cells is described by probabilities and probability distributions provided as the input. The adaptation of nucleation and catastrophe theories, well known in physics, yields sigmoidal relationships for carcinogenic risk as a function of the irradiation. Adaptive response and bystander effect, incorporated into the model, improves its application. The results show that behavior of virtual cells can be successfully modeled, e.g. cancer transformation, creation of mutations, radioadaptation or radiotherapy. The used methodology makes the model universal and practical for simulations of general processes. Potential biophysical curves and relationships are also widely discussed in the paper. However, the presented theoretical model does not describe ...

  14. The Explanatory Models about the eukaryotic cell by secondary school students

    Directory of Open Access Journals (Sweden)

    Camacho González, Johanna Patricia;

    2012-04-01

    Full Text Available The main objective of this study was to examine the explanatory models of secondary school students, about the structure of the animal eukaryotic cells before and after an didactic intervention, based from the cognitive model of science (Giere, 1992 and the constructivist learning cycle (Sanmartí, 2000. The research took place in two stages: a. Descriptive and interpretative stage, we categorized the explanatory models identified in 18 families of models and b. The pre-experimental stage, it identifies whether there were significant differences between the models before and after the educational intervention by Wilcoxon test and data randomization, ANOVA. The main findings showed that didactic intervention encourages the building of explanatory models, which are characterized by more specialized language, new relationships between the organelles and cellular functions and the ability to incorporate new elements to enrich the school cell model, demonstrating that these models evolve progressively (RodrÍguez and Moreira, 1999; Justi, 2006.

  15. Mathematical modeling of polymer electrolyte fuel cells

    Science.gov (United States)

    Sousa, Ruy; Gonzalez, Ernesto R.

    Fuel cells with a polymer electrolyte membrane have been receiving more and more attention. Modeling plays an important role in the development of fuel cells. In this paper, the state-of-the-art regarding modeling of fuel cells with a polymer electrolyte membrane is reviewed. Modeling has allowed detailed studies concerning the development of these cells, e.g. in discussing the electrocatalysis of the reactions and the design of water-management schemes to cope with membrane dehydration. Two-dimensional models have been used to represent reality, but three-dimensional models can cope with some important additional aspects. Consideration of two-phase transport in the air cathode of a proton exchange membrane fuel cell seems to be very appropriate. Most fuel cells use hydrogen as a fuel. Besides safety concerns, there are problems associated with production, storage and distribution of this fuel. Methanol, as a liquid fuel, can be the solution to these problems and direct methanol fuel cells (DMFCs) are attractive for several applications. Mass transport is a factor that may limit the performance of the cell. Adsorption steps may be coupled to Tafel kinetics to describe methanol oxidation and methanol crossover must also be taken into account. Extending the two-phase approach to the DMFC modeling is a recent, important point.

  16. F-cell: The Aspen fuel cell model

    Science.gov (United States)

    Regenhardt, P. A.

    1985-03-01

    This report documents the fuel cell model created at the Morgantown Energy Technology Center for systems simulations that use the Advanced System for Process Engineering (ASPEN) simulator. The report includes: (1) an explanation of the thermodynamics involved, (2) an explanation of the efficiencies used to describe and compare a fuel cell, (3) the FORTRAN code and ASPEN system definition file entries required to install the model into the ASPEN system, (4) three sample ASPEN input files demonstrating how the model could be used for phosphoric acid, molten carbonate, and solid oxide fuel cells, (5) a detailed ASPEN input file that simulates a commercial 40-kW phosphoric acid fuel cell system, and (6) the technical and the user entries for the ASPEN manuals. F-CELL is designed to use the results of either a mechanistic model or experimental data to model a fuel cell in a system study. A double set of efficiencies is produced; the first is calculated from the user's input, and the second is based on ASPEN's results. The second set of efficiencies serves as a check on the input data and is not used in any internal calculations. The model also checks for carbon deposition.

  17. Metabolic memory: Evolving concepts.

    Science.gov (United States)

    Misra, Anoop; Bloomgarden, Zachary

    2018-03-01

    to standard control. However, the UKPDS blood pressure control trial showed a reduction in complications, but no difference between the intervention and control groups was seen during the follow-up of this portion of the study, suggesting that no such "memory" exists for these interventions. The molecular mechanisms underlying these long-term effects of prior periods of better or worse glycemic control continue to be investigated. Extended periods of exposure to high glucose levels persistently dysregulated fibrotic and inflammatory genes in endothelial and vascular smooth muscle cells. Furthermore, epigenetic processes may contribute to metabolic memory, with evidence that post-translational histone methylation and changes in microRNA may persist after exposure to high glucose levels is terminated. In this context, it is of note that the zebrafish model of T1D exhibits regeneration of the pancreas, becoming euglycemic after a period of hyperglycemia, but with evidence in this model that delay in skin wound healing persists indefinitely even after multiple rounds of fin regeneration, suggesting a long-lasting adverse effect of prior hyperglycemia. Such epigenetic differences were reported in genes related to the nuclear factor-κB inflammatory pathway and to diabetes complications in a study of intensive versus conventional treatment patients followed from the DCCT. A further mechanism that has been suggested is a role of dysregulated mitochondrial biogenesis contributing to deterioration of retinopathy even after a period of good glycemic control continues. Interestingly, in this issue of the Journal, Pantalone et al. present a study that touches upon our first question, failing to find a relationship between the HbA1c level measured at the time of diabetes diagnosis and subsequent outcome. The study analyzed relationships between glycemic control and complications among >30 000 people with newly diagnosed T2D followed for the subsequent decade. Might the level of

  18. Modeling cell behavior: moving beyond intuition

    Directory of Open Access Journals (Sweden)

    Mario Jolicoeur

    2014-04-01

    Full Text Available In the context of the launching of this new journal, we propose a forum to the community of researchers interested and involved in, or even simply questioning the why, what, how, and when of modeling cell or cell culture behavior. To start the discussion, we review some of the usual questions we are routinely asked on the pertinence of modeling cell behavior, and on who might benefit from conducting such work. To draw a global portrait, throughout this text we refer the reader to handbooks introducing the basics of modeling a biosystem, as well as to selected works that can help visualize the broad fields of applications.

  19. Microbial cell modeling via reacting diffusive particles

    Science.gov (United States)

    Plimpton, Steven J.; Slepoy, Alex

    2005-01-01

    We describe a particle-based simulator called ChemCell that we are developing with the goal of modeling the protein chemistry of biological cells for phenomena where spatial effects are important. Membranes and organelle structure are represented by triangulated surfaces. Diffusing particles represent proteins, complexes, or other biomolecules of interest. Particles interact with their neighbors in accord with Monte Carlo rules to perform biochemical reactions which can represent protein complex formation and dissociation, ligand binding, etc. In this brief paper we give the motivation for such a model, describe a few of the code's features, and highlight interesting computational issues that arise in particle-based cell modeling.

  20. On a poroviscoelastic model for cell crawling

    KAUST Repository

    Kimpton, L. S.

    2014-02-08

    In this paper a minimal, one-dimensional, two-phase, viscoelastic, reactive, flow model for a crawling cell is presented. Two-phase models are used with a variety of constitutive assumptions in the literature to model cell motility. We use an upper-convected Maxwell model and demonstrate that even the simplest of two-phase, viscoelastic models displays features relevant to cell motility. We also show care must be exercised in choosing parameters for such models as a poor choice can lead to an ill-posed problem. A stability analysis reveals that the initially stationary, spatially uniform strip of cytoplasm starts to crawl in response to a perturbation which breaks the symmetry of the network volume fraction or network stress. We also demonstrate numerically that there is a steady travelling-wave solution in which the crawling velocity has a bell-shaped dependence on adhesion strength, in agreement with biological observation.

  1. Natural selection promotes antigenic evolvability

    NARCIS (Netherlands)

    Graves, C.J.; Ros, V.I.D.; Stevenson, B.; Sniegowski, P.D.; Brisson, D.

    2013-01-01

    The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide

  2. Disgust: Evolved function and structure

    NARCIS (Netherlands)

    Tybur, J.M.; Lieberman, D.; Kurzban, R.; DeScioli, P.

    2013-01-01

    Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and

  3. A computational model of amoeboid cell swimming

    Science.gov (United States)

    Campbell, Eric J.; Bagchi, Prosenjit

    2017-10-01

    Amoeboid cells propel by generating pseudopods that are finger-like protrusions of the cell body that continually grow, bifurcate, and retract. Pseudopod-driven motility of amoeboid cells represents a complex and multiscale process that involves bio-molecular reactions, cell deformation, and cytoplasmic and extracellular fluid motion. Here we present a 3D model of pseudopod-driven swimming of an amoeba suspended in a fluid without any adhesion and in the absence of any chemoattractant. Our model is based on front-tracking/immersed-boundary methods, and it combines large deformation of the cell, a coarse-grain model for molecular reactions, and cytoplasmic and extracellular fluid flow. The predicted shapes of the swimming cell from our model show similarity with experimental observations. We predict that the swimming behavior changes from random-like to persistent unidirectional motion, and that the swimming speed increases, with increasing cell deformability and protein diffusivity. The unidirectionality in cell swimming is observed without any external cues and as a direct result of a change in pseudopod dynamics. We find that pseudopods become preferentially focused near the front of the cell and appear in greater numbers with increasing cell deformability and protein diffusivity, thereby increasing the swimming speed and making the cell shape more elongated. We find that the swimming speed is minimum when the cytoplasm viscosity is close to the extracellular fluid viscosity. We further find that the speed increases significantly as the cytoplasm becomes less viscous compared with the extracellular fluid, resembling the viscous fingering phenomenon observed in interfacial flows. While these results support the notion that softer cells migrate more aggressively, they also suggest a strong coupling between membrane elasticity, membrane protein diffusivity, and fluid viscosity.

  4. Modeling collective cell migration in geometric confinement

    Science.gov (United States)

    Tarle, Victoria; Gauquelin, Estelle; Vedula, S. R. K.; D'Alessandro, Joseph; Lim, C. T.; Ladoux, Benoit; Gov, Nir S.

    2017-06-01

    Monolayer expansion has generated great interest as a model system to study collective cell migration. During such an expansion the culture front often develops ‘fingers’, which we have recently modeled using a proposed feedback between the curvature of the monolayer’s leading edge and the outward motility of the edge cells. We show that this model is able to explain the puzzling observed increase of collective cellular migration speed of a monolayer expanding into thin stripes, as well as describe the behavior within different confining geometries that were recently observed in experiments. These comparisons give support to the model and emphasize the role played by the edge cells and the edge shape during collective cell motion.

  5. Evolving virtual creatures and catapults.

    Science.gov (United States)

    Chaumont, Nicolas; Egli, Richard; Adami, Christoph

    2007-01-01

    We present a system that can evolve the morphology and the controller of virtual walking and block-throwing creatures (catapults) using a genetic algorithm. The system is based on Sims' work, implemented as a flexible platform with an off-the-shelf dynamics engine. Experiments aimed at evolving Sims-type walkers resulted in the emergence of various realistic gaits while using fairly simple objective functions. Due to the flexibility of the system, drastically different morphologies and functions evolved with only minor modifications to the system and objective function. For example, various throwing techniques evolved when selecting for catapults that propel a block as far as possible. Among the strategies and morphologies evolved, we find the drop-kick strategy, as well as the systematic invention of the principle behind the wheel, when allowing mutations to the projectile.

  6. A MODEL FOR POSTRADIATION STEM CELL KINETICS,

    Science.gov (United States)

    In polycythemic rats observed for 17 days postradiation (300 R, 250 KVP X-rays) it was noted that stem cell release diminished to 8 percent of the...correlate these findings with a kinetic model of erythropoiesis. It was suggested that the initial depression in stem cell release might be due to cellular

  7. How the first biopolymers could have evolved.

    Science.gov (United States)

    Abkevich, V I; Gutin, A M; Shakhnovich, E I

    1996-01-01

    In this work, we discuss a possible origin of the first biopolymers with stable unique structures. We suggest that at the prebiotic stage of evolution, long organic polymers had to be compact to avoid hydrolysis and had to be soluble and thus must not be exceedingly hydrophobic. We present an algorithm that generates such sequences for model proteins. The evolved sequences turn out to have a stable unique structure, into which they quickly fold. This result illustrates the idea that the unique three-dimensional native structures of first biopolymers could have evolved as a side effect of nonspecific physicochemical factors acting at the prebiotic stage of evolution. PMID:8570645

  8. Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

    Science.gov (United States)

    Heddam, Salim

    2014-01-01

    In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

  9. Undergraduate Students' Mental Model of Cell Biology

    OpenAIRE

    S. Saptono; W. Isnaeni; S. Sukaesih

    2017-01-01

    A descriptive study of future teacher students' mental models of essential concepts in Cell Biology was carried out through explanatory mixed-methods. Some students (n=40) of Biology Education Universitas Negeri Semarang were involved as the research subject. We used a diagnostic test, structured interview guides, and field notes to describe students' mental model. In the early stage, we prepare a diagnostic test performed essential concepts of Cell Biology. Secondly, we define students' ment...

  10. Computational and Modeling Strategies for Cell Motility

    Science.gov (United States)

    Wang, Qi; Yang, Xiaofeng; Adalsteinsson, David; Elston, Timothy C.; Jacobson, Ken; Kapustina, Maryna; Forest, M. Gregory

    A predictive simulation of the dynamics of a living cell remains a fundamental modeling and computational challenge. The challenge does not even make sense unless one specifies the level of detail and the phenomena of interest, whether the focus is on near-equilibrium or strongly nonequilibrium behavior, and on localized, subcellular, or global cell behavior. Therefore, choices have to be made clear at the outset, ranging from distinguishing between prokaryotic and eukaryotic cells, specificity within each of these types, whether the cell is "normal," whether one wants to model mitosis, blebs, migration, division, deformation due to confined flow as with red blood cells, and the level of microscopic detail for any of these processes. The review article by Hoffman and Crocker [48] is both an excellent overview of cell mechanics and an inspiration for our approach. One might be interested, for example, in duplicating the intricate experimental details reported in [43]: "actin polymerization periodically builds a mechanical link, the lamellipodium, connecting myosin motors with the initiation of adhesion sites, suggesting that the major functions driving motility are coordinated by a biomechanical process," or to duplicate experimental evidence of traveling waves in cells recovering from actin depolymerization [42, 35]. Modeling studies of lamellipodial structure, protrusion, and retraction behavior range from early mechanistic models [84] to more recent deterministic [112, 97] and stochastic [51] approaches with significant biochemical and structural detail. Recent microscopic-macroscopic models and algorithms for cell blebbing have been developed by Young and Mitran [116], which update cytoskeletal microstructure via statistical sampling techniques together with fluid variables. Alternatively, whole cell compartment models (without spatial details) of oscillations in spreading cells have been proposed [35, 92, 109] which show positive and negative feedback

  11. Mathematical modeling of solid oxide fuel cells

    Science.gov (United States)

    Lu, Cheng-Yi; Maloney, Thomas M.

    1988-01-01

    Development of predictive techniques, with regard to cell behavior, under various operating conditions is needed to improve cell performance, increase energy density, reduce manufacturing cost, and to broaden utilization of various fuels. Such technology would be especially beneficial for the solid oxide fuel cells (SOFC) at it early demonstration stage. The development of computer models to calculate the temperature, CD, reactant distributions in the tubular and monolithic SOFCs. Results indicate that problems of nonuniform heat generation and fuel gas depletion in the tubular cell module, and of size limitions in the monolithic (MOD 0) design may be encountered during FC operation.

  12. Evolving production network structures

    DEFF Research Database (Denmark)

    Grunow, Martin; Gunther, H.O.; Burdenik, H.

    2007-01-01

    When deciding about future production network configurations, the current structures have to be taken into account. Further, core issues such as the maturity of the products and the capacity requirements for test runs and ramp-ups must be incorporated. Our approach is based on optimization...... modelling and assigns products and capacity expansions to production sites under the above constraints. It also considers the production complexity at the individual sites and the flexibility of the network. Our implementation results for a large manufacturing network reveal substantial possible cost...... reductions compared to the traditional manual planning results of our industrial partner....

  13. An electrostatic model for biological cell division

    CERN Document Server

    Faraggi, Eshel

    2010-01-01

    Probably the most fundamental processes for biological systems is their ability to create themselves through the use of cell division and cell differentiation. In this work a simple physical model is proposed for biological cell division. The model consists of a positive ionic gradient across the cell membrane, and concentration of charge at the nodes of the spindle and on the chromosomes. A simple calculation, based on Coulomb's Law, shows that under such circumstances a chromosome will tend to break up to its constituent chromatids and that the chromatids will be separated by a distance that is an order of thirty percent of the distance between the spindle nodes. Further repulsion between the nodes will tend to stretch the cell and eventually break the cell membrane between the separated chromatids, leading to cell division. The importance of this work is in continuing the understanding of the electromagnetic basis of cell division and providing it with an analytical model. A central implication of this and...

  14. Mathematical modeling of a thermovoltaic cell

    Science.gov (United States)

    White, Ralph E.; Kawanami, Makoto

    1992-01-01

    A new type of battery named 'Vaporvolt' cell is in the early stage of its development. A mathematical model of a CuO/Cu 'Vaporvolt' cell is presented that can be used to predict the potential and the transport behavior of the cell during discharge. A sensitivity analysis of the various transport and electrokinetic parameters indicates which parameters have the most influence on the predicted energy and power density of the 'Vaporvolt' cell. This information can be used to decide which parameters should be optimized or determined more accurately through further modeling or experimental studies. The optimal thicknesses of electrodes and separator, the concentration of the electrolyte, and the current density are determined by maximizing the power density. These parameter sensitivities and optimal design parameter values will help in the development of a better CuO/Cu 'Vaporvolt' cell.

  15. Large animal models for stem cell therapy.

    Science.gov (United States)

    Harding, John; Roberts, R Michael; Mirochnitchenko, Oleg

    2013-03-28

    The field of regenerative medicine is approaching translation to clinical practice, and significant safety concerns and knowledge gaps have become clear as clinical practitioners are considering the potential risks and benefits of cell-based therapy. It is necessary to understand the full spectrum of stem cell actions and preclinical evidence for safety and therapeutic efficacy. The role of animal models for gaining this information has increased substantially. There is an urgent need for novel animal models to expand the range of current studies, most of which have been conducted in rodents. Extant models are providing important information but have limitations for a variety of disease categories and can have different size and physiology relative to humans. These differences can preclude the ability to reproduce the results of animal-based preclinical studies in human trials. Larger animal species, such as rabbits, dogs, pigs, sheep, goats, and non-human primates, are better predictors of responses in humans than are rodents, but in each case it will be necessary to choose the best model for a specific application. There is a wide spectrum of potential stem cell-based products that can be used for regenerative medicine, including embryonic and induced pluripotent stem cells, somatic stem cells, and differentiated cellular progeny. The state of knowledge and availability of these cells from large animals vary among species. In most cases, significant effort is required for establishing and characterizing cell lines, comparing behavior to human analogs, and testing potential applications. Stem cell-based therapies present significant safety challenges, which cannot be addressed by traditional procedures and require the development of new protocols and test systems, for which the rigorous use of larger animal species more closely resembling human behavior will be required. In this article, we discuss the current status and challenges of and several major directions

  16. Cardiac Electromechanical Models: From Cell to Organ

    Directory of Open Access Journals (Sweden)

    Natalia A Trayanova

    2011-08-01

    Full Text Available The heart is a multiphysics and multiscale system that has driven the development of the most sophisticated mathematical models at the frontiers of computation physiology and medicine. This review focuses on electromechanical (EM models of the heart from the molecular level of myofilaments to anatomical models of the organ. Because of the coupling in terms of function and emergent behaviors at each level of biological hierarchy, separation of behaviors at a given scale is difficult. Here, a separation is drawn at the cell level so that the first half addresses subcellular/single cell models and the second half addresses organ models. At the subcelluar level, myofilament models represent actin-myosin interaction and Ca-based activation. Myofilament models and their refinements represent an overview of the development in the field. The discussion of specific models emphasizes the roles of cooperative mechanisms and sarcomere length dependence of contraction force, considered the cellular basis of the Frank-Starling law. A model of electrophysiology and Ca handling can be coupled to a myofilament model to produce an EM cell model, and representative examples are summarized to provide an overview of the progression of field. The second half of the review covers organ-level models that require solution of the electrical component as a reaction-diffusion system and the mechanical component, in which active tension generated by the myocytes produces deformation of the organ as described by the equations of continuum mechanics. As outlined in the review, different organ-level models have chosen to use different ionic and myofilament models depending on the specific application; this choice has been largely dictated by compromises between model complexity and computational tractability. The review also addresses application areas of EM models such as cardiac resynchronization therapy and the role of mechano-electric coupling in arrhythmias and

  17. Introductory review of computational cell cycle modeling.

    Science.gov (United States)

    Kriete, Andres; Noguchi, Eishi; Sell, Christian

    2014-01-01

    Recent advances in the modeling of the cell cycle through computer simulation demonstrate the power of systems biology. By definition, systems biology has the goal to connect a parts list, prioritized through experimental observation or high-throughput screens, by the topology of interactions defining intracellular networks to predict system function. Computer modeling of biological systems is often compared to a process of reverse engineering. Indeed, designed or engineered technical systems share many systems-level properties with biological systems; thus studying biological systems within an engineering framework has proven successful. Here we review some aspects of this process as it pertains to cell cycle modeling.

  18. Cell-specific cardiac electrophysiology models.

    Directory of Open Access Journals (Sweden)

    Willemijn Groenendaal

    2015-04-01

    Full Text Available The traditional cardiac model-building paradigm involves constructing a composite model using data collected from many cells. Equations are derived for each relevant cellular component (e.g., ion channel, exchanger independently. After the equations for all components are combined to form the composite model, a subset of parameters is tuned, often arbitrarily and by hand, until the model output matches a target objective, such as an action potential. Unfortunately, such models often fail to accurately simulate behavior that is dynamically dissimilar (e.g., arrhythmia to the simple target objective to which the model was fit. In this study, we develop a new approach in which data are collected via a series of complex electrophysiology protocols from single cardiac myocytes and then used to tune model parameters via a parallel fitting method known as a genetic algorithm (GA. The dynamical complexity of the electrophysiological data, which can only be fit by an automated method such as a GA, leads to more accurately parameterized models that can simulate rich cardiac dynamics. The feasibility of the method is first validated computationally, after which it is used to develop models of isolated guinea pig ventricular myocytes that simulate the electrophysiological dynamics significantly better than does a standard guinea pig model. In addition to improving model fidelity generally, this approach can be used to generate a cell-specific model. By so doing, the approach may be useful in applications ranging from studying the implications of cell-to-cell variability to the prediction of intersubject differences in response to pharmacological treatment.

  19. Radiobiological modeling with MarCell software

    Energy Technology Data Exchange (ETDEWEB)

    Hasan, J.S.; Jones, T.D. [Oak Ridge National Lab., TN (United States). Health Sciences Research Div.

    1999-01-01

    A nonlinear system of differential equations that models the bone marrow cellular kinetics associated with radiation injury, molecular repair, and compensatory cell proliferation has been extensively documented. Recently, that model has been implemented as MarCell, a user-friendly MS-DOS computer program that allows users with little knowledge of the original model to evaluate complex radiation exposure scenarios. The software allows modeling with the following radiations: tritium beta, 100 kVp X, 250 kVp X, 22 MV X, {sup 60}Co, {sup 137}Cs, 2 MeV electrons, triga neutrons, D-T neutrons, and 3 blends of mixed-field fission radiations. The possible cell lineages are stem, stroma, and leukemia/lymphoma, and the available species include mouse, rat, dog, sheep, swine, burro, and man. An attractive mathematical feature is that any protracted protocol can be expressed as an equivalent prompt dose for either the source used or for a reference, such as 250 kVp X rays or {sup 60}Co. Output from MarCell includes: risk of 30-day mortality; risk of cancer and leukemia based either on cytopenia or compensatory cell proliferation; cell survival plots as a function of time or dose; and 4-week recovery kinetics following treatment. In this article, the program`s applicability and ease of use are demonstrated by evaluating a medical total body irradiation protocol and a nuclear fallout scenario.

  20. When did oxygenic photosynthesis evolve?

    National Research Council Canada - National Science Library

    Roger Buick

    2008-01-01

    ...2.4 Ga ago, but when the photosynthetic oxygen production began is debatable. However, geological and geochemical evidence from older sedimentary rocks indicates that oxygenic photosynthesis evolved well before this oxygenation event...

  1. Stochastic modelling of cardiac cell structure.

    Science.gov (United States)

    Theakston, Elizabeth; Walker, Cameron; O'Sullivan, Michael; Rajagopal, Vijay

    2010-01-01

    Anatomically realistic and biophysically based computational models of the heart have provided valuable insights into cardiac function in health and disease. Nevertheless, these models typically use a "black-box" approach to describe the cellular level processes that underlie the heart beat. We are developing techniques to stochastically generate three-dimensional models of mammalian ventricular myocytes that exhibit salient characteristics of the spatial organisation of key cellular organelles in cardiac cell excitation and contraction. Such anatomically detailed models will facilitate a deeper understanding of cardiac function at multiple scales. This paper presents an important first step towards understanding and modelling the spatial distribution of two key organelles in cardiac cell contraction - myofibrils and mitochondria. The sarcolemma, myofibrils and mitochondria were segmented from transmission electron micrographs of ventricular cells from a healthy wistar rat. The centroids of the myofibrils and mitochondria were calculated, and various spatial statistical techniques for characterising the centroid distribution and inter-point interactions were investigated and implemented using the R spatstat package. Techniques for modelling the observed spatial patterns were also investigated, and preliminary results indicate that the Strauss Hard-core model best captures the interaction observed. We intend to confirm these results with larger sample of cells.

  2. Numerical Model of the DARHT Accelerating Cell

    CERN Document Server

    Hughes, Thomas P; Genoni, Thomas C; Kang, Mike; Prichard, Benjamin A

    2005-01-01

    The DARHT-2 facility at Los Alamos National Laboratory accelerates a 2 microsecond electron beam using a series of inductive accelerating cells. The cell inductance is provided by large Metglas cores, which are driven by a pulse-forming network. The original cell design was susceptible to electrical breakdown near the outer radius of the cores. We developed a numerical model for the magnetic properties of Metglas over the range of dB/dt (magnetization rate) relevant to DARHT. The model was implemented in a radially-resolved circuit code, and in the LSP* electromagnetic code. LSP simulations showed that the field stress distribution across the outer radius of the cores was highly nonuniform. This was subsequently confirmed in experiments at LBNL. The calculated temporal evolution of the electric field stress inside the cores approximately matches experimental measurements. The cells have been redesigned to greatly reduce the field stresses along the outer radius.

  3. Five-group cytogenetic risk classification, monosomal karyotype, and outcome after hematopoietic cell transplantation for MDS or acute leukemia evolving from MDS

    Science.gov (United States)

    Scott, Bart L.; Fang, Min; Shulman, Howard M.; Gyurkocza, Boglarka; Myerson, David; Pagel, John M.; Platzbecker, Uwe; Ramakrishnan, Aravind; Radich, Jerald P.; Sandmaier, Brenda M.; Sorror, Mohamed; Stirewalt, Derek L.; Wilson, Wendy A.; Storb, Rainer; Appelbaum, Frederick R.; Gooley, Ted

    2012-01-01

    Clonal cytogenetic abnormalities are a major risk factor for relapse after hematopoietic cell transplantation (HCT) for myelodysplastic syndrome (MDS). We determined the impact of the recently established 5-group cytogenetic classification of MDS on outcome after HCT. Results were compared with the impact of the International Prognostic Scoring System (IPSS) 3 cytogenetic risk groups, and the additional effect of a monosomal karyotype was assessed. The study included data on 1007 patients, 1-75 years old (median 45 years), transplanted from related (n = 547) or unrelated (n = 460) donors. Various conditioning regimens were used, and marrow, peripheral blood, or cord blood served as stem cell source. Both IPSS and 5-group cytogenetic risk classifications were significantly associated with post-HCT relapse and mortality, but the 5-group classification discriminated more clearly among the lowest- and highest-risk patients. A monosomal karyotype tended to further increase the rates of relapse and mortality, even after considering the IPSS or 5-group classifications. In addition, the pathologic disease category correlated with both relapse and mortality. Mortality was also impacted by patient age, donor type, conditioning regimen, platelet count, and etiology of MDS. Although mortality declined significantly in recent years, novel strategies are needed to overcome the barrier of high-risk cytogenetics. PMID:22767498

  4. Genomic profile of oral squamous cell carcinomas with an adjacent leukoplakia or with an erythroleukoplakia that evolved after the treatment of primary tumor: A report of two cases.

    Science.gov (United States)

    Ribeiro, Ilda P; Marques, Francisco; Barroso, Leonor; Rodrigues, Joana; Caramelo, Francisco; Melo, Joana B; Carreira, Isabel M

    2017-11-01

    Oral leukoplakia and erythroleukoplakia are common oral potentially malignant disorders diagnosed in the oral cavity. The specific outcome of these lesions remains to be elucidated, as their malignant transformation rate exhibits great variation. The ability to predict which of those potentially malignant lesions are likely to progress to cancer would be vital to guide their future clinical management. The present study reported two patients with tongue squamous cell carcinoma: Case study 1 was diagnosed with a simultaneous leukoplakia and case study 2 developed an erythroleukoplakia following the primary tumor treatment. Whole genome copy number alterations were analyzed using array comparative genomic hybridization. The present study determined more genomic imbalances in the tissues from leukoplakia and erythroleukoplakia compared with their respective tumors. The present study also identified in tumor and potentially malignant lesions common alterations of chromosomal regions and genes, including FBXL5, UGT2B15, UGT2B28, KANSL1, GSTT1 and DUSP22, being some of these typical aberrations described in oral cancer and others are linked to chemoradioresistance. Several putative genes associated with hallmarks of malignancy that may have an important role in predicting the progression of leukoplakia and erythroleukoplakia to squamous cell carcinoma, namely gains in BNIPL, MCL1, STAG2, CSPP1 and ZNRF3 genes were also identified.

  5. Large animal models for stem cell therapy

    OpenAIRE

    Harding, John; Roberts, R Michael; Mirochnitchenko, Oleg

    2013-01-01

    The field of regenerative medicine is approaching translation to clinical practice, and significant safety concerns and knowledge gaps have become clear as clinical practitioners are considering the potential risks and benefits of cell-based therapy. It is necessary to understand the full spectrum of stem cell actions and preclinical evidence for safety and therapeutic efficacy. The role of animal models for gaining this information has increased substantially. There is an urgent need for nov...

  6. Optical models for silicon solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, T.; Sopori, B. [National Renewable Energy Lab., Golden, CO (United States)

    1995-08-01

    Light trapping is an important design feature for high-efficiency silicon solar cells. Because light trapping can considerably enhance optical absorption, a thinner substrate can be used which, in turn, can lower the bulk carrier recombination and concommitantly increase open-circuit voltage, and fill factor of the cell. The basic concepts of light trapping are similar to that of excitation of an optical waveguide, where a prism or a grating structure increases the phase velocity of the incoming optical wave such that waves propagated within the waveguide are totally reflected at the interfaces. Unfortunately, these concepts break down because the entire solar cell is covered with such a structure, making it necessary to develop new analytical approaches to deal with incomplete light trapping in solar cells. This paper describes two models that analyze light trapping in thick and thin solar cells.

  7. Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

    Science.gov (United States)

    García-Morales, Vladimir; Manzanares, José A.; Mafe, Salvador

    2017-04-01

    We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ . This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

  8. Thermodynamic model for an alkaline fuel cell

    Science.gov (United States)

    Verhaert, Ivan; De Paepe, Michel; Mulder, Grietus

    Alkaline fuel cells are low temperature fuel cells for which stationary applications, e.g. cogeneration in buildings, are a promising market. In order to guarantee a long life, water and thermal management has to be done in a careful way. In order to better understand the water, alkali and thermal flows, a two-dimensional model for an Alkaline Fuel Cell is developed using a control volume approach. In each volume the electrochemical reactions together with the mass and energy balance are solved. The model is created in Aspen Custom Modeller, the development environment of Aspen Plus, where special attention is given to the physical flow of hydrogen, water and air in the system. In this way the developed component, the AFC-cell, can be built into stack configurations to understand its effect on the overall performance. The model is validated by experimental data from measured performance by VITO with their Cell Voltage Monitor at a test case, where the AFC-unit is used as a cogeneration unit.

  9. Modeling cell-in-cell structure into its biological significance

    OpenAIRE

    He, M-f; Wang, S; Wang, Y.; Wang, X-n

    2013-01-01

    Although cell-in-cell structure was noted 100 years ago, the molecular mechanisms of ?entering' and the destination of cell-in-cell remain largely unclear. It takes place among the same type of cells (homotypic cell-in-cell) or different types of cells (heterotypic cell-in-cell). Cell-in-cell formation affects both effector cells and their host cells in multiple aspects, while cell-in-cell death is under more intensive investigation. Given that cell-in-cell has an important role in maintainin...

  10. Evolvability Is an Evolved Ability: The Coding Concept as the Arch-Unit of Natural Selection.

    Science.gov (United States)

    Janković, Srdja; Ćirković, Milan M

    2016-03-01

    Physical processes that characterize living matter are qualitatively distinct in that they involve encoding and transfer of specific types of information. Such information plays an active part in the control of events that are ultimately linked to the capacity of the system to persist and multiply. This algorithmicity of life is a key prerequisite for its Darwinian evolution, driven by natural selection acting upon stochastically arising variations of the encoded information. The concept of evolvability attempts to define the total capacity of a system to evolve new encoded traits under appropriate conditions, i.e., the accessible section of total morphological space. Since this is dependent on previously evolved regulatory networks that govern information flow in the system, evolvability itself may be regarded as an evolved ability. The way information is physically written, read and modified in living cells (the "coding concept") has not changed substantially during the whole history of the Earth's biosphere. This biosphere, be it alone or one of many, is, accordingly, itself a product of natural selection, since the overall evolvability conferred by its coding concept (nucleic acids as information carriers with the "rulebook of meanings" provided by codons, as well as all the subsystems that regulate various conditional information-reading modes) certainly played a key role in enabling this biosphere to survive up to the present, through alterations of planetary conditions, including at least five catastrophic events linked to major mass extinctions. We submit that, whatever the actual prebiotic physical and chemical processes may have been on our home planet, or may, in principle, occur at some time and place in the Universe, a particular coding concept, with its respective potential to give rise to a biosphere, or class of biospheres, of a certain evolvability, may itself be regarded as a unit (indeed the arch-unit) of natural selection.

