Modeling growth and dissemination of lymphoma in a co-evolving lymph node: a diffuse-domain approach

Science.gov (United States)

Chuang, Yao-Li; Cristini, Vittorio; Chen, Ying; Li, Xiangrong; Frieboes, Hermann; Lowengrub, John

2013-03-01

While partial differential equation models of tumor growth have successfully described various spatiotemporal phenomena observed for in-vitro tumor spheroid experiments, one challenge towards taking these models to further study in-vivo tumors is that instead of relatively static tissue culture with regular boundary conditions, in-vivo tumors are often confined in organ tissues that co-evolve with the tumor growth. Here we adopt a recently developed diffuse-domain method to account for the co-evolving domain boundaries, adapting our previous in-vitro tumor model for the development of lymphoma encapsulated in a lymph node, which may swell or shrink due to proliferation and dissemination of lymphoma cells and treatment by chemotherapy. We use the model to study the induced spatial heterogeneity, which may arise as an emerging phenomenon in experimental observations and model analysis. Spatial heterogeneity is believed to lead to tumor infiltration patterns and reduce the efficacy of chemotherapy, leaving residuals that cause cancer relapse after the treatment. Understanding the spatiotemporal evolution of in-vivo tumors can be an essential step towards more effective strategies of curing cancer. Supported by NIH-PSOC grant 1U54CA143907-01.

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.

A novel evolving scale-free model with tunable attractiveness

International Nuclear Information System (INIS)

Xuan, Liu; Tian-Qi, Liu; Xing-Yuan, Li; Hao, Wang

2010-01-01

In this paper, a new evolving model with tunable attractiveness is presented. Based on the Barabasi–Albert (BA) model, we introduce the attractiveness of node which can change with node degree. Using the mean-field theory, we obtain the analytical expression of power-law degree distribution with the exponent γ in (3, ∞). The new model is more homogeneous and has a lower clustering coefficient and bigger average path length than the BA model. (general)

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.

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.

An evolving user-oriented model of Internet health information seeking.

Science.gov (United States)

Gaie, Martha J

2006-01-01

This paper presents an evolving user-oriented model of Internet health information seeking (IS) based on qualitative data collected from 22 lung cancer (LC) patients and caregivers. This evolving model represents information search behavior as more highly individualized, complex, and dynamic than previous models, including pre-search psychological activity, use of multiple heuristics throughout the process, and cost-benefit evaluation of search results. This study's findings suggest that IS occurs in four distinct phases: search initiation/continuation, selective exposure, message processing, and message evaluation. The identification of these phases and the heuristics used within them suggests a higher order of complexity in the decision-making processes that underlie IS, which could lead to the development of a conceptual framework that more closely reflects the complex nature of contextualized IS. It also illustrates the advantages of using qualitative methods to extract more subtle details of the IS process and fill in the gaps in existing models.

A local-world evolving hypernetwork model

International Nuclear Information System (INIS)

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. (interdisciplinary physics and related areas of science and technology)

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.

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

Long-term cultures of telomerase-transduced adult human mesenchymal stem cells (hMSC) may evolve spontaneous genetic changes leading to tumorigenicity in immunodeficient mice (e.g., hMSC-TERT20). We wished to clarify whether this unusual phenotype reflected a rare but dominant subpopulation or if...

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...... available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years...

Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective

NARCIS (Netherlands)

Janssen, A.B.G.; Gerla, D.J.

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

From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

Science.gov (United States)

Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan

2015-01-01

This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

Science.gov (United States)

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

Modeling Kidney Disease with iPS Cells

Science.gov (United States)

Freedman, Benjamin S.

2015-01-01

Induced pluripotent stem cells (iPSCs) are somatic cells that have been transcriptionally reprogrammed to an embryonic stem cell (ESC)-like state. iPSCs are a renewable source of diverse somatic cell types and tissues matching the original patient, including nephron-like kidney organoids. iPSCs have been derived representing several kidney disorders, such as ADPKD, ARPKD, Alport syndrome, and lupus nephritis, with the goals of generating replacement tissue and ‘disease in a dish’ laboratory models. Cellular defects in iPSCs and derived kidney organoids provide functional, personalized biomarkers, which can be correlated with genetic and clinical information. In proof of principle, disease-specific phenotypes have been described in iPSCs and ESCs with mutations linked to polycystic kidney disease or focal segmental glomerulosclerosis. In addition, these cells can be used to model nephrotoxic chemical injury. Recent advances in directed differentiation and CRISPR genome editing enable more specific iPSC models and present new possibilities for diagnostics, disease modeling, therapeutic screens, and tissue regeneration using human cells. This review outlines growth opportunities and design strategies for this rapidly expanding and evolving field. PMID:26740740

Calcium-manganese oxides as structural and functional models for active site in oxygen evolving complex in photosystem II: lessons from simple models.

Science.gov (United States)

Najafpour, Mohammad Mahdi

2011-01-01

The oxygen evolving complex in photosystem II which induces the oxidation of water to dioxygen in plants, algae and certain bacteria contains a cluster of one calcium and four manganese ions. It serves as a model to split water by sunlight. Reports on the mechanism and structure of photosystem II provide a more detailed architecture of the oxygen evolving complex and the surrounding amino acids. One challenge in this field is the development of artificial model compounds to study oxygen evolution reaction outside the complicated environment of the enzyme. Calcium-manganese oxides as structural and functional models for the active site of photosystem II are explained and reviewed in this paper. Because of related structures of these calcium-manganese oxides and the catalytic centers of active site of the oxygen evolving complex of photosystem II, the study may help to understand more about mechanism of oxygen evolution by the oxygen evolving complex of photosystem II. Copyright © 2010 Elsevier B.V. All rights reserved.

Evolving chemometric models for predicting dynamic process parameters in viscose production

Energy Technology Data Exchange (ETDEWEB)

Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

2012-05-06

Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

An evolving network model with modular growth

International Nuclear Information System (INIS)

Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi

2012-01-01

In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)

Modeling misidentification errors in capture-recapture studies using photographic identification of evolving marks

Science.gov (United States)

Yoshizaki, J.; Pollock, K.H.; Brownie, C.; Webster, R.A.

2009-01-01

Misidentification of animals is potentially important when naturally existing features (natural tags) are used to identify individual animals in a capture-recapture study. Photographic identification (photoID) typically uses photographic images of animals' naturally existing features as tags (photographic tags) and is subject to two main causes of identification errors: those related to quality of photographs (non-evolving natural tags) and those related to changes in natural marks (evolving natural tags). The conventional methods for analysis of capture-recapture data do not account for identification errors, and to do so requires a detailed understanding of the misidentification mechanism. Focusing on the situation where errors are due to evolving natural tags, we propose a misidentification mechanism and outline a framework for modeling the effect of misidentification in closed population studies. We introduce methods for estimating population size based on this model. Using a simulation study, we show that conventional estimators can seriously overestimate population size when errors due to misidentification are ignored, and that, in comparison, our new estimators have better properties except in cases with low capture probabilities (<0.2) or low misidentification rates (<2.5%). ?? 2009 by the Ecological Society of America.

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.

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.

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

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.

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.

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

Science.gov (United States)

Ombao, Hernando; Fiecas, Mark; Ting, Chee-Ming; Low, Yin Fen

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. Copyright © 2017. Published by Elsevier Inc.

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.

Impedance Modeling of Solid Oxide Fuel Cell Cathodes

DEFF Research Database (Denmark)

Mortensen, Jakob Egeberg; Søgaard, Martin; Jacobsen, Torben

2010-01-01

A 1-dimensional impedance model for a solid oxide fuel cell cathode is formulated and applied to a cathode consisting of 50/50 wt% strontium doped lanthanum cobaltite and gadolinia doped ceria. A total of 42 impedance spectra were recorded in the temperature range: 555-852°C and in the oxygen...... partial pressure range 0.028-1.00 atm. The recorded impedance spectra were successfully analyzed using the developed impedance model in the investigated temperature and oxygen partial pressure range. It is also demonstrated that the model can be used to predict how impedance spectra evolve with different...

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.

A model for the emergence of cooperation, interdependence, and structure in evolving networks

Science.gov (United States)

Jain, Sanjay; Krishna, Sandeep

2001-01-01

Evolution produces complex and structured networks of interacting components in chemical, biological, and social systems. We describe a simple mathematical model for the evolution of an idealized chemical system to study how a network of cooperative molecular species arises and evolves to become more complex and structured. The network is modeled by a directed weighted graph whose positive and negative links represent "catalytic" and "inhibitory" interactions among the molecular species, and which evolves as the least populated species (typically those that go extinct) are replaced by new ones. A small autocatalytic set, appearing by chance, provides the seed for the spontaneous growth of connectivity and cooperation in the graph. A highly structured chemical organization arises inevitably as the autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.

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.

Using Stem Cells to Model Diseases of the Outer Retina.

Science.gov (United States)

Yvon, Camille; Ramsden, Conor M; Lane, Amelia; Powner, Michael B; da Cruz, Lyndon; Coffey, Peter J; Carr, Amanda-Jayne F

2015-01-01

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).

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

Science.gov (United States)

Steiner, Christopher F.

2012-01-01

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. PMID:23284934

An oscillating dynamic model of collective cells in a monolayer

Science.gov (United States)

Lin, Shao-Zhen; Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao

2018-03-01

Periodic oscillations of collective cells occur in the morphogenesis and organogenesis of various tissues and organs. In this paper, an oscillating cytodynamic model is presented by integrating the chemomechanical interplay between the RhoA effector signaling pathway and cell deformation. We show that both an isolated cell and a cell aggregate can undergo spontaneous oscillations as a result of Hopf bifurcation, upon which the system evolves into a limit cycle of chemomechanical oscillations. The dynamic characteristics are tailored by the mechanical properties of cells (e.g., elasticity, contractility, and intercellular tension) and the chemical reactions involved in the RhoA effector signaling pathway. External forces are found to modulate the oscillation intensity of collective cells in the monolayer and to polarize their oscillations along the direction of external tension. The proposed cytodynamic model can recapitulate the prominent features of cell oscillations observed in a variety of experiments, including both isolated cells (e.g., spreading mouse embryonic fibroblasts, migrating amoeboid cells, and suspending 3T3 fibroblasts) and multicellular systems (e.g., Drosophila embryogenesis and oogenesis).

Universal Capacitance Model for Real-Time Biomass in Cell Culture

Directory of Open Access Journals (Sweden)

Viktor Konakovsky

2015-09-01

Full Text Available Capacitance probes have the potential to revolutionize bioprocess control due to their safe and robust use and ability to detect even the smallest capacitors in the form of biological cells. Several techniques have evolved to model biomass statistically, however, there are problems with model transfer between cell lines and process conditions. Errors of transferred models in the declining phase of the culture range for linear models around +100% or worse, causing unnecessary delays with test runs during bioprocess development. The goal of this work was to develop one single universal model which can be adapted by considering a potentially mechanistic factor to estimate biomass in yet untested clones and scales. The novelty of this work is a methodology to select sensitive frequencies to build a statistical model which can be shared among fermentations with an error between 9% and 38% (mean error around 20% for the whole process, including the declining phase. A simple linear factor was found to be responsible for the transferability of biomass models between cell lines, indicating a link to their phenotype or physiology.

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.

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.

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.

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....

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

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...... domains, such Evolvability Search produces solutions with higher evolvability than those produced with Novelty Search or traditional objective-based search algorithms. Further experiments demonstrate that the higher evolvability produced by Evolvability Search in a training environment also generalizes...

Evolving phenotypic networks in silico.

Science.gov (United States)

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

Selective Advantage of Recombination in Evolving Protein Populations:. a Lattice Model Study

Science.gov (United States)

Williams, Paul D.; Pollock, David D.; Goldstein, Richard A.

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population.

The Alpha Stem Cell Clinic: a model for evaluating and delivering stem cell-based therapies.

Science.gov (United States)

Trounson, Alan; DeWitt, Natalie D; Feigal, Ellen G

2012-01-01

Cellular therapies require the careful preparation, expansion, characterization, and delivery of cells in a clinical environment. There are major challenges associated with the delivery of cell therapies and high costs that will limit the companies available to fully evaluate their merit in clinical trials, and will handicap their application at the present financial environment. Cells will be manufactured in good manufacturing practice or near-equivalent facilities with prerequisite safety practices in place, and cell delivery systems will be specialized and require well-trained medical and nursing staff, technicians or nurses trained to handle cells once delivered, patient counselors, as well as statisticians and database managers who will oversee the monitoring of patients in relatively long-term follow-up studies. The model proposed for Alpha Stem Cell Clinics will initially use the capacities and infrastructure that exist in the most advanced tertiary medical clinics for delivery of established bone marrow stem cell therapies. As the research evolves, they will incorporate improved procedures and cell preparations. This model enables commercialization of medical devices, reagents, and other products required for cell therapies. A carefully constructed cell therapy clinical infrastructure with the requisite scientific, technical, and medical expertise and operational efficiencies will have the capabilities to address three fundamental and critical functions: 1) fostering clinical trials; 2) evaluating and establishing safe and effective therapies, and 3) developing and maintaining the delivery of therapies approved by the Food and Drug Administration, or other regulatory agencies.

Integration of Life Cycle Assessment Into Agent-Based Modeling : Toward Informed Decisions on Evolving Infrastructure Systems

NARCIS (Netherlands)

Davis, C.B.; Nikoli?, I.; Dijkema, G.P.J.

2009-01-01

A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making

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.

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.

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton

Directory of Open Access Journals (Sweden)

Likun Wang

2018-03-01

Full Text Available To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility.

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton

Science.gov (United States)

Wang, Likun; Du, Zhijiang; Dong, Wei; Shen, Yi; Zhao, Guangyu

2018-01-01

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility. PMID:29562684

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton.

Science.gov (United States)

Wang, Likun; Du, Zhijiang; Dong, Wei; Shen, Yi; Zhao, Guangyu

2018-03-19

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human-robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human-robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility.

The apolipoprotein L family of programmed cell death and immunity genes rapidly evolved in primates at discrete sites of host-pathogen interactions.

Science.gov (United States)

Smith, Eric E; Malik, Harmit S

2009-05-01

Apolipoprotein L1 (APOL1) is a human protein that confers immunity to Trypanosoma brucei infections but can be countered by a trypanosome-encoded antagonist SRA. APOL1 belongs to a family of programmed cell death genes whose proteins can initiate host apoptosis or autophagic death. We report here that all six members of the APOL gene family (APOL1-6) present in humans have rapidly evolved in simian primates. APOL6, furthermore, shows evidence of an adaptive sweep during recent human evolution. In each APOL gene tested, we found rapidly evolving codons in or adjacent to the SRA-interacting protein domain (SID), which is the domain of APOL1 that interacts with SRA. In APOL6, we also found a rapidly changing 13-amino-acid cluster in the membrane-addressing domain (MAD), which putatively functions as a pH sensor and regulator of cell death. We predict that APOL genes are antagonized by pathogens by at least two distinct mechanisms: SID antagonists, which include SRA, that interact with the SID of various APOL proteins, and MAD antagonists that interact with the MAD hinge base of APOL6. These antagonists either block or prematurely cause APOL-mediated programmed cell death of host cells to benefit the infecting pathogen. These putative interactions must occur inside host cells, in contrast to secreted APOL1 that trafficks to the trypanosome lysosome. Hence, the dynamic APOL gene family appears to be an important link between programmed cell death of host cells and immunity to pathogens.

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.

The General Evolving Model for Energy Supply-Demand Network with Local-World

Science.gov (United States)

Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

2013-10-01

In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

Particle-Resolved Modeling of Aerosol Mixing State in an Evolving Ship Plume

Science.gov (United States)

Riemer, N. S.; Tian, J.; Pfaffenberger, L.; Schlager, H.; Petzold, A.

2011-12-01

The aerosol mixing state is important since it impacts the particles' optical and CCN properties and thereby their climate impact. It evolves continuously during the particles' residence time in the atmosphere as a result of coagulation with other particles and condensation of secondary aerosol species. This evolution is challenging to represent in traditional aerosol models since they require the representation of a multi-dimensional particle distribution. While modal or sectional aerosol representations cannot practically resolve the aerosol mixing state for more than a few species, particle-resolved models store the composition of many individual aerosol particles directly. They thus sample the high-dimensional composition state space very efficiently and so can deal with tens of species, fully resolving the mixing state. Here we use the capabilities of the particle-resolved model PartMC-MOSAIC to simulate the evolution of particulate matter emitted from marine diesel engines and compare the results to aircraft measurements made in the English Channel in 2007 as part of the European campaign QUANTIFY. The model was initialized with values of gas concentrations and particle size distributions and compositions representing fresh ship emissions. These values were obtained from a test rig study in the European project HERCULES in 2006 using a serial four-stroke marine diesel engine operating on high-sulfur heavy fuel oil. The freshly emitted particles consisted of sulfate, black carbon, organic carbon and ash. We then tracked the particle population for several hours as it evolved undergoing coagulation, dilution with the background air, and chemical transformations in the aerosol and gas phase. This simulation was used to compute the evolution of CCN properties and optical properties of the plume on a per-particle basis. We compared our results to size-resolved data of aged ship plumes from the QUANTIFY Study in 2007 and showed that the model was able to reproduce

A comparative study on the forming limit diagram prediction between Marciniak-Kuczynski model and modified maximum force criterion by using the evolving non-associated Hill48 plasticity model

Science.gov (United States)

Shen, Fuhui; Lian, Junhe; Münstermann, Sebastian

2018-05-01

Experimental and numerical investigations on the forming limit diagram (FLD) of a ferritic stainless steel were performed in this study. The FLD of this material was obtained by Nakajima tests. Both the Marciniak-Kuczynski (MK) model and the modified maximum force criterion (MMFC) were used for the theoretical prediction of the FLD. From the results of uniaxial tensile tests along different loading directions with respect to the rolling direction, strong anisotropic plastic behaviour was observed in the investigated steel. A recently proposed anisotropic evolving non-associated Hill48 (enHill48) plasticity model, which was developed from the conventional Hill48 model based on the non-associated flow rule with evolving anisotropic parameters, was adopted to describe the anisotropic hardening behaviour of the investigated material. In the previous study, the model was coupled with the MMFC for FLD prediction. In the current study, the enHill48 was further coupled with the MK model. By comparing the predicted forming limit curves with the experimental results, the influences of anisotropy in terms of flow rule and evolving features on the forming limit prediction were revealed and analysed. In addition, the forming limit predictive performances of the MK and the MMFC models in conjunction with the enHill48 plasticity model were compared and evaluated.

Partially satisfied to fully satisfied transitions in co-evolving inverse voter model and possible scaling behavior

International Nuclear Information System (INIS)

Choi, C.W.; Xu, C.; Hui, P.M.

2015-01-01

Understanding co-evolving networks characterized by the mutual influence of agents' actions and network structure remains a challenge. We study a co-evolving inverse voter model in which agents adapt to achieve a preferred environment with more opposite-opinion neighbors by rewiring their connections and switching opinion. Numerical studies reveal a transition from a dynamic partially satisfied phase to a frozen fully satisfied phase as the rewiring probability is varied. A simple mean field theory is shown to capture the behavior only qualitatively. An improved mean field theory carrying a longer spatial correlation gives better results. Motivated by numerical results in networks of different degrees and mean field results, we propose a scaling variable that combines the rewiring probability and mean degree in a special form. The scaling variable is shown to work well in analyzing data corresponding to different networks and different rewiring probabilities. An application is to predict the results for networks of different degrees based solely on results obtained from networks of one degree. Studying scaling behavior provides an alternative path for understanding co-evolving agent-based dynamical systems, especially in light of the trade-off between complexity of a theory and its accuracy. - Highlights: • Identified key features and phase transitions in coevolving inverse voter model. • Constructed a better theory incorporating longer spatial correlation. • Proposed scaling variable and illustrated possible scaling behavior. • Used scaling behavior to predict results of IVM in a different network.

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.

Evolving Procurement Organizations

DEFF Research Database (Denmark)

Bals, Lydia; Laine, Jari; Mugurusi, Godfrey

Procurement has to find further levers and advance its contribution to corporate goals continuously. This places pressure on its organization in order to facilitate its performance. Therefore, procurement organizations constantly have to evolve in order to match these demands. A conceptual model...... and external contingency factors and having a more detailed look at the structural dimensions chosen, beyond the well-known characteristics of centralization, formalization, participation, specialization, standardization and size. From a theoretical perspective, it opens up insights that can be leveraged...

Homophyly/Kinship Model: Naturally Evolving Networks

Science.gov (United States)

Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

2015-10-01

It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

A Markovian model of evolving world input-output network.

Directory of Open Access Journals (Sweden)

Vahid Moosavi

Full Text Available 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.

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.

Assessing Air-Sea Interaction in the Evolving NASA GEOS Model

Science.gov (United States)

Clayson, Carol Anne; Roberts, J. Brent

2015-01-01

In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.

Gaian bottlenecks and planetary habitability maintained by evolving model biospheres: the ExoGaia model

Science.gov (United States)

Nicholson, Arwen E.; Wilkinson, David M.; Williams, Hywel T. P.; Lenton, Timothy M.

2018-06-01

The search for habitable exoplanets inspires the question - how do habitable planets form? Planet habitability models traditionally focus on abiotic processes and neglect a biotic response to changing conditions on an inhabited planet. The Gaia hypothesis postulates that life influences the Earth's feedback mechanisms to form a self-regulating system, and hence that life can maintain habitable conditions on its host planet. If life has a strong influence, it will have a role in determining a planet's habitability over time. We present the ExoGaia model - a model of simple `planets' host to evolving microbial biospheres. Microbes interact with their host planet via consumption and excretion of atmospheric chemicals. Model planets orbit a `star' that provides incoming radiation, and atmospheric chemicals have either an albedo or a heat-trapping property. Planetary temperatures can therefore be altered by microbes via their metabolisms. We seed multiple model planets with life while their atmospheres are still forming and find that the microbial biospheres are, under suitable conditions, generally able to prevent the host planets from reaching inhospitable temperatures, as would happen on a lifeless planet. We find that the underlying geochemistry plays a strong role in determining long-term habitability prospects of a planet. We find five distinct classes of model planets, including clear examples of `Gaian bottlenecks' - a phenomenon whereby life either rapidly goes extinct leaving an inhospitable planet or survives indefinitely maintaining planetary habitability. These results suggest that life might play a crucial role in determining the long-term habitability of planets.

Evolving provider payment models and patient access to innovative medical technology.

Science.gov (United States)

Long, Genia; Mortimer, Richard; Sanzenbacher, Geoffrey

2014-12-01

Abstract Objective: To investigate the evolving use and expected impact of pay-for-performance (P4P) and risk-based provider reimbursement on patient access to innovative medical technology. Structured interviews with leading private payers representing over 110 million commercially-insured lives exploring current and planned use of P4P provider payment models, evidence requirements for technology assessment and new technology coverage, and the evolving relationship between the two topics. Respondents reported rapid increases in the use of P4P and risk-sharing programs, with roughly half of commercial lives affected 3 years ago, just under two-thirds today, and an expected three-quarters in 3 years. All reported well-established systems for evaluating new technology coverage. Five of nine reported becoming more selective in the past 3 years in approving new technologies; four anticipated that in the next 3 years there will be a higher evidence requirement for new technology access. Similarly, four expected it will become more difficult for clinically appropriate but costly technologies to gain coverage. All reported planning to rely more on these types of provider payment incentives to control costs, but didn't see them as a substitute for payer technology reviews and coverage limitations; they each have a role to play. Interviews limited to nine leading payers with models in place; self-reported data. Likely implications include a more uncertain payment environment for providers, and indirectly for innovative medical technology and future investment, greater reliance on quality and financial metrics, and increased evidence requirements for favorable coverage and utilization decisions. Increasing provider financial risk may challenge the traditional technology adoption paradigm, where payers assumed a 'gatekeeping' role and providers a countervailing patient advocacy role with regard to access to new technology. Increased provider financial risk may result in an

A reproductive threat-based model of evolved sex differences in jealousy.

Science.gov (United States)

Sagarin, Brad J; Becker, D Vaughn; Guadagno, Rosanna E; Wilkinson, Wayne W; Nicastle, Lionel D

2012-08-10

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.

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.

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.

Effects of Orbital Lifetime Reduction on the Long-Term Earth Satellite Population as Modeled by EVOLVE 4.0

Science.gov (United States)

Krisko, Paula H.; Opiela, John N.; Liou, Jer-Chyi; Anz-Meador, Phillip D.; Theall, Jeffrey R.

1999-01-01

The latest update of the NASA orbital debris environment model, EVOLVE 4.0, has been used to study the effect of various proposed debris mitigation measures, including the NASA 25-year guideline. EVOLVE 4.0, which includes updates of the NASA breakup, solar activity, and the orbit propagator models, a GEO analysis option, and non-fragmentation debris source models, allows for the statistical modeling and predicted growth of the particle population >1 mm in characteristic length in LEO and GEO orbits. The initial implementation of this &odel has been to study the sensitivity of the overall LEO debris environment to mitigation measures designed to limit the lifetime of intact objects in LEO orbits. The mitigation measures test matrix for this study included several commonly accepted testing schemes, i.e., the variance of the maximum LEO lifetime from 10 to 50 years, the date of the initial implementation of this policy, the shut off of all explosions at some specified date, and the inclusion of disposal orbits. All are timely studies in that all scenarios have been suggested by researchers and satellite operators as options for the removal of debris from LEO orbits.

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

International Nuclear Information System (INIS)

Wang, Liang; Germaschewski, K.; Hakim, Ammar H.; Bhattacharjee, A.

2015-01-01

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

EVOLVING AN EMPIRICAL METHODOLOGY DOR DETERMINING ...

African Journals Online (AJOL)

The uniqueness of this approach, is that it can be applied to any forest or dynamic feature on the earth, and can enjoy universal application as well. KEY WORDS: Evolving empirical methodology, innovative mathematical model, appropriate interval, remote sensing, forest environment planning and management. Global Jnl ...

Evolving and energy dependent optical model description of heavy-ion elastic scattering

International Nuclear Information System (INIS)

Michaelian, K.

1996-01-01

We present the application of a genetic algorithm to the problem of determining an energy dependent optical model description of heavy-ion elastic scattering. The problem requires a search for the global best optical model potential and its energy dependence in a very rugged 12 dimensional parameter space of complex topographical features with many local minima. Random solutions are created in the first generation. The fitness of a solution is related to the χ 2 fit of the calculated differential cross sections with the experimental data. Best fit solutions are evolved through cross over and mutation following the biological example. This genetic algorithm approach combined with local gradient minimization is shown to provide a global, complete and extremely efficient search method, well adapted to complex fitness landscapes. These characteristics, combined with the facility of application, should make it the search method of choice for a wide variety of problems from nuclear physics. (Author)

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.

Laplacian Estrada and normalized Laplacian Estrada indices of evolving graphs.

Science.gov (United States)

Shang, Yilun

2015-01-01

Large-scale time-evolving networks have been generated by many natural and technological applications, posing challenges for computation and modeling. Thus, it is of theoretical and practical significance to probe mathematical tools tailored for evolving networks. In this paper, on top of the dynamic Estrada index, we study the dynamic Laplacian Estrada index and the dynamic normalized Laplacian Estrada index of evolving graphs. Using linear algebra techniques, we established general upper and lower bounds for these graph-spectrum-based invariants through a couple of intuitive graph-theoretic measures, including the number of vertices or edges. Synthetic random evolving small-world networks are employed to show the relevance of the proposed dynamic Estrada indices. It is found that neither the static snapshot graphs nor the aggregated graph can approximate the evolving graph itself, indicating the fundamental difference between the static and dynamic Estrada indices.

Non-Fourier conduction model with thermal source term of ultra short high power pulsed laser ablation and temperature evolvement before melting

International Nuclear Information System (INIS)

Zhang Duanming; Li, Li; Li Zhihua; Guan Li; Tan Xinyu

2005-01-01

A non-Fourier conduction model with heat source term is presented to study the target temperature evolvement when the target is radiated by high power (the laser intensity is above 10 9 w/cm 2 ) and ultra short (the pulse width is less than 150 ps) pulsed laser. By Laplace transform, the analytical expression of the space- and time-dependence of temperature is derived. Then as an example of aluminum target, the target temperature evolvement is simulated. Compared with the results of Fourier conduction model and non-Fourier model without heat source term, it is found that the effect of non-Fourier conduction is notable and the heat source plays an important role during non-Fourier conduction which makes surface temperature ascending quickly with time. Meanwhile, the corresponding physical mechanism is analyzed theoretically

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

Science.gov (United States)

Partha, Raghavendran; Raman, Karthik

2014-01-01

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to

Evolving software products, the design of a water-related modeling software ecosystem

DEFF Research Database (Denmark)

Manikas, Konstantinos

2017-01-01

more than 50 years ago. However, a radical change of software products to evolve both in the software engineering as much as the organizational and business aspects in a disruptive manner are rather rare. In this paper, we report on the transformation of one of the market leader product series in water......-related calculation and modeling from a traditional business-as-usual series of products to an evolutionary software ecosystem. We do so by relying on existing concepts on software ecosystem analysis to analyze the future ecosystem. We report and elaborate on the main focus points necessary for this transition. We...... argue for the generalization of our focus points to the transition from traditional business-as-usual software products to software ecosystems....

Evolving Ecological Social Dilemmas: A Spatial Individual-Based Model for the Evolution of Cooperation with a Minimal Number of Parameters

International Nuclear Information System (INIS)

Fort, H.

2007-01-01

Cooperation, both intraspecific and interspecific, is a well-documented phenomenon in nature that is not well understood. Evolutionary game theory is a powerful tool to approach this problem. However, it has important limitations. First, very often it is not obvious which game is more appropriate to use. Second, in general, identical payoff matrices are assumed for all players, a situation that is highly unlikely in nature. Third, slight changes in these payoff values can dramatically alter the outcomes. Here, I use an evolutionary spatial model in which players do not have a universal payoff matrix, so no payoff parameters are required. Instead, each is equipped with random values for the payoffs, fulfilling the constraints that define the game(s). These payoff matrices evolve by natural selection. Two versions of this model are studied. First is a simpler one, with just one evolving payoff. Second is the full version, with all the four payoffs evolving. The fraction of cooperator agents converges in both versions to nonzero values. In the case of the full version, the initial heterogeneity disappears and the selected game is the stag Hunt

Role of chemotherapy in the treatment of lung cancer: evolving strategies for non-small cell histologies

International Nuclear Information System (INIS)

Muggia, F.M.; Blum, R.H.; Foreman, J.D.

1984-01-01

Lung cancer treatment has been considered to have made little progress except for advances in small cell carcinoma. For other histologies an attitude of nihilism has prevailed principally because of lack of effective systemic therapy and of no persuasive evidence that results could be improved by combined modality treatment. On the other hand, favorable results from surgery are confined to a small percent of all patients with this disease. This review emphasizes possibilities for progress in evolving new therapeutic strategies. Although improvement over other systemic therapies is modest, cisplatin-containing regimens yield more consistent response rates and apparent survival advantage relative to single agents. Immediate progression occurs in the minority of patients. In addition, regimens combining cisplatin with vinca alkaloids have no substantial deleterious effects on the lung, marrow or esophagus to aggravate radiation-induced complications. These features encourage the evolution of strategies which begin with chemotherapy and then use consolidation with radiation therapy. Clinical trials using these and newer strategies must be instituted if progress is to occur in the treatment of non-small cell histologies at all stages

Role of chemotherapy in the treatment of lung cancer: evolving strategies for non-small cell histologies

Energy Technology Data Exchange (ETDEWEB)

Muggia, F.M. (NYU Medical Center, New York); Blum, R.H.; Foreman, J.D.

1984-01-01

Lung cancer treatment has been considered to have made little progress except for advances in small cell carcinoma. For other histologies an attitude of nihilism has prevailed principally because of lack of effective systemic therapy and of no persuasive evidence that results could be improved by combined modality treatment. On the other hand, favorable results from surgery are confined to a small percent of all patients with this disease. This review emphasizes possibilities for progress in evolving new therapeutic strategies. Although improvement over other systemic therapies is modest, cisplatin-containing regimens yield more consistent response rates and apparent survival advantage relative to single agents. Immediate progression occurs in the minority of patients. In addition, regimens combining cisplatin with vinca alkaloids have no substantial deleterious effects on the lung, marrow or esophagus to aggravate radiation-induced complications. These features encourage the evolution of strategies which begin with chemotherapy and then use consolidation with radiation therapy. Clinical trials using these and newer strategies must be instituted if progress is to occur in the treatment of non-small cell histologies at all stages.