  11. Biophysical models of transcription in cells

    Science.gov (United States)

    Choubey, Sandeep

    Cells constantly face environmental challenges and deal with them by changing their gene expression patterns. They make decisions regarding which genes to express and which genes not to express based on intra-cellular and environmental cues. These decisions are often made by regulating the process of transcription. While the identities of the different molecules that take part in regulating transcription have been determined for a number of different genes, their dynamics inside the cell are still poorly understood. One key feature of these regulatory dynamics is that the numbers of the bio-molecules involved is typically small, resulting in large temporal fluctuations in transcriptional outputs (mRNA and protein). In this thesis I show that measurements of the cell-to-cell variability of the distribution of transcribing RNA polymerases along a gene provide a previously unexplored method for deciphering the mechanism of its transcription in vivo. First, I propose a simple kinetic model of transcription initiation and elongation from which I calculate transcribing RNA polymerase copy-number fluctuations. I test my theory against published data obtained for yeast genes and propose a novel mechanism of transcription. Rather than transcription being initiated through a single rate-limiting step, as was previously proposed, my single-cell analysis reveals the presence of at least two rate limiting steps. Second, I compute the distribution of inter-polymerase distance distribution along a gene and propose a method for analyzing inter-polymerase distance distributions acquired in experiments. By applying this method to images of polymerases transcribing ribosomal genes in E.coli I show that one model of regulation of these genes is consistent with inter-polymerase distance data while a number of other models are not. The analytical framework described in this thesis can be used to extract quantitative information about the dynamics of transcription from single-cell

  12. Modeling human infertility with pluripotent stem cells

    Directory of Open Access Journals (Sweden)

    Di Chen

    2017-05-01

    Full Text Available Human fertility is dependent upon the correct establishment and differentiation of the germline. This is because no other cell type in the body is capable of passing a genome and epigenome from parent to child. Terminally differentiated germline cells in the adult testis and ovary are called gametes. However, the initial specification of germline cells occurs in the embryo around the time of gastrulation. Most of our knowledge regarding the cell and molecular events that govern human germline specification involves extrapolating scientific principles from model organisms, most notably the mouse. However, recent work using next generation sequencing, gene editing and differentiation of germline cells from pluripotent stem cells has revealed that the core molecular mechanisms that regulate human germline development are different from rodents. Here, we will discuss the major molecular pathways required for human germline differentiation and how pluripotent stem cells have revolutionized our ability to study the earliest steps in human embryonic lineage specification in order to understand human fertility.

  13. Comment on "Sandbox modeling of evolving thrust wedges with different preexisting topographic relief: Implications for the longmen Shan thrust belt, eastern Tibet" by C. Sun et al.

    Science.gov (United States)

    Tan, Xibin; Xu, Xiwei; Lu, Renqi

    2017-02-01

    Sun et al.'s (2016) sandbox modeling takes preexisting topographic relief into account for faulting activity at the compressional orogenic belt, which promotes better understanding of Longmenshan thrust belt's (LTB) orogenic process and faulting behavior. However, topographic relief in sandbox modeling is contradictory to central LTB's actual topographic relief, and as a result, both the comparison between sandbox modeling and actual tectonics and topography and the conclusion that Xiaoyudong Fault is a tear fault should be reconsidered. Actually, based on Sun et al.'s (2016) sandbox modeling, the Xiaoyudong Fault cannot be treated as a tear fault.

  14. Modeling of Silicon Heterojunction Solar Cells

    Energy Technology Data Exchange (ETDEWEB)

    Luppina, P.; Lugli, P.; Goodnick, S.

    2015-06-14

    Here we present modeling results on crystalline Si/amorphous Si (a-Si) heterojunction solar cells using Sentaurus including various models for defect states in the a-Si barriers, as well as explicit models for the ITO emitter contact. We investigate the impact of the band offsets and barrier heights of the a-Si/c-Si interface, particularly in terms of the open circuit voltage. It is also shown that the solar cell performance is sensitively dependent on the quality of the a-Si in terms of defect states and their distribution, particularly on the emitter side. Finally, we have investigate the role of tunneling and thermionic emission across the heterointerface in terms of transport from the Si to the ITO contact layer

  15. Computational Modeling of Laser-Cell Biochemical Interactions

    Science.gov (United States)

    2010-12-31

    The model contains a total of 18 diagrams, including ones for photoinitiation, the melanin effect, antioxidant enzymes, the reduction chain...Francisco, CA, June 19- 20, 2001. 6. Fink, P.K., & Morgan, K. T., “Evolving an Understanding of Gene Expression Data Resulting from Oxidative Stress

  16. Non linear behaviour of cell tensegrity models

    Science.gov (United States)

    Alippi, A.; Bettucci, A.; Biagioni, A.; Conclusio, D.; D'Orazio, A.; Germano, M.; Passeri, D.

    2012-05-01

    Tensegrity models for the cytoskeleton structure of living cells is largely used nowadays for interpreting the biochemical response of living tissues to mechanical stresses. Microtubules, microfilaments and filaments are the microscopic cell counterparts of struts (microtubules) and cables (microfilaments and filaments) in the macroscopic world: the formers oppose to compression, the latters to tension, thus yielding an overall structure, light and highly deformable. Specific cell surface receptors, such as integrins, act as the coupling elements that transmit the outside mechanical stress state into the cell body. Reversible finite deformations of tensegrity structures have been widely demonstrated experimentally and in a number of living cell simulations. In the present paper, the bistability behaviour of two general models, the linear bar oscillator and the icosahedron, is studied, as they are both obtained from mathematical simulation, the former, and from larger scale experiments, the latter. The discontinuity in the frequency response of the oscillation amplitude and the lateral bending of the resonance curves are put in evidence, as it grows larger as the driving amplitude increases, respectively.

  17. Fluctuation-Noise Model for PEM Fuel Cell

    Science.gov (United States)

    Denisov, E. S.; Salakhova, A. Sh.; Adiutantov, N. A.; Evdokimov, Yu. K.

    2017-08-01

    The fluctuation-noise model is presented. This model allows to describe the power spectral density of PEM fuel cell electrical fluctuation. The proposed model can be used for diagnostics of PEM fuel cell state of health.

  18. A Biophysical Model for Cytotoxic Cell Swelling.

    Science.gov (United States)

    Dijkstra, Koen; Hofmeijer, Jeannette; van Gils, Stephan A; van Putten, Michel J A M

    2016-11-23

    We present a dynamic biophysical model to explain neuronal swelling underlying cytotoxic edema in conditions of low energy supply, as observed in cerebral ischemia. Our model contains Hodgkin-Huxley-type ion currents, a recently discovered voltage-gated chloride flux through the ion exchanger SLC26A11, active KCC2-mediated chloride extrusion, and ATP-dependent pumps. The model predicts changes in ion gradients and cell swelling during ischemia of various severity or channel blockage with realistic timescales. We theoretically substantiate experimental observations of chloride influx generating cytotoxic edema, while sodium entry alone does not. We show a tipping point of Na(+)/K(+)-ATPase functioning, where below cell volume rapidly increases as a function of the remaining pump activity, and a Gibbs-Donnan-like equilibrium state is reached. This precludes a return to physiological conditions even when pump strength returns to baseline. However, when voltage-gated sodium channels are temporarily blocked, cell volume and membrane potential normalize, yielding a potential therapeutic strategy. Cytotoxic edema most commonly results from energy shortage, such as in cerebral ischemia, and refers to the swelling of brain cells due to the entry of water from the extracellular space. We show that the principle of electroneutrality explains why chloride influx is essential for the development of cytotoxic edema. With the help of a biophysical model of a single neuron, we show that a tipping point of the energy supply exists, below which the cell volume rapidly increases. We simulate realistic time courses to and reveal critical components of neuronal swelling in conditions of low energy supply. Furthermore, we show that, after transient blockade of the energy supply, cytotoxic edema may be reversed by temporary blockade of Na(+) channels. Copyright © 2016 the authors 0270-6474/16/3611881-10$15.00/0.

  19. Multi-scale models for cell adhesion

    Science.gov (United States)

    Wu, Yinghao; Chen, Jiawen; Xie, Zhong-Ru

    2014-03-01

    The interactions of membrane receptors during cell adhesion play pivotal roles in tissue morphogenesis during development. Our lab focuses on developing multi-scale models to decompose the mechanical and chemical complexity in cell adhesion. Recent experimental evidences show that clustering is a generic process for cell adhesive receptors. However, the physical basis of such receptor clustering is not understood. We introduced the effect of molecular flexibility to evaluate the dynamics of receptors. By delivering new theory to quantify the changes of binding free energy in different cellular environments, we revealed that restriction of molecular flexibility upon binding of membrane receptors from apposing cell surfaces (trans) causes large entropy loss, which dramatically increases their lateral interactions (cis). This provides a new molecular mechanism to initialize receptor clustering on the cell-cell interface. By using the subcellular simulations, we further found that clustering is a cooperative process requiring both trans and cis interactions. The detailed binding constants during these processes are calculated and compared with experimental data from our collaborator's lab.

  20. Fractionation and current time trends of PCB congeners: evolvement of distributions 1950–2010 studied using a global atmosphere-ocean general circulation model

    OpenAIRE

    G. Lammel; I. Stemmler

    2012-01-01

    PCBs are ubiquitous environmental pollutants expected to decline in abiotic environmental media in response to decreasing primary emissions since the 1970s. A coupled atmosphere-ocean general circulation model with embedded dynamic sub-models for atmospheric aerosols and the marine biogeochemistry and air-surface exchange processes with soils, vegetation and the cryosphere is used to study the transport and fate of four PCB congeners covering a range of 3–7 chlorine atoms.
    &...

  1. Fractionation and current time trends of PCB congeners: evolvement of distributions 1950–2010 studied using a global atmosphere-ocean general circulation model

    OpenAIRE

    G. Lammel; I. Stemmler

    2012-01-01

    PCBs are ubiquitous environmental pollutants expected to decline in abiotic environmental media in response to decreasing primary emissions since the 1970s. A coupled atmosphere-ocean general circulation model with embedded dynamic sub-models for atmospheric aerosols and the marine biogeochemistry and air-surface exchange processes with soils, vegetation and the cryosphere is used to study the transport and fate of four PCB congeners covering a range of 3–7 chlorine atoms.

  2. Temperature-dependent rate models of vascular cambium cell mortality

    Science.gov (United States)

    Matthew B. Dickinson; Edward A. Johnson

    2004-01-01

    We use two rate-process models to describe cell mortality at elevated temperatures as a means of understanding vascular cambium cell death during surface fires. In the models, cell death is caused by irreversible damage to cellular molecules that occurs at rates that increase exponentially with temperature. The models differ in whether cells show cumulative effects of...

  3. Information theory, evolutionary innovations and evolvability.

    Science.gov (United States)

    Wagner, Andreas

    2017-12-05

    How difficult is it to 'discover' an evolutionary adaptation or innovation? I here suggest that information theory, in combination with high-throughput DNA sequencing, can help answer this question by quantifying a new phenotype's information content. I apply this framework to compute the phenotypic information associated with novel gene regulation and with the ability to use novel carbon sources. The framework can also help quantify how DNA duplications affect evolvability, estimate the complexity of phenotypes and clarify the meaning of 'progress' in Darwinian evolution.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'. © 2017 The Author(s).

  4. PEM Fuel Cells from Single Cell to Stack - Fundamental, Modeling, Analysis, and Applications

    OpenAIRE

    Maher A.R. Sadiq Al-Baghdadi

    2015-01-01

    Part I: Fundamentals Chapter 1: Introduction. Chapter 2: PEM fuel cell thermodynamics, electrochemistry, and performance. Chapter 3: PEM fuel cell components. Chapter 4: PEM fuel cell failure modes. Part II: Modeling and Simulation Chapter 5: PEM fuel cell models based on semi-empirical simulation. Chapter 6: PEM fuel cell models based on computational fluid dynamics (CFD). Part III: Analysis Chapter 7: PEM fuel cell analysis. Chapter 8: PEM fuel cell stack desig...

  5. Loops and autonomy promote evolvability of ecosystem networks.

    Science.gov (United States)

    Luo, Jianxi

    2014-09-29

    The structure of ecological networks, in particular food webs, determines their ability to evolve further, i.e. evolvability. The knowledge about how food web evolvability is determined by the structures of diverse ecological networks can guide human interventions purposefully to either promote or limit evolvability of ecosystems. However, the focus of prior food web studies was on stability and robustness; little is known regarding the impact of ecological network structures on their evolvability. To correlate ecosystem structure and evolvability, we adopt the NK model originally from evolutionary biology to generate and assess the ruggedness of fitness landscapes of a wide spectrum of model food webs with gradual variation in the amount of feeding loops and link density. The variation in network structures is controlled by linkage rewiring. Our results show that more feeding loops and lower trophic link density, i.e. higher autonomy of species, of food webs increase the potential for the ecosystem to generate heritable variations with improved fitness. Our findings allow the prediction of the evolvability of actual food webs according to their network structures, and provide guidance to enhancing or controlling the evolvability of specific ecosystems.

  6. Reply to comment by Tan et al. on "Sandbox modeling of evolving thrust wedges with different preexisting topographic relief: Implications for the Longmen Shan thrust belt, eastern Tibet"

    Science.gov (United States)

    Sun, Chuang; Jia, Dong; Yin, Hongwei; Chen, Zhuxin; Li, Zhigang; Li, Shen; Wei, Dongtao; Li, Yiquan; Yan, Bin; Wang, Maomao; Fang, Shaozhi; Cui, Jian

    2017-02-01

    Tan et al. comment that the preexisting topographic relief in our sandbox is opposed to its prototype in the central Longmen Shan. Therefore, the comparison between our sandbox modeling and the natural topography is questionable and does not agree with our conclusion that the Xiaoyudong fault is a tear fault. First, we are grateful to the authors for their approval of our sandbox modeling and its contribution to understanding fault behavior within thrust wedges. However, after reading the comment carefully, we found that they misunderstood the meaning of topographic relief we conveyed. In response, we would like to address the differences between the topography in their comment and the orogen-scale topography we investigated in our modeling to defend our conclusion.

  7. f( R) gravity solutions for evolving wormholes

    Science.gov (United States)

    Bhattacharya, Subhra; Chakraborty, Subenoy

    2017-08-01

    The scalar-tensor f( R) theory of gravity is considered in the framework of a simple inhomogeneous space-time model. In this research we use the reconstruction technique to look for possible evolving wormhole solutions within viable f( R) gravity formalism. These f( R) models are then constrained so that they are consistent with existing experimental data. Energy conditions related to the matter threading the wormhole are analyzed graphically and are in general found to obey the null energy conditions (NEC) in regions around the throat, while in the limit f(R)=R, NEC can be violated at large in regions around the throat.

  8. Modelling fuel cell performance using artificial intelligence

    Science.gov (United States)

    Ogaji, S. O. T.; Singh, R.; Pilidis, P.; Diacakis, M.

    Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed.

  9. Machine Learning Optimization of Evolvable Artificial Cells

    DEFF Research Database (Denmark)

    Caschera, F.; Rasmussen, S.; Hanczyc, M.

    2011-01-01

    on a machine learning process is presented. The optimization proceeds over generations of experiments in iterative loop until optimal compositions are discovered. The fitness function is experimentally measured every time the loop is closed. Two examples of complex systems, namely a liposomal drug formulation...... can be explored. A machine learning approach (Evo-DoE) could be applied to explore this experimental space and define optimal interactions according to a specific fitness function. Herein an implementation of an evolutionary design of experiments to optimize chemical and biochemical systems based...

  10. Modeling malaria infected cells in microcirculation

    Science.gov (United States)

    Raffiee, Amir Hossein; Dabiri, Sadegh; Motavalizadeh Ardekani, Arezoo

    2016-11-01

    Plasmodim (P.) falciparum is one of the deadliest types of malaria species that invades healthy red blood cells (RBC) in human blood flow. This parasite develops through 48-hour intra-RBC process leading to significant morphological and mechanical (e.g., stiffening) changes in RBC membrane. These changes have remarkable effects on blood circulation such as increase in flow resistance and obstruction in microcirculation. In this work a computational framework is developed to model RBC suspension in blood flow using front-tracking technique. The present study focuses on blood flow behavior under normal and infected circumstances and predicts changes in blood rheology for different levels of parasitemia and hematocrit. This model allows better understanding of blood flow circulation up to a single cell level and provides us with realistic and deep insight into hematologic diseases such as malaria.

  11. Modeling of SONOS Memory Cell Erase Cycle

    Science.gov (United States)

    Phillips, Thomas A.; MacLeod, Todd C.; Ho, Fat H.

    2011-01-01

    Utilization of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) nonvolatile semiconductor memories as a flash memory has many advantages. These electrically erasable programmable read-only memories (EEPROMs) utilize low programming voltages, have a high erase/write cycle lifetime, are radiation hardened, and are compatible with high-density scaled CMOS for low power, portable electronics. In this paper, the SONOS memory cell erase cycle was investigated using a nonquasi-static (NQS) MOSFET model. Comparisons were made between the model predictions and experimental data.

  12. The Evolving Resource Metadata Infrastructure

    Science.gov (United States)

    Biemesderfer, Chris

    The search and discovery mechanisms that will facilitate and simplify systematic research on the Internet depend on systematic classifications of resources, as well as on standardized access to such metadata. The principles and technologies that will make this possible are evolving in the work of the Internet Engineering Task Force and the digital library initiatives, among others. The desired outcome is a set of standards, tools, and practices that permits both cataloging and retrieval to be comprehensive and efficient.

  13. Generative models: Human embryonic stem cells and multiple modeling relations.

    Science.gov (United States)

    Fagan, Melinda Bonnie

    2016-04-01

    Model organisms are at once scientific models and concrete living things. It is widely assumed by philosophers of science that (1) model organisms function much like other kinds of models, and (2) that insofar as their scientific role is distinctive, it is in virtue of representing a wide range of biological species and providing a basis for generalizations about those targets. This paper uses the case of human embryonic stem cells (hESC) to challenge both assumptions. I first argue that hESC can be considered model organisms, analogous to classic examples such as Escherichia coli and Drosophila melanogaster. I then discuss four contrasts between the epistemic role of hESC in practice, and the assumptions about model organisms noted above. These contrasts motivate an alternative view of model organisms as a network of systems related constructively and developmentally to one another. I conclude by relating this result to other accounts of model organisms in recent philosophy of science. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Synthetic biology of minimal living cells: primitive cell models and semi-synthetic cells

    National Research Council Canada - National Science Library

    Stano, Pasquale

    2010-01-01

    ... vesicles, which are relevant as primitive cell models is given. These studies can be used as a starting point for the construction of more complex systems, firstly being inspired by possible origins of life scenarioes...

  15. Structurally Governed Cell Mechanotransduction through Multiscale Modeling

    Science.gov (United States)

    Kang, John; Puskar, Kathleen M.; Ehrlicher, Allen J.; Leduc, Philip R.; Schwartz, Russell S.

    2015-02-01

    Mechanotransduction has been divided into mechanotransmission, mechanosensing, and mechanoresponse, although how a cell performs all three functions using the same set of structural components is still highly debated. Here, we bridge the gap between emerging molecular and systems-level understandings of mechanotransduction through a multiscale model linking these three phases. Our model incorporates a discrete network of actin filaments and associated proteins that responds to stretching through geometric relaxation. We assess three potential activating mechanisms at mechanosensitive crosslinks as inputs to a mixture model of molecular release and benchmark each using experimental data of mechanically-induced Rho GTPase FilGAP release from actin-filamin crosslinks. Our results suggest that filamin-FilGAP mechanotransduction response is best explained by a bandpass mechanism favoring release when crosslinking angles fall outside of a specific range. Our model further investigates the difference between ordered versus disordered networks and finds that a more disordered actin network may allow a cell to more finely tune control of molecular release enabling a more robust response.

  16. A depth-averaged debris-flow model that includes the effects of evolving dilatancy: II. Numerical predictions and experimental tests.

    Science.gov (United States)

    George, David L.; Iverson, Richard M.

    2014-01-01

    We evaluate a new depth-averaged mathematical model that is designed to simulate all stages of debris-flow motion, from initiation to deposition. A companion paper shows how the model’s five governing equations describe simultaneous evolution of flow thickness, solid volume fraction, basal pore-fluid pressure, and two components of flow momentum. Each equation contains a source term that represents the influence of state-dependent granular dilatancy. Here we recapitulate the equations and analyze their eigenstructure to show that they form a hyperbolic system with desirable stability properties. To solve the equations we use a shock-capturing numerical scheme with adaptive mesh refinement, implemented in an open-source software package we call D-Claw. As tests of D-Claw, we compare model output with results from two sets of large-scale debris-flow experiments. One set focuses on flow initiation from landslides triggered by rising pore-water pressures, and the other focuses on downstream flow dynamics, runout, and deposition. D-Claw performs well in predicting evolution of flow speeds, thicknesses, and basal pore-fluid pressures measured in each type of experiment. Computational results illustrate the critical role of dilatancy in linking coevolution of the solid volume fraction and pore-fluid pressure, which mediates basal Coulomb friction and thereby regulates debris-flow dynamics.

  17. Evolving Concepts in Lung Carcinogenesis

    Science.gov (United States)

    Gomperts, Brigitte N.; Spira, Avrum; Massion, Pierre P.; Walser, Tonya C.; Wistuba, Ignacio I.; Minna, John D.; Dubinett, Steven M.

    2012-01-01

    Lung carcinogenesis is a complex, stepwise process that involves the acquisition of genetic mutations and epigenetic changes that alter cellular processes, such as proliferation, differentiation, invasion, and metastasis. Here, we review some of the latest concepts in the pathogenesis of lung cancer and highlight the roles of inflammation, the “field of cancerization,” and lung cancer stem cells in the initiation of the disease. Furthermore, we review how high throughput genomics, transcriptomics, epigenomics, and proteomics are advancing the study of lung carcinogenesis. Finally, we reflect on the potential of current in vitro and in vivo models of lung carcinogenesis to advance the field and on the areas of investigation where major breakthroughs will lead to the identification of novel chemoprevention strategies and therapies for lung cancer. PMID:21500122

  18. The evolvability of programmable hardware

    Science.gov (United States)

    Raman, Karthik; Wagner, Andreas

    2011-01-01

    In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected ‘neutral networks’ in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 1045 logic circuits (‘genotypes’) and 1019 logic functions (‘phenotypes’). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry. PMID:20534598

  19. The 'E' factor -- evolving endodontics.

    Science.gov (United States)

    Hunter, M J

    2013-03-01

    Endodontics is a constantly developing field, with new instruments, preparation techniques and sealants competing with trusted and traditional approaches to tooth restoration. Thus general dental practitioners must question and understand the significance of these developments before adopting new practices. In view of this, the aim of this article, and the associated presentation at the 2013 British Dental Conference & Exhibition, is to provide an overview of endodontic methods and constantly evolving best practice. The presentation will review current preparation techniques, comparing rotary versus reciprocation, and question current trends in restoration of the endodontically treated tooth.

  20. Density functional calculations of (55)Mn, (14)N and (13)C electron paramagnetic resonance parameters support an energetically feasible model system for the S(2) state of the oxygen-evolving complex of photosystem II.

    Science.gov (United States)

    Schinzel, Sandra; Schraut, Johannes; Arbuznikov, Alexei V; Siegbahn, Per E M; Kaupp, Martin

    2010-09-10

    Metal and ligand hyperfine couplings of a previously suggested, energetically feasible Mn(4)Ca model cluster (SG2009(-1)) for the S(2) state of the oxygen-evolving complex (OEC) of photosystem II (PSII) have been studied by broken-symmetry density functional methods and compared with other suggested structural and spectroscopic models. This was carried out explicitly for different spin-coupling patterns of the S=1/2 ground state of the Mn(III)(Mn(IV))(3) cluster. By applying spin-projection techniques and a scaling of the manganese hyperfine couplings, computation of the hyperfine and nuclear quadrupole coupling parameters allows a direct evaluation of the proposed models in comparison with data obtained from the simulation of EPR, ENDOR, and ESEEM spectra. The computation of (55)Mn hyperfine couplings (HFCs) for SG2009(-1) gives excellent agreement with experiment. However, at the current level of spin projection, the (55)Mn HFCs do not appear sufficiently accurate to distinguish between different structural models. Yet, of all the models studied, SG2009(-1) is the only one with the Mn(III) site at the Mn(C) center, which is coordinated by histidine (D1-His332). The computed histidine (14)N HFC anisotropy for SG2009(-1) gives much better agreement with ESEEM data than the other models, in which Mn(C) is an Mn(IV) site, thus supporting the validity of the model. The (13)C HFCs of various carboxylates have been compared with (13)C ENDOR data for PSII preparations with (13)C-labelled alanine.

  1. Advanced methods of solid oxide fuel cell modeling

    CERN Document Server

    Milewski, Jaroslaw; Santarelli, Massimo; Leone, Pierluigi

    2011-01-01

    Fuel cells are widely regarded as the future of the power and transportation industries. Intensive research in this area now requires new methods of fuel cell operation modeling and cell design. Typical mathematical models are based on the physical process description of fuel cells and require a detailed knowledge of the microscopic properties that govern both chemical and electrochemical reactions. ""Advanced Methods of Solid Oxide Fuel Cell Modeling"" proposes the alternative methodology of generalized artificial neural networks (ANN) solid oxide fuel cell (SOFC) modeling. ""Advanced Methods

  2. Modeling Degradation in Solid Oxide Electrolysis Cells

    Energy Technology Data Exchange (ETDEWEB)

    Manohar S. Sohal; Anil V. Virkar; Sergey N. Rashkeev; Michael V. Glazoff

    2010-09-01

    Idaho National Laboratory has an ongoing project to generate hydrogen from steam using solid oxide electrolysis cells (SOECs). To accomplish this, technical and degradation issues associated with the SOECs will need to be addressed. This report covers various approaches being pursued to model degradation issues in SOECs. An electrochemical model for degradation of SOECs is presented. The model is based on concepts in local thermodynamic equilibrium in systems otherwise in global thermodynamic no equilibrium. It is shown that electronic conduction through the electrolyte, however small, must be taken into account for determining local oxygen chemical potential, , within the electrolyte. The within the electrolyte may lie out of bounds in relation to values at the electrodes in the electrolyzer mode. Under certain conditions, high pressures can develop in the electrolyte just near the oxygen electrode/electrolyte interface, leading to oxygen electrode delamination. These predictions are in accordance with the reported literature on the subject. Development of high pressures may be avoided by introducing some electronic conduction in the electrolyte. By combining equilibrium thermodynamics, no equilibrium (diffusion) modeling, and first-principles, atomic scale calculations were performed to understand the degradation mechanisms and provide practical recommendations on how to inhibit and/or completely mitigate them.

  3. Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D.

    Directory of Open Access Journals (Sweden)

    Maciej H Swat

    Full Text Available Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution. Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors.

  4. (N+1)-dimensional Lorentzian evolving wormholes supported by polytropic matter

    Energy Technology Data Exchange (ETDEWEB)

    Cataldo, Mauricio [Universidad del Bio-Bio, Departamento de Fisica, Facultad de Ciencias, Concepcion (Chile); Arostica, Fernanda; Bahamonde, Sebastian [Universidad de Concepcion, Departamento de Fisica, Concepcion (Chile)

    2013-08-15

    In this paper we study (N+1)-dimensional evolving wormholes supported by energy satisfying a polytropic equation of state. The considered evolving wormhole models are described by a constant redshift function and generalizes the standard flat Friedmann-Robertson-Walker spacetime. The polytropic equation of state allows us to consider in (3+1)-dimensions generalizations of the phantom energy and the generalized Chaplygin gas sources. (orig.)

  5. Analysis of individual cell trajectories in lattice-gas cellular automaton models for migrating cell populations.

    Science.gov (United States)

    Mente, Carsten; Voss-Böhme, Anja; Deutsch, Andreas

    2015-04-01

    Collective dynamics of migrating cell populations drive key processes in tissue formation and maintenance under normal and diseased conditions. Collective cell behavior at the tissue level is typically characterized by considering cell density patterns such as clusters and moving cell fronts. However, there are also important observables of collective dynamics related to individual cell behavior. In particular, individual cell trajectories are footprints of emergent behavior in populations of migrating cells. Lattice-gas cellular automata (LGCA) have proven successful to model and analyze collective behavior arising from interactions of migrating cells. There are well-established methods to analyze cell density patterns in LGCA models. Although LGCA dynamics are defined by cell-based rules, individual cells are not distinguished. Therefore, individual cell trajectories cannot be analyzed in LGCA so far. Here, we extend the classical LGCA framework to allow labeling and tracking of individual cells. We consider cell number conserving LGCA models of migrating cell populations where cell interactions are regulated by local cell density and derive stochastic differential equations approximating individual cell trajectories in LGCA. This result allows the prediction of complex individual cell trajectories emerging in LGCA models and is a basis for model-experiment comparisons at the individual cell level.

  6. Modeling cell migration in 3D: Status and challenges

    OpenAIRE

    Rangarajan, Rajagopal; Zaman, Muhammad H.

    2008-01-01

    Cell migration is a multi-scale process that integrates signaling, mechanics and biochemical reaction kinetics. Various mathematical models accurately predict cell migration on 2D surfaces, but are unable to capture the complexities of 3D migration. Additionally, quantitative 3D cell migration models have been few and far between. In this review we look and characterize various mathematical models available in literature to predict cell migration in 3D matrices and analyze their strengths and...

  7. Challenges on Probabilistic Modeling for Evolving Networks

    OpenAIRE

    Ding, Jianguo; Bouvry, Pascal

    2013-01-01

    With the emerging of new networks, such as wireless sensor networks, vehicle networks, P2P networks, cloud computing, mobile Internet, or social networks, the network dynamics and complexity expands from system design, hardware, software, protocols, structures, integration, evolution, application, even to business goals. Thus the dynamics and uncertainty are unavoidable characteristics, which come from the regular network evolution and unexpected hardware defects, unavoidable software errors,...

  8. Comparison of multi-fluid moment models with particle-in-cell simulations of collisionless magnetic reconnection

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Liang, E-mail: liang.wang@unh.edu; Germaschewski, K. [Space Science Center and Physics Department, University of New Hampshire, Durham, New Hampshire 03824 (United States); Hakim, Ammar H.; Bhattacharjee, A. [Center for Heliophysics, Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543-0451 (United States)

    2015-01-15

    We introduce an extensible multi-fluid moment model in the context of collisionless magnetic reconnection. This model evolves full Maxwell equations and simultaneously moments of the Vlasov-Maxwell equation for each species in the plasma. Effects like electron inertia and pressure gradient are self-consistently embedded in the resulting multi-fluid moment equations, without the need to explicitly solving a generalized Ohm's law. Two limits of the multi-fluid moment model are discussed, namely, the five-moment limit that evolves a scalar pressures for each species and the ten-moment limit that evolves the full anisotropic, non-gyrotropic pressure tensor for each species. We first demonstrate analytically and numerically that the five-moment model reduces to the widely used Hall magnetohydrodynamics (Hall MHD) model under the assumptions of vanishing electron inertia, infinite speed of light, and quasi-neutrality. Then, we compare ten-moment and fully kinetic particle-in-cell (PIC) simulations of a large scale Harris sheet reconnection problem, where the ten-moment equations are closed with a local linear collisionless approximation for the heat flux. The ten-moment simulation gives reasonable agreement with the PIC results regarding the structures and magnitudes of the electron flows, the polarities and magnitudes of elements of the electron pressure tensor, and the decomposition of the generalized Ohm's law. Possible ways to improve the simple local closure towards a nonlocal fully three-dimensional closure are also discussed.

  9. High-Grade B-Cell Neoplasm with Surface Light Chain Restriction and Tdt Coexpression Evolved in a MYC-Rearranged Diffuse Large B-Cell Lymphoma: A Dilemma in Classification

    Directory of Open Access Journals (Sweden)

    Dina Sameh Soliman

    2017-01-01

    Full Text Available According to World Health Organization (WHO classification (2008, B-cell neoplasms are classified into precursor B-cell or a mature B-cell phenotype and this classification was also kept in the latest WHO revision (2016. We are reporting a male patient in his fifties, with tonsillar swelling diagnosed as diffuse large B-cell lymphoma (DLBCL, germinal center. He received 6 cycles of RCHOP and showed complete metabolic response. Two months later, he presented with severe CNS symptoms. Flow cytometry on bone marrow (BM showed infiltration by CD10-positive Kappa-restricted B-cells with loss of CD20 and CD19, and downregulation of CD79b. Moreover, the malignant population showed Tdt expression. BM Cytogenetics revealed t(8;14(q24;q32 within a complex karyotype. Retrospectively, MYC and Tdt immunostains performed on original diagnostic tissue and came negative for Tdt and positive for MYC. It has been rarely reported that mature B-cell neoplasms present with features of immaturity; however the significance of Tdt acquisition during disease course was not addressed before. What is unique in this case is that the emerging disease has acquired an immaturity marker while retaining some features of the original mature clone. No definitive WHO category would adopt high-grade neoplasms that exhibit significant overlapping features between mature and immature phenotypes.

  10. Biomechanics of epithelial cell islands analyzed by modeling and experimentation

    CERN Document Server

    Coburn, Luke; Noppe, Adrian; Caldwell, Benjamin J; Moussa, Elliott; Yap, Chloe; Priya, Rashmi; Lobaskin, Vladimir; Roberts, Anthony P; Yap, Alpha S; Neufeld, Zoltan; Gomez, Guillermo A

    2016-01-01

    We generated a new computational approach to analyze the biomechanics of epithelial cell islands that combines both vertex and contact-inhibition-of-locomotion models to include both cell-cell and cell-substrate adhesion. Examination of the distribution of cell protrusions (adhesion to the substrate) in the model predicted high order profiles of cell organization that agree with those previously seen experimentally. Cells acquired an asymmetric distribution of protrusions (and traction forces) that decreased when moving from the edge to the island center. Our in silico analysis also showed that tension on cell-cell junctions (and monolayer stress) is not homogeneous across the island. Instead it is higher at the island center and scales up with island size, which we confirmed experimentally using laser ablation assays and immunofluorescence. Moreover, our approach has the minimal elements necessary to reproduce mechanical crosstalk between both cell-cell and cell substrate adhesion systems. We found that an i...

  11. Computational cell model based on autonomous cell movement regulated by cell-cell signalling successfully recapitulates the "inside and outside" pattern of cell sorting

    Directory of Open Access Journals (Sweden)

    Ajioka Itsuki

    2007-09-01

    Full Text Available Abstract Background Development of multicellular organisms proceeds from a single fertilized egg as the combined effect of countless numbers of cellular interactions among highly dynamic cells. Since at least a reminiscent pattern of morphogenesis can be recapitulated in a reproducible manner in reaggregation cultures of dissociated embryonic cells, which is known as cell sorting, the cells themselves must possess some autonomous cell behaviors that assure specific and reproducible self-organization. Understanding of this self-organized dynamics of heterogeneous cell population seems to require some novel approaches so that the approaches bridge a gap between molecular events and morphogenesis in developmental and cell biology. A conceptual cell model in a computer may answer that purpose. We constructed a dynamical cell model based on autonomous cell behaviors, including cell shape, growth, division, adhesion, transformation, and motility as well as cell-cell signaling. The model gives some insights about what cellular behaviors make an appropriate global pattern of the cell population. Results We applied the model to "inside and outside" pattern of cell-sorting, in which two different embryonic cell types within a randomly mixed aggregate are sorted so that one cell type tends to gather in the central region of the aggregate and the other cell type surrounds the first cell type. Our model can modify the above cell behaviors by varying parameters related to them. We explored various parameter sets with which the "inside and outside" pattern could be achieved. The simulation results suggested that direction of cell movement responding to its neighborhood and the cell's mobility are important for this specific rearrangement. Conclusion We constructed an in silico cell model that mimics autonomous cell behaviors and applied it to cell sorting, which is a simple and appropriate phenomenon exhibiting self-organization of cell population. The model

  12. Modeling Emerging Solar Cell Materials and Devices

    Science.gov (United States)

    Thongprong, Non

    Organic photovoltaics (OPVs) and perovskite solar cells are emerging classes of solar cell that are promising for clean energy alternatives to fossil fuels. Understanding fundamental physics of these materials is crucial for improving their energy conversion efficiencies and promoting them to practical applications. Current density-voltage (JV) curves; which are important indicators of OPV efficiency, have direct connections to many fundamental properties of solar cells. They can be described by the Shockley diode equation, resulting in fitting parameters; series and parallel resistance (Rs and Rp), diode saturation current ( J0) and ideality factor (n). However, the Shockley equation was developed specifically for inorganic p-n junction diodes, so it lacks physical meanings when it is applied to OPVs. Hence, the puRposes of this work are to understand the fundamental physics of OPVs and to develop new diode equations in the same form as the Shockley equation that are based on OPV physics. We develop a numerical drift-diffusion simulation model to study bilayer OPVs, which will be called the drift-diffusion for bilayer interface (DD-BI) model. The model solves Poisson, drift-diffusion and current-continuity equations self-consistently for charge densities and potential profiles of a bilayer device with an organic heterojunction interface described by the GWWF model. We also derive new diode equations that have JV curves consistent with the DD-BI model and thus will be called self-consistent diode (SCD) equations. Using the DD-BI and the SCD model allows us to understand working principles of bilayer OPVs and physical definitions of the Shockley parameters. Due to low carrier mobilities in OPVs, space charge accumulation is common especially near the interface and electrodes. Hence, quasi-Fermi levels (i.e. chemical potentials), which depend on charge densities, are modified around the interface, resulting in a splitting of quasi-Fermi levels that works as a driving

  13. A sub-cellular viscoelastic model for cell population mechanics.

    Directory of Open Access Journals (Sweden)

    Yousef Jamali

    Full Text Available Understanding the biomechanical properties and the effect of biomechanical force on epithelial cells is key to understanding how epithelial cells form uniquely shaped structures in two or three-dimensional space. Nevertheless, with the limitations and challenges posed by biological experiments at this scale, it becomes advantageous to use mathematical and 'in silico' (computational models as an alternate solution. This paper introduces a single-cell-based model representing the cross section of a typical tissue. Each cell in this model is an individual unit containing several sub-cellular elements, such as the elastic plasma membrane, enclosed viscoelastic elements that play the role of cytoskeleton, and the viscoelastic elements of the cell nucleus. The cell membrane is divided into segments where each segment (or point incorporates the cell's interaction and communication with other cells and its environment. The model is capable of simulating how cells cooperate and contribute to the overall structure and function of a particular tissue; it mimics many aspects of cellular behavior such as cell growth, division, apoptosis and polarization. The model allows for investigation of the biomechanical properties of cells, cell-cell interactions, effect of environment on cellular clusters, and how individual cells work together and contribute to the structure and function of a particular tissue. To evaluate the current approach in modeling different topologies of growing tissues in distinct biochemical conditions of the surrounding media, we model several key cellular phenomena, namely monolayer cell culture, effects of adhesion intensity, growth of epithelial cell through interaction with extra-cellular matrix (ECM, effects of a gap in the ECM, tensegrity and tissue morphogenesis and formation of hollow epithelial acini. The proposed computational model enables one to isolate the effects of biomechanical properties of individual cells and the

  14. Peripartum hysterectomy: an evolving picture.

    LENUS (Irish Health Repository)

    Turner, Michael J

    2012-02-01

    Peripartum hysterectomy (PH) is one of the obstetric catastrophes. Evidence is emerging that the role of PH in modern obstetrics is evolving. Improving management of postpartum hemorrhage and newer surgical techniques should decrease PH for uterine atony. Rising levels of repeat elective cesarean deliveries should decrease PH following uterine scar rupture in labor. Increasing cesarean rates, however, have led to an increase in the number of PHs for morbidly adherent placenta. In the case of uterine atony or rupture where PH is required, a subtotal PH is often sufficient. In the case of pathological placental localization involving the cervix, however, a total hysterectomy is required. Furthermore, the involvement of other pelvic structures may prospectively make the diagnosis difficult and the surgery challenging. If resources permit, PH for pathological placental localization merits a multidisciplinary approach. Despite advances in clinical practice, it is likely that peripartum hysterectomy will be more challenging for obstetricians in the future.

  15. Extreme evolved solar systems (EESS)

    Science.gov (United States)

    Gaensicke, Boris

    2017-08-01

    In just 20 years, we went from not knowing if the solar system is a fluke of Nature to realising that it is totally normal for stars to have planets. More remarkably, it is now clear that planet formation is a robust process, as rich multi-planet systems are found around stars more massive and less massive than the Sun. More recently, planetary systems have been identified in increasingly complex architectures, including circumbinary planets, wide binaries with planets orbiting one or both stellar components, and planets in triple stellar systems.We have also learned that many planetary systems will survive the evolution of their host stars into the white dwarf phase. Small bodies are scattered by unseen planets into the gravitational field of the white dwarfs, tidally disrupt, form dust discs, and eventually accrete onto the white dwarf, where they can be spectroscopically detected. HST/COS has played a critical role in the study these evolved planetary systems, demonstrating that overall the bulk composition of the debris is rocky and resembles in composition the inner the solar system, including evidence for water-rich planetesimals. Past observations of planetary systems at white dwarfs have focused on single stars with main-sequence progenitors of 1.5 to 2.5Msun. Here we propose to take the study of evolved planetary systems into the extremes of parameter ranges to answer questions such as: * How efficient is planet formation around 4-10Msun stars? * What are the metallicities of the progenitors of debris-accreting white dwarfs?* What is the fate of circumbinary planets?* Can star-planet interactions generate magnetic fields in the white dwarf host?

  16. Survivability is more fundamental than evolvability.

    Directory of Open Access Journals (Sweden)

    Michael E Palmer

    Full Text Available For a lineage to survive over long time periods, it must sometimes change. This has given rise to the term evolvability, meaning the tendency to produce adaptive variation. One lineage may be superior to another in terms of its current standing variation, or it may tend to produce more adaptive variation. However, evolutionary outcomes depend on more than standing variation and produced adaptive variation: deleterious variation also matters. Evolvability, as most commonly interpreted, is not predictive of evolutionary outcomes. Here, we define a predictive measure of the evolutionary success of a lineage that we call the k-survivability, defined as the probability that the lineage avoids extinction for k generations. We estimate the k-survivability using multiple experimental replicates. Because we measure evolutionary outcomes, the initial standing variation, the full spectrum of generated variation, and the heritability of that variation are all incorporated. Survivability also accounts for the decreased joint likelihood of extinction of sub-lineages when they 1 disperse in space, or 2 diversify in lifestyle. We illustrate measurement of survivability with in silico models, and suggest that it may also be measured in vivo using multiple longitudinal replicates. The k-survivability is a metric that enables the quantitative study of, for example, the evolution of 1 mutation rates, 2 dispersal mechanisms, 3 the genotype-phenotype map, and 4 sexual reproduction, in temporally and spatially fluctuating environments. Although these disparate phenomena evolve by well-understood microevolutionary rules, they are also subject to the macroevolutionary constraint of long-term survivability.

  17. Proceedings of the NETL Workshop on Fuel Cell Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Randall S. Gemmen; J. R. Selman

    2000-04-18

    This workshop was the first U.S. DOE sponsored meeting devoted to fuel cell modeling. The workshop was attended by over 45 people from industry, universities, and the government. The goals of the meeting were to assess the status of fuel cell modeling, and determine how new developments in fuel cell modeling can improve cell design, stack design, and power system design. The primary focus was on cell and stack modeling. Following a review of DOE/NETL fuel cell related programs and activities, Professor Robert Selman (Illinois Institute of Technology) kicked off the technical portion of the workshop by presenting an overview of fuel cell phenomena and the status of fuel cell modeling. This overview provided the necessary background for establishing a common framework for discussing fuel cell modeling. A distinction was made between micro modeling, electrode modeling, cell modeling, stack modeling, and system modeling. It was proposed that all modeling levels be supported for further development. In addition, due to significant advances being made outside the U.S., it was proposed that dialog/exchange with other international researchers be established. Following the Overview Session, eight leading researchers in modeling gave individual presentations. These presentations provided additional information on the status and present direction of model developments. All these presentations can be found in Attachment A. Before the workshop, a survey was sent out requesting comments from the attendees. Results from this survey can be found in Attachment B. This survey was then used as initial talking points at the individual breakout sessions on the afternoon of the workshop. Breakouts were organized by microfundamental modeling, cell modeling, stack modeling, and systems modeling.

  18. Modelling electrolyte conductivity in a water electrolyzer cell

    DEFF Research Database (Denmark)

    Caspersen, Michael; Kirkegaard, Julius Bier

    2012-01-01

    An analytical model describing the hydrogen gas evolution under natural convection in an electrolyzer cell is developed. Main purpose of the model is to investigate the electrolyte conductivity through the cell under various conditions. Cell conductivity is calculated from a parallel resistor...... for electrolyte conductivity from combinations of pressure, current density and electrolyte width among others....

  19. Validation of noise models for single-cell transcriptomics

    NARCIS (Netherlands)

    Grün, Dominic; Kester, Lennart; van Oudenaarden, Alexander

    Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity among single cells. Here we identify two major sources of technical variability: sampling noise and global cell-to-cell variation in sequencing efficiency. We propose noise models to

  20. Gradually softening hydrogels for modeling hepatic stellate cell behavior during fibrosis regression.

    Science.gov (United States)

    Caliari, Steven R; Perepelyuk, Maryna; Soulas, Elizabeth M; Lee, Gi Yun; Wells, Rebecca G; Burdick, Jason A

    2016-06-13

    The extracellular matrix (ECM) presents an evolving set of mechanical cues to resident cells. We developed methacrylated hyaluronic acid (MeHA) hydrogels containing both stable and hydrolytically degradable crosslinks to provide cells with a gradually softening (but not fully degradable) milieu, mimicking physiological events such as fibrosis regression. To demonstrate the utility of this cell culture system, we studied the phenotype of rat hepatic stellate cells, the major liver precursors of fibrogenic myofibroblasts, within this softening environment. Stellate cells that were mechanically primed on tissue culture plastic attained a myofibroblast phenotype, which persisted when seeded onto stiff (∼20 kPa) hydrogels. However, mechanically primed stellate cells on stiff-to-soft (∼20 to ∼3 kPa) hydrogels showed reversion of the myofibroblast phenotype over 14 days, with reductions in cell area, expression of the myofibroblast marker alpha-smooth muscle actin (α-SMA), and Yes-associated protein/Transcriptional coactivator with PDZ-binding motif (YAP/TAZ) nuclear localization when compared to stellate cells on stiff hydrogels. Cells on stiff-to-soft hydrogels did not fully revert, however. They displayed reduced expression of glial fibrillary acidic protein (GFAP), and underwent abnormally rapid re-activation to myofibroblasts in response to re-stiffening of the hydrogels through introduction of additional crosslinks. These features are typical of stellate cells with an intermediate phenotype, reported to occur in vivo with fibrosis regression and re-injury. Together, these data suggest that mechanics play an important role in fibrosis regression and that integrating dynamic mechanical cues into model systems helps capture cell behaviors observed in vivo.

  1. Evolving MEMS Resonator Designs for Fabrication

    Science.gov (United States)

    Hornby, Gregory S.; Kraus, William F.; Lohn, Jason D.

    2008-01-01

    Because of their small size and high reliability, microelectromechanical (MEMS) devices have the potential to revolution many areas of engineering. As with conventionally-sized engineering design, there is likely to be a demand for the automated design of MEMS devices. This paper describes our current status as we progress toward our ultimate goal of using an evolutionary algorithm and a generative representation to produce designs of a MEMS device and successfully demonstrate its transfer to an actual chip. To produce designs that are likely to transfer to reality, we present two ways to modify evaluation of designs. The first is to add location noise, differences between the actual dimensions of the design and the design blueprint, which is a technique we have used for our work in evolving antennas and robots. The second method is to add prestress to model the warping that occurs during the extreme heat of fabrication. In future we expect to fabricate and test some MEMS resonators that are evolved in this way.

  2. Cell sources for in vitro human liver cell culture models.

    Science.gov (United States)

    Zeilinger, Katrin; Freyer, Nora; Damm, Georg; Seehofer, Daniel; Knöspel, Fanny

    2016-09-01

    In vitro liver cell culture models are gaining increasing importance in pharmacological and toxicological research. The source of cells used is critical for the relevance and the predictive value of such models. Primary human hepatocytes (PHH) are currently considered to be the gold standard for hepatic in vitro culture models, since they directly reflect the specific metabolism and functionality of the human liver; however, the scarcity and difficult logistics of PHH have driven researchers to explore alternative cell sources, including liver cell lines and pluripotent stem cells. Liver cell lines generated from hepatomas or by genetic manipulation are widely used due to their good availability, but they are generally altered in certain metabolic functions. For the past few years, adult and pluripotent stem cells have been attracting increasing attention, due their ability to proliferate and to differentiate into hepatocyte-like cells in vitro However, controlling the differentiation of these cells is still a challenge. This review gives an overview of the major human cell sources under investigation for in vitro liver cell culture models, including primary human liver cells, liver cell lines, and stem cells. The promises and challenges of different cell types are discussed with a focus on the complex 2D and 3D culture approaches under investigation for improving liver cell functionality in vitro Finally, the specific application options of individual cell sources in pharmacological research or disease modeling are described. © 2016 by the Society for Experimental Biology and Medicine.

  3. Modeling bi-modality improves characterization of cell cycle on gene expression in single cells.

    Science.gov (United States)

    McDavid, Andrew; Dennis, Lucas; Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

    2014-07-01

    Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%-17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome.

  4. PEM Fuel Cell Modelling Using Artificial Neural Networks

    OpenAIRE

    Doumbia, Mamadou Lamine

    2016-01-01

    Fuel cells are electrochemical devices that convert the chemical energy of a reaction directly into dc electrical energy. Proton Exchange Membrane (PEM) fuel cell is a suitable alternative for both electrical transportation and stationary applications. In this article, an Artificial Neural Network (ANN) modelling approach of a PEM fuel cell is developed. This model describes the behaviour of PEM fuel cell voltage under both steady-state and transient conditions. Moreover, the prediction of th...

  5. Solid-State 55Mn NMR Spectroscopy of bis(μ-oxo)dimanganese(IV) [Mn2O2(salpn)2], a Model for the Oxygen Evolving Complex in Photosystem II

    Energy Technology Data Exchange (ETDEWEB)

    Ellis, Paul D.; Sears, Jesse A.; Yang, Ping; Dupuis, Michel; Boron, Ted; Pecoraro, Vince; Stich, Troy; Britt, R. David; Lipton, Andrew S.

    2010-12-01

    Given the obvious global energy needs, it has become imperative to develop a catalytic process for converting water to molecular oxygen and protons. Many have sought to understand the details of photosynthesis and in particular the water splitting reaction to help in the development of the appropriate catalysis.1-3 While the scientific community has made great strides towards this goal, it has fallen short at the critical stage of the determination of the structure associated with the oxygen evolving complex (OEC) within photosystem II (PSII).4,5 Despite the existence of x-ray structures of PSII,6-8 the best data we have for the structure of the OEC comes from models derived from EPR and EXAFS measurements.9-14 This experimental situation has led to collaborations with theoreticians to enable the development of models for the structure of the OEC where the experimental observables (EXAFS and magnetic resonance parameters) serve as constraints to the theoretical calculations. Of particular interest to this study is the observation of the S1 state of the Kok cycle15 where the core of the OEC can be described as a tetranuclear manganese cluster composed of Mn4OxCa. The simplest model for the OEC can be thought of as two Mn-pairs and a Ca2+ where each Mn-pair is antiferromagnetically coupled to its partner. We utilize the term "pair" to describe the Mn atoms within the OEC with the same oxidation state, which for the S1 state is (Mn2(III, III) and Mn2(IV, IV)).16 It is unclear as to the degree of interaction between the pairs as well as the role of the Ca2+. At cryogenic temperatures the S1 state of the OEC is diamagnetic and in principle amenable to solid-state NMR experiments.

  6. CERN internal communication is evolving

    CERN Multimedia

    2016-01-01

    CERN news will now be regularly updated on the CERN People page (see here).      Dear readers, All over the world, communication is becoming increasingly instantaneous, with news published in real time on websites and social networks. In order to keep pace with these changes, CERN's internal communication is evolving too. From now on, you will be informed of what’s happening at CERN more often via the “CERN people” page, which will frequently be updated with news. The Bulletin is following this trend too: twice a month, we will compile the most important articles published on the CERN site, with a brand-new layout. You will receive an e-mail every two weeks as soon as this new form of the Bulletin is available. If you have interesting news or stories to share, tell us about them through the form at: https://communications.web.cern.ch/got-story-cern-website​. You can also find out about news from CERN in real time...

  7. Animal models to study cancer-initiating cells from glioblastoma.

    Science.gov (United States)

    Wee, Boyoung; Charles, Nikki; Holland, Eric C

    2011-06-01

    Three main subtypes of gliomas with distinct molecular pathologies have been modeled in animals to better understand their biology. Genetically engineered mouse models that take advantage of genetic abnormalities observed in human gliomas have been instrumental in this process. These models better recapitulate signaling transduction pathways and the microenvironment that play crucial roles in glioma formation than in vitro systems or transplantation models. An increasing amount of data supports the existence of cells functionally defined by their self-renewal ability and tumor-initiating potential upon serial transplantation. As the issue of these cells with stem cell character in gliomagenesis becomes more illusive, animal models that provide an accurate experimental system where the stem cell character can be manipulated and studied are urgently needed. This review provides an overview of the current state of the literature with respect to animal models used in the study of gliomas and cells with stem cell character in their native environment.

  8. Therapeutic Antibodies to Ganglioside GD2 Evolved from Highly Selective Germline Antibodies

    Directory of Open Access Journals (Sweden)

    Eric Sterner

    2017-08-01

    Full Text Available Antibodies play a crucial role in host defense and are indispensable research tools, diagnostics, and therapeutics. Antibody generation involves binding of genomically encoded germline antibodies followed by somatic hypermutation and in vivo selection to obtain antibodies with high affinity and selectivity. Understanding this process is critical for developing monoclonal antibodies, designing effective vaccines, and understanding autoantibody formation. Prior studies have found that antibodies to haptens, peptides, and proteins evolve from polyspecific germline antibodies. The immunological evolution of antibodies to mammalian glycans has not been studied. Using glycan microarrays, protein microarrays, cell binding studies, and molecular modeling, we demonstrate that therapeutic antibodies to the tumor-associated ganglioside GD2 evolved from highly specific germline precursors. The results have important implications for developing vaccines and monoclonal antibodies that target carbohydrate antigens. In addition, they demonstrate an alternative pathway for antibody evolution within the immune system that is distinct from the polyspecific germline pathway.

  9. Electronic circuit model for proton exchange membrane fuel cells

    Science.gov (United States)

    Yu, Dachuan; Yuvarajan, S.

    The proton exchange membrane (PEM) fuel cell is being investigated as an alternate power source for various applications like transportation and emergency power supplies. The paper presents a novel circuit model for a PEM fuel cell that can be used to design and analyze fuel cell power systems. The PSPICE-based model uses bipolar junction transistors (BJTs) and LC elements available in the PSPICE library with some modification. The model includes the phenomena like activation polarization, ohmic polarization, and mass transport effect present in a PEM fuel cell. The static and dynamic characteristics obtained through simulation are compared with experimental results obtained on a commercial fuel cell module.

  10. Track structure model of cell damage in space flight

    Science.gov (United States)

    Katz, Robert; Cucinotta, Francis A.; Wilson, John W.; Shinn, Judy L.; Ngo, Duc M.

    1992-01-01

    The phenomenological track-structure model of cell damage is discussed. A description of the application of the track-structure model with the NASA Langley transport code for laboratory and space radiation is given. Comparisons to experimental results for cell survival during exposure to monoenergetic, heavy-ion beams are made. The model is also applied to predict cell damage rates and relative biological effectiveness for deep-space exposures.

  11. Kinetic models in industrial biotechnology - Improving cell factory performance.

    Science.gov (United States)

    Almquist, Joachim; Cvijovic, Marija; Hatzimanikatis, Vassily; Nielsen, Jens; Jirstrand, Mats

    2014-07-01

    An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Tracking correlated, simultaneously evolving target populations, II

    Science.gov (United States)

    Mahler, Ronald

    2017-05-01

    This paper is the sixth in a series aimed at weakening the independence assumptions that are typically presumed in multitarget tracking. Earlier papers investigated Bayes …lters that propagate the correlations between two evolving multitarget systems. Last year at this conference we attempted to derive PHD …lter-type approximations that account for both spatial correlation and cardinality correlation (i.e., correlation between the target numbers of the two systems). Unfortunately, this approach required heuristic models of both clutter and target appearance in order to incorporate both spatial and cardinality correlation. This paper describes a fully rigorous approach- provided, however, that spatial correlation between the two populations is ignored and only their cardinality correlations are taken into account. We derive the time-update and measurement-update equations for a CPHD …lter describing the evolution of such correlated multitarget populations.

  13. Epidemic spreading on evolving signed networks

    CERN Document Server

    Saeedian, M; Jafari, G R; Kertesz, J

    2016-01-01

    Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences peoples willingness to contact others: A friendly contact may be turned to unfriendly to avoid infection. We study the susceptible-infected (SI) disease spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heiders theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte-Carlo simulations on complete networks to test the energy landscape, where we find loc...

  14. Cell models lead to understanding of multi-cellular morphogenesis consisting of successive self-construction of cells.

    Science.gov (United States)

    Honda, Hisao; Nagai, Tatsuzo

    2015-03-01

    Morphogenesis of multi-cellular organisms occurs through cell behaviours within a cell aggregate. Cell behaviours have been described using cell models involving equations of motion for cells. Cells in cell models construct shapes of the cell aggregate by themselves. Here, a history of cell models, the cell centre model and the vertex cell model, which we have constructed, are described. Furthermore, the application of these cell models is explained in detail. These cell models have been applied to transformation of cell aggregates to become spherical, formation of mammalian blastocysts and cell intercalation in elongating tissues. These are all elemental processes of morphogenesis and take place in succession during the whole developmental process. A chain of successive elemental processes leads to morphogenesis. Finally, we highlight that cell models are indispensable to understand the process whereby genes direct biological shapes. © The Authors 2014. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

  15. The Space-Jump Model of the Movement of Tumor Cells and Healthy Cells

    Directory of Open Access Journals (Sweden)

    Meng-Rong Li

    2014-01-01

    Full Text Available We establish the interaction model of two cell populations following the concept of the random-walk, and assume the cell movement is constrained by space limitation primarily. Furthermore, we analyze the model to obtain the behavior of two cell populations as time is closed to initial state and far into the future.

  16. Trichomes as models for studying plant cell differentiation.

    Science.gov (United States)

    Yang, Changxian; Ye, Zhibiao

    2013-06-01

    Trichomes, originating from epidermal cells, are present on nearly all terrestrial plants. They exist in diverse forms, are readily accessible, and serve as an excellent model system for analyzing the molecular mechanisms in plant cell differentiation, including cell fate choices, cell cycle control, and cell morphogenesis. In Arabidopsis, two regulatory models have been identified that function in parallel in trichome formation; the activator-inhibitor model and the activator-depletion model. Cotton fiber, a similar unicellular structure, is controlled by some functional homologues of Arabidopsis trichome-patterning genes. Multicellular trichomes, as in tobacco and tomato, may form through a distinct pathway from unicellular trichomes. Recent research has shown that cell cycle control participates in trichome formation. In this review, we summarize the molecular mechanisms involved in the formation of unicellular and multicellular trichomes, and discuss the integration of the cell cycle in its initiation and morphogenesis.

  17. The mathematical cell model reconstructed from interference microscopy data

    Science.gov (United States)

    Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

    2017-09-01

    The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

  18. Mathematical models in cell biology and cancer chemotherapy

    CERN Document Server

    Eisen, Martin

    1979-01-01

    The purpose of this book is to show how mathematics can be applied to improve cancer chemotherapy. Unfortunately, most drugs used in treating cancer kill both normal and abnormal cells. However, more cancer cells than normal cells can be destroyed by the drug because tumor cells usually exhibit different growth kinetics than normal cells. To capitalize on this last fact, cell kinetics must be studied by formulating mathematical models of normal and abnormal cell growth. These models allow the therapeutic and harmful effects of cancer drugs to be simulated quantitatively. The combined cell and drug models can be used to study the effects of different methods of administering drugs. The least harmful method of drug administration, according to a given criterion, can be found by applying optimal control theory. The prerequisites for reading this book are an elementary knowledge of ordinary differential equations, probability, statistics, and linear algebra. In order to make this book self-contained, a chapter on...

  19. E. coli as a biological model for cancer cells

    Science.gov (United States)

    Liao, David; Lambert, Guillaume; Austin, Robert

    2010-03-01

    Uninhibited growth and invasion of healthy tissue characterize cancer. We co-cultured two strains of E. coli bacteria in a microfabricated environment to model cancer. During starvation, growth-advantage-in-stationary-phase, or GASP, cells grew to a higher population than wild-type cells. GASP cells also displaced wild-type cells from nutrient-rich chambers. When we repeated the experiment with medium depleted by wild-type cells, the peak GASP population density increased 54%, and the ``invasion,'' or displacement of wild-type cells from nutrient-rich chambers, occurred 5 hours earlier. We mathematically modeled both this increase in GASP population and this acceleration of spatial invasion by assuming that GASP cells consume detritus secreted by wild-type cells. Our experimental and model results corroborate recent caution against using tumor starvation as a cancer therapy.

  20. Modeling the Chagas’ disease after stem cell transplantation

    Science.gov (United States)

    Galvão, Viviane; Miranda, José Garcia Vivas

    2009-04-01

    A recent model for Chagas’ disease after stem cell transplantation is extended for a three-dimensional multi-agent-based model. The computational model includes six different types of autonomous agents: inflammatory cell, fibrosis, cardiomyocyte, proinflammatory cytokine tumor necrosis factor- α, Trypanosoma cruzi, and bone marrow stem cell. Only fibrosis is fixed and the other types of agents can move randomly through the empty spaces using the three-dimensional Moore neighborhood. Bone marrow stem cells can promote apoptosis in inflammatory cells, fibrosis regression and can differentiate in cardiomyocyte. T. cruzi can increase the number of inflammatory cells. Inflammatory cells and tumor necrosis factor- α can increase the quantity of fibrosis. Our results were compared with experimental data giving a fairly fit and they suggest that the inflammatory cells are important for the development of fibrosis.

  1. Comparative modeling of InP solar cell structures

    Science.gov (United States)

    Jain, R. K.; Weinberg, I.; Flood, D. J.

    1991-01-01

    The comparative modeling of p(+)n and n(+)p indium phosphide solar cell structures is studied using a numerical program PC-1D. The optimal design study has predicted that the p(+)n structure offers improved cell efficiencies as compared to n(+)p structure, due to higher open-circuit voltage. The various cell material and process parameters to achieve the maximum cell efficiencies are reported. The effect of some of the cell parameters on InP cell I-V characteristics was studied. The available radiation resistance data on n(+)p and p(+)p InP solar cells are also critically discussed.

  2. Determinants of brain cell metabolic phenotypes and energy substrate utilization unraveled with a modeling approach.

    Directory of Open Access Journals (Sweden)

    Aitana Neves

    Full Text Available Although all brain cells bear in principle a comparable potential in terms of energetics, in reality they exhibit different metabolic profiles. The specific biochemical characteristics explaining such disparities and their relative importance are largely unknown. Using a modeling approach, we show that modifying the kinetic parameters of pyruvate dehydrogenase and mitochondrial NADH shuttling within a realistic interval can yield a striking switch in lactate flux direction. In this context, cells having essentially an oxidative profile exhibit pronounced extracellular lactate uptake and consumption. However, they can be turned into cells with prominent aerobic glycolysis by selectively reducing the aforementioned parameters. In the case of primarily oxidative cells, we also examined the role of glycolysis and lactate transport in providing pyruvate to mitochondria in order to sustain oxidative phosphorylation. The results show that changes in lactate transport capacity and extracellular lactate concentration within the range described experimentally can sustain enhanced oxidative metabolism upon activation. Such a demonstration provides key elements to understand why certain brain cell types constitutively adopt a particular metabolic profile and how specific features can be altered under different physiological and pathological conditions in order to face evolving energy demands.

  3. Modeling Of Proton Exchange Membrane Fuel Cell Systems

    DEFF Research Database (Denmark)

    Nielsen, Mads Pagh

    The objective of this doctoral thesis was to develop reliable steady-state and transient component models suitable to asses-, develop- and optimize proton exchange membrane (PEM) fuel cell systems. Several components in PEM fuel cell systems were characterized and modeled. The developed component...... cell systems. Consequences of indirectly fueling PEM stacks with hydrocarbons using reforming technology were investigated using a PEM stack model including CO poisoning kinetics and a transient Simulink steam reforming system model. Aspects regarding the optimization of PEM fuel cell systems......- and system models match experimental data from the literature. However, limited data were available for verification so further work is necessary to confirm detailed aspects of the models. It is nonetheless expected that the developed models will be useful for system modeling and optimization of PEM fuel...

  4. Odor supported place cell model and goal navigation in rodents

    DEFF Research Database (Denmark)

    Kulvicius, Tomas; Tamosiunaite, Minija; Ainge, James

    2008-01-01

    -generated scent marks to find a food source. Here we model odor supported place cells by using a simple feed-forward network and analyze the impact of olfactory cues on place cell formation and spatial navigation. The obtained place cells are used to solve a goal navigation task by a novel mechanism based on self...

  5. Amicon Stirred Ultrafiltration Cells (Models 8050, 8400)

    OpenAIRE

    sprotocols

    2014-01-01

    Author: Sosnick Lab, University of Chicago ### Description For protein concentration, gas pressure is applied directly to ultrafiltration cell. Solutes above the membrane's molecular weight (MW) cut-off are retained in cell, while water and solutes below the cut-off pass into the filtrate and out of cell. ![Table ](http://i.imgur.com/oytODQD.png "`Table 1") ### Membranes 1. YM10 Ø43 mm (for 8050), Amicon #13622, 10 pack: $108 - YM10 Ø76 mm (for 8400), Amicon ...

  6. Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

    Science.gov (United States)

    2015-03-03

    1984, 26, 203–216. 3. Steinmeyer, D.; Shuler, M. Structured model for Saccharomyces cerevisiae . Chem. Eng. Sci. 1989, 44, 2017–2030. 4. Wu, P.; Ray...consider cell growth . Thus, cell-free operation holds several significant advantages for model development, identification The views, opinions and/or...longer have to consider cell growth . Thus, cell-free operation holds several significant advantages for model development, identification and validation

  7. From cells to tissue: A continuum model of epithelial mechanics

    Science.gov (United States)

    Ishihara, Shuji; Marcq, Philippe; Sugimura, Kaoru

    2017-08-01

    A two-dimensional continuum model of epithelial tissue mechanics was formulated using cellular-level mechanical ingredients and cell morphogenetic processes, including cellular shape changes and cellular rearrangements. This model incorporates stress and deformation tensors, which can be compared with experimental data. Focusing on the interplay between cell shape changes and cell rearrangements, we elucidated dynamical behavior underlying passive relaxation, active contraction-elongation, and tissue shear flow, including a mechanism for contraction-elongation, whereby tissue flows perpendicularly to the axis of cell elongation. This study provides an integrated scheme for the understanding of the orchestration of morphogenetic processes in individual cells to achieve epithelial tissue morphogenesis.

  8. Modeling intrinsic electrophysiology of AII amacrine cells: preliminary results.

    Science.gov (United States)

    Apollo, Nick; Grayden, David B; Burkitt, Anthony N; Meffin, Hamish; Kameneva, Tatiana

    2013-01-01

    In patients who have lost their photoreceptors due to retinal degenerative diseases, it is possible to restore rudimentary vision by electrically stimulating surviving neurons. AII amacrine cells, which reside in the inner plexiform layer, split the signal from rod bipolar cells into ON and OFF cone pathways. As a result, it is of interest to develop a computational model to aid in the understanding of how these cells respond to the electrical stimulation delivered by a prosthetic implant. The aim of this work is to develop and constrain parameters in a single-compartment model of an AII amacrine cell using data from whole-cell patch clamp recordings. This model will be used to explore responses of AII amacrine cells to electrical stimulation. Single-compartment Hodgkin-Huxley-type neural models are simulated in the NEURON environment. Simulations showed successful reproduction of the potassium currentvoltage relationship and some of the spiking properties observed in vitro.