Laplacian Estrada and normalized Laplacian Estrada indices of evolving graphs.

Directory of Open Access Journals (Sweden)

Yilun Shang

Full Text Available Large-scale time-evolving networks have been generated by many natural and technological applications, posing challenges for computation and modeling. Thus, it is of theoretical and practical significance to probe mathematical tools tailored for evolving networks. In this paper, on top of the dynamic Estrada index, we study the dynamic Laplacian Estrada index and the dynamic normalized Laplacian Estrada index of evolving graphs. Using linear algebra techniques, we established general upper and lower bounds for these graph-spectrum-based invariants through a couple of intuitive graph-theoretic measures, including the number of vertices or edges. Synthetic random evolving small-world networks are employed to show the relevance of the proposed dynamic Estrada indices. It is found that neither the static snapshot graphs nor the aggregated graph can approximate the evolving graph itself, indicating the fundamental difference between the static and dynamic Estrada indices.

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.

Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits.

Science.gov (United States)

Milano, Nicola; Nolfi, Stefano

2016-01-01

We demonstrate how the need to cope with operational faults enables evolving circuits to find more fit solutions. The analysis of the results obtained in different experimental conditions indicates that, in absence of faults, evolution tends to select circuits that are small and have low phenotypic variability and evolvability. The need to face operation faults, instead, drives evolution toward the selection of larger circuits that are truly robust with respect to genetic variations and that have a greater level of phenotypic variability and evolvability. Overall our results indicate that the need to cope with operation faults leads to the selection of circuits that have a greater probability to generate better circuits as a result of genetic variation with respect to a control condition in which circuits are not subjected to faults.

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

Analysis of motility in multicellular Chlamydomonas reinhardtii evolved under predation.

Directory of Open Access Journals (Sweden)

Margrethe Boyd

Full Text Available The advent of multicellularity was a watershed event in the history of life, yet the transition from unicellularity to multicellularity is not well understood. Multicellularity opens up opportunities for innovations in intercellular communication, cooperation, and specialization, which can provide selective advantages under certain ecological conditions. The unicellular alga Chlamydomonas reinhardtii has never had a multicellular ancestor yet it is closely related to the volvocine algae, a clade containing taxa that range from simple unicells to large, specialized multicellular colonies. Simple multicellular structures have been observed to evolve in C. reinhardtii in response to predation or to settling rate-based selection. Structures formed in response to predation consist of individual cells confined within a shared transparent extracellular matrix. Evolved isolates form such structures obligately under culture conditions in which their wild type ancestors do not, indicating that newly-evolved multicellularity is heritable. C. reinhardtii is capable of photosynthesis, and possesses an eyespot and two flagella with which it moves towards or away from light in order to optimize input of radiant energy. Motility contributes to C. reinhardtii fitness because it allows cells or colonies to achieve this optimum. Utilizing phototaxis to assay motility, we determined that newly evolved multicellular strains do not exhibit significant directional movement, even though the flagellae of their constituent unicells are present and active. In C. reinhardtii the first steps towards multicellularity in response to predation appear to result in a trade-off between motility and differential survivorship, a trade-off that must be overcome by further genetic change to ensure long-term success of the new multicellular organism.

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.

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.

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.

(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.)

Statistical models for brain signals with properties that evolve across trials

KAUST Repository

Ombao, Hernando; Fiecas, Mark; Ting, Chee-Ming; Low, Yin Fen

2017-01-01

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

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.

A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas

OpenAIRE

Wang, Haohan; Raj, Bhiksha

2015-01-01

This report will show the history of deep learning evolves. It will trace back as far as the initial belief of connectionism modelling of brain, and come back to look at its early stage realization: neural networks. With the background of neural network, we will gradually introduce how convolutional neural network, as a representative of deep discriminative models, is developed from neural networks, together with many practical techniques that can help in optimization of neural networks. On t...

CMIP6 Data Citation of Evolving Data

Directory of Open Access Journals (Sweden)

Martina Stockhause

2017-06-01

Full Text Available Data citations have become widely accepted. Technical infrastructures as well as principles and recommendations for data citation are in place but best practices or guidelines for their implementation are not yet available. On the other hand, the scientific climate community requests early citations on evolving data for credit, e.g. for CMIP6 (Coupled Model Intercomparison Project Phase 6. The data citation concept for CMIP6 is presented. The main challenges lie in limited resources, a strict project timeline and the dependency on changes of the data dissemination infrastructure ESGF (Earth System Grid Federation to meet the data citation requirements. Therefore a pragmatic, flexible and extendible approach for the CMIP6 data citation service was developed, consisting of a citation for the full evolving data superset and a data cart approach for citing the concrete used data subset. This two citation approach can be implemented according to the RDA recommendations for evolving data. Because of resource constraints and missing project policies, the implementation of the second part of the citation concept is postponed to CMIP7.

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

International Nuclear Information System (INIS)

Fenech, Michael

2006-01-01

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

Evolving RBF neural networks for adaptive soft-sensor design.

Science.gov (United States)

Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

An artemisinin-mediated ROS evolving and dual protease light-up nanocapsule for real-time imaging of lysosomal tumor cell death.

Science.gov (United States)

Huang, Liwei; Luo, Yingping; Sun, Xian; Ju, Huangxian; Tian, Jiangwei; Yu, Bo-Yang

2017-06-15

Lysosomes are critical organelles for cellular homeostasis and can be used as potential targets to kill tumor cells from inside. Many photo-therapeutic methods have been developed to overproduce reactive oxygen species (ROS) to trigger lysosomal membrane permeabilization (LMP)-associated cell death pathway. However, these technologies rely on extra irradiation to activate the photosensitizers, which limits the applications in treating deep seated tumors and widespread metastatic lesions. This work reports a multifunctional nanocapsule to achieve targeted lysosomal tumor cell death without irradiation and real-time monitoring of drug effect through encapsulating artemisinin and dual protease light-up nanoprobe in a folate-functionalized liposome. The nanocapsule can be specifically uptaken by tumor cells via folate receptor-mediated endocytosis to enter lysosomes, in which artemisinin reacts with ferrous to generate ROS for LMP-associated cell death. By virtue of confocal fluorescence imaging, the artemisinin location in lysosome, ROS-triggered LMP and ultimate cell apoptosis can be visualized with the cathepsin B and caspase-3 activatable nanoprobe. Notably, the artemisinin-mediated ROS evolving for tumor therapy and real-time therapeutic monitoring were successfully implemented by living imaging in tumor-bearing mice, which broaden the nanocapsule for in vivo theranostics and may offer new opportunities for precise medicine. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatiotemporal impacts of LULC changes on hydrology from the perspective of runoff generation mechanism using SWAT model with evolving parameters

Science.gov (United States)

Li, Y.; Chang, J.; Luo, L.

2017-12-01

It is of great importance for water resources management to model the truly hydrological process under changing environment, especially under significant changes of underlying surfaces like the Wei River Bain (WRB) where the subsurface hydrology is highly influenced by human activities, and to systematically investigate the interactions among LULC change, streamflow variation and changes in runoff generation process. Therefore, we proposed the idea of evolving parameters in hydrological model (SWAT) to reflect the changes in physical environment with different LULC conditions. Then with these evolving parameters, the spatiotemporal impacts of LULC changes on streamflow were quantified, and qualitative analysis was conducted to further explore how LULC changes affect the streamflow from the perspective of runoff generation mechanism. Results indicate the following: 1) evolving parameter calibration is not only effective but necessary to ensure the validity of the model when dealing with significant changes in underlying surfaces due to human activities. 2) compared to the baseline period, the streamflow in wet seasons increased in the 1990s but decreased in the 2000s. While at yearly and dry seasonal scales, the streamflow decreased in both two decades; 3) the expansion of cropland is the major contributor to the reduction of surface water component, thus causing the decline in streamflow at yearly and dry seasonal scales. While compared to the 1990s, the expansions of woodland in the middle stream and grassland in the downstream are the main stressors that increased the soil water component, thus leading to the more decline of the streamflow in the 2000s.

Cell therapy worldwide: an incipient revolution.

Science.gov (United States)

Rao, Mahendra; Mason, Chris; Solomon, Susan

2015-01-01

The regenerative medicine field is large, diverse and active worldwide. A variety of different organizational and product models have been successful, and pioneering entrepreneurs have shown both what can work and, critically, what does not. Evolving regulations, novel funding mechanisms combined with new technological breakthroughs are keeping the field in a state of flux. The field struggles to cope with the lack of infrastructure and investment, it nevertheless has evolved from its roots in human stem cell therapy and tissue and organ transplants to a field composed of a variety of products from multiple cell sources with approval for use in numerous countries. Currently, tens of thousands of patients have been treated with some kind of cell therapy.

A method of evolving novel feature extraction algorithms for detecting buried objects in FLIR imagery using genetic programming

Science.gov (United States)

Paino, A.; Keller, J.; Popescu, M.; Stone, K.

2014-06-01

In this paper we present an approach that uses Genetic Programming (GP) to evolve novel feature extraction algorithms for greyscale images. Our motivation is to create an automated method of building new feature extraction algorithms for images that are competitive with commonly used human-engineered features, such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). The evolved feature extraction algorithms are functions defined over the image space, and each produces a real-valued feature vector of variable length. Each evolved feature extractor breaks up the given image into a set of cells centered on every pixel, performs evolved operations on each cell, and then combines the results of those operations for every cell using an evolved operator. Using this method, the algorithm is flexible enough to reproduce both LBP and HOG features. The dataset we use to train and test our approach consists of a large number of pre-segmented image "chips" taken from a Forward Looking Infrared Imagery (FLIR) camera mounted on the hood of a moving vehicle. The goal is to classify each image chip as either containing or not containing a buried object. To this end, we define the fitness of a candidate solution as the cross-fold validation accuracy of the features generated by said candidate solution when used in conjunction with a Support Vector Machine (SVM) classifier. In order to validate our approach, we compare the classification accuracy of an SVM trained using our evolved features with the accuracy of an SVM trained using mainstream feature extraction algorithms, including LBP and HOG.

Evolving Procurement Organizations

DEFF Research Database (Denmark)

Bals, Lydia; Laiho, Aki; Laine, Jari

Procurement has to find further levers and advance its contribution to corporate goals continuously. This places pressure on its organization in order to facilitate its performance. Therefore, Procurement organizations constantly have to evolve in order to match these demands. A conceptual model...... is presented and results of a first case study discussed. The findings highlight the importance of taking a contingency perspective on Procurement organization, understanding the internal and internal contingency factors. From a theoretical perspective, it opens up insights that can be furthermore leveraged...... in future studies in the fields of hybrid procurement organizations, global sourcing organizations as well as international procurement offices (IPOs). From a practical standpoint, an assessment of external and internal contingencies provides the opportunity to consciously match organization to its...

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.

EVOLVE : a Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

CERN Document Server

Coello, Carlos; Tantar, Alexandru-Adrian; Tantar, Emilia; Bouvry, Pascal; Moral, Pierre; Legrand, Pierrick; EVOLVE 2012

2013-01-01

This book comprises a selection of papers from the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics and evolutionary computing, as to identify new common and challenging research aspects. The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE is intended to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements may echo in different domains. Summarizing, the EVOLVE focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability,  performance guarantees and modeling. The papers of the EVOLVE 2012 make a contribution to this goal. 

Tetraploid cells from cytokinesis failure induce aneuploidy and spontaneous transformation of mouse ovarian surface epithelial cells.

Science.gov (United States)

Lv, Lei; Zhang, Tianwei; Yi, Qiyi; Huang, Yun; Wang, Zheng; Hou, Heli; Zhang, Huan; Zheng, Wei; Hao, Qiaomei; Guo, Zongyou; Cooke, Howard J; Shi, Qinghua

2012-08-01

Most ovarian cancers originate from the ovarian surface epithelium and are characterized by aneuploid karyotypes. Aneuploidy, a consequence of chromosome instability, is an early event during the development of ovarian cancers. However, how aneuploid cells are evolved from normal diploid cells in ovarian cancers remains unknown. In the present study, cytogenetic analyses of a mouse syngeneic ovarian cancer model revealed that diploid mouse ovarian surface epithelial cells (MOSECs) experienced an intermediate tetraploid cell stage, before evolving to aneuploid (mainly near-tetraploid) cells. Using long-term live-cell imaging followed by fluorescence in situ hybridization (FISH), we demonstrated that tetraploid cells originally arose from cytokinesis failure of bipolar mitosis in diploid cells, and gave rise to aneuploid cells through chromosome mis-segregation during both bipolar and multipolar mitoses. Injection of the late passage aneuploid MOSECs resulted in tumor formation in C57BL/6 mice. Therefore, we reveal a pathway for the evolution of diploid to aneuploid MOSECs and elucidate a mechanism for the development of near-tetraploid ovarian cancer cells.

Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics.

Science.gov (United States)

Kaneko, Kunihiko; Furusawa, Chikara

2018-05-20

We present a macroscopic theory to characterize the plasticity, robustness, and evolvability of biological responses and their fluctuations. First, linear approximation in intracellular reaction dynamics is used to demonstrate proportional changes in the expression of all cellular components in response to a given environmental stress, with the proportion coefficient determined by the change in growth rate as a consequence of the steady growth of cells. We further demonstrate that this relationship is supported through adaptation experiments of bacteria, perhaps too well as this proportionality is held even across cultures of different types of conditions. On the basis of simulations of cell models, we further show that this global proportionality is a consequence of evolution in which expression changes in response to environmental or genetic perturbations are constrained along a unique one-dimensional curve, which is a result of evolutionary robustness. It then follows that the expression changes induced by environmental changes are proportionally reduced across different components of a cell by evolution, which is akin to the Le Chatelier thermodynamics principle. Finally, with the aid of a fluctuation-response relationship, this proportionality is shown to hold between fluctuations caused by genetic changes and those caused by noise. Overall, these results and support from the theoretical and experimental literature suggest a formulation of cellular systems akin to thermodynamics, in which a macroscopic potential is given by the growth rate (or fitness) represented as a function of environmental and evolutionary changes.

Stem cells and the evolving notion of cellular identity

OpenAIRE

Daley, George Q.

2015-01-01

Stem cells are but one class of the myriad types of cells within an organism. With potential to self-renew and capacity to differentiate, stem cells play essential roles at multiple stages of development. In the early embryo, pluripotent stem cells represent progenitors for all tissues while later in development, tissue-restricted stem cells give rise to cells with highly specialized functions. As best understood in the blood, skin and gut, stem cells are the seeds that sustain tissue homeost...

Genome duplication and mutations in ACE2 cause multicellular, fast-sedimenting phenotypes in evolved Saccharomyces cerevisiae.

Science.gov (United States)

Oud, Bart; Guadalupe-Medina, Victor; Nijkamp, Jurgen F; de Ridder, Dick; Pronk, Jack T; van Maris, Antonius J A; Daran, Jean-Marc

2013-11-05

Laboratory evolution of the yeast Saccharomyces cerevisiae in bioreactor batch cultures yielded variants that grow as multicellular, fast-sedimenting clusters. Knowledge of the molecular basis of this phenomenon may contribute to the understanding of natural evolution of multicellularity and to manipulating cell sedimentation in laboratory and industrial applications of S. cerevisiae. Multicellular, fast-sedimenting lineages obtained from a haploid S. cerevisiae strain in two independent evolution experiments were analyzed by whole genome resequencing. The two evolved cell lines showed different frameshift mutations in a stretch of eight adenosines in ACE2, which encodes a transcriptional regulator involved in cell cycle control and mother-daughter cell separation. Introduction of the two ace2 mutant alleles into the haploid parental strain led to slow-sedimenting cell clusters that consisted of just a few cells, thus representing only a partial reconstruction of the evolved phenotype. In addition to single-nucleotide mutations, a whole-genome duplication event had occurred in both evolved multicellular strains. Construction of a diploid reference strain with two mutant ace2 alleles led to complete reconstruction of the multicellular-fast sedimenting phenotype. This study shows that whole-genome duplication and a frameshift mutation in ACE2 are sufficient to generate a fast-sedimenting, multicellular phenotype in S. cerevisiae. The nature of the ace2 mutations and their occurrence in two independent evolution experiments encompassing fewer than 500 generations of selective growth suggest that switching between unicellular and multicellular phenotypes may be relevant for competitiveness of S. cerevisiae in natural environments.