  9. In vitro Cell Culture Model for Toxic Inhaled Chemical Testing

    Science.gov (United States)

    Ahmad, Shama; Ahmad, Aftab; Neeves, Keith B.; Hendry-Hofer, Tara; Loader, Joan E.; White, Carl W.; Veress, Livia

    2014-01-01

    Cell cultures are indispensable to develop and study efficacy of therapeutic agents, prior to their use in animal models. We have the unique ability to model well differentiated human airway epithelium and heart muscle cells. This could be an invaluable tool to study the deleterious effects of toxic inhaled chemicals, such as chlorine, that can normally interact with the cell surfaces, and form various byproducts upon reacting with water, and limiting their effects in submerged cultures. Our model using well differentiated human airway epithelial cell cultures at air-liqiuid interface circumvents this limitation as well as provides an opportunity to evaluate critical mechanisms of toxicity of potential poisonous inhaled chemicals. We describe enhanced loss of membrane integrity, caspase release and death upon toxic inhaled chemical such as chlorine exposure. In this article, we propose methods to model chlorine exposure in mammalian heart and airway epithelial cells in culture and simple tests to evaluate its effect on these cell types. PMID:24837339

  10. Device and materials modeling in PEM fuel cells

    CERN Document Server

    Promislow, Keith

    2009-01-01

    Device and Materials Modeling in PEM Fuel Cells is a specialized text that compiles the mathematical details and results of both device and materials modeling in a single volume. Proton exchange membrane (PEM) fuel cells will likely have an impact on our way of life similar to the integrated circuit. The potential applications range from the micron scale to large scale industrial production. Successful integration of PEM fuel cells into the mass market will require new materials and a deeper understanding of the balance required to maintain various operational states. This book contains articles from scientists who contribute to fuel cell models from both the materials and device perspectives. Topics such as catalyst layer performance and operation, reactor dynamics, macroscopic transport, and analytical models are covered under device modeling. Materials modeling include subjects relating to the membrane and the catalyst such as proton conduction, atomistic structural modeling, quantum molecular dynamics, an...

  11. A kinetic model for flavonoid production in tea cell culture.

    Science.gov (United States)

    Shibasaki-Kitakawa, Naomi; Iizuka, Yasuhiro; Takahashi, Atsushi; Yonemoto, Toshikuni

    2017-02-01

    As one of the strategies for efficient production of a metabolite from cell cultures, a kinetic model is very useful tool to predict productivity under various culture conditions. In this study, we propose a kinetic model for flavonoid production in tea cell culture based on the cell life cycle and expression of PAL, the gene encoding phenylalanine ammonia-lyase (PAL)-the key enzyme in flavonoid biosynthesis. The flavonoid production rate was considered to be related to the amount of active PAL. Synthesis of PAL was modelled based on a general gene expression/translation mechanism, including the transcription of DNA encoding PAL into mRNA and the translation of PAL mRNA into the PAL protein. The transcription of DNA was assumed to be promoted at high light intensity and suppressed by a feedback regulatory mechanism at high flavonoid concentrations. In the model, mRNA and PAL were considered to self-decompose and to be lost by cell rupture. The model constants were estimated by fitting the experimental results obtained from tea cell cultures under various light intensities. The model accurately described the kinetic behaviors of dry and fresh cell concentrations, glucose concentration, cell viability, PAL specific activity, and flavonoid content under a wide range of light intensities. The model simulated flavonoid productivity per medium under various culture conditions. Therefore, this model will be useful to predict optimum culture conditions for maximum flavonoid productivity in cultured tea cells.

  12. Lessons from models of pancreatic beta cells for engineering glucose-sensing cells.

    Science.gov (United States)

    Sherman, Arthur

    2010-09-01

    Mathematical models of pancreatic beta cells suggest design principles that can be applied to engineering cells to sense glucose and secrete insulin. Engineering cells can potentially both contribute to future diabetes therapies and generate new insights into beta-cell function. The focus is on ion channels, Ca(2+)handling, and elements of metabolism that combine to produce the varied oscillatory patterns exhibited by beta cells. Copyright 2010. Published by Elsevier Inc.

  13. Modelling of tandem cell temperature coefficients

    Energy Technology Data Exchange (ETDEWEB)

    Friedman, D.J. [National Renewable Energy Lab., Golden, CO (United States)

    1996-05-01

    This paper discusses the temperature dependence of the basic solar-cell operating parameters for a GaInP/GaAs series-connected two-terminal tandem cell. The effects of series resistance and of different incident solar spectra are also discussed.

  14. Eat Prey, Live: Dictyostelium discoideum As a Model for Cell-Autonomous Defenses

    Directory of Open Access Journals (Sweden)

    Joe Dan Dunn

    2018-01-01

    Full Text Available The soil-dwelling social amoeba Dictyostelium discoideum feeds on bacteria. Each meal is a potential infection because some bacteria have evolved mechanisms to resist predation. To survive such a hostile environment, D. discoideum has in turn evolved efficient antimicrobial responses that are intertwined with phagocytosis and autophagy, its nutrient acquisition pathways. The core machinery and antimicrobial functions of these pathways are conserved in the mononuclear phagocytes of mammals, which mediate the initial, innate-immune response to infection. In this review, we discuss the advantages and relevance of D. discoideum as a model phagocyte to study cell-autonomous defenses. We cover the antimicrobial functions of phagocytosis and autophagy and describe the processes that create a microbicidal phagosome: acidification and delivery of lytic enzymes, generation of reactive oxygen species, and the regulation of Zn2+, Cu2+, and Fe2+ availability. High concentrations of metals poison microbes while metal sequestration inhibits their metabolic activity. We also describe microbial interference with these defenses and highlight observations made first in D. discoideum. Finally, we discuss galectins, TNF receptor-associated factors, tripartite motif-containing proteins, and signal transducers and activators of transcription, microbial restriction factors initially characterized in mammalian phagocytes that have either homologs or functional analogs in D. discoideum.

  15. Cell adhesion heterogeneity reinforces tumour cell dissemination: novel insights from a mathematical model.

    Science.gov (United States)

    Reher, David; Klink, Barbara; Deutsch, Andreas; Voss-Böhme, Anja

    2017-08-11

    Cancer cell invasion, dissemination, and metastasis have been linked to an epithelial-mesenchymal transition (EMT) of individual tumour cells. During EMT, adhesion molecules like E-cadherin are downregulated and the decrease of cell-cell adhesion allows tumour cells to dissociate from the primary tumour mass. This complex process depends on intracellular cues that are subject to genetic and epigenetic variability, as well as extrinsic cues from the local environment resulting in a spatial heterogeneity in the adhesive phenotype of individual tumour cells. Here, we use a novel mathematical model to study how adhesion heterogeneity, influenced by intrinsic and extrinsic factors, affects the dissemination of tumour cells from an epithelial cell population. The model is a multiscale cellular automaton that couples intracellular adhesion receptor regulation with cell-cell adhesion. Simulations of our mathematical model indicate profound effects of adhesion heterogeneity on tumour cell dissemination. In particular, we show that a large variation of intracellular adhesion receptor concentrations in a cell population reinforces cell dissemination, regardless of extrinsic cues mediated through the local cell density. However, additional control of adhesion receptor concentration through the local cell density, which can be assumed in healthy cells, weakens the effect. Furthermore, we provide evidence that adhesion heterogeneity can explain the remarkable differences in adhesion receptor concentrations of epithelial and mesenchymal phenotypes observed during EMT and might drive early dissemination of tumour cells. Our results suggest that adhesion heterogeneity may be a universal trigger to reinforce cell dissemination in epithelial cell populations. This effect can be at least partially compensated by a control of adhesion receptor regulation through neighbouring cells. Accordingly, our findings explain how both an increase in intra-tumour adhesion heterogeneity and the

  16. Chimeric animal models in human stem cell biology.

    Science.gov (United States)

    Glover, Joel C; Boulland, Jean-Luc; Halasi, Gabor; Kasumacic, Nedim

    2009-01-01

    The clinical use of stem cells for regenerative medicine is critically dependent on preclinical studies in animal models. In this review we examine some of the key issues and challenges in the use of animal models to study human stem cell biology-experimental standardization, body size, immunological barriers, cell survival factors, fusion of host and donor cells, and in vivo imaging and tracking. We focus particular attention on the various imaging modalities that can be used to track cells in living animals, comparing their strengths and weaknesses and describing technical developments that are likely to lead to new opportunities for the dynamic assessment of stem cell behavior in vivo. We then provide an overview of some of the most commonly used animal models, their advantages and disadvantages, and examples of their use for xenotypic transplantation of human stem cells, with separate reviews of models involving rodents, ungulates, nonhuman primates, and the chicken embryo. As the use of human somatic, embryonic, and induced pluripotent stem cells increases, so too will the range of applications for these animal models. It is likely that increasingly sophisticated uses of human/animal chimeric models will be developed through advances in genetic manipulation, cell delivery, and in vivo imaging.

  17. Modelling of Yeast Mating Reveals Robustness Strategies for Cell-Cell Interactions.

    Directory of Open Access Journals (Sweden)

    Weitao Chen

    2016-07-01

    Full Text Available Mating of budding yeast cells is a model system for studying cell-cell interactions. Haploid yeast cells secrete mating pheromones that are sensed by the partner which responds by growing a mating projection toward the source. The two projections meet and fuse to form the diploid. Successful mating relies on precise coordination of dynamic extracellular signals, signaling pathways, and cell shape changes in a noisy background. It remains elusive how cells mate accurately and efficiently in a natural multi-cell environment. Here we present the first stochastic model of multiple mating cells whose morphologies are driven by pheromone gradients and intracellular signals. Our novel computational framework encompassed a moving boundary method for modeling both a-cells and α-cells and their cell shape changes, the extracellular diffusion of mating pheromones dynamically coupled with cell polarization, and both external and internal noise. Quantification of mating efficiency was developed and tested for different model parameters. Computer simulations revealed important robustness strategies for mating in the presence of noise. These strategies included the polarized secretion of pheromone, the presence of the α-factor protease Bar1, and the regulation of sensing sensitivity; all were consistent with data in the literature. In addition, we investigated mating discrimination, the ability of an a-cell to distinguish between α-cells either making or not making α-factor, and mating competition, in which multiple a-cells compete to mate with one α-cell. Our simulations were consistent with previous experimental results. Moreover, we performed a combination of simulations and experiments to estimate the diffusion rate of the pheromone a-factor. In summary, we constructed a framework for simulating yeast mating with multiple cells in a noisy environment, and used this framework to reproduce mating behaviors and to identify strategies for robust cell-cell

  18. DNA evolved to minimize frameshift mutations

    OpenAIRE

    Agoni, Valentina

    2013-01-01

    Point mutations can surely be dangerous but what is worst than to lose the reading frame?! Does DNA evolved a strategy to try to limit frameshift mutations?! Here we investigate if DNA sequences effectively evolved a system to minimize frameshift mutations analyzing the transcripts of proteins with high molecular weights.

  19. Recent Advances in Enzymatic Fuel Cells: Experiments and Modeling

    Directory of Open Access Journals (Sweden)

    Ivan Ivanov

    2010-04-01

    Full Text Available Enzymatic fuel cells convert the chemical energy of biofuels into electrical energy. Unlike traditional fuel cell types, which are mainly based on metal catalysts, the enzymatic fuel cells employ enzymes as catalysts. This fuel cell type can be used as an implantable power source for a variety of medical devices used in modern medicine to administer drugs, treat ailments and monitor bodily functions. Some advantages in comparison to conventional fuel cells include a simple fuel cell design and lower cost of the main fuel cell components, however they suffer from severe kinetic limitations mainly due to inefficiency in electron transfer between the enzyme and the electrode surface. In this review article, the major research activities concerned with the enzymatic fuel cells (anode and cathode development, system design, modeling by highlighting the current problems (low cell voltage, low current density, stability will be presented.

  20. Proton exchange membrane fuel cells modeling

    CERN Document Server

    Gao, Fengge; Miraoui, Abdellatif

    2013-01-01

    The fuel cell is a potential candidate for energy storage and conversion in our future energy mix. It is able to directly convert the chemical energy stored in fuel (e.g. hydrogen) into electricity, without undergoing different intermediary conversion steps. In the field of mobile and stationary applications, it is considered to be one of the future energy solutions.Among the different fuel cell types, the proton exchange membrane (PEM) fuel cell has shown great potential in mobile applications, due to its low operating temperature, solid-state electrolyte and compactness.This book pre

  1. Intelligent reservoir operation system based on evolving artificial neural networks

    Science.gov (United States)

    Chaves, Paulo; Chang, Fi-John

    2008-06-01

    We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.

  2. Evolving user needs and late-mover advantage

    NARCIS (Netherlands)

    Querbes, Adrien; Frenken, Koen

    2017-01-01

    We propose a generalized NK-model of late-mover advantage where late-mover firms leapfrog first-mover firms as user needs evolve over time. First movers face severe trade-offs between the provision of functionalities in which their products already excel and the additional functionalities requested

  3. Active Printed Materials for Complex Self-Evolving Deformations

    Science.gov (United States)

    Raviv, Dan; Zhao, Wei; McKnelly, Carrie; Papadopoulou, Athina; Kadambi, Achuta; Shi, Boxin; Hirsch, Shai; Dikovsky, Daniel; Zyracki, Michael; Olguin, Carlos; Raskar, Ramesh; Tibbits, Skylar

    2014-12-01

    We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus.

  4. Molecular modeling of PEM fuel cell electrochemistry

    Science.gov (United States)

    Rai, Varun

    Polymer Electrolyte Membrane fuel cell (PEMFC) is an electrochemical power-generating device that combines hydrogen (H2) with oxygen (O2) via electrochemical (electron-transfer) processes to form water. Among other features, its low operating temperatures, high theoretical efficiencies, and quick startup make PEMFC promising as a power source for several applications, like laptops, small-scale power generation, automobiles, etc. Although tremendous progress has been made in PEMFC technology in the last decade or so, a number of key technological issues still remain to be addressed before PEMFC comes to the consumer markets. The two main challenges are the cost and the performance of the PEMFC technology. A major contributor to both these limitations is the catalyst used in PEMFC---used to improve the efficiency of PEMFC by enhancing the rate of the electrochemical reactions, catalyst materials form about 20% of the total system cost. And yet, 15--20% of the theoretical efficiency of PEMFC is lost due to poor reaction rates at the catalysts. For its superior catalytic activity for the oxygen reduction reaction (ORR), which is the main electrochemical reaction in PEMFCs, Pt remains the leading choice for the cathode catalyst in PEMFCs. So, a solid grasp of the fundamental electrochemical processes at the Pt-electrolyte interface is necessary for the design of optimal catalysts (based on cost, activity, stability, and tolerance to contaminants) for PEMFCs. In this thesis, molecular modeling techniques were used to study the ORR on Pt, which resulted in two main contributions. First, two new computational algorithms for simulating advanced catalyst systems were developed. Second, the ORR on Pt(111) in acid solutions was studied using a combination of first-principles simulation methodologies, where both Dynamic Monte Carlo (DMC) simulations and Density Functional Theory (DFT) quantum simulations were employed. The results from this study provided several new insights

  5. Multiple scale model for cell migration in monolayers: Elastic mismatch between cells enhances motility.

    Science.gov (United States)

    Palmieri, Benoit; Bresler, Yony; Wirtz, Denis; Grant, Martin

    2015-07-02

    We propose a multiscale model for monolayer of motile cells that comprise normal and cancer cells. In the model, the two types of cells have identical properties except for their elasticity; cancer cells are softer and normal cells are stiffer. The goal is to isolate the role of elasticity mismatch on the migration potential of cancer cells in the absence of other contributions that are present in real cells. The methodology is based on a phase-field description where each cell is modeled as a highly-deformable self-propelled droplet. We simulated two types of nearly confluent monolayers. One contains a single cancer cell in a layer of normal cells and the other contains normal cells only. The simulation results demonstrate that elasticity mismatch alone is sufficient to increase the motility of the cancer cell significantly. Further, the trajectory of the cancer cell is decorated by several speed "bursts" where the cancer cell quickly relaxes from a largely deformed shape and consequently increases its translational motion. The increased motility and the amplitude and frequency of the bursts are in qualitative agreement with recent experiments.

  6. Running and rotating: modelling the dynamics of migrating cell clusters

    Science.gov (United States)

    Copenhagen, Katherine; Gov, Nir; Gopinathan, Ajay

    Collective motion of cells is a common occurrence in many biological systems, including tissue development and repair, and tumor formation. Recent experiments have shown cells form clusters in a chemical gradient, which display three different phases of motion: translational, rotational, and random. We present a model for cell clusters based loosely on other models seen in the literature that involves a Vicsek-like alignment as well as physical collisions and adhesions between cells. With this model we show that a mechanism for driving rotational motion in this kind of system is an increased motility of rim cells. Further, we examine the details of the relationship between rim and core cells, and find that the phases of the cluster as a whole are correlated with the creation and annihilation of topological defects in the tangential component of the velocity field.

  7. A Model of Dendritic Cell Therapy for Melanoma

    Directory of Open Access Journals (Sweden)

    Ami eRadunskaya

    2013-03-01

    Full Text Available Dendritic cells are a promising immunotherapy tool for boosting an individual's antigen specific immune response to cancer. We develop a mathematical model using differential and delay-differential equations to describe the interactions between dendritic cells, effector-immune cells and tumor cells. We account for the trafficking of immune cells between lymph, blood, and tumor compartments. Our model reflects experimental results both for dendritic-cell trafficking and for immune suppression of tumor growth in mice. In addition, in silico experiments suggest more effective immunotherapy treatment protocols can be achieved by modifying dose location and schedule. A sensitivity analysis of the model reveals which patient-specific parameters have the greatest impact on treatment efficacy.

  8. Modeling of a Microbial Fuel Cell

    OpenAIRE

    Calder, Michael Alexander

    2007-01-01

    It is clear that society worldwide must immediately begin to mitigate its environmental damage in order to sustain life on Earth. In this regard, researchers all over the global are exploring new energy efficient alternatives to power everything from cars to cell phones. The following brief describes research conducted on Microbial Fuel Cells (MFC) and its ability to utilize bacteria to produce electricity from biological masses for low energy consumer products While structurally the MFC i...

  9. A stochastic model dissects cell states in biological transition processes.

    Science.gov (United States)

    Armond, Jonathan W; Saha, Krishanu; Rana, Anas A; Oates, Chris J; Jaenisch, Rudolf; Nicodemi, Mario; Mukherjee, Sach

    2014-01-17

    Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

  10. A stochastic model dissects cell states in biological transition processes

    Science.gov (United States)

    Armond, Jonathan W.; Saha, Krishanu; Rana, Anas A.; Oates, Chris J.; Jaenisch, Rudolf; Nicodemi, Mario; Mukherjee, Sach

    2014-01-01

    Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

  11. Dynamic Model of High Temperature PEM Fuel Cell Stack Temperature

    DEFF Research Database (Denmark)

    Andreasen, Søren Juhl; Kær, Søren Knudsen

    2007-01-01

    The present work involves the development of a model for predicting the dynamic temperature of a high temperature PEM (HTPEM) fuel cell stack. The model is developed to test different thermal control strategies before implementing them in the actual system. The test system consists of a prototype...... cathode air cooled 30 cell HTPEM fuel cell stack developed at the Institute of Energy Technology at Aalborg University. This fuel cell stack uses PEMEAS Celtec P-1000 membranes, runs on pure hydrogen in a dead end anode configuration with a purge valve. The cooling of the stack is managed by running...... the stack at a high stoichiometric air flow. This is possible because of the PBI fuel cell membranes used, and the very low pressure drop in the stack. The model consists of a discrete thermal model dividing the stack into three parts: inlet, middle and end and predicting the temperatures in these three...

  12. Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

    Science.gov (United States)

    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.

  13. Thermal modelling of an AMTEC recirculating cell

    Science.gov (United States)

    Suitor, J. W.; Williams, R. M.; Underwood, M. L.; Ryan, M. A.; Jeffries-Nakamura, B.; O'Connor, D.

    1992-01-01

    A modeling program was developed to determine the impact of various design parameters on the operation of an AMTEC system. Temperature profiles generated by the modeling program were compared to actual experimental data to verify the model accuracy. The model was then extended to predict the impact of device design on operational performance. The effect of heat loss from the liquid sodium supply end was studied for this paper.

  14. Deconstructing stem cell population heterogeneity: Single-cell analysis and modeling approaches

    Science.gov (United States)

    Wu, Jincheng; Tzanakakis, Emmanuel S.

    2014-01-01

    Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives. PMID:24035899

  15. Tomato fruit growth : integrating cell division, cell growth and endoreduplication by experimentation and modelling

    NARCIS (Netherlands)

    Fanwoua, J.

    2012-01-01

    Keywords: cell division, cell growth, cell endoreduplication, fruit growth, genotype, G×E interaction, model, tomato. Fruit size is a major component of fruit yield and quality of many crops. Variations in fruit size can be tremendous due to genotypic and environmental factors. The mechanisms

  16. Evolving Nonthermal Electron Distributions in Simulations of Sgr A*

    Science.gov (United States)

    Chael, Andrew; Narayan, Ramesh

    2018-01-01

    The accretion flow around Sagittarius A* (Sgr A*), the black hole at the Galactic Center, produces strong variability from the radio to X-rays on timescales of minutes to hours. This rapid, powerful variability is thought to be powered by energetic particle acceleration by plasma processes like magnetic reconnection and shocks. These processes can accelerate particles into non-thermal distributions which do not quickly isothermal in the low densities found around hot accretion flows. Current state-of-the-art simulations of accretion flows around black holes assume either a single-temperature gas or, at best, a two-temperature gas with thermal ions and electrons. We present results from incorporating the self-consistent evolution of a non-thermal electron population in a GRRMHD simulation of Sgr A*. The electron distribution is evolved across space, time, and Lorentz factor in parallel with background thermal ion, electron, and radiation fluids. Energy injection into the non-thermal distribution is modeled with a sub-grid prescription based on results from particle-in-cell simulations of magnetic reconnection. The energy distribution of the non-thermal electrons shows strong variability, and the spectral shape traces the complex interplay between the local viscous heating rate, magnetic field strength, and fluid velocity. Results from these simulations will be used in interpreting forthcoming data from the Event Horizon Telescope that resolves Sgr A*'s sub-mm variability in both time and space.

  17. Model checking to assess T-helper cell plasticity.

    Science.gov (United States)

    Abou-Jaoudé, Wassim; Monteiro, Pedro T; Naldi, Aurélien; Grandclaudon, Maximilien; Soumelis, Vassili; Chaouiya, Claudine; Thieffry, Denis

    2014-01-01

    Computational modeling constitutes a crucial step toward the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g., stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity. In this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models. We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions. As a case study, we consider the cellular network regulating the differentiation of T-helper (Th) cells, which orchestrate many physiological and pathological immune responses. To account for novel cellular subtypes, we present an extended version of a published model of Th cell differentiation. We then use symbolic model checking to analyze reachability properties between Th subtypes upon changes of environmental cues. This allows for the construction of a synthetic view of Th cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions. Finally, we explore novel strategies enabling specific Th cell polarizing or reprograming events.

  18. Model checking to assess T-helper cell plasticity

    Directory of Open Access Journals (Sweden)

    Wassim eAbou-Jaoudé

    2015-01-01

    Full Text Available Computational modeling constitutes a crucial step towards the functional understanding of complex cellular networks.In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks.In this context, signaling input components are generally meant to convey external stimuli, or environmental cues.In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors ({em e.g.} stable states.The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity.In this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models.We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions.As a case study, we consider the cellular network regulating the differentiation of T-helper cells, which orchestrate many physiological and pathological immune responses.To account for novel cellular subtypes, we present an extended version of a published model of T-helper cell differentiation. We then use symbolic model checking to analyze reachability properties between T-helper subtypes upon changes of environmental cues.This allows for the construction of a synthetic view of T-helper cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions.Finally, we explore novel strategies enabling specific T-helper cell polarizing or reprograming events.

  19. Triple co-culture cell model as an in vitro model for oral particulate vaccine systems

    DEFF Research Database (Denmark)

    Nielsen, Line Hagner; De Rossi, C.; Lehr, C-M.

    values of the co-cultures were found to be 860-1340 Ω∙cm2; the formulations were incubated with the co-cultures at this time point. From confocal microscopy images, it was observed that the THP-1 cells (macrophages) migrated into the overlying Caco-2 cell monolayer when the co-cultures were incubated......A triple co-culture cell model of Caco-2 cells, dendritic cells and macrophages (Figure 1) has previously been developed for studying intestinal permeability in a state of inflammation [1],[2]. The aim of this study was to investigate the applicability of this cell model for testing...... the model antigen ovalbumin was spray dried to obtain a particulate vaccine model system for testing in the cell model. The precursors were shown to form cubosomes when dispersed in aqueous medium, and was therefore used as the vaccine formulation for testing on the co-cultures. After 11 days, the TEER...

  20. Similarity on neural stem cells and brain tumor stem cells in transgenic brain tumor mouse models

    OpenAIRE

    Qiao, Guanqun; Li, Qingquan; Peng, Gang; Ma, Jun; Fan, Hongwei; Li, Yingbin

    2013-01-01

    Although it is believed that glioma is derived from brain tumor stem cells, the source and molecular signal pathways of these cells are still unclear. In this study, we used stable doxycycline-inducible transgenic mouse brain tumor models (c-myc+/SV40Tag+/Tet-on+) to explore the malignant trans-formation potential of neural stem cells by observing the differences of neural stem cells and brain tumor stem cells in the tumor models. Results showed that chromosome instability occurred in brain t...

  1. Modeling selective elimination of quiescent cancer cells from bone marrow.

    Science.gov (United States)

    Cavnar, Stephen P; Rickelmann, Andrew D; Meguiar, Kaille F; Xiao, Annie; Dosch, Joseph; Leung, Brendan M; Cai Lesher-Perez, Sasha; Chitta, Shashank; Luker, Kathryn E; Takayama, Shuichi; Luker, Gary D

    2015-08-01

    Patients with many types of malignancy commonly harbor quiescent disseminated tumor cells in bone marrow. These cells frequently resist chemotherapy and may persist for years before proliferating as recurrent metastases. To test for compounds that eliminate quiescent cancer cells, we established a new 384-well 3D spheroid model in which small numbers of cancer cells reversibly arrest in G1/G0 phase of the cell cycle when cultured with bone marrow stromal cells. Using dual-color bioluminescence imaging to selectively quantify viability of cancer and stromal cells in the same spheroid, we identified single compounds and combination treatments that preferentially eliminated quiescent breast cancer cells but not stromal cells. A treatment combination effective against malignant cells in spheroids also eliminated breast cancer cells from bone marrow in a mouse xenograft model. This research establishes a novel screening platform for therapies that selectively target quiescent tumor cells, facilitating identification of new drugs to prevent recurrent cancer. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  2. A cell-based model of Nematostella vectensis gastrulation including bottle cell formation, invagination and zippering.

    Science.gov (United States)

    Tamulonis, Carlos; Postma, Marten; Marlow, Heather Q; Magie, Craig R; de Jong, Johann; Kaandorp, Jaap

    2011-03-01

    The gastrulation of Nematostella vectensis, the starlet sea anemone, is morphologically simple yet involves many conserved cell behaviors such as apical constriction, invagination, bottle cell formation, cell migration and zippering found during gastrulation in a wide range of more morphologically complex animals. In this article we study Nematostella gastrulation using a combination of morphometrics and computational modeling. Through this analysis we frame gastrulation as a non-trivial problem, in which two distinct cell domains must change shape to match each other geometrically, while maintaining the integrity of the embryo. Using a detailed cell-based model capable of representing arbitrary cell-shapes such as bottle cells, as well as filopodia, localized adhesion and constriction, we are able to simulate gastrulation and associate emergent macroscopic changes in embryo shape to individual cell behaviors. We have developed a number of testable hypotheses based on the model. First, we hypothesize that the blastomeres need to be stiffer at their apical ends, relative to the rest of the cell perimeter, in order to be able to hold their wedge shape and the dimensions of the blastula, regardless of whether the blastula is sealed or leaky. We also postulate that bottle cells are a consequence of cell strain and low cell-cell adhesion, and can be produced within an epithelium even without apical constriction. Finally, we postulate that apical constriction, filopodia and de-epithelialization are necessary and sufficient for gastrulation based on parameter variation studies. Copyright © 2010 Elsevier Inc. All rights reserved.

  3. A transient model to simulate HTPEM fuel cell impedance spectra

    DEFF Research Database (Denmark)

    Vang, Jakob Rabjerg; Andreasen, Søren Juhl; Kær, Søren Knudsen

    2012-01-01

    diffusion of cathode gas species in gas diffusion layers and catalyst layer, transport of protons in the membrane and the catalyst layers, and double layer capacitive effects in the catalyst layers. The model has been fitted simultaneously to a polarization curve and to an impedance spectrum recorded......This paper presents a spatially resolved transient fuel cell model applied to the simulation of high temperature PEM fuel cell impedance spectra. The model is developed using a 2D finite volume method approach. The model is resolved along the channel and across the membrane. The model considers...

  4. Modelling and fabrication of high-efficiency silicon solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Rohatgi, A.; Smith, A.W.; Salami, J. [Georgia Inst. of Tech., Atlanta, GA (United States). School of Electrical Engineering

    1991-10-01

    This report covers the research conducted on modelling and development of high-efficiency silicon solar cells during the period May 1989 to August 1990. First, considerable effort was devoted toward developing a ray-tracing program for the photovoltaic community to quantify and optimize surface texturing for solar cells. Second, attempts were made to develop a hydrodynamic model for device simulation. Such a model is somewhat slower than drift-diffusion type models like PC-1D, but it can account for more physical phenomena in the device, such as hot carrier effects, temperature gradients, thermal diffusion, and lattice heat flow. In addition, Fermi-Dirac statistics have been incorporated into the model to deal with heavy doping effects more accurately. Third and final component of the research includes development of silicon cell fabrication capabilities and fabrication of high-efficiency silicon cells. 84 refs., 46 figs., 10 tabs.

  5. Cassini Radar at Titan : Evolving Studies of an Evolving World

    Science.gov (United States)

    Lorenz, Ralph D.

    2013-04-01

    The Cassini RADAR investigation continues to explore Titan : here I summarize some recent and ongoing developments. Geological interpretation of SAR imaging engages a wide community, in particular addressing Titan's dunes, lakes, seas and fluvial systems, impact craters and possible cryovolcanic features. Mapping of these features continues to suggest a dynamic world, with geologically-recent surface change due to tectonic, hydrological and aeolian processes. Mapping of fluvial channels and shoreline features suggests some tectonic controls and spatially-variable land/sea level changes. A despeckle filter applied to the images has proven popular for image interpretation, for example in resolving what may be star- and barchanoid dune morphologies which contrast with the dominant linear type. New observations in 2012 (T83, T84 and T86) place bounds on liquid accumulation in the northern polar regions - not expected to be substantial for another couple of years - and have highlighted a possibly cryomagma-inflated 'hot cross bun' feature and anomalous midlatitude ridges that may be paleodunes from a different climate epoch. The accumulating body of topographic data from altimetry and SARtopo has permitted the assembly of a global topographic map (albeit substantially interpolated) and an estimate of the spherical harmonic shape out to degree ~12. These datasets will be of substantial value in interpreting Titan's structure and geology, and as a boundary condition on global circulation models and fluvial studies. The growing number of overlap regions also permits stereo topography on smaller scales (e.g. of impact structures Ksa and Soi) which helps to understand the processes obliterating craters on Titan.

  6. Phase-segregated model for plant cell culture: The effect of cell volume fraction

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, W. [Univ. of Adelaide, Adelaide (Australia). Dept. of Chemical Engineering]|[Tokyo Univ. (Japan)hinese Academy of Sciences, Dalian (China). Dalian Inst. of Chemical Physics; Furusaki, S. [Tokyo Univ. (Japan)] Middelberg, A. [Univ. of Adelaide, Adelaide (Australia). Dept. of Chemical Engineering

    1998-06-01

    Plant cells are characterized by low water content, so the fraction of cell volume (volume fraction) in a vessel is large compared with other cell systems, even if the cell concentrations are the same. Therefore, concentration of plant cells should preferably be expressed by the liquid volume basis rather than by the total vessel volume basis. In this paper, a new model is proposed to analyze behavior of a plant cell culture by dividing the cell suspension into the biotic- and abiotic-phases. Using this model, we analyzed the cell-growth and the alkaloid production by Catharanthus roseus. Large errors in the simulated results were observed if the phase-segregation was not considered. 12 refs., 3 figs.

  7. A computationally efficient electrophysiological model of human ventricular cells

    NARCIS (Netherlands)

    Bernus, O.; Wilders, R.; Zemlin, C. W.; Verschelde, H.; Panfilov, A. V.

    2002-01-01

    Recent experimental and theoretical results have stressed the importance of modeling studies of reentrant arrhythmias in cardiac tissue and at the whole heart level. We introduce a six-variable model obtained by a reformulation of the Priebe-Beuckelmann model of a single human ventricular cell. The

  8. Systems modelling and the development of coherent cell biological knowledge

    NARCIS (Netherlands)

    Verhoeff, R.; Waarlo, A.J.|info:eu-repo/dai/nl/074372246; Boersma, K.T.|info:eu-repo/dai/nl/073043141

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing systems modelling as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of freeliving

  9. Agent-Based Computational Modeling of Cell Culture ...

    Science.gov (United States)

    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

  10. Pharmacodynamic Modeling of Cell Cycle Effects for Gemcitabine and Trabectedin Combinations in Pancreatic Cancer Cells

    Science.gov (United States)

    Miao, Xin; Koch, Gilbert; Ait-Oudhia, Sihem; Straubinger, Robert M.; Jusko, William J.

    2016-01-01

    Combinations of gemcitabine and trabectedin exert modest synergistic cytotoxic effects on two pancreatic cancer cell lines. Here, systems pharmacodynamic (PD) models that integrate cellular response data and extend a prototype model framework were developed to characterize dynamic changes in cell cycle phases of cancer cell subpopulations in response to gemcitabine and trabectedin as single agents and in combination. Extensive experimental data were obtained for two pancreatic cancer cell lines (MiaPaCa-2 and BxPC-3), including cell proliferation rates over 0–120 h of drug exposure, and the fraction of cells in different cell cycle phases or apoptosis. Cell cycle analysis demonstrated that gemcitabine induced cell cycle arrest in S phase, and trabectedin induced transient cell cycle arrest in S phase that progressed to G2/M phase. Over time, cells in the control group accumulated in G0/G1 phase. Systems cell cycle models were developed based on observed mechanisms and were used to characterize both cell proliferation and cell numbers in the sub G1, G0/G1, S, and G2/M phases in the control and drug-treated groups. The proposed mathematical models captured well both single and joint effects of gemcitabine and trabectedin. Interaction parameters were applied to quantify unexplainable drug-drug interaction effects on cell cycle arrest in S phase and in inducing apoptosis. The developed models were able to identify and quantify the different underlying interactions between gemcitabine and trabectedin, and captured well our large datasets in the dimensions of time, drug concentrations, and cellular subpopulations. PMID:27895579

  11. Systems Level Modeling of the Cell Cycle Using Budding Yeast

    Directory of Open Access Journals (Sweden)

    D.R. Kim

    2007-01-01

    Full Text Available Proteins involved in the regulation of the cell cycle are highly conserved across all eukaryotes, and so a relatively simple eukaryote such as yeast can provide insight into a variety of cell cycle perturbations including those that occur in human cancer. To date, the budding yeast Saccharomyces cerevisiae has provided the largest amount of experimental and modeling data on the progression of the cell cycle, making it a logical choice for in-depth studies of this process. Moreover, the advent of methods for collection of high-throughput genome, transcriptome, and proteome data has provided a means to collect and precisely quantify simultaneous cell cycle gene transcript and protein levels, permitting modeling of the cell cycle on the systems level. With the appropriate mathematical framework and suffi cient and accurate data on cell cycle components, it should be possible to create a model of the cell cycle that not only effectively describes its operation, but can also predict responses to perturbations such as variation in protein levels and responses to external stimuli including targeted inhibition by drugs. In this review, we summarize existing data on the yeast cell cycle, proteomics technologies for quantifying cell cycle proteins, and the mathematical frameworks that can integrate this data into representative and effective models. Systems level modeling of the cell cycle will require the integration of high-quality data with the appropriate mathematical framework, which can currently be attained through the combination of dynamic modeling based on proteomics data and using yeast as a model organism.

  12. Mechanical behavior in living cells consistent with the tensegrity model

    Science.gov (United States)

    Wang, N.; Naruse, K.; Stamenovic, D.; Fredberg, J. J.; Mijailovich, S. M.; Tolic-Norrelykke, I. M.; Polte, T.; Mannix, R.; Ingber, D. E.

    2001-01-01

    Alternative models of cell mechanics depict the living cell as a simple mechanical continuum, porous filament gel, tensed cortical membrane, or tensegrity network that maintains a stabilizing prestress through incorporation of discrete structural elements that bear compression. Real-time microscopic analysis of cells containing GFP-labeled microtubules and associated mitochondria revealed that living cells behave like discrete structures composed of an interconnected network of actin microfilaments and microtubules when mechanical stresses are applied to cell surface integrin receptors. Quantitation of cell tractional forces and cellular prestress by using traction force microscopy confirmed that microtubules bear compression and are responsible for a significant portion of the cytoskeletal prestress that determines cell shape stability under conditions in which myosin light chain phosphorylation and intracellular calcium remained unchanged. Quantitative measurements of both static and dynamic mechanical behaviors in cells also were consistent with specific a priori predictions of the tensegrity model. These findings suggest that tensegrity represents a unified model of cell mechanics that may help to explain how mechanical behaviors emerge through collective interactions among different cytoskeletal filaments and extracellular adhesions in living cells.

  13. Cell words: modelling the visual appearance of cells in histopathology images.

    Science.gov (United States)

    Sirinukunwattana, Korsuk; Khan, Adnan M; Rajpoot, Nasir M

    2015-06-01

    Detection and classification of cells in histological images is a challenging task because of the large intra-class variation in the visual appearance of various types of biological cells. In this paper, we propose a discriminative dictionary learning paradigm, termed as Cell Words, for modelling the visual appearance of cells which includes colour, shape, texture and context in a unified manner. The proposed framework is capable of distinguishing mitotic cells from non-mitotic cells (apoptotic, necrotic, epithelial) in breast histology images with high accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. UML as a cell and biochemistry modeling language.

    Science.gov (United States)

    Webb, Ken; White, Tony

    2005-06-01

    The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top-down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.

  15. Cell kinetic modelling and the chemotherapy of cancer

    CERN Document Server

    Knolle, Helmut

    1988-01-01

    During the last 30 years, many chemical compounds that are active against tumors have been discovered or developed. At the same time, new methods of testing drugs for cancer therapy have evolved. nefore 1964, drug testing on animal tumors was directed to observation of the incfease in life span of the host after a single dose. A new approach, in which the effects of multiple doses on the proliferation kinetics of the tumor in vivo as well as of cell lines in vitro are investigated, has been outlined by Skipper and his co-workers in a series of papers beginning in 1964 (Skipper, Schabel and Wilcox, 1964 and 1965). They also investigated the influence of the time schedule in the treatment of experimental tumors. Since the publication of those studies, cell population kinetics cannot be left out of any discussion of the rational basis of chemotherapy. When clinical oncologists began to apply cell kinetic concepts in practice about 15 years ago, the theoretical basis was still very poor, in spite of Skipper's pro...

  16. Modelling and control of cell reaction networks

    NARCIS (Netherlands)

    S. Jha; J.H. van Schuppen (Jan)

    2001-01-01

    textabstractThe project aims at a study of the nonlinear systems arising in the biochemical processes occuring inside a cell. The cellular regulation has been formulated in the more familiar framework used in control and system theory in terms of inputs as the variables which can be influenced

  17. Hydrodynamic behavior of tumor cells in a confined model microvessel

    Science.gov (United States)

    Khan, Zeina S.; Vanapalli, Siva A.

    2012-02-01

    An important step in cancer metastasis is the hydrodynamic transport of circulating tumor cells (CTCs) through microvasculature. In vivo imaging studies in mice models show episodes of confined motion and trapping of tumor cells at microvessel bifurcations, suggesting that hydrodynamic phenomena are important processes regulating CTC dissemination. Our goal is to use microfluidics to understand the interplay between tumor cell rheology, confinement and fluid forces that may help to identify physical factors determining CTC transport. We use leukemia cells as model CTCs and mimic the in vivo setting by investigating their motion in a confined microchannel with an integrated microfluidic manometer to measure time variations in the excess pressure drop during cell motion. Using image analysis, variations in excess pressure drop, cell shape and cell velocity are simultaneously quantified. We find that the throughput of the technique is high enough ( 100 cells/min) to assess tumor cell heterogeneity. Therefore, in addition to measuring the hydrodynamic response of tumor cells in confined channels, our results indicate that the microfluidic manometer device could be used for rapid mechanical phenotyping of tumor cells.

  18. Mechanical behavior of cells within a cell-based model of wheat leaf growth

    Directory of Open Access Journals (Sweden)

    Ulyana Zubairova

    2016-12-01

    Full Text Available Understanding the principles and mechanisms of cell growth coordination in plant tissue remains an outstanding challenge for modern developmental biology. Cell-based modeling is a widely used technique for studying the geometric and topological features of plant tissue morphology during growth. We developed a quasi-one-dimensional model of unidirectional growth of a tissue layer in a linear leaf blade that takes cell autonomous growth mode into account. The model allows for fitting of the visible cell length using the experimental cell length distribution along the longitudinal axis of a wheat leaf epidermis. Additionally, it describes changes in turgor and osmotic pressures for each cell in the growing tissue. Our numerical experiments show that the pressures in the cell change over the cell cycle, and in symplastically growing tissue, they vary from cell to cell and strongly depend on the leaf growing zone to which the cells belong. Therefore, we believe that the mechanical signals generated by pressures are important to consider in simulations of tissue growth as possible targets for molecular genetic regulators of individual cell growth.

  19. Engineering Therapies that Evolve to Autonomously Control Epidemics

    Science.gov (United States)

    2017-06-01

    FINAL TECHNICAL REPORT Grant No. D15AP00024 “ Engineering Therapies that Evolve to Autonomously Control Epidemics” PI: Leor Weinberger...viruses could be engineered into therapeutics, known as Therapeutic Interfering Particles (’TIPs’), using the virus HIV as a model system. By engineering ... engineered TIPs could have indefinite, population-scale impact. To achieve this aim, we developed novel multi-scale models that connected the measured

  20. PEM fuel cell geometry optimisation using mathematical modeling

    Directory of Open Access Journals (Sweden)

    E Carcadea

    2008-09-01

    Full Text Available There have been extensive efforts devoted to proton exchangemembrane (PEM fuel cell modeling and simulations to study fuel cellperformance. Although fuel cells have been successfully demonstrated inboth automotive and stationary power applications, there are numeroustechnical and logistic issues that still have to be solved, such asperformance, cost, and system issues. A model based on steady,isothermal, electrochemical, three-dimensional computational fluiddynamics using the FLUENT CFD software package has been developedto predict the fluid flow pattern within a PEMFC. Three types of flow field areinvestigated with serpentine, parallel or spiral channels in order todetermine the best configuration for the fuel cell performance. In thiscontext, the paper presents the results that we have obtained and, as aconclusion of the simulations, we have achieved the best configurationregarding the performance for the fuel cell with serpentine channels. Weconsider the mathematical and computational modeling as an importantalternative for fuel cell optimization and for the exploitation/experimentationin cost reduction.

  1. Modeling of Flow in Nuclear Reactor Fuel Cell Outlet

    Directory of Open Access Journals (Sweden)

    František URBAN

    2010-12-01

    Full Text Available Safe and effective load of nuclear reactor fuel cells demands qualitative and quantitative analysis of relations between coolant temperature in fuel cell outlet temperature measured by thermocouple and middle temperature of coolant in thermocouple plane position. In laboratory at Insitute of thermal power engineering of the Slovak University of Technology in Bratislava was installed an experimental physical fuel cell model of VVER 440 nuclear power plant with V 213 nuclear reactors. Objective of measurements on physical model was temperature and velocity profiles analysis in the fuel cell outlet. In this paper the measured temperature and velocity profiles are compared with the results of CFD simulation of fuel cell physical model coolant flow.

  2. Support Vector Regression Model for Direct Methanol Fuel Cell

    Science.gov (United States)

    Tang, J. L.; Cai, C. Z.; Xiao, T. T.; Huang, S. J.

    2012-07-01

    The purpose of this paper is to establish a direct methanol fuel cell (DMFC) prediction model by using the support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter selection. Two variables, cell temperature and cell current density were employed as input variables, cell voltage value of DMFC acted as output variable. Using leave-one-out cross-validation (LOOCV) test on 21 samples, the maximum absolute percentage error (APE) yields 5.66%, the mean absolute percentage error (MAPE) is only 0.93% and the correlation coefficient (R2) as high as 0.995. Compared with the result of artificial neural network (ANN) approach, it is shown that the modeling ability of SVR surpasses that of ANN. These suggest that SVR prediction model can be a good predictor to estimate the cell voltage for DMFC system.

  3. Cytoview: Development of a cell modelling framework

    Indian Academy of Sciences (India)

    2007-07-06

    Jul 6, 2007 ... The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves ...

  4. A Biophysical Model for Cytotoxic Cell Swelling

    NARCIS (Netherlands)

    Dijkstra, Koen; Hofmeijer, Jeannette; van Gils, Stephanus A.; van Putten, Michel Johannes Antonius Maria

    2016-01-01

    We present a dynamic biophysical model to explain neuronal swelling underlying cytotoxic edema in conditions of low energy supply, as observed in cerebral ischemia. Our model contains Hodgkin—Huxley-type ion currents, a recently discovered voltage-gated chloride flux through the ion exchanger

  5. An In Vitro Nematic Model for Proliferating Cell Cultures

    CERN Document Server

    Pai, Sunil; Green, Morgaine; Cordeiro, Christine; Cabral, Elise; Chen, Bertha; Baer, Thomas

    2016-01-01

    Confluent populations of elongated cells give rise to ordered patterns seen in nematic phase liquid crystals. We correlate cell elongation and intercellular distance with intercellular alignment using an amorphous spin glass model. We compare in vitro time-lapse imaging with Monte Carlo simulation results by framing a novel hard ellipses model in terms of Boltzmann statistics. Furthermore, we find a statistically distinct alignment energy at quasi-steady state among fibroblasts, smooth muscle cells, and pluripotent cell populations when cultured in vitro. These findings have important implications in both non-invasive clinical screening of the stem cell differentiation process and in relating shape parameters to coupling in active crystal systems such as nematic cell monolayers.

  6. Accelerated Caco-2 cell permeability model for drug discovery.

    Science.gov (United States)

    Sevin, E; Dehouck, L; Fabulas-da Costa, A; Cecchelli, R; Dehouck, M P; Lundquist, S; Culot, M

    2013-01-01

    By culturing Caco-2 cells according to a new and optimized protocol, it has been possible to accelerate the cell culture process in such a way that the cells can be used for experiments after only 6 days. The accelerated Caco-2 model has been compared to the traditional model (requiring 21-25 days of culture) in terms of tightness of the junctions, ability to rank chemical compounds for apparent permeability, active efflux and to discriminate P-gp substrates. In the new protocol, Caco-2 cells were cultured with the classical Caco-2 medium supplemented with puromycin. The initial cell seeding density was increased two times compared to the traditional procedure and the presence of a low concentration of puromycin in the culture medium reduced the Caco-2 permeability of mannitol. Bi-directional studies were performed with known P-gp substrates (rhodamine 123, digoxin and saquinavir) and with a total of 20 marketed drugs covering a wide range of physicochemical characteristics and therapeutic indications. Strong correlations were obtained between the apparent permeability in absorptive (Papp A→B) or secretory (Papp B→A) of the drugs in the accelerated model and in the traditional models and comparable efflux ratios were observed in the two studied models. The new protocol reduces costs for screening and leads to higher throughput compared to traditional Caco-2 cell models. This accelerated model provides short time-feedback to the drug design during the early stage of drug discovery. © 2013.

  7. Epidemic spreading on evolving signed networks

    Science.gov (United States)

    Saeedian, M.; Azimi-Tafreshi, N.; Jafari, G. R.; Kertesz, J.

    2017-02-01

    Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences people's willingness to contact others: A "friendly" contact may be turned to "unfriendly" to avoid infection. We study the susceptible-infected disease-spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heider's theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte Carlo simulations on complete networks to test the energy landscape, where we find local minima corresponding to the so-called jammed states. We study the effect of the ratio of initial friendly to unfriendly connections on the propagation of disease. The steady state can be balanced or a jammed state such that a coexistence occurs between susceptible and infected nodes in the system.

  8. COMPUTATION MODELING OF TCDD DISRUPTION OF B CELL TERMINAL DIFFERENTIATION

    Science.gov (United States)

    In this study, we established a computational model describing the molecular circuit underlying B cell terminal differentiation and how TCDD may affect this process by impinging upon various molecular targets.

  9. Modeling familial Alzheimer's disease with induced pluripotent stem cells

    National Research Council Canada - National Science Library

    Yagi, Takuya; Ito, Daisuke; Okada, Yohei; Akamatsu, Wado; Nihei, Yoshihiro; Yoshizaki, Takahito; Yamanaka, Shinya; Okano, Hideyuki; Suzuki, Norihiro

    2011-01-01

    ...). Induced pluripotent stem cell (iPSC) technology can be used to model human disorders and provide novel opportunities to study cellular mechanisms and establish therapeutic strategies against various diseases, including neurodegenerative diseases...

  10. Design, Modeling, and Development of Microbial Cell Factories

    KAUST Repository

    Kodzius, Rimantas

    2014-03-26

    Using Metagenomic analysis, computational modeling, single cell and genome editing technologies, we will express desired microbial genes and their networks in suitable hosts for mass production of energy, food, and fine chemicals.

  11. WSC-07: Evolving the Web Services Challenge

    NARCIS (Netherlands)

    Blake, M. Brian; Cheung, William K.W.; Jaeger, Michael C.; Wombacher, Andreas

    Service-oriented architecture (SOA) is an evolving architectural paradigm where businesses can expose their capabilities as modular, network-accessible software services. By decomposing capabilities into modular services, organizations can share their offerings at multiple levels of granularity

  12. Satcom access in the evolved packet core

    NARCIS (Netherlands)

    Cano, M.D.; Norp, A.H.J.; Popova, M.P.

    2012-01-01

    Satellite communications (Satcom) networks are increasingly integrating with terrestrial communications networks, namely Next Generation Networks (NGN). In the area of NGN the Evolved Packet Core (EPC) is a new network architecture that can support multiple access technologies. When Satcom is

  13. Acquisition: Acquisition of the Evolved SEASPARROW Missile

    National Research Council Canada - National Science Library

    2002-01-01

    .... The Evolved SEASPARROW Missile, a Navy Acquisition Category II program, is an improved version of the RIM-7P SEASPARROW missile that will intercept high-speed maneuvering, anti-ship cruise missiles...

  14. Modeling neurodegenerative diseases with patient-derived induced pluripotent cells

    DEFF Research Database (Denmark)

    Poon, Anna; Zhang, Yu; Chandrasekaran, Abinaya

    2017-01-01

    patient-specific induced pluripotent stem cells (iPSCs) and isogenic controls generated using CRISPR-Cas9 mediated genome editing. The iPSCs are self-renewable and capable of being differentiated into the cell types affected by the diseases. These in vitro models based on patient-derived iPSCs provide...

  15. Computation Molecular Kinetics Model of HZE Induced Cell Cycle Arrest

    Science.gov (United States)

    Cucinotta, Francis A.; Ren, Lei

    2004-01-01

    Cell culture models play an important role in understanding the biological effectiveness of space radiation. High energy and charge (HZE) ions produce prolonged cell cycle arrests at the G1/S and G2/M transition points in the cell cycle. A detailed description of these phenomena is needed to integrate knowledge of the expression of DNA damage in surviving cells, including the determination of relative effectiveness factors between different types of radiation that produce differential types of DNA damage and arrest durations. We have developed a hierarchical kinetics model that tracks the distribution of cells in various cell phase compartments (early G1, late G1, S, G2, and M), however with transition rates that are controlled by rate-limiting steps in the kinetics of cyclin-cdk's interactions with their families of transcription factors and inhibitor molecules. The coupling of damaged DNA molecules to the downstream cyclin-cdk inhibitors is achieved through a description of the DNA-PK and ATM signaling pathways. For HZE irradiations we describe preliminary results, which introduce simulation of the stochastic nature of the number of direct particle traversals per cell in the modulation of cyclin-cdk and cell cycle population kinetics. Comparison of the model to data for fibroblast cells irradiated photons or HZE ions are described.

  16. System-level modeling and simulation of the cell culture microfluidic biochip ProCell

    DEFF Research Database (Denmark)

    Minhass, Wajid Hassan; Pop, Paul; Madsen, Jan

    2010-01-01

    Microfluidic biochips offer a promising alternative to a conventional biochemical laboratory. There are two technologies for the microfluidic biochips: droplet-based and flow-based. In this paper we are interested in flow-based microfluidic biochips, where the liquid flows continuously through pre......-defined micro-channels using valves and pumps. We present an approach to the system-level modeling and simulation of a cell culture microfluidic biochip called ProCell, Programmable Cell Culture Chip. ProCell contains a cell culture chamber, which is envisioned to run 256 simultaneous experiments (viewed...... and a comprehensive fault model that captures permanent faults occurring during chip operation. Using the proposed modeling and simulation framework, we perform an architectural level evaluation of two cell culture chamber implementations. A qualitative success metric is also proposed to evaluate chip performance...

  17. Cyberspace Operations: Influence Upon Evolving War Theory

    Science.gov (United States)

    2011-03-18

    St ra te gy R es ea rc h Pr oj ec t CYBERSPACE OPERATIONS: INFLUENCE UPON EVOLVING WAR THEORY BY COLONEL KRISTIN BAKER United States...DATES COVERED (From - To) 4. TITLE AND SUBTITLE Cyberspace Operations: Influence Upon Evolving War Theory 5a. CONTRACT NUMBER... Leadership 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S

  18. Evolving effective incremental SAT solvers with GP

    OpenAIRE

    Bader, Mohamed; Poli, R.

    2008-01-01

    Hyper-Heuristics could simply be defined as heuristics to choose other heuristics, and it is a way of combining existing heuristics to generate new ones. In a Hyper-Heuristic framework, the framework is used for evolving effective incremental (Inc*) solvers for SAT. We test the evolved heuristics (IncHH) against other known local search heuristics on a variety of benchmark SAT problems.

  19. A 3D Hydrodynamic Model for Cytokinesis of Eukaryotic Cells

    Science.gov (United States)

    2014-08-01

    proposed a mathematical model for cell cleavage for the sea urchin by considering chemotactic motion of the centro- somes. In [23], the author...approach to study the cellular morphological change during cytokinesis. In this model, the force along the contracting ring or cytokinetic ring induced by...during cytokinesis, surface tension of the cell membrane also contributes to this process by retaining the morphological integrity of the offspring

  20. How can cells sense the elasticity of a substrate? An analysis using a cell tensegrity model.

    Science.gov (United States)

    De Santis, G; Lennon, A B; Boschetti, F; Verhegghe, B; Verdonck, P; Prendergast, P J

    2011-10-11

    A eukaryotic cell attaches and spreads on substrates, whether it is the extracellular matrix naturally produced by the cell itself, or artificial materials, such as tissue-engineered scaffolds. Attachment and spreading require the cell to apply forces in the nN range to the substrate via adhesion sites, and these forces are balanced by the elastic response of the substrate. This mechanical interaction is one determinant of cell morphology and, ultimately, cell phenotype. In this paper we use a finite element model of a cell, with a tensegrity structure to model the cytoskeleton of actin filaments and microtubules, to explore the way cells sense the stiffness of the substrate and thereby adapt to it. To support the computational results, an analytical 1D model is developed for comparison. We find that (i) the tensegrity hypothesis of the cytoskeleton is sufficient to explain the matrix-elasticity sensing, (ii) cell sensitivity is not constant but has a bell-shaped distribution over the physiological matrix-elasticity range, and (iii) the position of the sensitivity peak over the matrix-elasticity range depends on the cytoskeletal structure and in particular on the F-actin organisation. Our model suggests that F-actin reorganisation observed in mesenchymal stem cells (MSCs) in response to change of matrix elasticity is a structural-remodelling process that shifts the sensitivity peak towards the new value of matrix elasticity. This finding discloses a potential regulatory role of scaffold stiffness for cell differentiation.

  1. A Three-Dimensional Cell Culture Model To Study Enterovirus Infection of Polarized Intestinal Epithelial Cells.

    Science.gov (United States)

    Drummond, Coyne G; Nickerson, Cheryl A; Coyne, Carolyn B

    2016-01-01

    Despite serving as the primary entry portal for coxsackievirus B (CVB), little is known about CVB infection of the intestinal epithelium, owing at least in part to the lack of suitable in vivo models and the inability of cultured cells to recapitulate the complexity and structure associated with the gastrointestinal (GI) tract. Here, we report on the development of a three-dimensional (3-D) organotypic cell culture model of Caco-2 cells to model CVB infection of the gastrointestinal epithelium. We show that Caco-2 cells grown in 3-D using the rotating wall vessel (RWV) bioreactor recapitulate many of the properties of the intestinal epithelium, including the formation of well-developed tight junctions, apical-basolateral polarity, brush borders, and multicellular complexity. In addition, transcriptome analyses using transcriptome sequencing (RNA-Seq) revealed the induction of a number of genes associated with intestinal epithelial differentiation and/or intestinal processes in vivo when Caco-2 cells were cultured in 3-D. Applying this model to CVB infection, we found that although the levels of intracellular virus production were similar in two-dimensional (2-D) and 3-D Caco-2 cell cultures, the release of infectious CVB was enhanced in 3-D cultures at early stages of infection. Unlike CVB, the replication of poliovirus (PV) was significantly reduced in 3-D Caco-2 cell cultures. Collectively, our studies show that Caco-2 cells grown in 3-D using the RWV bioreactor provide a cell culture model that structurally and transcriptionally represents key aspects of cells in the human GI tract and can thus be used to expand our understanding of enterovirus-host interactions in intestinal epithelial cells. IMPORTANCE Coxsackievirus B (CVB), a member of the enterovirus family of RNA viruses, is associated with meningitis, pericarditis, diabetes, dilated cardiomyopathy, and myocarditis, among other pathologies. CVB is transmitted via the fecal-oral route and encounters the

  2. Genome Editing of Erythroid Cell Culture Model Systems.

    Science.gov (United States)

    Yik, Jinfen J; Crossley, Merlin; Quinlan, Kate G R

    2018-01-01

    Genome editing to introduce specific mutations or to knock out genes in model cell systems has become an efficient platform for research in the fields of molecular biology, genetics, and cell biology. With recent rapid improvements in genome editing techniques, bench-top manipulation of the genome in cell culture has become progressively easier. The application of this knowledge to erythroid cell culture systems now allows the rapid analysis of the downstream effects of virtually any engineered gene disruption or modification in cell systems. Here, we describe a CRISPR/Cas9-based approach to making genomic modifications in erythroid lineage cells which we have successfully used in both murine (MEL) and human (K562) erythroleukaemia immortalized cell lines.

  3. Simulation of Cell Adhesion using a Particle Transport Model

    Science.gov (United States)

    Chesnutt, Jennifer

    2005-11-01

    An efficient computational method for simulation of cell adhesion through protein binding forces is discussed. In this method, the cells are represented by deformable elastic particles, and the protein binding is represented by a rate equation. The method is first developed for collision and adhesion of two similar cells impacting on each other from opposite directions. The computational method is then applied in a particle-transport model for a cloud of interacting and colliding cells, each of which are represented by particles of finite size. One application might include red blood cells adhering together to form rouleaux, which are chains of red blood cells that are found in different parts of the circulatory system. Other potential applications include adhesion of platelets to a blood vessel wall or mechanical heart valve, which is a precursor of thrombosis formation, or adhesion of cancer cells to organ walls in the lymphatic, circulatory, digestive or pulmonary systems.

  4. Avoiding healthy cells extinction in a cancer model.

    Science.gov (United States)

    López, Álvaro G; Sabuco, Juan; Seoane, Jesús M; Duarte, Jorge; Januário, Cristina; Sanjuán, Miguel A F

    2014-05-21

    We consider a dynamical model of cancer growth including three interacting cell populations of tumor cells, healthy host cells and immune effector cells. For certain parameter choice, the dynamical system displays chaotic motion and by decreasing the response of the immune system to the tumor cells, a boundary crisis leading to transient chaotic dynamics is observed. This means that the system behaves chaotically for a finite amount of time until the unavoidable extinction of the healthy and immune cell populations occurs. Our main goal here is to apply a control method to avoid extinction. For that purpose, we apply the partial control method, which aims to control transient chaotic dynamics in the presence of external disturbances. As a result, we have succeeded to avoid the uncontrolled growth of tumor cells and the extinction of healthy tissue. The possibility of using this method compared to the frequently used therapies is discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Models to Study NK Cell Biology and Possible Clinical Application.

    Science.gov (United States)

    Zamora, Anthony E; Grossenbacher, Steven K; Aguilar, Ethan G; Murphy, William J

    2015-08-03

    Natural killer (NK) cells are large granular lymphocytes of the innate immune system, responsible for direct targeting and killing of both virally infected and transformed cells. NK cells rapidly recognize and respond to abnormal cells in the absence of prior sensitization due to their wide array of germline-encoded inhibitory and activating receptors, which differs from the receptor diversity found in B and T lymphocytes that is due to the use of recombination-activation gene (RAG) enzymes. Although NK cells have traditionally been described as natural killers that provide a first line of defense prior to the induction of adaptive immunity, a more complex view of NK cells is beginning to emerge, indicating they may also function in various immunoregulatory roles and have the capacity to shape adaptive immune responses. With the growing appreciation for the diverse functions of NK cells, and recent technological advancements that allow for a more in-depth understanding of NK cell biology, we can now begin to explore new ways to manipulate NK cells to increase their clinical utility. In this overview unit, we introduce the reader to various aspects of NK cell biology by reviewing topics ranging from NK cell diversity and function, mouse models, and the roles of NK cells in health and disease, to potential clinical applications. © 2015 by John Wiley & Sons, Inc. Copyright © 2015 John Wiley & Sons, Inc.

  6. Tensegrity finite element models of mechanical tests of individual cells.

    Science.gov (United States)

    Bursa, Jiri; Lebis, Radek; Holata, Jakub

    2012-01-01

    A three-dimensional finite element model of a vascular smooth muscle cell is based on models published recently; it comprehends elements representing cell membrane, cytoplasm and nucleus, and a complex tensegrity structure representing the cytoskeleton. In contrast to previous models of eucaryotic cells, this tensegrity structure consists of several parts. Its external and internal parts number 30 struts, 60 cables each, and their nodes are interconnected by 30 radial members; these parts represent cortical, nuclear and deep cytoskeletons, respectively. This arrangement enables us to simulate load transmission from the extracellular space to the nucleus or centrosome via membrane receptors (focal adhesions); the ability of the model was tested by simulation of some mechanical tests with isolated vascular smooth muscle cells. Although material properties of components defined on the basis of the mechanical tests are ambiguous, modelling of different types of tests has shown the ability of the model to simulate substantial global features of cell behaviour, e.g. "action at a distance effect" or the global load-deformation response of the cell under various types of loading. Based on computational simulations, the authors offer a hypothesis explaining the scatter of experimental results of indentation tests. © 2012 – IOS Press and the authors. All rights reserved

  7. Details Matter: Noise and Model Structure Set the Relationship between Cell Size and Cell Cycle Timing

    Directory of Open Access Journals (Sweden)

    Felix Barber

    2017-11-01

    Full Text Available Organisms across all domains of life regulate the size of their cells. However, the means by which this is done is poorly understood. We study two abstracted “molecular” models for size regulation: inhibitor dilution and initiator accumulation. We apply the models to two settings: bacteria like Escherichia coli, that grow fully before they set a division plane and divide into two equally sized cells, and cells that form a bud early in the cell division cycle, confine new growth to that bud, and divide at the connection between that bud and the mother cell, like the budding yeast Saccharomyces cerevisiae. In budding cells, delaying cell division until buds reach the same size as their mother leads to very weak size control, with average cell size and standard deviation of cell size increasing over time and saturating up to 100-fold higher than those values for cells that divide when the bud is still substantially smaller than its mother. In budding yeast, both inhibitor dilution or initiator accumulation models are consistent with the observation that the daughters of diploid cells add a constant volume before they divide. This “adder” behavior has also been observed in bacteria. We find that in bacteria an inhibitor dilution model produces adder correlations that are not robust to noise in the timing of DNA replication initiation or in the timing from initiation of DNA replication to cell division (the C+D period. In contrast, in bacteria an initiator accumulation model yields robust adder correlations in the regime where noise in the timing of DNA replication initiation is much greater than noise in the C + D period, as reported previously (Ho and Amir, 2015. In bacteria, division into two equally sized cells does not broaden the size distribution.

  8. Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses

    Science.gov (United States)

    Kriete, Andres; Bosl, William J.; Booker, Glenn

    2010-01-01

    Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-κB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype. PMID:20585546

  9. Mathematical and Computational Modeling of Polymer Exchange Membrane Fuel Cells

    Science.gov (United States)

    Ulusoy, Sehribani

    In this thesis a comprehensive review of fuel cell modeling has been given and based on the review, a general mathematical fuel cell model has been developed in order to understand the physical phenomena governing the fuel cell behavior and in order to contribute to the efforts investigating the optimum performance at different operating conditions as well as with different physical parameters. The steady state, isothermal model presented here accounts for the combined effects of mass and species transfer, momentum conservation, electrical current distribution through the gas channels, the electrodes and the membrane, and the electrochemical kinetics of the reactions in the anode and cathode catalyst layers. One of the important features of the model is that it proposes a simpler modified pseudo-homogeneous/agglomerate catalyst layer model which takes the advantage of the simplicity of pseudo-homogenous modeling while taking into account the effects of the agglomerates in the catalyst layer by using experimental geometric parameters published. The computation of the general mathematical model can be accomplished in 3D, 2D and 1D with the proper assumptions. Mainly, there are two computational domains considered in this thesis. The first modeling domain is a 2D Membrane Electrode Assembly (MEA) model including the modified agglomerate/pseudo-homogeneous catalyst layer modeling with consistent treatment of water transport in the MEA while the second domain presents a 3D model with different flow filed designs: straight, stepped and tapered. COMSOL Multiphysics along with Batteries and Fuel Cell Module have been used for 2D & 3D model computations while ANSYS FLUENT PEMFC Module has been used for only 3D two-phase computation. Both models have been validated with experimental data. With 2D MEA model, the effects of temperature and water content of the membrane as well as the equivalent weight of the membrane on the performance have been addressed. 3D COMSOL simulation

  10. A quantitative and dynamic model for plant stem cell regulation.

    Directory of Open Access Journals (Sweden)

    Florian Geier

    Full Text Available Plants maintain pools of totipotent stem cells throughout their entire life. These stem cells are embedded within specialized tissues called meristems, which form the growing points of the organism. The shoot apical meristem of the reference plant Arabidopsis thaliana is subdivided into several distinct domains, which execute diverse biological functions, such as tissue organization, cell-proliferation and differentiation. The number of cells required for growth and organ formation changes over the course of a plants life, while the structure of the meristem remains remarkably constant. Thus, regulatory systems must be in place, which allow for an adaptation of cell proliferation within the shoot apical meristem, while maintaining the organization at the tissue level. To advance our understanding of this dynamic tissue behavior, we measured domain sizes as well as cell division rates of the shoot apical meristem under various environmental conditions, which cause adaptations in meristem size. Based on our results we developed a mathematical model to explain the observed changes by a cell pool size dependent regulation of cell proliferation and differentiation, which is able to correctly predict CLV3 and WUS over-expression phenotypes. While the model shows stem cell homeostasis under constant growth conditions, it predicts a variation in stem cell number under changing conditions. Consistent with our experimental data this behavior is correlated with variations in cell proliferation. Therefore, we investigate different signaling mechanisms, which could stabilize stem cell number despite variations in cell proliferation. Our results shed light onto the dynamic constraints of stem cell pool maintenance in the shoot apical meristem of Arabidopsis in different environmental conditions and developmental states.

  11. Simple mechanisms of early life - simulation model on the origin of semi-cells.

    Science.gov (United States)

    Klein, Adrian; Bock, Martin; Alt, Wolfgang

    2017-01-01

    The development of first cellular structures played an important role in the early evolution of life. Early evolution of life probably took place on a molecular level in a reactive environment. The iron-sulfur theory postulates the formation of cell-like structures on catalytic surfaces. Experiments show that H2S together with FeS and other metallic centers drive auto-catalytic surface reactions, in which organic molecules such as pyruvic and amino acids occur. It is questionable which mechanisms are needed to form cell-like structures under these conditions. To address this question, we implemented a model system featuring the fundamentals of molecular dynamics: heat, attraction, repulsion and formation of covalent bonds. Our basic model exhibits a series of essential processes: self-organization of lipid micelles and bilayers, formation of fluid filled cavities, flux of molecules along membranes, transport of energized groups towards sinks and whole colonies of cell-like structures on a larger scale. The results demonstrate that only a few features are sufficient for discovering hitherto non described phenomena of self-assembly and dynamics of cell-like structures as candidates for early evolving proto-cells. Significance statement The quest for a possible origin of life continues to be one of the most fascinating problems in biology. In one theoretical scenario, early life originated from a solution of reactive chemicals in the ancient deep sea, similar to conditions as to be found in thermal vents. Experiments have shown that a variety of organic molecules, the building blocks of life, form under these conditions. Based on such experiments, the iron-sulfur theory postulates the growth of cell-like structures at certain catalytic surfaces. For an explanation and proof of such a process we have developed a computer model simulating molecular assembly of lipid bilayers and formation of semi-cell cavities. The results demonstrate the possibility of cell-like self

  12. On a Pioneering Polymer Electrolyte Fuel Cell Model

    Energy Technology Data Exchange (ETDEWEB)

    Weber, Adam Z.; Meyers, Jeremy P.