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

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

Behaviour of and mass transfer at gas-evolving electrodes

NARCIS (Netherlands)

Janssen, L.J.J.

1989-01-01

A completes set of models for the mass transfer of indicator ions to gas-evolving electrodes with different behaviour of bubbles is described theoretically. Sliding bubbles, rising detached single bubbles, jumping detached coalescence bubbles and ensembles of these types of bubbles are taken into

Radiobilogical cell survival models

International Nuclear Information System (INIS)

Zackrisson, B.

1992-01-01

A central issue in clinical radiobiological research is the prediction of responses to different radiation qualities. The choice of cell survival and dose-response model greatly influences the results. In this context the relationship between theory and model is emphasized. Generally, the interpretations of experimental data depend on the model. Cell survival models are systematized with respect to their relations to radiobiological theories of cell kill. The growing knowlegde of biological, physical, and chemical mechanisms is reflected in the formulation of new models. The present overview shows that recent modelling has been more oriented towards the stochastic fluctuations connected to radiation energy deposition. This implies that the traditional cell surivival models ought to be complemented by models of stochastic energy deposition processes and repair processes at the intracellular level. (orig.)

Analysis of recent type Ia supernova data based on evolving dark energy models

International Nuclear Information System (INIS)

Park, Jaehong; Park, Chan-Gyung; Hwang, Jai-chan

2011-01-01

We study characters of recent type Ia supernova data using evolving dark energy models with changing equation-of-state parameter w. We consider a sudden-jump approximation of w for some chosen redshift spans with double transitions and constrain these models based on the Markov chain Monte Carlo method using the type Ia supernova data (Constitution, Union, Union2), together with the baryon acoustic oscillation A parameter and the cosmic microwave background shift parameter in a flat background. In the double-transition model, the Constitution data shows deviation outside 1σ from the Λ cold dark matter (ΛCDM) model at low (z < or approx. 0.2) and middle (0.2 < or approx. z < or approx. 0.4) redshift bins, whereas no such deviations are noticeable in the Union and Union2 data. By analyzing the Union members in the Constitution set, however, we show that the same difference is actually due to different calibration of the same Union sample in the Constitution set and is not due to new data added in the Constitution set. All detected deviations are within 2σ from the ΛCDM world model. From the ΛCDM mock data analysis, we quantify biases in the dark energy equation-of-state parameters induced by insufficient data with inhomogeneous distribution of data points in the redshift space and distance modulus errors. We demonstrate that the location of the peak in the distribution of arithmetic means (computed from the Markov chain Monte Carlo chain for each mock data) behaves as an unbiased estimator for the average bias, which is valid even for nonsymmetric likelihood distributions.

Diffusion between evolving interfaces

International Nuclear Information System (INIS)

Juntunen, Janne; Merikoski, Juha

2010-01-01

Diffusion in an evolving environment is studied by continuous-time Monte Carlo simulations. Diffusion is modeled by continuous-time random walkers on a lattice, in a dynamic environment provided by bubbles between two one-dimensional interfaces driven symmetrically towards each other. For one-dimensional random walkers constrained by the interfaces, the bubble size distribution dominates diffusion. For two-dimensional random walkers, it is also controlled by the topography and dynamics of the interfaces. The results of the one-dimensional case are recovered in the limit where the interfaces are strongly driven. Even with simple hard-core repulsion between the interfaces and the particles, diffusion is found to depend strongly on the details of the dynamical rules of particles close to the interfaces.

Weighted Evolving Networks with Self-organized Communities

International Nuclear Information System (INIS)

Xie Zhou; Wang Xiaofan; Li Xiang

2008-01-01

In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of ν ≥ 1, γ > 2, and α > 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness

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

A tissue adaptation model based on strain-dependent collagen degradation and contact-guided cell traction.

Science.gov (United States)

Heck, T A M; Wilson, W; Foolen, J; Cilingir, A C; Ito, K; van Donkelaar, C C

2015-03-18

Soft biological tissues adapt their collagen network to the mechanical environment. Collagen remodeling and cell traction are both involved in this process. The present study presents a collagen adaptation model which includes strain-dependent collagen degradation and contact-guided cell traction. Cell traction is determined by the prevailing collagen structure and is assumed to strive for tensional homeostasis. In addition, collagen is assumed to mechanically fail if it is over-strained. Care is taken to use principally measurable and physiologically meaningful relationships. This model is implemented in a fibril-reinforced biphasic finite element model for soft hydrated tissues. The versatility and limitations of the model are demonstrated by corroborating the predicted transient and equilibrium collagen adaptation under distinct mechanical constraints against experimental observations from the literature. These experiments include overloading of pericardium explants until failure, static uniaxial and biaxial loading of cell-seeded gels in vitro and shortening of periosteum explants. In addition, remodeling under hypothetical conditions is explored to demonstrate how collagen might adapt to small differences in constraints. Typical aspects of all essentially different experimental conditions are captured quantitatively or qualitatively. Differences between predictions and experiments as well as new insights that emerge from the present simulations are discussed. This model is anticipated to evolve into a mechanistic description of collagen adaptation, which may assist in developing load-regimes for functional tissue engineered constructs, or may be employed to improve our understanding of the mechanisms behind physiological and pathological collagen remodeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evolved Control of Natural Plants: Crossing the Reality Gap for User-Defined Steering of Growth and Motion

DEFF Research Database (Denmark)

Hofstadler, Daniel Nicolas; Wahby, Mostafa; Heinrich, Mary Katherine

2017-01-01

in response to the simple controller is captured by image processing, and a model of the plant tip dynamics is developed. The model is used in simulation to evolve a robot controller that steers the plant tip such that it follows a number of randomly generated target points. Finally, we test the simulation-evolved...

Development and the evolvability of human limbs

OpenAIRE

Young, Nathan M.; Wagner, Günter P.; Hallgrímsson, Benedikt

2010-01-01

The long legs and short arms of humans are distinctive for a primate, the result of selection acting in opposite directions on each limb at different points in our evolutionary history. This mosaic pattern challenges our understanding of the relationship of development and evolvability because limbs are serially homologous and genetic correlations should act as a significant constraint on their independent evolution. Here we test a developmental model of limb covariation in anthropoid primate...

Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs

Science.gov (United States)

Suo, Qi; Guo, Jin-Li; Sun, Shiwei; Liu, Han

2018-01-01

A new evolutionary model is proposed to describe the characteristics and evolution pattern of supply chain systems using evolving hypergraphs, in which nodes represent enterprise entities while hyperedges represent the relationships among diverse trades. The nodes arrive at the system in accordance with a Poisson process, with the evolving process incorporating the addition of new nodes, linking of old nodes, and rewiring of links. Grounded in the Poisson process theory and continuum theory, the stationary average hyperdegree distribution is shown to follow a shifted power law (SPL), and the theoretical predictions are consistent with the results of numerical simulations. Testing the impact of parameters on the model yields a positive correlation between hyperdegree and degree. The model also uncovers macro characteristics of the relationships among enterprises due to the microscopic interactions among individuals.

Modeling fuel cell stack systems

Energy Technology Data Exchange (ETDEWEB)

Lee, J H [Los Alamos National Lab., Los Alamos, NM (United States); Lalk, T R [Dept. of Mech. Eng., Texas A and M Univ., College Station, TX (United States)

1998-06-15

A technique for modeling fuel cell stacks is presented along with the results from an investigation designed to test the validity of the technique. The technique was specifically designed so that models developed using it can be used to determine the fundamental thermal-physical behavior of a fuel cell stack for any operating and design configuration. Such models would be useful tools for investigating fuel cell power system parameters. The modeling technique can be applied to any type of fuel cell stack for which performance data is available for a laboratory scale single cell. Use of the technique is demonstrated by generating sample results for a model of a Proton Exchange Membrane Fuel Cell (PEMFC) stack consisting of 125 cells each with an active area of 150 cm{sup 2}. A PEMFC stack was also used in the verification investigation. This stack consisted of four cells, each with an active area of 50 cm{sup 2}. Results from the verification investigation indicate that models developed using the technique are capable of accurately predicting fuel cell stack performance. (orig.)

On the Critical Role of Divergent Selection in Evolvability

Directory of Open Access Journals (Sweden)

Joel Lehman

2016-08-01

Full Text Available An ambitious goal in evolutionary robotics is to evolve increasingly complex robotic behaviors with minimal human design effort. Reaching this goal requires evolutionary algorithms that can unlock from genetic encodings their latent potential for evolvability. One issue clouding this goal is conceptual confusion about evolvability, which often obscures the aspects of evolvability that are important or desirable. The danger from such confusion is that it may establish unrealistic goals for evolvability that prove unproductive in practice. An important issue separate from conceptual confusion is the common misalignment between selection and evolvability in evolutionary robotics. While more expressive encodings can represent higher-level adaptations (e.g. sexual reproduction or developmental systems that increase long-term evolutionary potential (i.e. evolvability, realizing such potential requires gradients of fitness and evolvability to align. In other words, selection is often a critical factor limiting increasing evolvability. Thus, drawing from a series of recent papers, this article seeks to both (1 clarify and focus the ways in which the term evolvability is used within artificial evolution, and (2 argue for the importance of one type of selection, i.e. divergent selection, for enabling evolvability. The main argument is that there is a fundamental connection between divergent selection and evolvability (on both the individual and population level that does not hold for typical goal-oriented selection. The conclusion is that selection pressure plays a critical role in realizing the potential for evolvability, and that divergent selection in particular provides a principled mechanism for encouraging evolvability in artificial evolution.

Evolved H II regions

International Nuclear Information System (INIS)

Churchwell, E.

1975-01-01

A probable evolutionary sequence of H II regions based on six distinct types of observed objects is suggested. Two examples which may deviate from this idealized sequence, are discussed. Even though a size-mean density relation of H II regions can be used as a rough indication of whether a nebula is very young or evolved, it is argued that such a relation is not likely to be useful for the quantitative assignment of ages to H II regions. Evolved H II regions appear to fit into one of four structural types: rings, core-halos, smooth structures, and irregular or filamentary structures. Examples of each type are given with their derived physical parameters. The energy balance in these nebulae is considered. The mass of ionized gas in evolved H II regions is in general too large to trace the nebula back to single compact H II regions. Finally, the morphological type of the Galaxy is considered from its H II region content. 2 tables, 2 figs., 29 refs

f(R) gravity solutions for evolving wormholes

Energy Technology Data Exchange (ETDEWEB)

Bhattacharya, Subhra [Presidency University, Department of Mathematics, Kolkata (India); Chakraborty, Subenoy [Jadavpur University, Department of Mathematics, Kolkata (India)

2017-08-15

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. (orig.)

Hydrodynamic characteristics of the two-phase flow field at gas-evolving electrodes: numerical and experimental studies

Science.gov (United States)

Liu, Cheng-Lin; Sun, Ze; Lu, Gui-Min; Yu, Jian-Guo

2018-05-01

Gas-evolving vertical electrode system is a typical electrochemical industrial reactor. Gas bubbles are released from the surfaces of the anode and affect the electrolyte flow pattern and even the cell performance. In the current work, the hydrodynamics induced by the air bubbles in a cold model was experimentally and numerically investigated. Particle image velocimetry and volumetric three-component velocimetry techniques were applied to experimentally visualize the hydrodynamics characteristics and flow fields in a two-dimensional (2D) plane and a three-dimensional (3D) space, respectively. Measurements were performed at different gas rates. Furthermore, the corresponding mathematical model was developed under identical conditions for the qualitative and quantitative analyses. The experimental measurements were compared with the numerical results based on the mathematical model. The study of the time-averaged flow field, three velocity components, instantaneous velocity and turbulent intensity indicate that the numerical model qualitatively reproduces liquid motion. The 3D model predictions capture the flow behaviour more accurately than the 2D model in this study.

Intrinsic immunogenicity of rapidly-degradable polymers evolves during degradation.

Science.gov (United States)

Andorko, James I; Hess, Krystina L; Pineault, Kevin G; Jewell, Christopher M

2016-03-01

Recent studies reveal many biomaterial vaccine carriers are able to activate immunostimulatory pathways, even in the absence of other immune signals. How the changing properties of polymers during biodegradation impact this intrinsic immunogenicity is not well studied, yet this information could contribute to rational design of degradable vaccine carriers that help direct immune response. We use degradable poly(beta-amino esters) (PBAEs) to explore intrinsic immunogenicity as a function of the degree of polymer degradation and polymer form (e.g., soluble, particles). PBAE particles condensed by electrostatic interaction to mimic a common vaccine approach strongly activate dendritic cells, drive antigen presentation, and enhance T cell proliferation in the presence of antigen. Polymer molecular weight strongly influences these effects, with maximum stimulation at short degradation times--corresponding to high molecular weight--and waning levels as degradation continues. In contrast, free polymer is immunologically inert. In mice, PBAE particles increase the numbers and activation state of cells in lymph nodes. Mechanistic studies reveal that this evolving immunogenicity occurs as the physicochemical properties and concentration of particles change during polymer degradation. This work confirms the immunological profile of degradable, synthetic polymers can evolve over time and creates an opportunity to leverage this feature in new vaccines. Degradable polymers are increasingly important in vaccination, but how the inherent immunogenicity of polymers changes during degradation is poorly understood. Using common rapidly-degradable vaccine carriers, we show that the activation of immune cells--even in the absence of other adjuvants--depends on polymer form (e.g., free, particulate) and the extent of degradation. These changing characteristics alter the physicochemical properties (e.g., charge, size, molecular weight) of polymer particles, driving changes in

Functional Identification of Dendritic Cells in the Teleost Model, Rainbow Trout (Oncorhynchus mykiss)

Science.gov (United States)

Bassity, Elizabeth; Clark, Theodore G.

2012-01-01

Dendritic cells are specialized antigen presenting cells that bridge innate and adaptive immunity in mammals. This link between the ancient innate immune system and the more evolutionarily recent adaptive immune system is of particular interest in fish, the oldest vertebrates to have both innate and adaptive immunity. It is unknown whether dendritic cells co-evolved with the adaptive response, or if the connection between innate and adaptive immunity relied on a fundamentally different cell type early in evolution. We approached this question using the teleost model organism, rainbow trout (Oncorhynchus mykiss), with the aim of identifying dendritic cells based on their ability to stimulate naïve T cells. Adapting mammalian protocols for the generation of dendritic cells, we established a method of culturing highly motile, non-adherent cells from trout hematopoietic tissue that had irregular membrane processes and expressed surface MHCII. When side-by-side mixed leukocyte reactions were performed, these cells stimulated greater proliferation than B cells or macrophages, demonstrating their specialized ability to present antigen and therefore their functional homology to mammalian dendritic cells. Trout dendritic cells were then further analyzed to determine if they exhibited other features of mammalian dendritic cells. Trout dendritic cells were found to have many of the hallmarks of mammalian DCs including tree-like morphology, the expression of dendritic cell markers, the ability to phagocytose small particles, activation by toll-like receptor-ligands, and the ability to migrate in vivo. As in mammals, trout dendritic cells could be isolated directly from the spleen, or larger numbers could be derived from hematopoietic tissue and peripheral blood mononuclear cells in vitro. PMID:22427987

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).

Evolving Technologies: A View to Tomorrow

Science.gov (United States)

Tamarkin, Molly; Rodrigo, Shelley

2011-01-01

Technology leaders must participate in strategy creation as well as operational delivery within higher education institutions. The future of higher education--the view to tomorrow--is irrevocably integrated and intertwined with evolving technologies. This article focuses on two specific evolving technologies: (1) alternative IT sourcing; and (2)…

Impact of the spatial distribution of morphological pattern on the efficiency of electrocatalytic gas evolving reactions

Directory of Open Access Journals (Sweden)

Žerađanin Aleksandar R.

2014-01-01

Full Text Available The efficiency of electrocatalytic gas evolving reactions (hydrogen, chlorine and oxygen evolution is a key challenge for the important industrial processes, such as chlor-alkali electrolysis or water electrolysis. Central issue for the aforementioned electrocatalytic processes is huge power consumption. Experimental results accumulated in the past, as well as some predictive models ("volcano" plots indicate that altering the nature of the electrode material cannot significantly increase the activity of mentioned reactions. Consequently, it is necessary to find a qualitatively different strategy for improving the energy efficiency of electrocatalytic gas evolving reactions. Usually disregarded fact is that the gas evolution is an oscillatory phenomenon. Given the oscillatory behavior, a key parameter of macrokinetics of gas electrode is the frequency of gas-bubble detachment. Bearing in mind that the gas evolution greatly depends on the surface morphology, a methodology is proposed that establishes a rational link between the morphological pattern of electrode with electrode activity and stability. Characterization was performed using advanced analytical tools. Frequency of gas-bubble detachment is obtained in the configuration of scanning electrochemical microscopy (SECM while the corrosion stability is analyzed using miniaturized scanning flow electrochemical cell connected to the mass spectrometer (SFC-ICPMS.