    2010-07-07

    "Polymer Electrolyte Fuel Cell Model" is a seminal work that continues to form the basis for modern modeling efforts, especially models concerning the membrane and its behavior at the continuum level. The paper is complete with experimental data, modeling equations, model validation, and optimization scenarios. While the treatment of the underlying phenomena is limited to isothermal, single-phase conditions, and one-dimensional flow, it represents the key interactions within the membrane at the center of the PEFC. It focuses on analyzing the water balance within the cell and clearly demonstrates the complex interactions of water diffusion and electro-osmotic flux. Cell-level and system-level water balance are key to the development of efficient PEFCs going forward, particularly as researchers address the need to simplify humidification and recycle configurations while increasing the operating temperature of the stack to minimize radiator requirements.

  13. Social networks: Evolving graphs with memory dependent edges

    Science.gov (United States)

    Grindrod, Peter; Parsons, Mark

    2011-10-01

    The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

  14. Evolving R Coronae Borealis Stars with MESA

    Science.gov (United States)

    Clayton, Geoffrey C.; Lauer, Amber; Chatzopoulos, Emmanouil; Frank, Juhan

    2018-01-01

    R Coronae Borealis (RCB) stars form a small class of cool, carbon-rich supergiants that have almost no hydrogen. They undergo extreme, irregular declines in brightness of up to 8 magnitudes due to the formation of thick clouds of carbon dust. Two scenarios have been proposed for the origin of an RCB star: the merger of a CO/He white dwarf (WD) binary and a final helium-shell flash. We are using a combination of 3D hydrodynamics codes and the 1D MESA (Modules for Experiments in Stellar Astrophysics) stellar evolution code including nucleosynthesis to construct post-merger spherical models based on realistic merger progenitor models and on our hydrodynamical simulations, and then following the evolution into the region of the HR diagram where RCB stars are located. We are investigating nucleosynthesis in the dynamically accreting material of CO/He WD mergers which may provide a suitable environment for significant production of 18O and the very low 16O/18O values observed.Our MESA modeling consists of two steps: first mimicking the WD merger event using two different techniques, (a) by choosing a very high mass accretion rate with appropriate abundances and (b) by applying "stellar engineering" to an initial CO WD model to account for the newly merged material by applying an entropy adjusting procedure. Second, we follow the post-merger evolution using a large nuclear reaction network including the effects of convective and rotational instabilities to the mixing of material in order to match the observed RCB abundances. MESA follows the evolution of the merger product as it expands and cools to become an RCB star. We then examine the surface abundances and compare them to the observed RCB abundances. We also investigate how long fusion continues in the He shell near the core and how this processed material is mixed up to the surface of the star. We then model the later evolution of RCB stars to determine their likely lifetimes and endpoints when they have returned to

  15. Cell reprogramming modelled as transitions in a hierarchy of cell cycles

    Science.gov (United States)

    Hannam, Ryan; Annibale, Alessia; Kühn, Reimer

    2017-10-01

    We construct a model of cell reprogramming (the conversion of fully differentiated cells to a state of pluripotency, known as induced pluripotent stem cells, or iPSCs) which builds on key elements of cell biology viz. cell cycles and cell lineages. Although reprogramming has been demonstrated experimentally, much of the underlying processes governing cell fate decisions remain unknown. This work aims to bridge this gap by modelling cell types as a set of hierarchically related dynamical attractors representing cell cycles. Stages of the cell cycle are characterised by the configuration of gene expression levels, and reprogramming corresponds to triggering transitions between such configurations. Two mechanisms were found for reprogramming in a two level hierarchy: cycle specific perturbations and a noise induced switching. The former corresponds to a directed perturbation that induces a transition into a cycle-state of a different cell type in the potency hierarchy (mainly a stem cell) whilst the latter is a priori undirected and could be induced, e.g. by a (stochastic) change in the cellular environment. These reprogramming protocols were found to be effective in large regimes of the parameter space and make specific predictions concerning reprogramming dynamics which are broadly in line with experimental findings.

  16. Human normal bronchial epithelial cells: a novel in vitro cell model for toxicity evaluation.

    Directory of Open Access Journals (Sweden)

    Wenqiang Feng

    Full Text Available Human normal cell-based systems are needed for drug discovery and toxicity evaluation. hTERT or viral genes transduced human cells are currently widely used for these studies, while these cells exhibited abnormal differentiation potential or response to biological and chemical signals. In this study, we established human normal bronchial epithelial cells (HNBEC using a defined primary epithelial cell culture medium without transduction of exogenous genes. This system may involve decreased IL-1 signaling and enhanced Wnt signaling in cells. Our data demonstrated that HNBEC exhibited a normal diploid karyotype. They formed well-defined spheres in matrigel 3D culture while cancer cells (HeLa formed disorganized aggregates. HNBEC cells possessed a normal cellular response to DNA damage and did not induce tumor formation in vivo by xenograft assays. Importantly, we assessed the potential of these cells in toxicity evaluation of the common occupational toxicants that may affect human respiratory system. Our results demonstrated that HNBEC cells are more sensitive to exposure of 10~20 nm-sized SiO2, Cr(VI and B(aP compared to 16HBE cells (a SV40-immortalized human bronchial epithelial cells. This study provides a novel in vitro human cells-based model for toxicity evaluation, may also be facilitating studies in basic cell biology, cancer biology and drug discovery.

  17. Human normal bronchial epithelial cells: a novel in vitro cell model for toxicity evaluation.

    Science.gov (United States)

    Feng, Wenqiang; Guo, Juanjuan; Huang, Haiyan; Xia, Bo; Liu, Hongya; Li, Jie; Lin, Shaolin; Li, Tiyuan; Liu, Jianjun; Li, Hui

    2015-01-01

    Human normal cell-based systems are needed for drug discovery and toxicity evaluation. hTERT or viral genes transduced human cells are currently widely used for these studies, while these cells exhibited abnormal differentiation potential or response to biological and chemical signals. In this study, we established human normal bronchial epithelial cells (HNBEC) using a defined primary epithelial cell culture medium without transduction of exogenous genes. This system may involve decreased IL-1 signaling and enhanced Wnt signaling in cells. Our data demonstrated that HNBEC exhibited a normal diploid karyotype. They formed well-defined spheres in matrigel 3D culture while cancer cells (HeLa) formed disorganized aggregates. HNBEC cells possessed a normal cellular response to DNA damage and did not induce tumor formation in vivo by xenograft assays. Importantly, we assessed the potential of these cells in toxicity evaluation of the common occupational toxicants that may affect human respiratory system. Our results demonstrated that HNBEC cells are more sensitive to exposure of 10~20 nm-sized SiO2, Cr(VI) and B(a)P compared to 16HBE cells (a SV40-immortalized human bronchial epithelial cells). This study provides a novel in vitro human cells-based model for toxicity evaluation, may also be facilitating studies in basic cell biology, cancer biology and drug discovery.

  18. A transient fuel cell model to simulate HTPEM fuel cell impedance spectra

    DEFF Research Database (Denmark)

    Vang, Jakob Rabjerg; Andreasen, Søren Juhl; Kær, Søren Knudsen

    2011-01-01

    diffusion of cathode gas species in gas diffusion layers and catalyst layer, transport of protons in the membrane and the catalyst layers, and double layer capacitive effects in the catalyst layers. The model has been fitted simultaneously to a polarisation curve and to an impedance spectrum recorded......This paper presents a spatially resolved transient fuel cell model applied to the simulation of high temperature PEM fuel cell impedance spectra. The model is developed using a 2D finite volume method approach. The model is resolved along the channel and across the membrane. The model considers...

  19. PEM fuel cell modeling and simulation using Matlab

    CERN Document Server

    Spiegel, Colleen

    2011-01-01

    Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas. PEM Fuel Cell Modeling and Simulation Using Matlab, provides design engineers and researchers with a valuable tool for understanding and overcoming barriers to designing and building the next generation of PEM Fuel Cells. With this book, engineers can test components and verify designs in the development phase, saving both time and money.Easy to read and understand, this book provides design and modelling tips for

  20. ApoSense: a novel technology for functional molecular imaging of cell death in models of acute renal tubular necrosis

    Energy Technology Data Exchange (ETDEWEB)

    Damianovich, Maya; Ziv, Ilan; Aloya, Tali; Grimberg, Hagit; Levin, Galit; Reshef, Ayelet; Bentolila, Alfonso; Cohen, Avi; Shirvan, Anat [NeuroSurvival Technologies (NST) Ltd., Petah Tikva (Israel); Heyman, Samuel N.; Shina, Ahuva [Mt.Scopus and the Hebrew University Medical School, Department of Medicine, Hadassah Hospital, Jerusalem (Israel); Rosen, Seymour [Beth Israel Deaconess Medical Center and Harvard Medical School, Department of Pathology, Boston, MA (United States); Kidron, Dvora [Meir Hospital, Department of Pathology, Kfar-Saba (Israel)

    2006-03-15

    Acute renal tubular necrosis (ATN), a common cause of acute renal failure, is a dynamic, rapidly evolving clinical condition associated with apoptotic and necrotic tubular cell death. Its early identification is critical, but current detection methods relying upon clinical assessment, such as kidney biopsy and functional assays, are insufficient. We have developed a family of small molecule compounds, ApoSense, that is capable, upon systemic administration, of selectively targeting and accumulating within apoptotic/necrotic cells and is suitable for attachment of different markers for clinical imaging. The purpose of this study was to test the applicability of these molecules as a diagnostic imaging agent for the detection of renal tubular cell injury following renal ischemia. Using both fluorescent and radiolabeled derivatives of one of the ApoSense compounds, didansyl cystine, we evaluated cell death in three experimental, clinically relevant animal models of ATN: renal ischemia/reperfusion, radiocontrast-induced distal tubular necrosis, and cecal ligature and perforation-induced sepsis. ApoSense showed high sensitivity and specificity in targeting injured renal tubular epithelial cells in vivo in all three models used. Uptake of ApoSense in the ischemic kidney was higher than in the non-ischemic one, and the specificity of ApoSense targeting was demonstrated by its localization to regions of apoptotic/necrotic cell death, detected morphologically and by TUNEL staining. (orig.)

  1. Modeling, signaling and cytoskeleton dynamics: integrated modeling-experimental frameworks in cell migration.

    Science.gov (United States)

    Sun, Meng; Zaman, Muhammad H

    2017-01-01

    Cell migration is a complex and multistep process involved in homeostasis maintenance, morphogenesis, and disease development, such as cancer metastasis. Modeling cell migration and the relevant cytoskeleton dynamics have profound implications for studying fundamental development and disease diagnosis. This review focuses on some recent models of both cell migration and migration-related cytoskeleton dynamics, addressing issues such as the difference between amoeboid and mesenchymal migration modes, and between single-cell migration and collective cell migration. The review also highlights the computational integration among variable external cues, especially the biochemical and mechanical signaling that affects cell migration. Finally, we aim to identify the gaps in our current knowledge and potential strategies to develop integrated modeling-experimental frameworks for multiscale behavior integrating gene expression, cell signaling, mechanics, and multicellular dynamics. WIREs Syst Biol Med 2017, 9:e1365. doi: 10.1002/wsbm.1365 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

  2. Muscle Stem Cells: A Model System for Adult Stem Cell Biology.

    Science.gov (United States)

    Cornelison, Ddw; Perdiguero, Eusebio

    2017-01-01

    Skeletal muscle stem cells, originally termed satellite cells for their position adjacent to differentiated muscle fibers, are absolutely required for the process of skeletal muscle repair and regeneration. In the last decade, satellite cells have become one of the most studied adult stem cell systems and have emerged as a standard model not only in the field of stem cell-driven tissue regeneration but also in stem cell dysfunction and aging. Here, we provide background in the field and discuss recent advances in our understanding of muscle stem cell function and dysfunction, particularly in the case of aging, and the potential involvement of muscle stem cells in genetic diseases such as the muscular dystrophies.

  3. LG Solid Oxide Fuel Cell (SOFC) Model Development

    Energy Technology Data Exchange (ETDEWEB)

    Haberman, Ben [LG Fuel Cell Systems Inc., North Canton, OH (United States); Martinez-Baca, Carlos [LG Fuel Cell Systems Inc., North Canton, OH (United States); Rush, Greg [LG Fuel Cell Systems Inc., North Canton, OH (United States)

    2013-05-31

    This report presents a summary of the work performed by LG Fuel Cell Systems Inc. during the project LG Solid Oxide Fuel Cell (SOFC) Model Development (DOE Award Number: DE-FE0000773) which commenced on October 1, 2009 and was completed on March 31, 2013. The aim of this project is for LG Fuel Cell Systems Inc. (formerly known as Rolls-Royce Fuel Cell Systems (US) Inc.) (LGFCS) to develop a multi-physics solid oxide fuel cell (SOFC) computer code (MPC) for performance calculations of the LGFCS fuel cell structure to support fuel cell product design and development. A summary of the initial stages of the project is provided which describes the MPC requirements that were developed and the selection of a candidate code, STAR-CCM+ (CD-adapco). This is followed by a detailed description of the subsequent work program including code enhancement and model verification and validation activities. Details of the code enhancements that were implemented to facilitate MPC SOFC simulations are provided along with a description of the models that were built using the MPC and validated against experimental data. The modeling work described in this report represents a level of calculation detail that has not been previously available within LGFCS.

  4. Modeling dynamics of HIV infected cells using stochastic cellular automaton

    Science.gov (United States)

    Precharattana, Monamorn; Triampo, Wannapong

    2014-08-01

    Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.

  5. Stem cells in animal asthma models: a systematic review.

    Science.gov (United States)

    Srour, Nadim; Thébaud, Bernard

    2014-12-01

    Asthma control frequently falls short of the goals set in international guidelines. Treatment options for patients with poorly controlled asthma despite inhaled corticosteroids and long-acting β-agonists are limited, and new therapeutic options are needed. Stem cell therapy is promising for a variety of disorders but there has been no human clinical trial of stem cell therapy for asthma. We aimed to systematically review the literature regarding the potential benefits of stem cell therapy in animal models of asthma to determine whether a human trial is warranted. The MEDLINE and Embase databases were searched for original studies of stem cell therapy in animal asthma models. Nineteen studies were selected. They were found to be heterogeneous in their design. Mesenchymal stromal cells were used before sensitization with an allergen, before challenge with the allergen and after challenge, most frequently with ovalbumin, and mainly in BALB/c mice. Stem cell therapy resulted in a reduction of bronchoalveolar lavage fluid inflammation and eosinophilia as well as Th2 cytokines such as interleukin-4 and interleukin-5. Improvement in histopathology such as peribronchial and perivascular inflammation, epithelial thickness, goblet cell hyperplasia and smooth muscle layer thickening was universal. Several studies showed a reduction in airway hyper-responsiveness. Stem cell therapy decreases eosinophilic and Th2 inflammation and is effective in several phases of the allergic response in animal asthma models. Further study is warranted, up to human clinical trials. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  6. Understanding pollen tube growth: the hydrodynamic model versus the cell wall model

    NARCIS (Netherlands)

    Zonia, L.; Munnik, T.

    2011-01-01

    Scientific progress stimulates the evolution of models used to understand and conceptualize biological behaviors. The widely accepted cell wall model of pollen tube growth explains stochastic growth of the apical pectin wall, but fails to explain the mechanism driving oscillations in growth and cell

  7. Modelling Neurodegenerative Diseases Using Human Pluripotent Stem Cells

    DEFF Research Database (Denmark)

    Hall, Vanessa Jane

    2016-01-01

    Neurodegenerative diseases are being modelled in-vitro using human patient-specific, induced pluripotent stem cells and transgenic embryonic stem cells to determine more about disease mechanisms, as well as to discover new treatments for patients. Current research in modelling Alzheimer’s disease......, frontotemporal dementia and Parkinson’s disease using pluripotent stem cells is described, along with the advent of gene-editing, which has been the complimentary tool for the field. Current methods used to model these diseases are predominantly dependent on 2D cell culture methods. Outcomes reveal that only...... some of the phenotype can be observed in-vitro, but these phenotypes, when compared to the patient, correlate extremely well. Many studies have found novel molecular mechanisms involved in the disease and therefore elucidate new potential targets for reversing the phenotype. Future research...

  8. Genome engineering of stem cell organoids for disease modeling

    Directory of Open Access Journals (Sweden)

    Yingmin Sun

    2017-01-01

    Full Text Available Abstract Precision medicine emerges as a new approach that takes into account individual variability. Successful realization of precision medicine requires disease models that are able to incorporate personalized disease information and recapitulate disease development processes at the molecular, cellular and organ levels. With recent development in stem cell field, a variety of tissue organoids can be derived from patient specific pluripotent stem cells and adult stem cells. In combination with the state-of-the-art genome editing tools, organoids can be further engineered to mimic disease-relevant genetic and epigenetic status of a patient. This has therefore enabled a rapid expansion of sophisticated in vitro disease models, offering a unique system for fundamental and biomedical research as well as the development of personalized medicine. Here we summarize some of the latest advances and future perspectives in engineering stem cell organoids for human disease modeling.

  9. Modeling Human Natural Killer Cell Development in the Era of Innate Lymphoid Cells.

    Science.gov (United States)

    Scoville, Steven D; Freud, Aharon G; Caligiuri, Michael A

    2017-01-01

    Decades after the discovery of natural killer (NK) cells, their developmental pathways in mice and humans have not yet been completely deciphered. Accumulating evidence indicates that NK cells can develop in multiple tissues throughout the body. Moreover, detailed and comprehensive models of NK cell development were proposed soon after the turn of the century. However, with the recent identification and characterization of other subtypes of innate lymphoid cells (ILCs), which show some overlapping functional and phenotypic features with NK cell developmental intermediates, the distinct stages through which human NK cells develop from early hematopoietic progenitor cells remain unclear. Thus, there is a need to reassess and refine older models of NK cell development in the context of new data and in the era of ILCs. Our group has focused on elucidating the developmental pathway of human NK cells in secondary lymphoid tissues (SLTs), including tonsils and lymph nodes. Here, we provide an update of recent progress that has been made with regard to human NK cell development in SLTs, and we discuss these new findings in the context of contemporary models of ILC development.

  10. Modeling Human Natural Killer Cell Development in the Era of Innate Lymphoid Cells

    Science.gov (United States)

    Scoville, Steven D.; Freud, Aharon G.; Caligiuri, Michael A.

    2017-01-01

    Decades after the discovery of natural killer (NK) cells, their developmental pathways in mice and humans have not yet been completely deciphered. Accumulating evidence indicates that NK cells can develop in multiple tissues throughout the body. Moreover, detailed and comprehensive models of NK cell development were proposed soon after the turn of the century. However, with the recent identification and characterization of other subtypes of innate lymphoid cells (ILCs), which show some overlapping functional and phenotypic features with NK cell developmental intermediates, the distinct stages through which human NK cells develop from early hematopoietic progenitor cells remain unclear. Thus, there is a need to reassess and refine older models of NK cell development in the context of new data and in the era of ILCs. Our group has focused on elucidating the developmental pathway of human NK cells in secondary lymphoid tissues (SLTs), including tonsils and lymph nodes. Here, we provide an update of recent progress that has been made with regard to human NK cell development in SLTs, and we discuss these new findings in the context of contemporary models of ILC development. PMID:28396671

  11. On a model of pattern regeneration based on cell memory.

    Directory of Open Access Journals (Sweden)

    Nikolai Bessonov

    Full Text Available We present here a new model of the cellular dynamics that enable regeneration of complex biological morphologies. Biological cell structures are considered as an ensemble of mathematical points on the plane. Each cell produces a signal which propagates in space and is received by other cells. The total signal received by each cell forms a signal distribution defined on the cell structure. This distribution characterizes the geometry of the cell structure. If a part of this structure is removed, the remaining cells have two signals. They keep the value of the signal which they had before the amputation (memory, and they receive a new signal produced after the amputation. Regeneration of the cell structure is stimulated by the difference between the old and the new signals. It is stopped when the two signals coincide. The algorithm of regeneration contains certain rules which are essential for its functioning, being the first quantitative model of cellular memory that implements regeneration of complex patterns to a specific target morphology. Correct regeneration depends on the form and the size of the cell structure, as well as on some parameters of regeneration.

  12. cellGPU: Massively parallel simulations of dynamic vertex models

    Science.gov (United States)

    Sussman, Daniel M.

    2017-10-01

    Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

  13. Polyunsaturated fatty acid metabolism in enterocyte models: T84 cell line vs. Caco-2 cell line.

    Science.gov (United States)

    Beguin, Pauline; Schneider, Anne-Catherine; Mignolet, Eric; Schneider, Yves-Jacques; Larondelle, Yvan

    2014-02-01

    Human colon carcinoma cell lines such as Caco-2 cells, model of mature enterocytes and T84 cells, model of crypt cells are useful to study interactions between nutrient processing and metabolic functions at intestinal level. Our study aimed at comparing the ability of Caco-2 and T84 cells (1) to incorporate dietary polyunsaturated fatty acids (PUFA), (2) to process them and (3) to sort them into neutral lipids (NL), free fatty acids (FFA) and phospholipids (PL). Caco-2 and T84 cells were exposed to a 7-day long supplementation with PUFA. The amounts of fatty acids accumulated and incorporated into the NL, FFA or PL fractions were higher in Caco-2 than in T84 cells. Caco-2 cells were able to significantly elongate C18 PUFA and C20 PUFA of both n-3 and n-6 families. In contrast, T84 cells were unable to elongate the n-6 fatty acids whereas elongation of n-3 fatty acids was detectable but marginal. Similarly, a Δ6 desaturase activity was observed in Caco-2 but not in T84 cells. In T84 cells, each exogenous fatty acid was predominantly accumulated in the PL fraction. In Caco-2 cells, C20 fatty acids and C18:2n-6 was preferentially accumulated in the PL fraction, while C22 PUFA and C18:3n-3 was preferentially accumulated in the NL fraction. Overall, this study has shown that Caco-2 and T84 cells, as models of intestinal mucosal cells, present large differences in PUFA accumulation capacity, specific elongase and desaturase activities and distribution pattern of exogenous PUFA and of their metabolites in the lipid classes.

  14. Conformon-driven biopolymer shape changes in cell modeling.

    Science.gov (United States)

    Ji, Sungchul; Ciobanu, Gabriel

    2003-07-01

    Conceptual models of the atom preceded the mathematical model of the hydrogen atom in physics in the second decade of the 20th century. The computer modeling of the living cell in the 21st century may follow a similar course of development. A conceptual model of the cell called the Bhopalator was formulated in the mid-1980s, along with its twin theories known as the conformon theory of molecular machines and the cell language theory of biopolymer interactions [Ann. N.Y. Acad. Sci. 227 (1974) 211; BioSystems 44 (1997) 17; Ann. N.Y. Acad. Sci. 870 (1999a) 411; BioSystems 54 (2000) 107; Semiotica 138 (1-4) (2002a) 15; Fundamenta Informaticae 49 (2002b) 147]. The conformon theory accounts for the reversible actions of individual biopolymers coupled to irreversible chemical reactions, while the cell language theory provides a theoretical framework for understanding the complex networks of dynamic interactions among biopolymers in the cell. These two theories are reviewed and further elaborated for the benefit of both computational biologists and computer scientists who are interested in modeling the living cell and its functions. One of the critical components of the mechanisms of cell communication and cell computing has been postulated to be space- and time-organized teleonomic (i.e. goal-directed) shape changes of biopolymers that are driven by exergonic (free energy-releasing) chemical reactions. The generalized Franck-Condon principle is suggested to be essential in resolving the apparent paradox arising when one attempts to couple endergonic (free energy-requiring) biopolymer shape changes to the exergonic chemical reactions that are catalyzed by biopolymer shape changes themselves. Conformons, defined as sequence-specific mechanical strains of biopolymers first invoked three decades ago to account for energy coupling in mitochondria, have been identified as shape changers, the agents that cause shape changes in biopolymers. Given a set of space- and time

  15. New Model of Wood Cell Wall Microfibril and Its Implications

    Science.gov (United States)

    Umesh P. Agarwal; Sally A. Ralph; Rick S. Reiner; Carlos Baez

    2015-01-01

    Traditionally it has been accepted that the cell walls are made up of microfibrils which are partly crystalline. However, based on the recently obtained Raman evidence that showed that the interior of the microfibril was significantly disordered and water accessible, a new model is proposed. In this model, the molecular chains of cellulose are still organized along the...

  16. A novel xenograft model of cutaneous T-cell lymphoma

    DEFF Research Database (Denmark)

    Krejsgaard, Thorbjørn; Kopp, Katharina; Ralfkiaer, Elisabeth

    2010-01-01

    , because of the lack of suitable animal models, little is known about the mechanisms driving CTCL development and progression in vivo. Here, we describe a novel xenograft model of tumor stage CTCL, where malignant T cells (MyLa2059) are transplanted to NOD/SCID-B2m(-/-) (NOD.Cg-Prkdc(scid) B2m(tm1Unc...

  17. Towards a whole-cell modeling approach for synthetic biology

    Science.gov (United States)

    Purcell, Oliver; Jain, Bonny; Karr, Jonathan R.; Covert, Markus W.; Lu, Timothy K.

    2013-06-01

    Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of whole-cell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline.

  18. Determining the optimum cell size of digital elevation model for ...

    Indian Academy of Sciences (India)

    Scale is one of the most important but unsolved issues in various scientific disciplines that deal with spatial data. The arbitrary choice of grid cell size for contour interpolated digital elevation models. (DEM) is one of the major sources of uncertainty in the hydrologic modelling process. In this paper, an attempt was made to ...

  19. Modelling Morphogenesis: From Single Cells to Crawling Slugs

    NARCIS (Netherlands)

    Savill, N.J.; Hogeweg, P.

    1996-01-01

    We present a three-dimensional hybrid cellular automata (CA)/partial differential equation (PDE) model that allows for the study of morphogenesis in simple cellular systems. We apply the model to the cellular slime mold Dictyostelium discoideum "from single cells to crawling slug". Using simple

  20. Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It

    DEFF Research Database (Denmark)

    Mengistu, Henok; Lehman, Joel Anthony; Clune, Jeff

    2016-01-01

    One hallmark of natural organisms is their significant evolvability, i.e.,their increased potential for further evolution. However, reproducing such evolvability in artificial evolution remains a challenge, which both reduces the performance of evolutionary algorithms and inhibits the study...... of evolvable digital phenotypes. Although some types of selection in evolutionary computation indirectly encourage evolvability, one unexplored possibility is to directly select for evolvability. To do so, we estimate an individual's future potential for diversity by calculating the behavioral diversity of its...... immediate offspring, and select organisms with increased offspring variation. While the technique is computationally expensive, we hypothesized that direct selection would better encourage evolvability than indirect methods. Experiments in two evolutionary robotics domains confirm this hypothesis: in both...

  1. Human Lipoproteins at Model Cell Membranes

    DEFF Research Database (Denmark)

    Browning, K L; Lind, T K; Maric, S

    2017-01-01

    High and low density lipoproteins (HDL and LDL) are thought to play vital roles in the onset and development of atherosclerosis; the biggest killer in the western world. Key issues of initial lipoprotein (LP) interactions at cellular membranes need to be addressed including LP deposition and lipid...... exchange and lipid removal can be distinguished thanks to the combined use of hydrogenated and tail-deuterated lipids. Both HDL and LDL remove lipids from the bilayer and deposit hydrogenated material into the lipid bilayer, however, the extent of removal and exchange depends on LP type. These results...... support the notion of HDL acting as the 'good' cholesterol, removing lipid material from lipid-loaded cells, whereas LDL acts as the 'bad' cholesterol, depositing lipid material into the vascular wall....

  2. Ionic channel changes in glaucomatous retinal ganglion cells: multicompartment modeling.

    Science.gov (United States)

    Maturana, Matias I; Turpin, Andrew; McKendrick, Allison M; Kameneva, Tatiana

    2014-01-01

    This research takes a step towards discovering underlying ionic channel changes in the glaucomatous ganglion cells. Glaucoma is characterized by a gradual death of retinal ganglion cells. In this paper, we propose a hypothesis that the ionic channel concentrations change during the progression of glaucoma. We use computer simulation of a multi-compartment morphologically correct model of a mouse retinal ganglion cell to verify our hypothesis. Using published experimental data, we alter the morphology of healthy ganglion cells to replicate glaucomatous cells. Our results suggest that in glaucomatous cell, the sodium channel concentration decreases in the soma by 30% and by 60% in the dendrites, calcium channel concentration decreases by 10% in all compartments, and leak channel concentration increases by 40% in the soma and by 100% in the dendrites.

  3. Aging and immortality in a cell proliferation model.

    Science.gov (United States)

    Antal, T; Blagoev, K B; Trugman, S A; Redner, S

    2007-10-07

    We investigate a model of cell division in which the length of telomeres within a cell regulates its proliferative potential. At each division, telomeres undergo a systematic length decrease as well as a superimposed fluctuation due to exchange of telomere DNA between the two daughter cells. A cell becomes senescent when one or more of its telomeres become shorter than a critical length. We map this telomere dynamics onto a biased branching-diffusion process with an absorbing boundary condition whenever any telomere reaches the critical length. Using first-passage ideas, we find a phase transition between finite lifetime and immortality (infinite proliferation) of the cell population as a function of the influence of telomere shortening, fluctuations, and cell division.

  4. Empirical membrane lifetime model for heavy duty fuel cell systems

    Science.gov (United States)

    Macauley, Natalia; Watson, Mark; Lauritzen, Michael; Knights, Shanna; Wang, G. Gary; Kjeang, Erik

    2016-12-01

    Heavy duty fuel cells used in transportation system applications such as transit buses expose the fuel cell membranes to conditions that can lead to lifetime-limiting membrane failure via combined chemical and mechanical degradation. Highly durable membranes and reliable predictive models are therefore needed in order to achieve the ultimate heavy duty fuel cell lifetime target of 25,000 h. In the present work, an empirical membrane lifetime model was developed based on laboratory data from a suite of accelerated membrane durability tests. The model considers the effects of cell voltage, temperature, oxygen concentration, humidity cycling, humidity level, and platinum in the membrane using inverse power law and exponential relationships within the framework of a general log-linear Weibull life-stress statistical distribution. The obtained model is capable of extrapolating the membrane lifetime from accelerated test conditions to use level conditions during field operation. Based on typical conditions for the Whistler, British Columbia fuel cell transit bus fleet, the model predicts a stack lifetime of 17,500 h and a membrane leak initiation time of 9200 h. Validation performed with the aid of a field operated stack confirmed the initial goal of the model to predict membrane lifetime within 20% of the actual operating time.

  5. Reactivation of proliferin gene expression is associated with increased angiogenesis in a cell culture model of fibrosarcoma tumor progression

    Science.gov (United States)

    Toft, Daniel J.; Rosenberg, Suzanne B.; Bergers, Gabriele; Volpert, Olga; Linzer, Daniel I. H.

    2001-01-01

    Proliferin (PLF) is an angiogenic placental hormone. We now report that PLF gene expression can also occur in a progressive fibrosarcoma mouse tumor cell model. PLF mRNA and protein are detectable at very low levels in cell lines derived from the mild noninvasive stage of tumor development. Expression is greatly augmented in cell lines from the aggressively invasive stage of development, a stage at which the tumor becomes highly angiogenic, and PLF expression remains high in cell lines from the end stage of fibrosarcoma. Activator protein 1 factors present at high levels in the more invasive stages of the tumor may in part allow for increased PLF expression, as cells from the mild stage in which c-jun and junB are stably expressed secrete levels of PLF comparable to that of the advanced stages. Secreted PLF protein is functionally important in tumor cell angiogenic activity, as demonstrated by the reduction of angiogenic activity in fibrosarcoma cell culture medium by immunodepletion of PLF. These results suggest that an extraembryonic genetic program, which has evolved to support fetal growth, may be reactivated in certain tumors and contribute to tumor growth. PMID:11606769

  6. Versatility of peroxisomes: An evolving concept.

    Science.gov (United States)

    Deb, Rachayeeta; Nagotu, Shirisha

    2017-04-01

    Research spanning almost 50 years has highlighted unique characteristics and irreplaceable list of diverse functions performed by peroxisomes in various model systems. Peroxisomes are single membrane bound highly dynamic organelles ubiquitous to most eukaryotic cells. Proliferation by division of pre-existing organelles and the role of endoplasmic reticulum in the biogenesis of these organelles is now well established. The earliest identified conserved functions of peroxisomes are β-oxidation of fatty acids and reactive oxygen species metabolism. Several studies over the last few decades have reported the importance of this organelle and its numerous cell type, tissue and environment-dependent functions. Their role in several aspects of human health and disease is now under investigation. Studies related to peroxisome biology and functions are now also extended to diverse model systems like Drosophila melanogaster, trypanosomatids, etc. Peroxisomes also intricately collaborate and carry out these functions together with several other organelles in a cell. In this review, we aim to present an overview of our current knowledge of the repertoire of functions of peroxisomes in various model systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. A model for astral stimulation of cytokinesis in animal cells

    Science.gov (United States)

    1989-01-01

    A model is proposed in which stimulation of cortical cytoplasm occurs near the distal ends of astral rays. Levels of stimulation sufficient to cause furrowing occur only in equatorial zones between asters. The model can account for positioning of furrows in very large cells (fertilized eggs of amphibians, birds, and fish) and in cells with several mitotic apparatuses (insects). Finally, the model correctly predicts the positioning and occurrence of furrowing in two experiments in which cellular shape was manipulated into either an hourglass or a cylindrical form before division. These results are consistent with equatorial stimulation theories in which mitotic asters differentially stimulate the future furrow region (equatorial cortex). The results are not consistent with models requiring differential stimulation of nonfurrowing, polar regions of the cell. PMID:2808526

  8. Noninvasive Assessment of Tumor Cell Proliferation in Animal Models

    Directory of Open Access Journals (Sweden)

    Matthias Edinger

    1999-10-01

    Full Text Available Revealing the mechanisms of neoplastic disease and enhancing our ability to intervene in these processes requires an increased understanding of cellular and molecular changes as they occur in intact living animal models. We have begun to address these needs by developing a method of labeling tumor cells through constitutive expression of an optical reporter gene, noninvasively monitoring cellular proliferation in vivo using a sensitive photon detection system. A stable line of HeLa cells that expressed a modified firefly luciferase gene was generated, proliferation of these cells in irradiated severe combined immunodeficiency (SCID mice was monitored. Tumor cells were introduced into animals via subcutaneous, intraperitoneal and intravenous inoculation and whole body images, that revealed tumor location and growth kinetics, were obtained. The number of photons that were emitted from the labeled tumor cells and transmitted through murine tissues was sufficient to detect 1×103 cells in the peritoneal cavity, 1×104 cells at subcutaneous sites and 1×106 circulating cells immediately following injection. The kinetics of cell proliferation, as measured by photon emission, was exponential in the peritoneal cavity and at subcutaneous sites. Intravenous inoculation resulted in detectable colonies of tumor cells in animals receiving more than 1×103 cells. Our demonstrated ability to detect small numbers of tumor cells in living animals noninvasively suggests that therapies designed to treat minimal disease states, as occur early in the disease course and after elimination of the tumor mass, may be monitored using this approach. Moreover, it may be possible to monitor micrometastases and evaluate the molecular steps in the metastatic process. Spatiotemporal analyses of neoplasia will improve the predictability of animal models of human disease as study groups can be followed over time, this method will accelerate development of novel therapeutic

  9. Evolved atmospheric entry corridor with safety factor

    Science.gov (United States)

    Liang, Zixuan; Ren, Zhang; Li, Qingdong

    2018-02-01

    Atmospheric entry corridors are established in previous research based on the equilibrium glide condition which assumes the flight-path angle to be zero. To get a better understanding of the highly constrained entry flight, an evolved entry corridor that considers the exact flight-path angle is developed in this study. Firstly, the conventional corridor in the altitude vs. velocity plane is extended into a three-dimensional one in the space of altitude, velocity, and flight-path angle. The three-dimensional corridor is generated by a series of constraint boxes. Then, based on a simple mapping method, an evolved two-dimensional entry corridor with safety factor is obtained. The safety factor is defined to describe the flexibility of the flight-path angle for a state within the corridor. Finally, the evolved entry corridor is simulated for the Space Shuttle and the Common Aero Vehicle (CAV) to demonstrate the effectiveness of the corridor generation approach. Compared with the conventional corridor, the evolved corridor is much wider and provides additional information. Therefore, the evolved corridor would benefit more to the entry trajectory design and analysis.

  10. Emergent spacetime in stochastically evolving dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Afshordi, Niayesh [Perimeter Institute for Theoretical Physics, 31 Caroline St. N., Waterloo, ON, N2L 2Y5 (Canada); Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, N2L 3G1 (Canada); HEPCOS, Department of Physics, SUNY at Buffalo, Buffalo, NY 14260-1500 (United States); Stojkovic, Dejan, E-mail: ds77@buffalo.edu [Perimeter Institute for Theoretical Physics, 31 Caroline St. N., Waterloo, ON, N2L 2Y5 (Canada); HEPCOS, Department of Physics, SUNY at Buffalo, Buffalo, NY 14260-1500 (United States)

    2014-12-12

    Changing the dimensionality of the space–time at the smallest and largest distances has manifold theoretical advantages. If the space is lower dimensional in the high energy regime, then there are no ultraviolet divergencies in field theories, it is possible to quantize gravity, and the theory of matter plus gravity is free of divergencies or renormalizable. If the space is higher dimensional at cosmological scales, then some cosmological problems (including the cosmological constant problem) can be attacked from a completely new perspective. In this paper, we construct an explicit model of “evolving dimensions” in which the dimensions open up as the temperature of the universe drops. We adopt the string theory framework in which the dimensions are fields that live on the string worldsheet, and add temperature dependent mass terms for them. At the Big Bang, all the dimensions are very heavy and are not excited. As the universe cools down, dimensions open up one by one. Thus, the dimensionality of the space we live in depends on the energy or temperature that we are probing. In particular, we provide a kinematic Brandenberger–Vafa argument for how a discrete causal set, and eventually a continuum (3+1)-dim spacetime along with Einstein gravity emerges in the Infrared from the worldsheet action. The (3+1)-dim Planck mass and the string scale become directly related, without any compactification. Amongst other predictions, we argue that LHC might be blind to new physics even if it comes at the TeV scale. In contrast, cosmic ray experiments, especially those that can register the very beginning of the shower, and collisions with high multiplicity and density of particles, might be sensitive to the dimensional cross-over.

  11. Emergent spacetime in stochastically evolving dimensions

    Science.gov (United States)

    Afshordi, Niayesh; Stojkovic, Dejan

    2014-12-01

    Changing the dimensionality of the space-time at the smallest and largest distances has manifold theoretical advantages. If the space is lower dimensional in the high energy regime, then there are no ultraviolet divergencies in field theories, it is possible to quantize gravity, and the theory of matter plus gravity is free of divergencies or renormalizable. If the space is higher dimensional at cosmological scales, then some cosmological problems (including the cosmological constant problem) can be attacked from a completely new perspective. In this paper, we construct an explicit model of ;evolving dimensions; in which the dimensions open up as the temperature of the universe drops. We adopt the string theory framework in which the dimensions are fields that live on the string worldsheet, and add temperature dependent mass terms for them. At the Big Bang, all the dimensions are very heavy and are not excited. As the universe cools down, dimensions open up one by one. Thus, the dimensionality of the space we live in depends on the energy or temperature that we are probing. In particular, we provide a kinematic Brandenberger-Vafa argument for how a discrete causal set, and eventually a continuum (3 + 1)-dim spacetime along with Einstein gravity emerges in the Infrared from the worldsheet action. The (3 + 1)-dim Planck mass and the string scale become directly related, without any compactification. Amongst other predictions, we argue that LHC might be blind to new physics even if it comes at the TeV scale. In contrast, cosmic ray experiments, especially those that can register the very beginning of the shower, and collisions with high multiplicity and density of particles, might be sensitive to the dimensional cross-over.

  12. Emergent spacetime in stochastically evolving dimensions

    Directory of Open Access Journals (Sweden)

    Niayesh Afshordi

    2014-12-01

    Full Text Available Changing the dimensionality of the space–time at the smallest and largest distances has manifold theoretical advantages. If the space is lower dimensional in the high energy regime, then there are no ultraviolet divergencies in field theories, it is possible to quantize gravity, and the theory of matter plus gravity is free of divergencies or renormalizable. If the space is higher dimensional at cosmological scales, then some cosmological problems (including the cosmological constant problem can be attacked from a completely new perspective. In this paper, we construct an explicit model of “evolving dimensions” in which the dimensions open up as the temperature of the universe drops. We adopt the string theory framework in which the dimensions are fields that live on the string worldsheet, and add temperature dependent mass terms for them. At the Big Bang, all the dimensions are very heavy and are not excited. As the universe cools down, dimensions open up one by one. Thus, the dimensionality of the space we live in depends on the energy or temperature that we are probing. In particular, we provide a kinematic Brandenberger–Vafa argument for how a discrete causal set, and eventually a continuum (3+1-dim spacetime along with Einstein gravity emerges in the Infrared from the worldsheet action. The (3+1-dim Planck mass and the string scale become directly related, without any compactification. Amongst other predictions, we argue that LHC might be blind to new physics even if it comes at the TeV scale. In contrast, cosmic ray experiments, especially those that can register the very beginning of the shower, and collisions with high multiplicity and density of particles, might be sensitive to the dimensional cross-over.

  13. Induced pluripotent stem cells for modeling neurological disorders

    Science.gov (United States)

    Russo, Fabiele B; Cugola, Fernanda R; Fernandes, Isabella R; Pignatari, Graciela C; Beltrão-Braga, Patricia C B

    2015-01-01

    Several diseases have been successfully modeled since the development of induced pluripotent stem cell (iPSC) technology in 2006. Since then, methods for increased reprogramming efficiency and cell culture maintenance have been optimized and many protocols for differentiating stem cell lines have been successfully developed, allowing the generation of several cellular subtypes in vitro. Gene editing technologies have also greatly advanced lately, enhancing disease-specific phenotypes by creating isogenic cell lines, allowing mutations to be corrected in affected samples or inserted in control lines. Neurological disorders have benefited the most from iPSC-disease modeling for its capability for generating disease-relevant cell types in vitro from the central nervous system, such as neurons and glial cells, otherwise only available from post-mortem samples. Patient-specific iPSC-derived neural cells can recapitulate the phenotypes of these diseases and therefore, considerably enrich our understanding of pathogenesis, disease mechanism and facilitate the development of drug screening platforms for novel therapeutic targets. Here, we review the accomplishments and the current progress in human neurological disorders by using iPSC modeling for Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, spinal muscular atrophy, amyotrophic lateral sclerosis, duchenne muscular dystrophy, schizophrenia and autism spectrum disorders, which include Timothy syndrome, Fragile X syndrome, Angelman syndrome, Prader-Willi syndrome, Phelan-McDermid, Rett syndrome as well as Nonsyndromic Autism. PMID:26722648

  14. THP-1 cell line: an in vitro cell model for immune-modulation approach : Review

    NARCIS (Netherlands)

    Chanput, W.; Mes, J.J.; Wichers, H.J.

    2014-01-01

    THP-1 is a human leukemia monocytic cell line, which has been extensively used to study monocyte/macrophage functions, mechanisms, signaling pathways, and nutrient and drug transport. This cell line has become a common model to estimate modulation of monocyte and macrophage activities. This review

  15. Mobile Applications in Cell Biology Present New Approaches for Cell Modelling

    Science.gov (United States)

    de Oliveira, Mayara Lustosa; Galembeck, Eduardo

    2016-01-01

    Cell biology apps were surveyed in order to identify whether there are new approaches for modelling cells allowed by the new technologies implemented in tablets and smartphones. A total of 97 apps were identified in 3 stores surveyed (Apple, Google Play and Amazon), they are presented as: education 48.4%, games 26.8% and medicine 15.4%. The apps…

  16. Application of alternating current impedance to fuel cell modeling

    Energy Technology Data Exchange (ETDEWEB)

    Springer, T.E.

    1999-05-02

    AC impedance has provided a useful diagnostic tool in the Los Alamos polymer electrolyte fuel cell (PEFC) program. The author reviews the techniques he has used in ac impedance modeling. These techniques include equation implementation, model simplification and verification, least squares fitting, application of two-dimensional Laplace equation solvers handling complex interfacial boundary conditions, and interpretation of impedance features. The separate features of the complete electrode model are explained by analytic examples.

  17. Using Human Induced Pluripotent Stem Cells to Model Skeletal Diseases.

    Science.gov (United States)

    Barruet, Emilie; Hsiao, Edward C

    2016-01-01

    Musculoskeletal disorders affecting the bones and joints are major health problems among children and adults. Major challenges such as the genetic origins or poor diagnostics of severe skeletal disease hinder our understanding of human skeletal diseases. The recent advent of human induced pluripotent stem cells (human iPS cells) provides an unparalleled opportunity to create human-specific models of human skeletal diseases. iPS cells have the ability to self-renew, allowing us to obtain large amounts of starting material, and have the potential to differentiate into any cell types in the body. In addition, they can carry one or more mutations responsible for the disease of interest or be genetically corrected to create isogenic controls. Our work has focused on modeling rare musculoskeletal disorders including fibrodysplasia ossificans progressive (FOP), a congenital disease of increased heterotopic ossification. In this review, we will discuss our experiences and protocols differentiating human iPS cells toward the osteogenic lineage and their application to model skeletal diseases. A number of critical challenges and exciting new approaches are also discussed, which will allow the skeletal biology field to harness the potential of human iPS cells as a critical model system for understanding diseases of abnormal skeletal formation and bone regeneration.

  18. Analytical modeling of PEM fuel cell i-V curve

    Energy Technology Data Exchange (ETDEWEB)

    Haji, Shaker [College of Engineering, Department of Chemical Engineering, University of Bahrain, P.O. Box 32038 (Bahrain)

    2011-02-15

    The performance of a fuel cell is characterized by its i-V curve. In this study, the performance of a bench scale fuel cell stack, run on hydrogen/air, is measured experimentally for different air flow rates and temperatures. The experimental data, obtained from the 40-W proton exchange membrane fuel cell (PEMFC), are used in estimating the parameters of a completely analytical model that describes the i-V curve. The analytical model consists of the three fundamental losses experienced by a fuel cell, namely: activation, ohmic, and concentration losses. The current loss is also considered in the model. While the Tafel constants, ohmic resistance, and the concentration loss constant are estimated through regression, the limiting current density and the current loss are obtained through measurements. The effect of temperature on the fuel cell performance, exchange current density, and current loss is also investigated. Both the exchange current density and the current loss are plotted against temperature on an Arrhenius-like plot and the related parameters are estimated. The theoretical equations derived in the literature, which model fuel cell performance, are found to reasonably fit the obtained experimental data. (author)

  19. Boolean network model predicts cell cycle sequence of fission yeast.

    Directory of Open Access Journals (Sweden)

    Maria I Davidich

    Full Text Available A Boolean network model of the cell-cycle regulatory network of fission yeast (Schizosaccharomyces Pombe is constructed solely on the basis of the known biochemical interaction topology. Simulating the model in the computer faithfully reproduces the known activity sequence of regulatory proteins along the cell cycle of the living cell. Contrary to existing differential equation models, no parameters enter the model except the structure of the regulatory circuitry. The dynamical properties of the model indicate that the biological dynamical sequence is robustly implemented in the regulatory network, with the biological stationary state G1 corresponding to the dominant attractor in state space, and with the biological regulatory sequence being a strongly attractive trajectory. Comparing the fission yeast cell-cycle model to a similar model of the corresponding network in S. cerevisiae, a remarkable difference in circuitry, as well as dynamics is observed. While the latter operates in a strongly damped mode, driven by external excitation, the S. pombe network represents an auto-excited system with external damping.

  20. Preliminary Modeling and Simulation Study on Olfactory Cell Sensation

    Science.gov (United States)

    Zhou, Jun; Yang, Wei; Chen, Peihua; Liu, Qingjun; Wang, Ping

    2009-05-01

    This paper introduced olfactory sensory neuron's whole-cell model with a concrete voltage-gated ionic channels and simulation. Though there are many models in olfactory sensory neuron and olfactory bulb, it remains uncertain how they express the logic of olfactory information processing. In this article, the olfactory neural network model is also introduced. This model specifies the connections among neural ensembles of the olfactory system. The simulation results of the neural network model are consistent with the observed olfactory biological characteristics such as 1/f-type power spectrum and oscillations.

  1. Multi-population model of a microbial electrolysis cell.

    Science.gov (United States)

    Pinto, R P; Srinivasan, B; Escapa, A; Tartakovsky, B

    2011-06-01

    This work presents a multi-population dynamic model of a microbial electrolysis cell (MEC). The model describes the growth and metabolic activity of fermentative, electricigenic, methanogenic acetoclastic, and methanogenic hydrogenophilic microorganisms and is capable of simulating hydrogen production in a MEC fed with complex organic matter, such as wastewater. The model parameters were estimated with the experimental results obtained in continuous flow MECs fed with acetate or synthetic wastewater. Following successful model validation with an independent data set, the model was used to analyze and discuss the influence of applied voltage and organic load on hydrogen production and COD removal.

  2. Model for glucagon secretion by pancreatic α-cells.

    Directory of Open Access Journals (Sweden)

    Virginia González-Vélez

    Full Text Available Glucagon hormone is synthesized and released by pancreatic α-cells, one of the islet-cell types. This hormone, along with insulin, maintains blood glucose levels within the physiological range. Glucose stimulates glucagon release at low concentrations (hypoglycemia. However, the mechanisms involved in this secretion are still not completely clear. Here, using experimental calcium time series obtained in mouse pancreatic islets at low and high glucose conditions, we propose a glucagon secretion model for α-cells. Our model takes into account that the resupply of releasable granules is not only controlled by cytoplasmic Ca2+, as in other neuroendocrine and endocrine cells, but also by the level of extracellular glucose. We found that, although calcium oscillations are highly variable, the average secretion rates predicted by the model fall into the range of values reported in the literature, for both stimulated and non-stimulated conditions. For low glucose levels, the model predicts that there would be a well-controlled number of releasable granules refilled slowly from a large reserve pool, probably to ensure a secretion rate that could last for several minutes. Studying the α-cell response to the addition of insulin at low glucose, we observe that the presence of insulin reduces glucagon release by decreasing the islet Ca2+ level. This observation is in line with previous work reporting that Ca2+ dynamics, mainly frequency, is altered by insulin. Thus, the present results emphasize the main role played by Ca2+ and glucose in the control of glucagon secretion by α-cells. Our modeling approach also shows that calcium oscillations potentiate glucagon secretion as compared to constant levels of this cellular messenger. Altogether, the model sheds new light on the subcellular mechanisms involved in α-cell exocytosis, and provides a quantitative predictive tool for studying glucagon secretion modulators in physiological and pathological

  3. Establishing credibility: Evolving perceptions of the European Central Bank

    OpenAIRE

    Linda S. Goldberg; Klein, Michael W

    2005-01-01

    The credibility of a central bank’s anti-inflation stance, a key determinant of its success, may reflect institutional structure or, more dynamically, the history of policy decisions. The first years of the European Central Bank (ECB) provide a natural experiment for considering whether, and how, central bank credibility evolves. In this paper, we present a model demonstrating how the high-frequency response of asset prices to news reflects market perceptions of the anti-inflation stance of a...

  4. Diffuse Large B Cell Lymphoma Cell Line U-2946: Model for MCL1 Inhibitor Testing.

    Directory of Open Access Journals (Sweden)

    Hilmar Quentmeier

    Full Text Available Diffuse large B cell lymphoma (DLBCL is the most common form of non-Hodgkin lymphoma worldwide. We describe the establishment and molecular characteristics of the DLBCL cell line U-2946. This cell line was derived from a 52-year-old male with DLBCL. U-2946 cells carried the chromosomal translocation t(8;14 and strongly expressed MYC, but not the mature B-cell lymphoma associated oncogenes BCL2 and BCL6. Instead, U-2946 cells expressed the antiapoptotic BCL2 family member MCL1 which was highly amplified genomically (14n. MCL1 amplification is recurrent in DLBCL, especially in the activated B cell (ABC variant. Results of microarray expression cluster analysis placed U-2946 together with ABC-, but apart from germinal center (GC-type DLBCL cell lines. The 1q21.3 region including MCL1 was focally coamplified with a short region of 17p11.2 (also present at 14n. The MCL1 inhibitor A-1210477 triggered apoptosis in U-2946 (MCL1pos/BCL2neg cells. In contrast to BCL2pos DLBCL cell lines, U-2946 did not respond to the BCL2 inhibitor ABT-263. In conclusion, the novel characteristics of cell line U-2946 renders it a unique model system to test the function of small molecule inhibitors, especially when constructing a panel of DLBCL cell lines expressing broad combinations of antiapoptotic BCL2-family members.

  5. Interactively Evolving Compositional Sound Synthesis Networks

    DEFF Research Database (Denmark)

    Jónsson, Björn Þór; Hoover, Amy K.; Risi, Sebastian

    2015-01-01

    While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved......, CPPNs can theoretically compute any function and can build on those present in traditional synthesizers (e.g. square, sawtooth, triangle, and sine waves functions) to produce completely novel timbres. Evolved with NeuroEvolution of Augmenting Topologies (NEAT), the aim of this paper is to explore...... the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first...

  6. Quantifying evolvability in small biological networks

    Energy Technology Data Exchange (ETDEWEB)

    Nemenman, Ilya [Los Alamos National Laboratory; Mugler, Andrew [COLUMBIA UNIV; Ziv, Etay [COLUMBIA UNIV; Wiggins, Chris H [COLUMBIA UNIV

    2008-01-01

    The authors introduce a quantitative measure of the capacity of a small biological network to evolve. The measure is applied to a stochastic description of the experimental setup of Guet et al. (Science 2002, 296, pp. 1466), treating chemical inducers as functional inputs to biochemical networks and the expression of a reporter gene as the functional output. The authors take an information-theoretic approach, allowing the system to set parameters that optimise signal processing ability, thus enumerating each network's highest-fidelity functions. All networks studied are highly evolvable by the measure, meaning that change in function has little dependence on change in parameters. Moreover, each network's functions are connected by paths in the parameter space along which information is not significantly lowered, meaning a network may continuously change its functionality without completely losing it along the way. This property further underscores the evolvability of the networks.

  7. Modelling and simulation of two-chamber microbial fuel cell

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Yingzhi; Wu, Ping [Institute of High Performance Computing, 1 Fusionopolis Way, 16-16 Connexis, Singapore 138632 (Singapore); Choo, Yeng Fung [Environment and Process Research Division, Korea Institute of Science and Technology, Hawolgok-dong, Sungbuk-ku, Seoul 136-791 (Korea); Kim, Byung-Hong [Environment and Process Research Division, Korea Institute of Science and Technology, Hawolgok-dong, Sungbuk-ku, Seoul 136-791 (Korea); School of Life Science and Biotechnology, Korea University, Anam-dong, Sungbuk-ku, Seoul 136-701 (Korea)

    2010-01-01

    Microbial fuel cells (MFCs) offer great promise for simultaneous treatment of wastewater and energy recovery. While past research has been based extensively on experimental studies, modelling and simulation remains scarce. A typical MFC shares many similarities with chemical fuel cells such as direct ascorbic acid fuel cells and direct methanol fuel cells. Therefore, an attempt is made to develop a MFC model similar to that for chemical fuel cells. By integrating biochemical reactions, Butler-Volmer expressions and mass/charge balances, a MFC model based on a two-chamber configuration is developed that simulates both steady and dynamic behaviour of a MFC, including voltage, power density, fuel concentration, and the influence of various parameters on power generation. Results show that the cathodic reaction is the most significant limiting factor of MFC performance. Periodic changes in the flow rate of fuel result in a boost of power output; this offers further insight into MFC behaviour. In addition to a MFC fuelled by acetate, the present method is also successfully extended to using artificial wastewater (solution of glucose and glutamic acid) as fuel. Since the proposed modelling method is easy to implement, it can serve as a framework for modelling other types of MFC and thereby will facilitate the development and scale-up of more efficient MFCs. (author)

  8. Multiway modeling and analysis in stem cell systems biology

    Directory of Open Access Journals (Sweden)

    Vandenberg Scott L

    2008-07-01

    Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

  9. Anti-CD123 chimeric antigen receptor T-cells (CART): an evolving treatment strategy for hematological malignancies, and a potential ace-in-the-hole against antigen-negative relapse.

    Science.gov (United States)

    Cummins, Katherine D; Gill, Saar

    2017-09-13

    Chimeric antigen receptor-modified T-cells (CART) are a potent and targeted immunotherapy which have induced remissions in some patients with chemotherapy refractory or relapsed (RR) hematologic malignancies. Hundreds of patients have now been treated worldwide with anti-CD19 CART cells, with complete response rates of up to 90%. CART therapy has a unique toxicity profile, and unfortunately not all responses are durable. Treatment failure occurs via two main routes - by loss of the CART cell population, or relapse with antigen loss. Emerging data indicate that targeting an alternative antigen instead of, or as well as CD19, could improve CART cell efficacy and reduce antigen-negative relapse. Other strategies include the addition of other immune-based therapies. This review explores the rationale, pre-clinical data and currently investigative strategies underway for CART therapy targeting the myeloid and lymphoid stem/progenitor antigen CD123.

  10. Proteomic assessment of a cell model of spinal muscular atrophy

    Directory of Open Access Journals (Sweden)

    Lee Kelvin H

    2011-03-01

    Full Text Available Abstract Background Deletion or mutation(s of the survival motor neuron 1 (SMN1 gene causes spinal muscular atrophy (SMA, a neuromuscular disease characterized by spinal motor neuron death and muscle paralysis. Complete loss of the SMN protein is embryonically lethal, yet reduced levels of this protein result in selective death of motor neurons. Why motor neurons are specifically targeted by SMN deficiency remains to be determined. In this study, embryonic stem (ES cells derived from a severe SMA mouse model were differentiated into motor neurons in vitro by addition of retinoic acid and sonic hedgehog agonist. Proteomic and western blot analyses were used to probe protein expression alterations in this cell-culture model of SMA that could be relevant to the disease. Results When ES cells were primed with Noggin/fibroblast growth factors (bFGF and FGF-8 in a more robust neural differentiation medium for 2 days before differentiation induction, the efficiency of in vitro motor neuron differentiation was improved from ~25% to ~50%. The differentiated ES cells expressed a pan-neuronal marker (neurofilament and motor neuron markers (Hb9, Islet-1, and ChAT. Even though SMN-deficient ES cells had marked reduced levels of SMN (~20% of that in control ES cells, the morphology and differentiation efficiency for these cells are comparable to those for control samples. However, proteomics in conjunction with western blot analyses revealed 6 down-regulated and 14 up-regulated proteins with most of them involved in energy metabolism, cell stress-response, protein degradation, and cytoskeleton stability. Some of these activated cellular pathways showed specificity for either undifferentiated or differentiated cells. Increased p21 protein expression indicated that SMA ES cells were responding to cellular stress. Up-regulation of p21 was confirmed in spinal cord tissues from the same SMA mouse model from which the ES cells were derived. Conclusion SMN

  11. Modelling cell cycle synchronisation in networks of coupled radial glial cells.

    Science.gov (United States)

    Barrack, Duncan S; Thul, Rüdiger; Owen, Markus R

    2015-07-21

    Radial glial cells play a crucial role in the embryonic mammalian brain. Their proliferation is thought to be controlled, in part, by ATP mediated calcium signals. It has been hypothesised that these signals act to locally synchronise cell cycles, so that clusters of cells proliferate together, shedding daughter cells in uniform sheets. In this paper we investigate this cell cycle synchronisation by taking an ordinary differential equation model that couples the dynamics of intracellular calcium and the cell cycle and extend it to populations of cells coupled via extracellular ATP signals. Through bifurcation analysis we show that although ATP mediated calcium release can lead to cell cycle synchronisation, a number of other asynchronous oscillatory solutions including torus solutions dominate the parameter space and cell cycle synchronisation is far from guaranteed. Despite this, numerical results indicate that the transient and not the asymptotic behaviour of the system is important in accounting for cell cycle synchronisation. In particular, quiescent cells can be entrained on to the cell cycle via ATP mediated calcium signals initiated by a driving cell and crucially will cycle in near synchrony with the driving cell for the duration of neurogenesis. This behaviour is highly sensitive to the timing of ATP release, with release at the G1/S phase transition of the cell cycle far more likely to lead to near synchrony than release during mid G1 phase. This result, which suggests that ATP release timing is critical to radial glia cell cycle synchronisation, may help us to understand normal and pathological brain development. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Gravity Effects on Information Filtering and Network Evolving

    Science.gov (United States)

    Liu, Jin-Hu; Zhang, Zi-Ke; Chen, Lingjiao; Liu, Chuang; Yang, Chengcheng; Wang, Xueqi

    2014-01-01

    In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on two real-world data sets, Del.icio.us and MovieLens, show that it can not only enhance the algorithmic performance, but can also better characterize the properties of real networks. This work may shed some light on the in-depth understanding of the effect of gravity model. PMID:24622162

  13. Evolving Intelligent Systems Methodology and Applications

    CERN Document Server

    Angelov, Plamen; Kasabov, Nik

    2010-01-01

    From theory to techniques, the first all-in-one resource for EIS. There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on th

  14. Macroscopic Modeling of Transport Phenomena in Direct Methanol Fuel Cells

    DEFF Research Database (Denmark)

    Olesen, Anders Christian

    An increasing need for energy efficiency and high energy density has sparked a growing interest in direct methanol fuel cells for portable power applications. This type of fuel cell directly generates electricity from a fuel mixture consisting of methanol and water. Although this technology...... for studying their transport. In this PhD dissertation the macroscopic transport phenomena governing direct methanol fuel cell operation are analyzed, discussed and modeled using the two-fluid approach in the computational fluid dynamics framework of CFX 14. The overall objective of this work is to extend...... the present fundamental understanding of direct methanol fuel cell operation by developing a three-dimensional, two-phase, multi-component, non-isotherm mathematical model including detailed non-ideal thermodynamics, non-equilibrium phase change and non-equilibrium sorption-desorption of methanol and water...

  15. T Cell Integrin Overexpression as a Model of Murine Autoimmunity

    Directory of Open Access Journals (Sweden)

    Yung Raymond L.

    2003-01-01

    Full Text Available Integrin adhesion molecules have important adhesion and signaling functions. They also play a central role in the pathogenesis of many autoimmune diseases. Over the past few years we have described a T cell adoptive transfer model to investigate the role of T cell integrin adhesion molecules in the development of autoimmunity. This report summarizes the methods we used in establishing this murine model. By treating murine CD4+ T cells with DNA hypomethylating agents and by transfection we were able to test the in vitro effects of integrin overexpression on T cell autoreactive proliferation, cytotoxicity, adhesion and trafficking. Furthermore, we showed that the ability to induce in vivo autoimmunity may be unique to the integrin lymphocyte function associated antigen-1 (LFA-1.

  16. Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

    CERN Document Server

    Baianu, I C

    2004-01-01

    Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

  17. Global Dynamics of a Virus Dynamical Model with Cell-to-Cell Transmission and Cure Rate

    Directory of Open Access Journals (Sweden)

    Tongqian Zhang

    2015-01-01

    Full Text Available The cure effect of a virus model with both cell-to-cell transmission and cell-to-virus transmission is studied. By the method of next generation matrix, the basic reproduction number is obtained. The locally asymptotic stability of the virus-free equilibrium and the endemic equilibrium is considered by investigating the characteristic equation of the model. The globally asymptotic stability of the virus-free equilibrium is proved by constructing suitable Lyapunov function, and the sufficient condition for the globally asymptotic stability of the endemic equilibrium is obtained by constructing suitable Lyapunov function and using LaSalle invariance principal.

  18. Engineering of Microbial Fuel Cells technology: Materials, Modelling and Architecture

    OpenAIRE

    Gerosa, Matteo

    2017-01-01

    A Microbial fuel cell (MFC) is a bio-electrochemical reactor, able to convert chemical energy, contained in organic substrate, in electrical energy, thanks to the metabolic activity of microorganisms. Firstly, a fluid-dynamic modelling of different Microbial Fuel Cell configurations to study trajectories and concentration profile of the liquid containing the organic substrate during operation of the device was developed. The study of the device was joined with the study and the synthesis of c...

  19. Modelling of Dual-Junction Solar Cells including Tunnel Junction

    Directory of Open Access Journals (Sweden)

    Abdelaziz Amine

    2013-01-01

    Full Text Available Monolithically stacked multijunction solar cells based on III–V semiconductors materials are the state-of-art of approach for high efficiency photovoltaic energy conversion, in particular for space applications. The individual subcells of the multi-junction structure are interconnected via tunnel diodes which must be optically transparent and connect the component cells with a minimum electrical resistance. The quality of these diodes determines the output performance of the solar cell. The purpose of this work is to contribute to the investigation of the tunnel electrical resistance of such a multi-junction cell through the analysis of the current-voltage (J-V characteristics under illumination. Our approach is based on an equivalent circuit model of a diode for each subcell. We examine the effect of tunnel resistance on the performance of a multi-junction cell using minimization of the least squares technique.

  20. Human pluripotent stem cells: an emerging model in developmental biology.

    Science.gov (United States)

    Zhu, Zengrong; Huangfu, Danwei

    2013-02-01

    Developmental biology has long benefited from studies of classic model organisms. Recently, human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, have emerged as a new model system that offers unique advantages for developmental studies. Here, we discuss how studies of hPSCs can complement classic approaches using model organisms, and how hPSCs can be used to recapitulate aspects of human embryonic development 'in a dish'. We also summarize some of the recently developed genetic tools that greatly facilitate the interrogation of gene function during hPSC differentiation. With the development of high-throughput screening technologies, hPSCs have the potential to revolutionize gene discovery in mammalian development.

  1. New paradigms for metabolic modeling of human cells

    DEFF Research Database (Denmark)

    Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally......Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we......, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented....

  2. Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models.

    Science.gov (United States)

    Barberis, Matteo; Todd, Robert G; van der Zee, Lucas

    2017-01-01

    The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network. © FEMS 2016.

  3. Cancer Stem Cells of Differentiated B-Cell Malignancies: Models and Consequences

    Directory of Open Access Journals (Sweden)

    Jean-Jacques Fournie

    2011-03-01

    Full Text Available The concept of cancer stem cells has revolutionized our current vision of cancer development and was validated in solid tumors and cancers of the primitive hematopoietic compartment. Proof of the principle is still lacking, however, in malignancies of differentiated B-cells. We review here the current literature, which nevertheless suggests hierarchical organizations of the tumor clone for mostly incurable B-cell cancers such as multiple myeloma, lymphomas and B-chronic lymphocytic leukemia. We propose two models accounting for cancer stem cells in these contexts: a “top-to-bottom” clonal hierarchy from memory B-cells and a “bottom-to-top” model of clonal reprogramming. Selection pressure on the growing tumor can drive such reprogramming and increase its genetic diversity.

  4. Modeling and Analysis of Aluminum/Air Fuel Cell

    Science.gov (United States)

    Leon, Armando J.

    The technical and scientific challenges to provide reliable sources energy for US and global economy are enormous tasks, and especially so when combined with strategic and recent economic concerns of the last five years. It is clear that as part of the mix of energy sources necessary to deal with these challenges, fuel cells technology will play critical or even a central role. The US Department of Energy, as well as a number of the national laboratories and academic institutions have been aware of the importance such technology for some time. Recently, car manufacturers, transportation experts, and even utilities are paying attention to this vital source of energy for the future. In this thesis, a review of the main fuel cell technologies is presented with the focus on the modeling, and control of one particular and promising fuel cell technology, aluminum air fuel cells. The basic principles of this fuel cell technology are presented. A major part of the study consists of a description of the electrochemistry of the process, modeling, and simulations of aluminum air FC using Matlab Simulink(TM). The controller design of the proposed model is also presented. In sequel, a power management unit is designed and analyzed as an alternative source of power. Thus, the system commutes between the fuel cell output and the alternative power source in order to fulfill a changing power load demand. Finally, a cost analysis and assessment of this technology for portable devices, conclusions and future recommendations are presented.

  5. Optimization methods and silicon solar cell numerical models

    Science.gov (United States)

    Girardini, K.; Jacobsen, S. E.