Spacetimes containing slowly evolving horizons

International Nuclear Information System (INIS)

Kavanagh, William; Booth, Ivan

2006-01-01

Slowly evolving horizons are trapping horizons that are ''almost'' isolated horizons. This paper reviews their definition and discusses several spacetimes containing such structures. These include certain Vaidya and Tolman-Bondi solutions as well as (perturbatively) tidally distorted black holes. Taking into account the mass scales and orders of magnitude that arise in these calculations, we conjecture that slowly evolving horizons are the norm rather than the exception in astrophysical processes that involve stellar-scale black holes

Evolved osmotolerant Escherichia coli mutants frequently exhibit defective N-acetylglucosamine catabolism and point mutations in cell shape-regulating protein MreB.

Science.gov (United States)

Winkler, James D; Garcia, Carlos; Olson, Michelle; Callaway, Emily; Kao, Katy C

2014-06-01

Biocatalyst robustness toward stresses imposed during fermentation is important for efficient bio-based production. Osmotic stress, imposed by high osmolyte concentrations or dense populations, can significantly impact growth and productivity. In order to better understand the osmotic stress tolerance phenotype, we evolved sexual (capable of in situ DNA exchange) and asexual Escherichia coli strains under sodium chloride (NaCl) stress. All isolates had significantly improved growth under selection and could grow in up to 0.80 M (47 g/liter) NaCl, a concentration that completely inhibits the growth of the unevolved parental strains. Whole genome resequencing revealed frequent mutations in genes controlling N-acetylglucosamine catabolism (nagC, nagA), cell shape (mrdA, mreB), osmoprotectant uptake (proV), and motility (fimA). Possible epistatic interactions between nagC, nagA, fimA, and proV deletions were also detected when reconstructed as defined mutations. Biofilm formation under osmotic stress was found to be decreased in most mutant isolates, coupled with perturbations in indole secretion. Transcriptional analysis also revealed significant changes in ompACGL porin expression and increased transcription of sulfonate uptake systems in the evolved mutants. These findings expand our current knowledge of the osmotic stress phenotype and will be useful for the rational engineering of osmotic tolerance into industrial strains in the future. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Implications of a Culturally Evolved Self for Notions of Free Will

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Lloyd Hawkeye Robertson

2017-10-01

Full Text Available Most schools in psychology have emphasized individual choice despite evidence of genetic and cultural determinism. It is suggested in this paper that the rejection of classical behaviorism by psychology and other humanities flowed from deeply held cultural assumptions about volition and free will. While compatibilists have suggested that notions of free will and determinism are not mutually exclusive, the psychological mechanisms by which such an accommodation could be explained have been inadequately explored. Drawing on research into classical cultures, this paper builds an argument that the notion of free will was adaptive flowing from culturally evolved changes to the self, and that this “evolved self,” containing assumptions of personal volition, continuity, and reason, became benchmarks of what it means to be human. The paper proposes a model of a culturally evolved self that is compatible with understandings of free will and determinism. Implications for therapeutic practice and future research are discussed.

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.

A Weighted Evolving Network with Community Size Preferential Attachment

International Nuclear Information System (INIS)

Zhuo Zhiwei; Shan Erfang

2010-01-01

Community structure is an important characteristic in real complex network. It is a network consists of groups of nodes within which links are dense but among which links are sparse. In this paper, the evolving network include node, link and community growth and we apply the community size preferential attachment and strength preferential attachment to a growing weighted network model and utilize weight assigning mechanism from BBV model. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

canEvolve: a web portal for integrative oncogenomics.

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Mehmet Kemal Samur

Full Text Available BACKGROUND & OBJECTIVE: Genome-wide profiles of tumors obtained using functional genomics platforms are being deposited to the public repositories at an astronomical scale, as a result of focused efforts by individual laboratories and large projects such as the Cancer Genome Atlas (TCGA and the International Cancer Genome Consortium. Consequently, there is an urgent need for reliable tools that integrate and interpret these data in light of current knowledge and disseminate results to biomedical researchers in a user-friendly manner. We have built the canEvolve web portal to meet this need. RESULTS: canEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. canEvolve provides results of integrative analysis of gene expression profiles with copy number alterations and with miRNA profiles as well as generalized integrative analysis using gene set enrichment analysis. The network analysis capability includes storage and visualization of gene co-expression, inferred gene regulatory networks and protein-protein interaction information. Finally, canEvolve provides correlations between gene expression and clinical outcomes in terms of univariate survival analysis. CONCLUSION: At present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network

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.

Cell Growth Rate Dictates the Onset of Glass to Fluidlike Transition and Long Time Superdiffusion in an Evolving Cell Colony

Science.gov (United States)

Malmi-Kakkada, Abdul N.; Li, Xin; Samanta, Himadri S.; Sinha, Sumit; Thirumalai, D.

2018-04-01

Collective migration dominates many phenomena, from cell movement in living systems to abiotic self-propelling particles. Focusing on the early stages of tumor evolution, we enunciate the principles involved in cell dynamics and highlight their implications in understanding similar behavior in seemingly unrelated soft glassy materials and possibly chemokine-induced migration of CD 8+T cells. We performed simulations of tumor invasion using a minimal three-dimensional model, accounting for cell elasticity and adhesive cell-cell interactions, as well as cell birth and death, to establish that cell-growth-rate-dependent tumor expansion results in the emergence of distinct topological niches. Cells at the periphery move with higher velocity perpendicular to the tumor boundary, while the motion of interior cells is slower and isotropic. The mean-square displacement Δ (t ) of cells exhibits glassy behavior at times comparable to the cell cycle time, while exhibiting superdiffusive behavior, Δ (t )≈tα (α >1 ), at longer times. We derive the value of α ≈1.33 using a field theoretic approach based on stochastic quantization. In the process, we establish the universality of superdiffusion in a class of seemingly unrelated nonequilibrium systems. Superdiffusion at long times arises only if there is an imbalance between cell birth and death rates. Our findings for the collective migration, which also suggest that tumor evolution occurs in a polarized manner, are in quantitative agreement with in vitro experiments. Although set in the context of tumor invasion, the findings should also hold in describing the collective motion in growing cells and in active systems, where creation and annihilation of particles play a role.

Simplified fuel cell system model identification

Energy Technology Data Exchange (ETDEWEB)

Caux, S.; Fadel, M. [Laboratoire d' Electrotechnique et d' Electronique Industrielle, Toulouse (France); Hankache, W. [Laboratoire d' Electrotechnique et d' Electronique Industrielle, Toulouse (France)]|[Laboratoire de recherche en Electronique, Electrotechnique et Systemes, Belfort (France); Hissel, D. [Laboratoire de recherche en Electronique, Electrotechnique et Systemes, Belfort (France)

2006-07-01

This paper discussed a simplified physical fuel cell model used to study fuel cell and supercap energy applications for vehicles. Anode, cathode, membrane, and electrode elements of the cell were modelled. A quasi-static Amphlett model was used to predict voltage responses of the fuel cell as a function of the current, temperature, and partial pressures of the reactive gases. The potential of each cell was multiplied by the number of cells in order to model a fuel cell stack. The model was used to describe the main phenomena associated with current voltage behaviour. Data were then compared with data from laboratory tests conducted on a 20 cell stack subjected to a current and time profile developed using speed data from a vehicle operating in an urban environment. The validated model was used to develop iterative optimization algorithms for an energy management strategy that linked 3 voltage sources with fuel cell parameters. It was concluded that classic state and dynamic measurements using a simple least square algorithm can be used to identify the most important parameters for optimal fuel cell operation. 9 refs., 1 tab., 6 figs.

A mapping closure for turbulent scalar mixing using a time-evolving reference field

Science.gov (United States)

Girimaji, Sharath S.

1992-01-01

A general mapping-closure approach for modeling scalar mixing in homogeneous turbulence is developed. This approach is different from the previous methods in that the reference field also evolves according to the same equations as the physical scalar field. The use of a time-evolving Gaussian reference field results in a model that is similar to the mapping closure model of Pope (1991), which is based on the methodology of Chen et al. (1989). Both models yield identical relationships between the scalar variance and higher-order moments, which are in good agreement with heat conduction simulation data and can be consistent with any type of epsilon(phi) evolution. The present methodology can be extended to any reference field whose behavior is known. The possibility of a beta-pdf reference field is explored. The shortcomings of the mapping closure methods are discussed, and the limit at which the mapping becomes invalid is identified.

Evolving the use of peptides as biomaterials components

Science.gov (United States)

Collier, Joel H.; Segura, Tatiana

2012-01-01

This manuscript is part of a debate on the statement that “the use of short synthetic adhesion peptides, like RGD, is the best approach in the design of biomaterials that guide cell behavior for regenerative medicine and tissue engineering”. We take the position that although there are some acknowledged disadvantages of using short peptide ligands within biomaterials, it is not necessary to discard the notion of using peptides within biomaterials entirely, but rather to reinvent and evolve their use. Peptides possess advantageous chemical definition, access to non-native chemistries, amenability to de novo design, and applicability within parallel approaches. Biomaterials development programs that require such aspects may benefit from a peptide-based strategy. PMID:21515167

On the Benefits of Divergent Search for Evolved Representations

DEFF Research Database (Denmark)

Lehman, Joel; Risi, Sebastian; Stanley, Kenneth O

2012-01-01

Evolved representations in evolutionary computation are often fragile, which can impede representation-dependent mechanisms such as self-adaptation. In contrast, evolved representations in nature are robust, evolvable, and creatively exploit available representational features. This paper provide...

A hybrid mammalian cell cycle model

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Vincent Noël

2013-08-01

Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

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

3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth

KAUST Repository

Perfahl, H.; Byrne, H. M.; Chen, T.; Estrella, V.; Alarcó n, T.; Lapin, A.; Gatenby, R. A.; Gillies, R. J.; Lloyd, M. C.; Maini, P. K.; Reuss, M.; Owen, M. R.

2012-01-01

We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.

3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth

KAUST Repository

Perfahl, H.

2012-11-01

We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.

The genotype-phenotype map of an evolving digital organism

OpenAIRE

Fortuna, Miguel A.; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms fr...

The Evolving Political Economy of Education and the Implications for Educational Evaluation.

Science.gov (United States)

Guthrie, James W.

1990-01-01

Explains the evolving transformation of school systems into engines of economic development, summarizes the conventional orientation of educational evaluation, assesses the impact of the human capital imperative on expectations for evaluation, and proposes a new model for national educational appraisal. (SK)

Cell-oriented modeling of angiogenesis.

Science.gov (United States)

Guidolin, Diego; Rebuffat, Piera; Albertin, Giovanna

2011-01-01

Due to its significant involvement in various physiological and pathological conditions, angiogenesis (the development of new blood vessels from an existing vasculature) represents an important area of the actual biological research and a field in which mathematical modeling proved particularly useful in supporting the experimental work. In this paper, we focus on a specific modeling strategy, known as "cell-centered" approach. This type of mathematical models work at a "mesoscopic scale," assuming the cell as the natural level of abstraction for computational modeling of development. They treat cells phenomenologically, considering their essential behaviors to study how tissue structure and organization emerge from the collective dynamics of multiple cells. The main contributions of the cell-oriented approach to the study of the angiogenic process will be described. From one side, they have generated "basic science understanding" about the process of capillary assembly during development, growth, and pathology. On the other side, models were also developed supporting "applied biomedical research" for the purpose of identifying new therapeutic targets and clinically relevant approaches for either inhibiting or stimulating angiogenesis.

Páramo is the world’s fastest evolving and coolest biodiversity hotspot

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Santiago eMadriñán

2013-10-01

Full Text Available Understanding the processes that cause speciation is a key aim of evolutionary biology. Lineages or biomes that exhibit recent and rapid diversification are ideal model systems for determining these processes. Species rich biomes reported to be of relatively recent origin, i.e., since the beginning of the Miocene, include Mediterranean ecosystems such as the California Floristic Province, oceanic islands such as the Hawaiian archipelago and the Neotropical high elevation ecosystem of the Páramos. Páramos constitute grasslands above the forest tree-line (at elevations of c. 2800–4700 m with high species endemism. Organisms that occupy this ecosystem are a likely product of unique adaptations to an extreme environment that evolved during the last three to five million years when the Andes reached an altitude that was capable of sustaining this type of vegetation. We compared net diversification rates of lineages in fast evolving biomes using 73 dated molecular phylogenies. Based on our sample, we demonstrate that average net diversification rates of Páramo plant lineages are faster than those of other reportedly fast evolving hotspots and that the faster evolving lineages are more likely to be found in Páramos than the other hotspots. Páramos therefore represent the ideal model system for studying diversification processes. Most of the speciation events that we observed in the Páramos (144 out of 177 occurred during the Pleistocene possibly due to the effects of species range contraction and expansion that may have resulted from the well-documented climatic changes during that period. Understanding these effects will assist with efforts to determine how future climatic changes will impact plant populations.

Cell sources for in vitro human liver cell culture models

Science.gov (United States)

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

2016-01-01

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. PMID:27385595

Forming limit prediction by an evolving non-quadratic yield criterion considering the anisotropic hardening and r-value evolution

Science.gov (United States)

Lian, Junhe; Shen, Fuhui; Liu, Wenqi; Münstermann, Sebastian

2018-05-01

The constitutive model development has been driven to a very accurate and fine-resolution description of the material behaviour responding to various environmental variable changes. The evolving features of the anisotropic behaviour during deformation, therefore, has drawn particular attention due to its possible impacts on the sheet metal forming industry. An evolving non-associated Hill48 (enHill48) model was recently proposed and applied to the forming limit prediction by coupling with the modified maximum force criterion. On the one hand, the study showed the significance to include the anisotropic evolution for accurate forming limit prediction. On the other hand, it also illustrated that the enHill48 model introduced an instability region that suddenly decreases the formability. Therefore, in this study, an alternative model that is based on the associated flow rule and provides similar anisotropic predictive capability is extended to chapter the evolving effects and further applied to the forming limit prediction. The final results are compared with experimental data as well as the results by enHill48 model.

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...

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

A clade in the QUASIMODO2 family evolved with vascular plants and supports a role for cell wall composition in adaptation to environmental changes.

Science.gov (United States)

Fuentes, Sara; Pires, Nuno; Østergaard, Lars

2010-08-01

The evolution of plant vascular tissue is tightly linked to the evolution of specialised cell walls. Mutations in the QUASIMODO2 (QUA2) gene from Arabidopsis thaliana were previously shown to result in cell adhesion defects due to reduced levels of the cell wall component homogalacturonic acid. In this study, we provide additional information about the role of QUA2 and its closest paralogues, QUASIMODO2 LIKE1 (QUL1) and QUL2. Within the extensive QUA2 family, our phylogenetic analysis shows that these three genes form a clade that evolved with vascular plants. Consistent with a possible role of this clade in vasculature development, QUA2 is highly expressed in the vascular tissue of embryos and inflorescence stems and overexpression of QUA2 resulted in temperature-sensitive xylem collapse. Moreover, in-depth characterisation of qua2 qul1 qul2 triple mutant and 35S::QUA2 overexpression plants revealed contrasting temperature-dependent stem development with dramatic effects on stem width. Taken together, our results suggest that the QUA2-specific clade contributed to the evolution of vasculature and illustrate the important role that modification of cell wall composition plays in the adaptation to changing environmental conditions, including changes in temperature.

The genotype-phenotype map of an evolving digital organism.

Directory of Open Access Journals (Sweden)

Miguel A Fortuna

2017-02-01

Full Text Available To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences, which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism.

Science.gov (United States)

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

Evolvability as a Quality Attribute of Software Architectures

NARCIS (Netherlands)

Ciraci, S.; van den Broek, P.M.; Duchien, Laurence; D'Hondt, Maja; Mens, Tom

We review the definition of evolvability as it appears on the literature. In particular, the concept of software evolvability is compared with other system quality attributes, such as adaptability, maintainability and modifiability.