    1986-01-01

    An optimization algorithm for use with numerical silicon solar cell models was developed. By coupling an optimization algorithm with a solar cell model, it is possible to simultaneously vary design variables such as impurity concentrations, front junction depth, back junction depth, and cell thickness to maximize the predicted cell efficiency. An optimization algorithm was developed and interfaced with the Solar Cell Analysis Program in 1 Dimension (SCAP1D). SCAP1D uses finite difference methods to solve the differential equations which, along with several relations from the physics of semiconductors, describe mathematically the performance of a solar cell. A major obstacle is that the numerical methods used in SCAP1D require a significant amount of computer time, and during an optimization the model is called iteratively until the design variables converge to the values associated with the maximum efficiency. This problem was alleviated by designing an optimization code specifically for use with numerically intensive simulations, to reduce the number of times the efficiency has to be calculated to achieve convergence to the optimal solution.

  6. Preface: evolving rotifers, evolving science: Proceedings of the XIV International Rotifer Symposium

    Czech Academy of Sciences Publication Activity Database

    Devetter, Miloslav; Fontaneto, D.; Jersabek, Ch.D.; Welch, D.B.M.; May, L.; Walsh, E.J.

    2017-01-01

    Roč. 796, č. 1 (2017), s. 1-6 ISSN 0018-8158 Institutional support: RVO:60077344 Keywords : evolving rotifers * 14th International Rotifer Symposium * evolving science Subject RIV: EG - Zoology OBOR OECD: Zoology Impact factor: 2.056, year: 2016

  7. Modeling and Simulation of the Direct Methanol Fuel Cell

    Science.gov (United States)

    Wohr, M.; Narayanan, S. R.; Halpert, G.

    1996-01-01

    From intro.: The direct methanol liquid feed fuel cell uses aqueous solutions of methanol as fuel and oxygen or air as the oxidant and uses an ionically conducting polymer membrane such as Nafion(sup r)117 and the electrolyte. This type of direct oxidation cell is fuel versatile and offers significant advantages in terms of simplicity of design and operation...The present study focuses on the results of a phenomenological model based on current understanding of the various processed operating in these cells.

  8. Modelling IRF8 Deficient Human Hematopoiesis and Dendritic Cell Development with Engineered iPS Cells.

    Science.gov (United States)

    Sontag, Stephanie; Förster, Malrun; Qin, Jie; Wanek, Paul; Mitzka, Saskia; Schüler, Herdit M; Koschmieder, Steffen; Rose-John, Stefan; Seré, Kristin; Zenke, Martin

    2017-04-01

    Human induced pluripotent stem (iPS) cells can differentiate into cells of all three germ layers, including hematopoietic stem cells and their progeny. Interferon regulatory factor 8 (IRF8) is a transcription factor, which acts in hematopoiesis as lineage determining factor for myeloid cells, including dendritic cells (DC). Autosomal recessive or dominant IRF8 mutations occurring in patients cause severe monocytic and DC immunodeficiency. To study IRF8 in human hematopoiesis we generated human IRF8-/- iPS cells and IRF8-/- embryonic stem (ES) cells using RNA guided CRISPR/Cas9n genome editing. Upon induction of hematopoietic differentiation, we demonstrate that IRF8 is dispensable for iPS cell and ES cell differentiation into hemogenic endothelium and for endothelial-to-hematopoietic transition, and thus development of hematopoietic progenitors. We differentiated iPS cell and ES cell derived progenitors into CD141+ cross-presenting cDC1 and CD1c+ classical cDC2 and CD303+ plasmacytoid DC (pDC). We found that IRF8 deficiency compromised cDC1 and pDC development, while cDC2 development was largely unaffected. Additionally, in an unrestricted differentiation regimen, IRF8-/- iPS cells and ES cells exhibited a clear bias toward granulocytes at the expense of monocytes. IRF8-/- DC showed reduced MHC class II expression and were impaired in cytokine responses, migration, and antigen presentation. Taken together, we engineered a human IRF8 knockout model that allows studying molecular mechanisms of human immunodeficiencies in vitro, including the pathophysiology of IRF8 deficient DC. Stem Cells 2017;35:898-908. © 2017 The Authors Stem Cells published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

  9. A stochastic model of epigenetic dynamics in somatic cell reprogramming

    Directory of Open Access Journals (Sweden)

    Max eFloettmann

    2012-06-01

    Full Text Available Somatic cell reprogramming has dramatically changed stem cell research inrecent years. The high pace of new findings in the field and an ever increasingamount of data from new high throughput techniques make it challengingto isolate core principles of the process. In order to analyze suchmechanisms, we developed an abstract mechanistic model of a subset of theknown regulatory processes during cell differentiation and production of inducedpluripotent stem cells. This probabilistic Boolean network describesthe interplay between gene expression, chromatin modifications and DNAmethylation. The model incorporates recent findings in epigenetics and reproducesexperimentally observed reprogramming efficiencies and changes inmethylation and chromatin remodeling. It enables us to investigate in detail,how the temporal progression of the process is regulated. It also explicitlyincludes the transduction of factors using viral vectors and their silencing inreprogrammed cells, since this is still a standard procedure in somatic cellreprogramming. Based on the model we calculate an epigenetic landscape.Simulation results show good reproduction of experimental observations duringreprogramming, despite the simple stucture of the model. An extensiveanalysis and introduced variations hint towards possible optimizations of theprocess, that could push the technique closer to clinical applications. Fasterchanges in DNA methylation increase the speed of reprogramming at theexpense of efficiency, while accelerated chromatin modifications moderatelyimprove efficiency.

  10. Auxin induces cell proliferation in an experimental model of mammalian renal tubular epithelial cells.

    Science.gov (United States)

    Cernaro, Valeria; Medici, Maria Antonietta; Leonello, Giuseppa; Buemi, Antoine; Kohnke, Franz Heinrich; Villari, Antonino; Santoro, Domenico; Buemi, Michele

    2015-06-01

    Indole-3-acetic acid is the main auxin produced by plants and plays a key role in the plant growth and development. This hormone is also present in humans where it is considered as a uremic toxin deriving from tryptophan metabolism. However, beyond this peculiar aspect, the involvement of auxin in human pathophysiology has not been further investigated. Since it is a growth hormone, we evaluated its proliferative properties in an in vitro model of mammalian renal tubular epithelial cells. We employed an experimental model of renal tubular epithelial cells belonging to the LLC-PK1 cell line that is derived from the kidney of healthy male pig. Growth effects of auxin against LLC-PK1 cell lines were determined by a rapid colorimetric assay. Increasing concentrations of auxin (to give a final concentration from 1 to 1000 ng/mL) were added and microplates were incubated for 72 h. Each auxin concentration was assayed in four wells and repeated four times. Cell proliferation significantly increased, compared to control cells, 72 h after addition of auxin to cultured LLC-PK1 cells. Statistically significant values were observed when 100 ng/mL (p auxin influences cell growth not only in plants, where its role is well documented, but also in mammalian cell lines. This observation opens new scenarios in the field of tissue regeneration and may stimulate a novel line of research aiming at investigating whether this hormone really influences human physiology and pathophysiology and in particular, kidney regeneration.

  11. Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background.

    Directory of Open Access Journals (Sweden)

    Julien Vibert

    2017-03-01

    Full Text Available Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific "signature" that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2'-deoxyuridine (EdU data, revealing T cell proliferation heterogeneity and specific signatures.

  12. Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background.

    Science.gov (United States)

    Vibert, Julien; Thomas-Vaslin, Véronique

    2017-03-01

    Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs) the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific "signature" that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2'-deoxyuridine (EdU) data, revealing T cell proliferation heterogeneity and specific signatures.

  13. Building Single-Cell Models of Planktonic Metabolism Using PSAMM

    Science.gov (United States)

    Dufault-Thompson, K.; Zhang, Y.; Steffensen, J. L.

    2016-02-01

    The Genome-scale models (GEMs) of metabolic networks simulate the metabolic activities of individual cells by integrating omics data with biochemical and physiological measurements. GEMs were applied in the simulation of various photo-, chemo-, and heterotrophic organisms and provide significant insights into the function and evolution of planktonic cells. Despite the quick accumulation of GEMs, challenges remain in assembling the individual cell-based models into community-level models. Among various problems, the lack of consistencies in model representation and model quality checking has hindered the integration of individual GEMs and can lead to erroneous conclusions in the development of new modeling algorithms. Here, we present a Portable System for the Analysis of Metabolic Models (PSAMM). Along with the software a novel format of model representation was developed to enhance the readability of model files and permit the inclusion of heterogeneous, model-specific annotation information. A number of quality checking procedures was also implemented in PSAMM to ensure stoichiometric balance and to identify unused reactions. Using a case study of Shewanella piezotolerans WP3, we demonstrated the application of PSAMM in simulating the coupling of carbon utilization and energy production pathways under low-temperature and high-pressure stress. Applying PSAMM, we have also analyzed over 50 GEMs in the current literature and released an updated collection of the models with corrections on a number of common inconsistencies. Overall, PSAMM opens up new opportunities for integrating individual GEMs for the construction and mathematical simulation of community-level models in the scope of entire ecosystems.

  14. Stochastic modeling of oligodendrocyte generation in cell culture: model validation with time-lapse data

    Directory of Open Access Journals (Sweden)

    Noble Mark

    2006-05-01

    Full Text Available Abstract Background The purpose of this paper is two-fold. The first objective is to validate the assumptions behind a stochastic model developed earlier by these authors to describe oligodendrocyte generation in cell culture. The second is to generate time-lapse data that may help biomathematicians to build stochastic models of cell proliferation and differentiation under other experimental scenarios. Results Using time-lapse video recording it is possible to follow the individual evolutions of different cells within each clone. This experimental technique is very laborious and cannot replace model-based quantitative inference from clonal data. However, it is unrivalled in validating the structure of a stochastic model intended to describe cell proliferation and differentiation at the clonal level. In this paper, such data are reported and analyzed for oligodendrocyte precursor cells cultured in vitro. Conclusion The results strongly support the validity of the most basic assumptions underpinning the previously proposed model of oligodendrocyte development in cell culture. However, there are some discrepancies; the most important is that the contribution of progenitor cell death to cell kinetics in this experimental system has been underestimated.

  15. Establishment of the mesodermal cell line QCE-6. A model system for cardiac cell differentiation.

    Science.gov (United States)

    Eisenberg, C A; Bader, D M

    1996-02-01

    lineages. More important, since the QCE-6 cells are representative of early cardiogenic cells, this cell line offers a unique model system to study cardiac cell differentiation.

  16. A simple model system enabling human CD34(+ cells to undertake differentiation towards T cells.

    Directory of Open Access Journals (Sweden)

    Antonio Lapenna

    Full Text Available BACKGROUND: Channelling the development of haematopoietic progenitor cells into T lymphocytes is dependent upon a series of extrinsic prompts whose temporal and spatial sequence is critical for a productive outcome. Simple models of human progenitor cells development depend in the main on the use of xenogeneic systems which may provide some limitations to development. METHODS AND FINDINGS: Here we provide evidence that a simple model system which utilises both human keratinocyte and fibroblast cell lines arrayed on a synthetic tantalum coated matrix provides a permissive environment for the development of human CD34⁺ haematopoietic cells into mature CD4⁺ or CD8⁺ T lymphocytes in the presence of Interleukin 7 (IL-7, Interleukin 15 (IL-15 and the Fms-like tyrosine kinase 3 ligand (Flt-3L. This system was used to compare the ability of CD34(+ cells to produce mature thymocytes and showed that whilst these cells derived from cord blood were able to productively differentiate into thymocytes the system was not permissive for the development of CD34(+ cells from adult peripheral blood. CONCLUSIONS/SIGNIFICANCE: Our study provides direct evidence for the capacity of human cord blood CD34(+ cells to differentiate along the T lineage in a simple human model system. Productive commitment of the CD34⁺ cells to generate T cells was found to be dependent on a three-dimensional matrix which induced the up-regulation of the Notch delta-like ligand 4 (Dll-4 by epithelial cells.

  17. Thermal and Evolved-Gas Analyzer Illustration

    Science.gov (United States)

    2008-01-01

    This is a computer-aided drawing of the Thermal and Evolved-Gas Analyzer, or TEGA, on NASA's Phoenix Mars Lander. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  18. Apollo 16 Evolved Lithology Sodic Ferrogabbro

    Science.gov (United States)

    Zeigler, Ryan; Jolliff, B. L.; Korotev, R. L.

    2014-01-01

    Evolved lunar igneous lithologies, often referred to as the alkali suite, are a minor but important component of the lunar crust. These evolved samples are incompatible-element rich samples, and are, not surprisingly, most common in the Apollo sites in (or near) the incompatible-element rich region of the Moon known as the Procellarum KREEP Terrane (PKT). The most commonly occurring lithologies are granites (A12, A14, A15, A17), monzogabbro (A14, A15), alkali anorthosites (A12, A14), and KREEP basalts (A15, A17). The Feldspathic Highlands Terrane is not entirely devoid of evolved lithologies, and rare clasts of alkali gabbronorite and sodic ferrogabbro (SFG) have been identified in Apollo 16 station 11 breccias 67915 and 67016. Curiously, nearly all pristine evolved lithologies have been found as small clasts or soil particles, exceptions being KREEP basalts 15382/6 and granitic sample 12013 (which is itself a breccia). Here we reexamine the petrography and geochemistry of two SFG-like particles found in a survey of Apollo 16 2-4 mm particles from the Cayley Plains 62283,7-15 and 62243,10-3 (hereafter 7-15 and 10-3 respectively). We will compare these to previously reported SFG samples, including recent analyses on the type specimen of SFG from lunar breccia 67915.

  19. A possible temperature measurement model for fuel cell

    Science.gov (United States)

    Yu, Qiaoling; Zhang, Pu; Mao, Wenping; Liu, Wenzhong

    2017-11-01

    In this paper, an improved temperature measuring model for fuel cell temperature measurement is proposed based on the existed nanothermometer model, which is regarded as traditional temperature measuring model. With more realistic cases taken into consideration, the results of the improved model are more practical and accurate compared with the traditional one. Limited by the existed experimental conditions, this paper emphases on simulating the different conditions of the temperature distribution inside SOFC. As a result, the experiments are carried out with similar temperature distribution but under relatively lower temperatures, which can come to similar conclusions as by simulation.

  20. Queueing models of potentially lethal damage repair in irradiated cells.

    Science.gov (United States)

    Myasnikova, E M; Rachev, S T; Yakovlev, A Y

    1996-07-01

    Some of the ideas arising in queueing theory are applied to describe the repair mechanisms responsible for recovery of cells from potentially lethal radiation damage. Two alternative versions are presented of a queueing model of damage repair after a single dose of irradiation. The first version represents a linear misrepair model, and the second invokes the idea of spontaneous lesion fixation. They are pieced together in the third model, allowing for both mechanisms. The consistency of the proposed models with published experimental data is tested.

  1. Modelling real solar cell using PSCAD/MATLAB

    Energy Technology Data Exchange (ETDEWEB)

    Ramos, Sergio; Silva, Marco; Fernandes, Filipe; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

    2012-07-01

    This paper presents the development of a solar photovoltaic (PV) model based on PSCAD/EMTDC - Power System Computer Aided Design - including a mathematical model study. An additional algorithm has been implemented in MATLAB software in order to calculate several parameters required by the PSCAD developed model. All the simulation study has been performed in PSCAD/MATLAB software simulation tool. A real data base concerning irradiance, cell temperature and PV power generation was used in order to support the evaluation of the implemented PV model. (orig.)

  2. Modeling bacterial population growth from stochastic single-cell dynamics.

    Science.gov (United States)

    Alonso, Antonio A; Molina, Ignacio; Theodoropoulos, Constantinos

    2014-09-01

    A few bacterial cells may be sufficient to produce a food-borne illness outbreak, provided that they are capable of adapting and proliferating on a food matrix. This is why any quantitative health risk assessment policy must incorporate methods to accurately predict the growth of bacterial populations from a small number of pathogens. In this aim, mathematical models have become a powerful tool. Unfortunately, at low cell concentrations, standard deterministic models fail to predict the fate of the population, essentially because the heterogeneity between individuals becomes relevant. In this work, a stochastic differential equation (SDE) model is proposed to describe variability within single-cell growth and division and to simulate population growth from a given initial number of individuals. We provide evidence of the model ability to explain the observed distributions of times to division, including the lag time produced by the adaptation to the environment, by comparing model predictions with experiments from the literature for Escherichia coli, Listeria innocua, and Salmonella enterica. The model is shown to accurately predict experimental growth population dynamics for both small and large microbial populations. The use of stochastic models for the estimation of parameters to successfully fit experimental data is a particularly challenging problem. For instance, if Monte Carlo methods are employed to model the required distributions of times to division, the parameter estimation problem can become numerically intractable. We overcame this limitation by converting the stochastic description to a partial differential equation (backward Kolmogorov) instead, which relates to the distribution of division times. Contrary to previous stochastic formulations based on random parameters, the present model is capable of explaining the variability observed in populations that result from the growth of a small number of initial cells as well as the lack of it compared to

  3. A Delayed Virus Infection Model with Cell-to-Cell Transmission and CTL Immune Response

    Science.gov (United States)

    Yang, Yu; Zhang, Tonghua; Xu, Yancong; Zhou, Jinling

    In this paper, a delayed virus infection model with cell-to-cell transmission and CTL immune response is investigated. In the model, time delay is incorporated into the CTL response. By constructing Lyapunov functionals, global dynamical properties of the two boundary equilibria are established. Our results show that time delay in the CTL response process may lead to sustained oscillation. To further investigate the nature of the oscillation, we apply the method of multiple time scales to calculate the normal form on the center manifold of the model. At the end of the paper, numerical simulations are carried out, which support our theoretical results.

  4. Dynamics of a stochastic cell-to-cell HIV-1 model with distributed delay

    Science.gov (United States)

    Ji, Chunyan; Liu, Qun; Jiang, Daqing

    2018-02-01

    In this paper, we consider a stochastic cell-to-cell HIV-1 model with distributed delay. Firstly, we show that there is a global positive solution of this model before exploring its long-time behavior. Then sufficient conditions for extinction of the disease are established. Moreover, we obtain sufficient conditions for the existence of an ergodic stationary distribution of the model by constructing a suitable stochastic Lyapunov function. The stationary distribution implies that the disease is persistent in the mean. Finally, we provide some numerical examples to illustrate theoretical results.

  5. Mechanistic modeling confronts the complexity of molecular cell biology.

    Science.gov (United States)

    Phair, Robert D

    2014-11-05

    Mechanistic modeling has the potential to transform how cell biologists contend with the inescapable complexity of modern biology. I am a physiologist-electrical engineer-systems biologist who has been working at the level of cell biology for the past 24 years. This perspective aims 1) to convey why we build models, 2) to enumerate the major approaches to modeling and their philosophical differences, 3) to address some recurrent concerns raised by experimentalists, and then 4) to imagine a future in which teams of experimentalists and modelers build-and subject to exhaustive experimental tests-models covering the entire spectrum from molecular cell biology to human pathophysiology. There is, in my view, no technical obstacle to this future, but it will require some plasticity in the biological research mind-set. © 2014 Phair. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. A stochastic transcriptional switch model for single cell imaging data.

    Science.gov (United States)

    Hey, Kirsty L; Momiji, Hiroshi; Featherstone, Karen; Davis, Julian R E; White, Michael R H; Rand, David A; Finkenstädt, Bärbel

    2015-10-01

    Gene expression is made up of inherently stochastic processes within single cells and can be modeled through stochastic reaction networks (SRNs). In particular, SRNs capture the features of intrinsic variability arising from intracellular biochemical processes. We extend current models for gene expression to allow the transcriptional process within an SRN to follow a random step or switch function which may be estimated using reversible jump Markov chain Monte Carlo (MCMC). This stochastic switch model provides a generic framework to capture many different dynamic features observed in single cell gene expression. Inference for such SRNs is challenging due to the intractability of the transition densities. We derive a model-specific birth-death approximation and study its use for inference in comparison with the linear noise approximation where both approximations are considered within the unifying framework of state-space models. The methodology is applied to synthetic as well as experimental single cell imaging data measuring expression of the human prolactin gene in pituitary cells. © The Author 2015. Published by Oxford University Press.

  7. New Modeling Approaches to Investigate Cell Signaling in Radiation Response

    Science.gov (United States)

    Plante, Ianik; Cucinotta, Francis A.; Ponomarev, Artem L.

    2011-01-01

    Ionizing radiation damages individual cells and tissues leading to harmful biological effects. Among many radiation-induced lesions, DNA double-strand breaks (DSB) are considered the key precursors of most early and late effects [1] leading to direct mutation or aberrant signal transduction processes. In response to damage, a flow of information is communicated to cells not directly hit by the radiation through signal transduction pathways [2]. Non-targeted effects (NTE), which includes bystander effects and genomic instability in the progeny of irradiated cells and tissues, may be particularly important for space radiation risk assessment [1], because astronauts are exposed to a low fluence of heavy ions and only a small fraction of cells are traversed by an ion. NTE may also have important consequences clinical radiotherapy [3]. In the recent years, new simulation tools and modeling approaches have become available to study the tissue response to radiation. The simulation of signal transduction pathways require many elements such as detailed track structure calculations, a tissue or cell culture model, knowledge of biochemical pathways and Brownian Dynamics (BD) propagators of the signaling molecules in their micro-environment. Recently, the Monte-Carlo simulation code of radiation track structure RITRACKS was used for micro and nano-dosimetry calculations [4]. RITRACKS will be used to calculate the fraction of cells traversed by an ion and delta-rays and the energy deposited in cells in a tissue model. RITRACKS also simulates the formation of chemical species by the radiolysis of water [5], notably the .OH radical. This molecule is implicated in DNA damage and in the activation of the transforming growth factor beta (TGF), a signaling molecule involved in NTE. BD algorithms for a particle near a membrane comprising receptors were also developed and will be used to simulate trajectories of signaling molecules in the micro-environment and characterize autocrine

  8. Artificial cell mimics as simplified models for the study of cell biology.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

    2017-07-01

    Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

  9. Fuzzily Connected Multimodel Systems Evolving Autonomously From Data Streams.

    Science.gov (United States)

    Angelov, P

    2011-08-01

    A general framework and a holistic concept are proposed in this paper that combine computationally light machine learning from streaming data with the online identification and adaptation of dynamic systems in regard to their structure and parameters. According to this concept, the system is assumed to be decomposable into a set of fuzzily connected simple local models. The main thrust of this paper is in the development of an original approach for the self-design, self-monitoring, self-management, and self-learning of such systems in a dynamic manner from data streams which automatically detect and react to the shift in the data distribution by evolving the system structure. Novelties of this contribution lie in the following: 1) the computationally simple approach (simpl_e_Clustering-simplified evolving Clustering) to data space partitioning by recursive evolving clustering based on the relative position of the new data sample to the mean of the overall data, 2) the learning technique for online structure evolution as a reaction to the shift in the data distribution, 3) the method for online system structure simplification based on utility and inputs/feature selection, and 4) the novel graphical illustration of the spatiotemporal evolution of the data stream. The application domain for this computationally efficient technique ranges from clustering, modeling, prognostics, classification, and time-series prediction to pattern recognition, image segmentation, vector quantization, etc., to more general problems in various application areas, e.g., intelligent sensors, mobile robotics, advanced manufacturing processes, etc.

  10. The Pyrolysis Behavior of Evolved Species from Date Palm Seeds

    Directory of Open Access Journals (Sweden)

    Babiker Mohammed Elamen

    2014-07-01

    Full Text Available The pyrolytic behavior of evolved gases from date palm seeds (DPSs were measured to gain insight into the mechanism of DPSs pyrolysis. Six different cultivars were used in this study, namely Deglet nour, Piarom, Suffry, Safawi, Mabroom and Aliya. A thermo-gravimetric analyzer (TGA and a real-time gas analyzer (GA were used to calculate the mass losses and the mole fraction of evolved gases, respectively. DPSs samples were pyrolyzed in an inert atmosphere condition using argon with a purge rate of 100 mL/minute. The samples were subjected to non-isothermal operation. An independent single model and parallel reaction model were adopted to interpret the empirical data collected from TGA and GA, respectively. The results reveled that there are three types of pyrolysis zones depending on the main constituents of every cultivars. Moreover, the potentialty of the zones in controlling the pyrolysis behavior was noticeable. The dominant hydrocarbon species in DPSs were CO and CH4 (40 to 50% higher than the rest of species. The mole fraction of CO was 2 to 4 times higher than the mole fraction of CO2. The activation energy and frequency factor of DPSs evolved species showed that Mabroom has the highest activation energy regarding H2 (63.21kJ/mol and CO (74.32 kJ/mol.

  11. The 40-year history of modeling active dendrites in cerebellar Purkinje cells: Emergence of the first single cell 'Community Model'

    Directory of Open Access Journals (Sweden)

    James M Bower

    2015-10-01

    Full Text Available The subject of the effects of the active properties of the Purkinje cell dendrite on neuronal function has been an active subject of study for more than 40 years. Somewhat unusually, some of these investigations, from the outset have involved an interacting combination of experimental and model-based techniques. This paper recounts that 40-year history, and the view of the functional significance of the active properties of the Purkinje cell dendrite that has emerged. It specifically considers the emergence from these efforts of what is arguably the first single cell ‘community’ model in neuroscience. The paper also considers the implications of the development of this model for future studies of the complex properties of neuronal dendrites.

  12. Induced pluripotent stem cell models of lysosomal storage disorders

    Science.gov (United States)

    Borger, Daniel K.; McMahon, Benjamin; Roshan Lal, Tamanna; Serra-Vinardell, Jenny; Aflaki, Elma

    2017-01-01

    ABSTRACT Induced pluripotent stem cells (iPSCs) have provided new opportunities to explore the cell biology and pathophysiology of human diseases, and the lysosomal storage disorder research community has been quick to adopt this technology. Patient-derived iPSC models have been generated for a number of lysosomal storage disorders, including Gaucher disease, Pompe disease, Fabry disease, metachromatic leukodystrophy, the neuronal ceroid lipofuscinoses, Niemann-Pick types A and C1, and several of the mucopolysaccharidoses. Here, we review the strategies employed for reprogramming and differentiation, as well as insights into disease etiology gleaned from the currently available models. Examples are provided to illustrate how iPSC-derived models can be employed to develop new therapeutic strategies for these disorders. We also discuss how models of these rare diseases could contribute to an enhanced understanding of more common neurodegenerative disorders such as Parkinson’s disease, and discuss key challenges and opportunities in this area of research. PMID:28592657

  13. Automated Physico-Chemical Cell Model Development through Information Theory

    Energy Technology Data Exchange (ETDEWEB)

    Peter J. Ortoleva

    2005-11-29

    The objective of this project was to develop predictive models of the chemical responses of microbial cells to variations in their surroundings. The application of these models is optimization of environmental remediation and energy-producing biotechnical processes.The principles on which our project is based are as follows: chemical thermodynamics and kinetics; automation of calibration through information theory; integration of multiplex data (e.g. cDNA microarrays, NMR, proteomics), cell modeling, and bifurcation theory to overcome cellular complexity; and the use of multiplex data and information theory to calibrate and run an incomplete model. In this report we review four papers summarizing key findings and a web-enabled, multiple module workflow we have implemented that consists of a set of interoperable systems biology computational modules.

  14. Induced pluripotent stem cell models of lysosomal storage disorders

    Directory of Open Access Journals (Sweden)

    Daniel K. Borger

    2017-06-01

    Full Text Available Induced pluripotent stem cells (iPSCs have provided new opportunities to explore the cell biology and pathophysiology of human diseases, and the lysosomal storage disorder research community has been quick to adopt this technology. Patient-derived iPSC models have been generated for a number of lysosomal storage disorders, including Gaucher disease, Pompe disease, Fabry disease, metachromatic leukodystrophy, the neuronal ceroid lipofuscinoses, Niemann-Pick types A and C1, and several of the mucopolysaccharidoses. Here, we review the strategies employed for reprogramming and differentiation, as well as insights into disease etiology gleaned from the currently available models. Examples are provided to illustrate how iPSC-derived models can be employed to develop new therapeutic strategies for these disorders. We also discuss how models of these rare diseases could contribute to an enhanced understanding of more common neurodegenerative disorders such as Parkinson’s disease, and discuss key challenges and opportunities in this area of research.

  15. A semi-stochastic cell-based formalism to model the dynamics of migration of cells in colonies

    NARCIS (Netherlands)

    Vermolen, F.J.; Gefen, A.

    2011-01-01

    We consider the movement and viability of individual cells in cell colonies. Cell movement is assumed to take place as a result of sensing the strain energy density as a mechanical stimulus. The model is based on tracking the displacement and viability of each individual cell in a cell colony.

  16. Method for generating realistic 3-dimensional models of neuronal cells

    OpenAIRE

    Mata Fernández, Susana; Brito Menéndez, Juan Pedro; Bayona Beriso, Sofía; Pastor Pérez, Luis; Benavides-Piccione, Ruth; Felipe, Javier de

    2014-01-01

    [EN] The present invention relates to a method for the generation of 3-dimensional models of neuronal cells based on incomplete morphological information extracted by means of standard sampling methods. The models generated include a realistic soma, dendritic and axonal trees and dendritic spines, which may be generated at different resolution levels. The invention proposes an innovative technique that makes it possible to obtain a realistic soma form based on a simple definition thereof (suc...

  17. A hybrid model of mammalian cell cycle regulation.

    Directory of Open Access Journals (Sweden)

    Rajat Singhania

    2011-02-01

    Full Text Available The timing of DNA synthesis, mitosis and cell division is regulated by a complex network of biochemical reactions that control the activities of a family of cyclin-dependent kinases. The temporal dynamics of this reaction network is typically modeled by nonlinear differential equations describing the rates of the component reactions. This approach provides exquisite details about molecular regulatory processes but is hampered by the need to estimate realistic values for the many kinetic constants that determine the reaction rates. It is difficult to estimate these kinetic constants from available experimental data. To avoid this problem, modelers often resort to 'qualitative' modeling strategies, such as Boolean switching networks, but these models describe only the coarsest features of cell cycle regulation. In this paper we describe a hybrid approach that combines the best features of continuous differential equations and discrete Boolean networks. Cyclin abundances are tracked by piecewise linear differential equations for cyclin synthesis and degradation. Cyclin synthesis is regulated by transcription factors whose activities are represented by discrete variables (0 or 1 and likewise for the activities of the ubiquitin-ligating enzyme complexes that govern cyclin degradation. The discrete variables change according to a predetermined sequence, with the times between transitions determined in part by cyclin accumulation and degradation and as well by exponentially distributed random variables. The model is evaluated in terms of flow cytometry measurements of cyclin proteins in asynchronous populations of human cell lines. The few kinetic constants in the model are easily estimated from the experimental data. Using this hybrid approach, modelers can quickly create quantitatively accurate, computational models of protein regulatory networks in cells.

  18. Modeling of hemophilia A using patient-specific induced pluripotent stem cells derived from urine cells.

    Science.gov (United States)

    Jia, Bei; Chen, Shen; Zhao, Zhiju; Liu, Pengfei; Cai, Jinglei; Qin, Dajiang; Du, Juan; Wu, Changwei; Chen, Qianyu; Cai, Xiujuan; Zhang, Hui; Yu, Yanhong; Pei, Duanqing; Zhong, Mei; Pan, Guangjin

    2014-07-11

    Hemophilia A (HA) is a severe, congenital bleeding disorder caused by the deficiency of clotting factor VIII (FVIII). For years, traditional laboratory animals have been used to study HA and its therapies, although animal models may not entirely mirror the human pathophysiology. Human induced pluripotent stem cells (iPSCs) can undergo unlimited self-renewal and differentiate into all cell types. This study aims to generate hemophilia A (HA) patient-specific iPSCs that differentiate into disease-affected hepatocyte cells. These hepatocytes are potentially useful for in vitro disease modeling and provide an applicable cell source for autologous cell therapy after genetic correction. In this study, we mainly generated iPSCs from urine collected from HA patients with integration-free episomal vectors PEP4-EO2S-ET2K containing human genes OCT4, SOX2, SV40LT and KLF4, and differentiated these iPSCs into hepatocyte-like cells. We further identified the genetic phenotype of the FVIII genes and the FVIII activity in the patient-specific iPSC derived hepatic cells. HA patient-specific iPSCs (HA-iPSCs) exhibited typical pluripotent properties evident by immunostaining, in vitro assays and in vivo assays. Importantly, we showed that HA-iPSCs could differentiate into functional hepatocyte-like cells and the HA-iPSC-derived hepatocytes failed to produce FVIII, but otherwise functioned normally, recapitulating the phenotype of HA disease in vitro. HA-iPSCs, particular those generated from the urine using a non-viral approach, provide an efficient way for modeling HA in vitro. Furthermore, HA-iPSCs and their derivatives serve as an invaluable cell source that can be used for gene and cell therapy in regenerative medicine. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Regenerative technologies to bed side: Evolving the regulatory framework

    Directory of Open Access Journals (Sweden)

    Daisuke Sakai

    2017-04-01

    Full Text Available There are high expectations for the clinical application of regenerative medicine technologies to treat musculoskeletal disorders. However, there are still big hurdles in bringing cell-based products to the market, mainly due to strict regulatory frameworks to approve these. Recently, the Japanese Pharmaceuticals and Medical Devices Agency adopted new regulations under legislature. The translational potential of this article is to inform on the regulations to bring experimental phase regenerative concepts to market approval in the United States and Europe, and highlight the opportunities granted by Japanese regulatory framework. Furthermore, we discuss the perspectives on the quickly evolving regulatory environment.

  20. Modelling and validation of Proton exchange membrane fuel cell (PEMFC)

    Science.gov (United States)

    Mohiuddin, A. K. M.; Basran, N.; Khan, A. A.

    2018-01-01

    This paper is the outcome of a small scale fuel cell project. Fuel cell is an electrochemical device that converts energy from chemical reaction to electrical work. Proton Exchange Membrane Fuel Cell (PEMFC) is one of the different types of fuel cell, which is more efficient, having low operational temperature and fast start up capability results in high energy density. In this study, a mathematical model of 1.2 W PEMFC is developed and simulated using MATLAB software. This model describes the PEMFC behaviour under steady-state condition. This mathematical modeling of PEMFC determines the polarization curve, power generated, and the efficiency of the fuel cell. Simulation results were validated by comparing with experimental results obtained from the test of a single PEMFC with a 3 V motor. The performance of experimental PEMFC is little lower compared to simulated PEMFC, however both results were found in good agreement. Experiments on hydrogen flow rate also been conducted to obtain the amount of hydrogen consumed to produce electrical work on PEMFC.