Clustering impact regime with shocks in freely evolving granular gas

Science.gov (United States)

Isobe, Masaharu

2017-06-01

A freely cooling granular gas without any external force evolves from the initial homogeneous state to the inhomogeneous clustering state, at which the energy decay deviates from the Haff's law. The asymptotic behavior of energy in the inelastic hard sphere model have been predicted by several theories, which are based on the mode coupling theory or extension of inelastic hard rods gas. In this study, we revisited the clustering regime of freely evolving granular gas via large-scale molecular dynamics simulation with up to 16.7 million inelastic hard disks. We found novel regime regarding on collisions between "clusters" spontaneously appearing after clustering regime, which can only be identified more than a few million particles system. The volumetric dilatation pattern of semicircular shape originated from density shock propagation are well characterized on the appearing of "cluster impact" during the aggregation process of clusters.

Removal of Contaminants from Waste Streams at Gas Evolving Flow-Through Porous Electrodes

International Nuclear Information System (INIS)

Mahmoud Saleh, M.

1999-01-01

Electrochemical techniques have been used for the removal of inorganic and organic toxic materials from industrial waste streams. One of the most important branch of these electrochemical techniques is the flow-through porous electrode. Such systems allow for the continuous operation and hence continuous removal of the contaminants from waste streams at high rates and high efficiency. However, when there is an evolution of gas bubbles with the removal process, the treatment process needs a much different treatment of both the design and the mathematical treatment of the such these systems. The evolving gas bubbles within the electrode decrease the pore electrolyte conductivity of the porous electrodes, decrease the efficiency and make the current more non-uniform. This cause the under utilization of the reaction area and finally make the electrode inoperable. In this work the harmful effects of the gas bubbles on the performance of the porous electrode will be modeled. The model accounts for the effects of kinetic, mass transfer and gas bubbles resistance on the overall performance of the electrode. This will help in optimizing the operating conditions and the cell design

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...

Computer support for physiological cell modelling using an ontology on cell physiology.

Science.gov (United States)

Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda

2006-01-01

The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.

Cell-Oriented Modeling of Angiogenesis

Directory of Open Access Journals (Sweden)

Diego Guidolin

2011-01-01

Full Text Available Due to its significant involvement in various physiological and pathological conditions, angiogenesis (the development of new blood vessels from an existing vasculature represents an important area of the actual biological research and a field in which mathematical modeling proved particularly useful in supporting the experimental work. In this paper, we focus on a specific modeling strategy, known as “cell-centered” approach. This type of mathematical models work at a “mesoscopic scale,” assuming the cell as the natural level of abstraction for computational modeling of development. They treat cells phenomenologically, considering their essential behaviors to study how tissue structure and organization emerge from the collective dynamics of multiple cells. The main contributions of the cell-oriented approach to the study of the angiogenic process will be described. From one side, they have generated “basic science understanding” about the process of capillary assembly during development, growth, and pathology. On the other side, models were also developed supporting “applied biomedical research” for the purpose of identifying new therapeutic targets and clinically relevant approaches for either inhibiting or stimulating angiogenesis.

The aldehyde dehydrogenase, AldA, is essential for L-1,2-propanediol utilization in laboratory-evolved Escherichia coli

DEFF Research Database (Denmark)

Aziz, Ramy K.; Monk, Jonathan M.; Andrews, Kathleen A.

2017-01-01

is highly conserved among members of the family Enterobacteriacea. To test this hypothesis, we first performed computational model simulation, which confirmed the essentiality of the aldA gene for 1,2-PDO utilization by the evolved PDO-degrading E. coli. Next, we deleted the aldA gene from the evolved...

A new evolutionary system for evolving artificial neural networks.

Science.gov (United States)

Yao, X; Liu, Y

1997-01-01

This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

Minority games, evolving capitals and replicator dynamics

International Nuclear Information System (INIS)

Galla, Tobias; Zhang, Yi-Cheng

2009-01-01

We discuss a simple version of the minority game (MG) in which agents hold only one strategy each, but in which their capitals evolve dynamically according to their success and in which the total trading volume varies in time accordingly. This feature is known to be crucial for MGs to reproduce stylized facts of real market data. The stationary states and phase diagram of the model can be computed, and we show that the ergodicity breaking phase transition common for MGs, and marked by a divergence of the integrated response, is present also in this simplified model. An analogous majority game turns out to be relatively void of interesting features, and the total capital is found to diverge in time. Introducing a restraining force leads to a model akin to the replicator dynamics of evolutionary game theory, and we demonstrate that here a different type of phase transition is observed. Finally we briefly discuss the relation of this model with one strategy per player to more sophisticated minority games with dynamical capitals and several trading strategies per agent

Mesenchymal stem cells as therapeutic delivery vehicles targeting tumor stroma

DEFF Research Database (Denmark)

Serakinci, Nedime; Christensen, Rikke; Sørensen, Flemming Brandt

2011-01-01

The field of stem cell biology continues to evolve by characterization of further types of stem cells and by exploring their therapeutic potential for experimental and clinical applications. Human mesenchymal stem cells (hMSCs) are one of the most promising candidates simply because...... better understanding and in vivo supporting data. The homing ability of hMSCs was investigated by creating a human xenograft model by transplanting an ovarian cancer cell line into immunocompromised mice. Then, genetically engineered hMSC-telo1 cells were injected through the tail vein...

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...

Nonsynonymous substitution rate (Ka is a relatively consistent parameter for defining fast-evolving and slow-evolving protein-coding genes

Directory of Open Access Journals (Sweden)

Wang Lei

2011-02-01

Full Text Available Abstract Background Mammalian genome sequence data are being acquired in large quantities and at enormous speeds. We now have a tremendous opportunity to better understand which genes are the most variable or conserved, and what their particular functions and evolutionary dynamics are, through comparative genomics. Results We chose human and eleven other high-coverage mammalian genome data–as well as an avian genome as an outgroup–to analyze orthologous protein-coding genes using nonsynonymous (Ka and synonymous (Ks substitution rates. After evaluating eight commonly-used methods of Ka and Ks calculation, we observed that these methods yielded a nearly uniform result when estimating Ka, but not Ks (or Ka/Ks. When sorting genes based on Ka, we noticed that fast-evolving and slow-evolving genes often belonged to different functional classes, with respect to species-specificity and lineage-specificity. In particular, we identified two functional classes of genes in the acquired immune system. Fast-evolving genes coded for signal-transducing proteins, such as receptors, ligands, cytokines, and CDs (cluster of differentiation, mostly surface proteins, whereas the slow-evolving genes were for function-modulating proteins, such as kinases and adaptor proteins. In addition, among slow-evolving genes that had functions related to the central nervous system, neurodegenerative disease-related pathways were enriched significantly in most mammalian species. We also confirmed that gene expression was negatively correlated with evolution rate, i.e. slow-evolving genes were expressed at higher levels than fast-evolving genes. Our results indicated that the functional specializations of the three major mammalian clades were: sensory perception and oncogenesis in primates, reproduction and hormone regulation in large mammals, and immunity and angiotensin in rodents. Conclusion Our study suggests that Ka calculation, which is less biased compared to Ks and Ka

Interactively Evolving Compositional Sound Synthesis Networks

DEFF Research Database (Denmark)

Jónsson, Björn Þór; Hoover, Amy K.; Risi, Sebastian

2015-01-01

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......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...

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.

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

Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability.

Directory of Open Access Journals (Sweden)

Sam F Greenbury

2016-03-01

Full Text Available Mutational neighbourhoods in genotype-phenotype (GP maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps-a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure-to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i If a particular (non-neutral phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i and ii reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii may instead facilitate evolutionary exploration

Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability

Science.gov (United States)

Greenbury, Sam F.; Schaper, Steffen; Ahnert, Sebastian E.; Louis, Ard A.

2016-01-01

Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so

Human neuronal cell based assay: A new in vitro model for toxicity evaluation of ciguatoxin.

Science.gov (United States)

Coccini, Teresa; Caloni, Francesca; De Simone, Uliana

2017-06-01

Ciguatoxins (CTXs) are emerging marine neurotoxins representing the main cause of ciguatera fish poisoning, an intoxication syndrome which configures a health emergency and constitutes an evolving issue constantly changing due to new vectors and derivatives of CTXs, as well as their presence in new non-endemic areas. The study applied the neuroblastoma cell model of human origin (SH-SY5Y) to evaluate species-specific mechanistic information on CTX toxicity. Metabolic functionality, cell morphology, cytosolic Ca 2+ i responses, neuronal cell growth and proliferation were assessed after short- (4-24h) and long-term exposure (10days) to P-CTX-3C. In SH-SY5Y, P-CTX-3C displayed a powerful cytotoxicity requiring the presence of both Veratridine and Ouabain. SH-SY5Y were very sensitive to Ouabain: 10 and 0.25nM appeared the optimal concentrations, for short- and long-term toxicity studies, respectively, to be used in co-incubation with Veratridine (25μM), simulating the physiological and pathological endogenous Ouabain levels in humans. P-CTX-3C cytotoxic effect, on human neurons co-incubated with OV (Ouabain+Veratridine) mix, was expressed starting from 100pM after short- and 25pM after long-term exposure. Notably, P-CTX-3C alone at 25nM induced cytotoxicity after 24h and prolonged exposure. This human brain-derived cell line appears a suitable cell-based-model to evaluate cytotoxicity of CTX present in marine food contaminated at low toxic levels and to characterize the toxicological profile of other/new congeners. Copyright © 2017 Elsevier B.V. All rights reserved.

Microphysical characteristics of squall-line stratiform precipitation and transition zones inferred using an ice particle property-evolving model

Science.gov (United States)

Jensen, A. A.; Harrington, J. Y.; Morrison, H.

2017-12-01

A quasi-idealized 3D squall line (based on a June 2007 Oklahoma case) is simulated using a novel bulk microphysics scheme called the Ice-Spheroids Habit Model with Aspect-ratio Evolution (ISHMAEL). In ISHMAEL, the evolution of ice particle properties, such as mass, shape, maximum diameter, density, and fall speed, are tracked as these properties evolve from vapor growth, sublimation, riming, and melting. Thus, ice properties evolve from various microphysical processes without needing separate unrimed and rimed ice categories. Simulation results show that ISHMAEL produces both a squall-line transition zone and an enhanced stratiform precipitation region. The ice particle properties produced in this simulation are analyzed and compared to observations to determine the characteristics of ice that lead to the development of these squall-line features. It is shown that rimed particles advected rearward from the convective region produce the enhanced stratiform precipitation region. The development of the transition zone results from hydrometer sorting: the evolution of ice particle properties in the convective region produces specific fall speeds that favor significant ice advecting rearward of the transition zone before reaching the melting level, causing a local minimum in precipitation rate and reflectivity there. Microphysical sensitivity studies, for example turning rime splintering off, that lead to changes in ice particle properties reveal that the fall speed of ice particles largely determines both the location of the enhanced stratiform precipitation region and whether or not a transition zone forms.

Mathematical modeling of cell adhesion in shear flow: application to targeted drug delivery in inflammation and cancer metastasis.

Science.gov (United States)

Jadhav, Sameer; Eggleton, Charles D; Konstantopoulos, Konstantinos

2007-01-01

Cell adhesion plays a pivotal role in diverse biological processes that occur in the dynamic setting of the vasculature, including inflammation and cancer metastasis. Although complex, the naturally occurring processes that have evolved to allow for cell adhesion in the vasculature can be exploited to direct drug carriers to targeted cells and tissues. Fluid (blood) flow influences cell adhesion at the mesoscale by affecting the mechanical response of cell membrane, the intercellular contact area and collisional frequency, and at the nanoscale level by modulating the kinetics and mechanics of receptor-ligand interactions. Consequently, elucidating the molecular and biophysical nature of cell adhesion requires a multidisciplinary approach involving the synthesis of fundamentals from hydrodynamic flow, molecular kinetics and cell mechanics with biochemistry/molecular cell biology. To date, significant advances have been made in the identification and characterization of the critical cell adhesion molecules involved in inflammatory disorders, and, to a lesser degree, in cancer metastasis. Experimental work at the nanoscale level to determine the lifetime, interaction distance and strain responses of adhesion receptor-ligand bonds has been spurred by the advent of atomic force microscopy and biomolecular force probes, although our current knowledge in this area is far from complete. Micropipette aspiration assays along with theoretical frameworks have provided vital information on cell mechanics. Progress in each of the aforementioned research areas is key to the development of mathematical models of cell adhesion that incorporate the appropriate biological, kinetic and mechanical parameters that would lead to reliable qualitative and quantitative predictions. These multiscale mathematical models can be employed to predict optimal drug carrier-cell binding through isolated parameter studies and engineering optimization schemes, which will be essential for developing

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

Evolving technologies drive the new roles of Biomedical Engineering.

Science.gov (United States)

Frisch, P H; St Germain, J; Lui, W

2008-01-01

Rapidly changing technology coupled with the financial impact of organized health care, has required hospital Biomedical Engineering organizations to augment their traditional operational and business models to increase their role in developing enhanced clinical applications utilizing new and evolving technologies. The deployment of these technology based applications has required Biomedical Engineering organizations to re-organize to optimize the manner in which they provide and manage services. Memorial Sloan-Kettering Cancer Center has implemented a strategy to explore evolving technologies integrating them into enhanced clinical applications while optimally utilizing the expertise of the traditional Biomedical Engineering component (Clinical Engineering) to provide expanded support in technology / equipment management, device repair, preventive maintenance and integration with legacy clinical systems. Specifically, Biomedical Engineering is an integral component of the Medical Physics Department which provides comprehensive and integrated support to the Center in advanced physical, technical and engineering technology. This organizational structure emphasizes the integration and collaboration between a spectrum of technical expertise for clinical support and equipment management roles. The high cost of clinical equipment purchases coupled with the increasing cost of service has driven equipment management responsibilities to include significant business and financial aspects to provide a cost effective service model. This case study details the dynamics of these expanded roles, future initiatives and benefits for Biomedical Engineering and Memorial Sloan Kettering Cancer Center.

Methods Evolved by Observation

Science.gov (United States)

Montessori, Maria

2016-01-01

Montessori's idea of the child's nature and the teacher's perceptiveness begins with amazing simplicity, and when she speaks of "methods evolved," she is unveiling a methodological system for observation. She begins with the early childhood explosion into writing, which is a familiar child phenomenon that Montessori has written about…

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.

The evolving Planck mass in classically scale-invariant theories

Energy Technology Data Exchange (ETDEWEB)

Kannike, K.; Raidal, M.; Spethmann, C.; Veermäe, H. [National Institute of Chemical Physics and Biophysics,Rävala 10, 10143 Tallinn (Estonia)

2017-04-05

We consider classically scale-invariant theories with non-minimally coupled scalar fields, where the Planck mass and the hierarchy of physical scales are dynamically generated. The classical theories possess a fixed point, where scale invariance is spontaneously broken. In these theories, however, the Planck mass becomes unstable in the presence of explicit sources of scale invariance breaking, such as non-relativistic matter and cosmological constant terms. We quantify the constraints on such classical models from Big Bang Nucleosynthesis that lead to an upper bound on the non-minimal coupling and require trans-Planckian field values. We show that quantum corrections to the scalar potential can stabilise the fixed point close to the minimum of the Coleman-Weinberg potential. The time-averaged motion of the evolving fixed point is strongly suppressed, thus the limits on the evolving gravitational constant from Big Bang Nucleosynthesis and other measurements do not presently constrain this class of theories. Field oscillations around the fixed point, if not damped, contribute to the dark matter density of the Universe.

The evolving Planck mass in classically scale-invariant theories

Science.gov (United States)

Kannike, K.; Raidal, M.; Spethmann, C.; Veermäe, H.

2017-04-01

We consider classically scale-invariant theories with non-minimally coupled scalar fields, where the Planck mass and the hierarchy of physical scales are dynamically generated. The classical theories possess a fixed point, where scale invariance is spontaneously broken. In these theories, however, the Planck mass becomes unstable in the presence of explicit sources of scale invariance breaking, such as non-relativistic matter and cosmological constant terms. We quantify the constraints on such classical models from Big Bang Nucleosynthesis that lead to an upper bound on the non-minimal coupling and require trans-Planckian field values. We show that quantum corrections to the scalar potential can stabilise the fixed point close to the minimum of the Coleman-Weinberg potential. The time-averaged motion of the evolving fixed point is strongly suppressed, thus the limits on the evolving gravitational constant from Big Bang Nucleosynthesis and other measurements do not presently constrain this class of theories. Field oscillations around the fixed point, if not damped, contribute to the dark matter density of the Universe.

Evolving artificial metalloenzymes via random mutagenesis

Science.gov (United States)

Yang, Hao; Swartz, Alan M.; Park, Hyun June; Srivastava, Poonam; Ellis-Guardiola, Ken; Upp, David M.; Lee, Gihoon; Belsare, Ketaki; Gu, Yifan; Zhang, Chen; Moellering, Raymond E.; Lewis, Jared C.

2018-03-01

Random mutagenesis has the potential to optimize the efficiency and selectivity of protein catalysts without requiring detailed knowledge of protein structure; however, introducing synthetic metal cofactors complicates the expression and screening of enzyme libraries, and activity arising from free cofactor must be eliminated. Here we report an efficient platform to create and screen libraries of artificial metalloenzymes (ArMs) via random mutagenesis, which we use to evolve highly selective dirhodium cyclopropanases. Error-prone PCR and combinatorial codon mutagenesis enabled multiplexed analysis of random mutations, including at sites distal to the putative ArM active site that are difficult to identify using targeted mutagenesis approaches. Variants that exhibited significantly improved selectivity for each of the cyclopropane product enantiomers were identified, and higher activity than previously reported ArM cyclopropanases obtained via targeted mutagenesis was also observed. This improved selectivity carried over to other dirhodium-catalysed transformations, including N-H, S-H and Si-H insertion, demonstrating that ArMs evolved for one reaction can serve as starting points to evolve catalysts for others.

The evolution of resource adaptation: how generalist and specialist consumers evolve.

Science.gov (United States)

Ma, Junling; Levin, Simon A

2006-07-01

Why and how specialist and generalist strategies evolve are important questions in evolutionary ecology. In this paper, with the method of adaptive dynamics and evolutionary branching, we identify conditions that select for specialist and generalist strategies. Generally, generalist strategies evolve if there is a switching benefit; specialists evolve if there is a switching cost. If the switching cost is large, specialists always evolve. If the switching cost is small, even though the consumer will first evolve toward a generalist strategy, it will eventually branch into two specialists.

Evolving insights on metabolism, autophagy and epigenetics in liver myofibroblasts

Directory of Open Access Journals (Sweden)

Zeribe Chike Nwosu

2016-06-01

Full Text Available Liver myofibroblasts (MFB are crucial mediators of extracellular matrix (ECM deposition in liver fibrosis. They arise mainly from hepatic stellate cells (HSCs upon a process termed activation. To a lesser extent, and depending on the cause of liver damage, portal fibroblasts, mesothelial cells and fibrocytes may also contribute to the MFB population. Targeting MFB to reduce liver fibrosis is currently an area of intense research. Unfortunately, a clog in the wheel of antifibrotic therapies is the fact that although MFB are known to mediate scar formation, and participate in liver inflammatory response, many of their molecular portraits are currently unknown. In this review, we discuss recent understanding of MFB in health and diseases, focusing specifically on three evolving research fields: metabolism, autophagy and epigenetics. We have emphasized on therapeutic prospects where applicable and mentioned techniques for use in MFB studies. Subsequently, we highlighted uncharted territories in MFB research to help direct future efforts aimed at bridging gaps in current knowledge.

Adaptation of Escherichia coli to glucose promotes evolvability in lactose.

Science.gov (United States)

Phillips, Kelly N; Castillo, Gerardo; Wünsche, Andrea; Cooper, Tim F

2016-02-01

The selective history of a population can influence its subsequent evolution, an effect known as historical contingency. We previously observed that five of six replicate populations that were evolved in a glucose-limited environment for 2000 generations, then switched to lactose for 1000 generations, had higher fitness increases in lactose than populations started directly from the ancestor. To test if selection in glucose systematically increased lactose evolvability, we started 12 replay populations--six from a population subsample and six from a single randomly selected clone--from each of the six glucose-evolved founder populations. These replay populations and 18 ancestral populations were evolved for 1000 generations in a lactose-limited environment. We found that replay populations were initially slightly less fit in lactose than the ancestor, but were more evolvable, in that they increased in fitness at a faster rate and to higher levels. This result indicates that evolution in the glucose environment resulted in genetic changes that increased the potential of genotypes to adapt to lactose. Genome sequencing identified four genes--iclR, nadR, spoT, and rbs--that were mutated in most glucose-evolved clones and are candidates for mediating increased evolvability. Our results demonstrate that short-term selective costs during selection in one environment can lead to changes in evolvability that confer longer term benefits. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Modeling and Understanding Time-Evolving Scenarios

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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.

Evolving fuzzy rules for relaxed-criteria negotiation.

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Sim, Kwang Mong

2008-12-01

In the literature on automated negotiation, very few negotiation agents are designed with the flexibility to slightly relax their negotiation criteria to reach a consensus more rapidly and with more certainty. Furthermore, these relaxed-criteria negotiation agents were not equipped with the ability to enhance their performance by learning and evolving their relaxed-criteria negotiation rules. The impetus of this work is designing market-driven negotiation agents (MDAs) that not only have the flexibility of relaxing bargaining criteria using fuzzy rules, but can also evolve their structures by learning new relaxed-criteria fuzzy rules to improve their negotiation outcomes as they participate in negotiations in more e-markets. To this end, an evolutionary algorithm for adapting and evolving relaxed-criteria fuzzy rules was developed. Implementing the idea in a testbed, two kinds of experiments for evaluating and comparing EvEMDAs (MDAs with relaxed-criteria rules that are evolved using the evolutionary algorithm) and EMDAs (MDAs with relaxed-criteria rules that are manually constructed) were carried out through stochastic simulations. Empirical results show that: 1) EvEMDAs generally outperformed EMDAs in different types of e-markets and 2) the negotiation outcomes of EvEMDAs generally improved as they negotiated in more e-markets.

Evolving to the edge of chaos: Chance or necessity?

International Nuclear Information System (INIS)

Rai, Vikas; Upadhyay, Ranjit Kumar

2006-01-01

We show that ecological systems evolve to edges of chaos (EOC). This has been demonstrated by analyzing three diverse model ecosystems using numerical simulations in combination with analytical procedures. It has been found that all these systems reside on EOC and display short-term recurrent chaos (strc). The first two are non-linear food chains and the third one is a linear food chain. The dynamics of first two is dictated by deterministic changes in system parameters. In contrast to this, dynamics of the third model system (the linear food chain) is governed by both deterministic changes in system parameters as well as exogenous stochastic perturbations (unforeseen changes in initial conditions) of these dynamical systems

DrawCompileEvolve: Sparking interactive evolutionary art with human creations

DEFF Research Database (Denmark)

Zhang, Jinhong; Taarnby, Rasmus; Liapis, Antonios

2015-01-01

This paper presents DrawCompileEvolve, a web-based drawing tool which allows users to draw simple primitive shapes, group them together or define patterns in their groupings (e.g. symmetry, repetition). The user’s vector drawing is then compiled into an indirectly encoded genetic representation......, which can be evolved interactively, allowing the user to change the image’s colors, patterns and ultimately transform it. The human artist has direct control while drawing the initial seed of an evolutionary run and indirect control while interactively evolving it, thus making DrawCompileEvolve a mixed...

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

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Joseph A. Wayman

2015-03-01

Full Text Available Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge

Did the notochord evolve from an ancient axial muscle? The axochord hypothesis.

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Brunet, Thibaut; Lauri, Antonella; Arendt, Detlev

2015-08-01

The origin of the notochord is one of the key remaining mysteries of our evolutionary ancestry. Here, we present a multi-level comparison of the chordate notochord to the axochord, a paired axial muscle spanning the ventral midline of annelid worms and other invertebrates. At the cellular level, comparative molecular profiling in the marine annelids P. dumerilii and C. teleta reveals expression of similar, specific gene sets in presumptive axochordal and notochordal cells. These cells also occupy corresponding positions in a conserved anatomical topology and undergo similar morphogenetic movements. At the organ level, a detailed comparison of bilaterian musculatures reveals that most phyla form axochord-like muscles, suggesting that such a muscle was already present in urbilaterian ancestors. Integrating comparative evidence at the cell and organ level, we propose that the notochord evolved by modification of a ventromedian muscle followed by the assembly of an axial complex supporting swimming in vertebrate ancestors. © 2015 The Authors. Bioessays published by WILEY Periodicals, Inc.

Classical vs. evolved quenching parameters and procedures in scintillation measurements: The importance of ionization quenching

International Nuclear Information System (INIS)

Bagan, H.; Tarancon, A.; Rauret, G.; Garcia, J.F.

2008-01-01

The quenching parameters used to model detection efficiency variations in scintillation measurements have not evolved since the decade of 1970s. Meanwhile, computer capabilities have increased enormously and ionization quenching has appeared in practical measurements using plastic scintillation. This study compares the results obtained in activity quantification by plastic scintillation of 14 C samples that contain colour and ionization quenchers, using classical (SIS, SCR-limited, SCR-non-limited, SIS(ext), SQP(E)) and evolved (MWA-SCR and WDW) parameters and following three calibration approaches: single step, which does not take into account the quenching mechanism; two steps, which takes into account the quenching phenomena; and multivariate calibration. Two-step calibration (ionization followed by colour) yielded the lowest relative errors, which means that each quenching phenomenon must be specifically modelled. In addition, the sample activity was quantified more accurately when the evolved parameters were used. Multivariate calibration-PLS also yielded better results than those obtained using classical parameters, which confirms that the quenching phenomena must be taken into account. The detection limits for each calibration method and each parameter were close to those obtained theoretically using the Currie approach

Pressure effects on interfacial surface contacts and performance of organic solar cells

NARCIS (Netherlands)

Agyei-Tuffour, B.; Doumon, Nutifafa Y.; Rwenyagila, E. R.; Asare, J.; Oyewole, O. K.; Shen, Z.; Petoukhoff, C. E.; Zebaze Kana, M. G.; Ocarroll, D. M.; Soboyejo, W. O.

2017-01-01

This paper explores the effects of pressure on the interfacial surface contacts and the performance of organic solar cells. A combination of experimental techniques and analytical/computational models is used to study the evolving surface contacts profiles that occur when compliant, semi-rigid and

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

Evolving Capabilities for Virtual Globes

Science.gov (United States)

Glennon, A.

2006-12-01

Though thin-client spatial visualization software like Google Earth and NASA World Wind enjoy widespread popularity, a common criticism is their general lack of analytical functionality. This concern, however, is rapidly being addressed; standard and advanced geographic information system (GIS) capabilities are being developed for virtual globes--though not centralized into a single implementation or software package. The innovation is mostly originating from the user community. Three such capabilities relevant to the earth science, education, and emergency management communities are modeling dynamic spatial phenomena, real-time data collection and visualization, and multi-input collaborative databases. Modeling dynamic spatial phenomena has been facilitated through joining virtual globe geometry definitions--like KML--to relational databases. Real-time data collection uses short scripts to transform user-contributed data into a format usable by virtual globe software. Similarly, collaborative data collection for virtual globes has become possible by dynamically referencing online, multi-person spreadsheets. Examples of these functions include mapping flows within a karst watershed, real-time disaster assessment and visualization, and a collaborative geyser eruption spatial decision support system. Virtual globe applications will continue to evolve further analytical capabilities, more temporal data handling, and from nano to intergalactic scales. This progression opens education and research avenues in all scientific disciplines.

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

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Downey, Brandon; Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-11-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Predator confusion is sufficient to evolve swarming behaviour.

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Olson, Randal S; Hintze, Arend; Dyer, Fred C; Knoester, David B; Adami, Christoph

2013-08-06

Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator-prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator-prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint--predator confusion--could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey.

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network

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Adam ePonzi

2012-03-01

Full Text Available The striatal medium spiny neuron (MSNs network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri stimulus time histograms (PSTH of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioural task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviourally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would in when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and delineate the range of parameters where this behaviour is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

Science.gov (United States)

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

Asymmetries in Cell Division, Cell Size, and Furrowing in the Xenopus laevis Embryo.

Science.gov (United States)

Tassan, Jean-Pierre; Wühr, Martin; Hatte, Guillaume; Kubiak, Jacek

2017-01-01

Asymmetric cell divisions produce two daughter cells with distinct fate. During embryogenesis, this mechanism is fundamental to build tissues and organs because it generates cell diversity. In adults, it remains crucial to maintain stem cells. The enthusiasm for asymmetric cell division is not only motivated by the beauty of the mechanism and the fundamental questions it raises, but has also very pragmatic reasons. Indeed, misregulation of asymmetric cell divisions is believed to have dramatic consequences potentially leading to pathogenesis such as cancers. In diverse model organisms, asymmetric cell divisions result in two daughter cells, which differ not only by their fate but also in size. This is the case for the early Xenopus laevis embryo, in which the two first embryonic divisions are perpendicular to each other and generate two pairs of blastomeres, which usually differ in size: one pair of blastomeres is smaller than the other. Small blastomeres will produce embryonic dorsal structures, whereas the larger pair will evolve into ventral structures. Here, we present a speculative model on the origin of the asymmetry of this cell division in the Xenopus embryo. We also discuss the apparently coincident asymmetric distribution of cell fate determinants and cell-size asymmetry of the 4-cell stage embryo. Finally, we discuss the asymmetric furrowing during epithelial cell cytokinesis occurring later during Xenopus laevis embryo development.

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

Modelling cell population growth with applications to cancer therapy in human tumour cell lines.

Science.gov (United States)

Basse, Britta; Baguley, Bruce C; Marshall, Elaine S; Wake, Graeme C; Wall, David J N

2004-01-01

In this paper we present an overview of the work undertaken to model a population of cells and the effects of cancer therapy. We began with a theoretical one compartment size structured cell population model and investigated its asymptotic steady size distributions (SSDs) (On a cell growth model for plankton, MMB JIMA 21 (2004) 49). However these size distributions are not similar to the DNA (size) distributions obtained experimentally via the flow cytometric analysis of human tumour cell lines (data obtained from the Auckland Cancer Society Research Centre, New Zealand). In our one compartment model, size was a generic term, but in order to obtain realistic steady size distributions we chose size to be DNA content and devised a multi-compartment mathematical model for the cell division cycle where each compartment corresponds to a distinct phase of the cell cycle (J. Math. Biol. 47 (2003) 295). We then incorporated another compartment describing the possible induction of apoptosis (cell death) from mitosis phase (Modelling cell death in human tumour cell lines exposed to anticancer drug paclitaxel, J. Math. Biol. 2004, in press). This enabled us to compare our model to flow cytometric data of a melanoma cell line where the anticancer drug, paclitaxel, had been added. The model gives a dynamic picture of the effects of paclitaxel on the cell cycle. We hope to use the model to describe the effects of other cancer therapies on a number of different cell lines. Copyright 2004 Elsevier Ltd.

Impact of evolving greenhouse gas forcing on the warming signal in regional climate model experiments.

Science.gov (United States)

Jerez, S; López-Romero, J M; Turco, M; Jiménez-Guerrero, P; Vautard, R; Montávez, J P

2018-04-03

Variations in the atmospheric concentrations of greenhouse gases (GHG) may not be included as external forcing when running regional climate models (RCMs); at least, this is a non-regulated, non-documented practice. Here we investigate the so far unexplored impact of considering the rising evolution of the CO 2 , CH 4 , and N 2 O atmospheric concentrations on near-surface air temperature (TAS) trends, for both the recent past and the near future, as simulated by a state-of-the-art RCM over Europe. The results show that the TAS trends are significantly affected by 1-2 K century -1 , which under 1.5 °C global warming translates into a non-negligible impact of up to 1 K in the regional projections of TAS, similarly affecting projections for maximum and minimum temperatures. In some cases, these differences involve a doubling signal, laying further claim to careful reconsideration of the RCM setups with regard to the inclusion of GHG concentrations as an evolving external forcing which, for the sake of research reproducibility and reliability, should be clearly documented in the literature.

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

Retinal Cell Degeneration in Animal Models

Directory of Open Access Journals (Sweden)

Masayuki Niwa

2016-01-01

Full Text Available The aim of this review is to provide an overview of various retinal cell degeneration models in animal induced by chemicals (N-methyl-d-aspartate- and CoCl2-induced, autoimmune (experimental autoimmune encephalomyelitis, mechanical stress (optic nerve crush-induced, light-induced and ischemia (transient retinal ischemia-induced. The target regions, pathology and proposed mechanism of each model are described in a comparative fashion. Animal models of retinal cell degeneration provide insight into the underlying mechanisms of the disease, and will facilitate the development of novel effective therapeutic drugs to treat retinal cell damage.

Death and population dynamics affect mutation rate estimates and evolvability under stress in bacteria.

Science.gov (United States)

Frenoy, Antoine; Bonhoeffer, Sebastian

2018-05-01

numbers of cell divisions are crucial but neglected parameters in the evolvability of a population, and we provide experimental and computational tools and methods to study evolvability under stress, leading to a reassessment of the magnitude and significance of the stress-induced mutagenesis paradigm.

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.

Modelling collective cell migration of neural crest.

Science.gov (United States)

Szabó, András; Mayor, Roberto

2016-10-01

Collective cell migration has emerged in the recent decade as an important phenomenon in cell and developmental biology and can be defined as the coordinated and cooperative movement of groups of cells. Most studies concentrate on tightly connected epithelial tissues, even though collective migration does not require a constant physical contact. Movement of mesenchymal cells is more independent, making their emergent collective behaviour less intuitive and therefore lending importance to computational modelling. Here we focus on such modelling efforts that aim to understand the collective migration of neural crest cells, a mesenchymal embryonic population that migrates large distances as a group during early vertebrate development. By comparing different models of neural crest migration, we emphasize the similarity and complementary nature of these approaches and suggest a future direction for the field. The principles derived from neural crest modelling could aid understanding the collective migration of other mesenchymal cell types. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reconsidering evolved sex differences in jealousy: comment on Harris (2003).

Science.gov (United States)

Sagarin, Brad J

2005-01-01

In a recent article, Harris (2003) concluded that the data do not support the existence of evolved sex differences in jealousy. Harris' review correctly identifies fatal flaws in three lines of evidence (spousal abuse, homicide, morbid jealousy), but her criticism of two other lines of evidence (self-report responses, psychophysiological measures) is based, in part, on a mischaracterization of the evolutionary psychological theory and a misunderstanding of the empirical implications of the theory. When interpreted according to the correct criterion (i.e., an interaction between sex and infidelity type), self-report studies (both forced-choice and non-forced choice) offer strong support for the existence of sex differences in jealousy. Psychophysiological data also offer some support, although these data are weakened by validity-related concerns. In addition, some refutational evidence cited by Harris (responses to real infidelity, responses under cognitive load) actually does not refute the theory. An integrative model that describes how jealousy might result from the interaction of sociocultural variables and evolved sex differences and suggestions for future research directions are discussed.

Mathematical modeling of a zinc/bromine flow cell and a lithium/thionyl chloride primary cell

Energy Technology Data Exchange (ETDEWEB)

Evans, T.I.

1988-01-01

Three mathematical models are presented, one for the secondary zinc/bromine flow cell and two for the lithium/thionyl chloride primary cell. The objectives in this modeling work are to aid in understanding the physical phenomena affecting cell performance, determine methods of improving cell performance and safety, and reduce the experimental efforts needed to develop these electrochemical systems. The zinc/bromine cell model is the first such model to include a porous layer on the bromine electrode and to predict discharge behavior. The model is used to solve simultaneously the component material balances and the electroneutrality condition for the unknowns, species concentrations and the solution potential. Two models are presented for the lithium/thionyl chloride cell. The first model is a detailed one-dimensional model which is used to solve simultaneously the component material balances, Ohm's law relations, and current balance. The independent design criteria are identified from the model development. The second model presented here is a two-dimensional thermal model for the spirally would configuration of the lithium/thionyl chloride cell. This is the first model to address the effects of the spiral geometry on heat transfer in the cell.

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.

Alcohol use and policy formation: an evolving social problem.

Science.gov (United States)

Levine, Amir

2012-01-01

This article explores the evolutionary course that the social problem of alcohol use has taken in the United States since the Colonial Era. This article utilizes a range of theoretical models to analyze the evolving nature of alcohol use from an unrecognized to a perceived social problem. The models used include critical constructionism (Heiner, 2002), top-down policy model (Dye, 2001) and Mauss'(1975) understanding of social problems and movements. These theoretical constructs exhibit the relative nature of alcohol use as a social problem in regards to a specific time, place, and social context as well as the powerful and influential role that social elites have in defining alcohol asa social problem. Studies regarding the development of alcohol policy formation are discussed to illuminate the different powers, constituents, and factors that play a role in alcohol policy formation.Finally, implications for future study are discussed [corrected].

The Rise of CRISPR/Cas for Genome Editing in Stem Cells

Directory of Open Access Journals (Sweden)

Bing Shui

2016-01-01

Full Text Available Genetic manipulation is a powerful tool to establish the causal relationship between a genetic lesion and a particular pathological phenotype. The rise of CRISPR/Cas9 genome-engineering tools overcame the traditional technical bottleneck for routine site-specific genetic manipulation in cells. To create the perfect in vitro cell model, there is significant interest from the stem cell research community to adopt this fast evolving technology. This review addresses this need directly by providing both the up-to-date biochemical rationale of CRISPR-mediated genome engineering and detailed practical guidelines for the design and execution of CRISPR experiments in cell models. Ultimately, this review will serve as a timely and comprehensive guide for this fast developing technology.

Present and future challenges of induced pluripotent stem cells.

Science.gov (United States)

Ohnuki, Mari; Takahashi, Kazutoshi

2015-10-19

Growing old is our destiny. However, the mature differentiated cells making up our body can be rejuvenated to an embryo-like fate called pluripotency which is an ability to differentiate into all cell types by enforced expression of defined transcription factors. The discovery of this induced pluripotent stem cell (iPSC) technology has opened up unprecedented opportunities in regenerative medicine, disease modelling and drug discovery. In this review, we introduce the applications and future perspectives of human iPSCs and we also show how iPSC technology has evolved along the way. © 2015 The Author(s).

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.

Recommendation in evolving online networks

Science.gov (United States)

Hu, Xiao; Zeng, An; Shang, Ming-Sheng

2016-02-01

Recommender system is an effective tool to find the most relevant information for online users. By analyzing the historical selection records of users, recommender system predicts the most likely future links in the user-item network and accordingly constructs a personalized recommendation list for each user. So far, the recommendation process is mostly investigated in static user-item networks. In this paper, we propose a model which allows us to examine the performance of the state-of-the-art recommendation algorithms in evolving networks. We find that the recommendation accuracy in general decreases with time if the evolution of the online network fully depends on the recommendation. Interestingly, some randomness in users' choice can significantly improve the long-term accuracy of the recommendation algorithm. When a hybrid recommendation algorithm is applied, we find that the optimal parameter gradually shifts towards the diversity-favoring recommendation algorithm, indicating that recommendation diversity is essential to keep a high long-term recommendation accuracy. Finally, we confirm our conclusions by studying the recommendation on networks with the real evolution data.

PCBA demand forecasting using an evolving Takagi-Sugeno system

NARCIS (Netherlands)

van Rooijen, M.; Almeida, R.J.; Kaymak, U.

2016-01-01

This paper investigates the use of using an evolving fuzzy system for printed circuit board (PCBA) demand forecasting. The algorithm is based on the evolving Takagi-Sugeno (eTS) fuzzy system, which has the ability to incorporate new patterns by changing its internal structure in an on-line fashion.

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...

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...... that includes studying more complex 3D cell cultures, as well as accelerating aging of the neurons, may help to yield stronger phenotypes in the cultured cells. Thus, the use and application of pluripotent stem cells for modelling disease have already shown to be a powerful approach for discovering more about...

Modeling in the Classroom: An Evolving Learning Tool

Science.gov (United States)

Few, A. A.; Marlino, M. R.; Low, R.

2006-12-01

Among the early programs (early 1990s) focused on teaching Earth System Science were the Global Change Instruction Program (GCIP) funded by NSF through UCAR and the Earth System Science Education Program (ESSE) funded by NASA through USRA. These two programs introduced modeling as a learning tool from the beginning, and they provided workshops, demonstrations and lectures for their participating universities. These programs were aimed at university-level education. Recently, classroom modeling is experiencing a revival of interest. Drs John Snow and Arthur Few conducted two workshops on modeling at the ESSE21 meeting in Fairbanks, Alaska, in August 2005. The Digital Library for Earth System Education (DLESE) at http://www.dlese.org provides web access to STELLA models and tutorials, and UCAR's Education and Outreach (EO) program holds workshops that include training in modeling. An important innovation to the STELLA modeling software by isee systems, http://www.iseesystems.com, called "isee Player" is available as a free download. The Player allows users to view and run STELLA models, change model parameters, share models with colleagues and students, and make working models available on the web. This is important because the expert can create models, and the user can learn how the modeled system works. Another aspect of this innovation is that the educational benefits of modeling concepts can be extended throughout most of the curriculum. The procedure for building a working computer model of an Earth Science System follows this general format: (1) carefully define the question(s) for which you seek the answer(s); (2) identify the interacting system components and inputs contributing to the system's behavior; (3) collect the information and data that will be required to complete the conceptual model; (4) construct a system diagram (graphic) of the system that displays all of system's central questions, components, relationships and required inputs. At this stage

Formation of a cylindrical bridge in cell division

Science.gov (United States)

Citron, Daniel; Schmidt, Laura E.; Reichl, Elizabeth; Ren, Yixin; Robinson, Douglas; Zhang, Wendy W.

2007-11-01

In nature, the shape transition associated with the division of a mother cell into two daughter cells proceeds via a variety of routes. In the cylinder-thinning route, which has been observed in Dictyostelium and most animal cells, the mother cell first forms a broad bridge-like region, also known as a furrow, between two daughter cells. The furrow then rapidly evolves into a cylindrical bridge, which thins and eventually severs the mother cell into two. The fundamental mechanism underlying this division route is not understood. Recent experiments on Dictyostelium found that, while the cylinder-thinning route persists even when key actin cross-linking proteins are missing, it is disrupted by the removal of force-generating myosin-II proteins. Other measurements revealed that mutant cells lacking myosin-II have a much more uniform tension over the cell surface than wild-type cells. This suggests that tension variation may be important. Here we use a fluid model, previously shown to reproduce the thinning dynamics [Zhang & Robinson, PNAS 102, 7186 (2005)], to test this idea. Consistent with the experiments, the model shows that the cylinder formation process occurs regardless of the exact viscoelastic properties of the cell. In contrast to the experiments, a tension variation in the model hinders, rather then expedites, the cylinder formation.

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.

Random Walk Model for Cell-To-Cell Misalignments in Accelerator Structures

International Nuclear Information System (INIS)

Stupakov, Gennady

2000-01-01

Due to manufacturing and construction errors, cells in accelerator structures can be misaligned relative to each other. As a consequence, the beam generates a transverse wakefield even when it passes through the structure on axis. The most important effect is the long-range transverse wakefield that deflects the bunches and causes growth of the bunch train projected emittance. In this paper, the effect of the cell-to-cell misalignments is evaluated using a random walk model that assumes that each cell is shifted by a random step relative to the previous one. The model is compared with measurements of a few accelerator structures

A simplified model for dynamics of cell rolling and cell-surface adhesion

International Nuclear Information System (INIS)

Cimrák, Ivan

2015-01-01

We propose a three dimensional model for the adhesion and rolling of biological cells on surfaces. We study cells moving in shear flow above a wall to which they can adhere via specific receptor-ligand bonds based on receptors from selectin as well as integrin family. The computational fluid dynamics are governed by the lattice-Boltzmann method. The movement and the deformation of the cells is described by the immersed boundary method. Both methods are fully coupled by implementing a two-way fluid-structure interaction. The adhesion mechanism is modelled by adhesive bonds including stochastic rules for their creation and rupture. We explore a simplified model with dissociation rate independent of the length of the bonds. We demonstrate that this model is able to resemble the mesoscopic properties, such as velocity of rolling cells

Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games

DEFF Research Database (Denmark)

Hintze, Arend; Olson, Randal; Lehman, Joel Anthony

2016-01-01

Computer games are most engaging when their difficulty is well matched to the player's ability, thereby providing an experience in which the player is neither overwhelmed nor bored. In games where the player interacts with computer-controlled opponents, the difficulty of the game can be adjusted...... not only by changing the distribution of opponents or game resources, but also through modifying the skill of the opponents. Applying evolutionary algorithms to evolve the artificial intelligence that controls opponent agents is one established method for adjusting opponent difficulty. Less-evolved agents...... (i.e. agents subject to fewer generations of evolution) make for easier opponents, while highly-evolved agents are more challenging to overcome. In this publication we test a new approach for difficulty adjustment in games: orthogonally evolved AI, where the player receives support from collaborating...

NKT cell self-reactivity: evolutionary master key of immune homeostasis?

DEFF Research Database (Denmark)

Navikas, Shohreh

2011-01-01

Complex immune responses have evolved to protect multicellular organisms against the invasion of pathogens. This has exerted strong developmental pressure for specialized functions that can also limit damage to self-tissue. Two arms of immunity, the innate and adaptive immune system, have evolved...... through evolution by higher vertebrates could be related to their central function as master regulators of immune homeostasis that in part is shared with regulatory T cells. Hypothetical views on how self-reactive NKT cells secure such a central role will also be proposed.......Complex immune responses have evolved to protect multicellular organisms against the invasion of pathogens. This has exerted strong developmental pressure for specialized functions that can also limit damage to self-tissue. Two arms of immunity, the innate and adaptive immune system, have evolved....... The recent finding of self-peptide reactivity of NKT cells in the context of CD1d, with capacity to regulate multiple autoimmune and inflammatory conditions, motivates the current proposal that self-reactive NKT cells might be the ancestral link between present NK and T cells. Their parallel selection...

Infrared Model Spectra for Evolving Red Supergiants

Directory of Open Access Journals (Sweden)

Kyung-Won Suh

1993-06-01

Full Text Available The space and ground based infrared spectra of red supergiants are modeled and arranged in order of their evolutionary status with their theoretical model parameters. The chemical compositions of the dust shells around red supergiants are affected by the nuclear reaction and dredge-up processes of the cental stars. The processes are sensitively dependent on the initial mass, the initial chemical composition, and the evolutionary status. Miras, infrared carbon stars, and OH/IR stars have close link in their evolution in manu aspects, i,e., the chemical composition, the optical depths and the mass loss rates. The evolutionary tracks for the three classes of red supergiants on infrared two-color diagrams have been made from model calculations and IRAS observational data.

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.

Radiobiological modelling with MarCell software

International Nuclear Information System (INIS)

Hasan, J.S.; Jones, T.D.

1996-01-01

Jones introduced a bone marrow radiation cell kinetics model with great potential for application in the fields of health physics, radiation research, and medicine. However, until recently, only the model developers have been able to apply it because of the complex array of biological and physical assignments needed for evaluation of a particular radiation exposure protocol. The purpose of this article is to illustrate the use of MarCell (MARrow CELL Kinetics) software for MS-DOS, a user-friendly computer implementation of that mathematical model that allows almost anyone with an elementary knowledge of radiation physics and/or medical procedures to apply the model. A hands-on demonstration of the software will be given by guiding the user through evaluation of a medical total body irradiation protocol and a nuclear fallout scenario. A brief overview of the software is given in the Appendix

Criticality is an emergent property of genetic networks that exhibit evolvability.

Directory of Open Access Journals (Sweden)

Christian Torres-Sosa

Full Text Available Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype while allowing for switching between multiple phenotypes (network states as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations. We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i preserve all the already acquired phenotypes (dynamical attractor states and (ii generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation while conserving the existing phenotypes (conservation suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape.

Action potential conduction between a ventricular cell model and an isolated ventricular cell

NARCIS (Netherlands)

Wilders, R.; Kumar, R.; Joyner, R. W.; Jongsma, H. J.; Verheijck, E. E.; Golod, D.; van Ginneken, A. C.; Goolsby, W. N.

1996-01-01

We used the Luo and Rudy (LR) mathematical model of the guinea pig ventricular cell coupled to experimentally recorded guinea pig ventricular cells to investigate the effects of geometrical asymmetry on action potential propagation. The overall correspondence of the LR cell model with the recorded

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.

Cancer Stem Cells of Differentiated B-Cell Malignancies: Models and Consequences

International Nuclear Information System (INIS)

Gross, Emilie; Quillet-Mary, Anne; Ysebaert, Loic; Laurent, Guy; Fournie, Jean-Jacques

2011-01-01

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

Repair-misrepair model of cell survival

International Nuclear Information System (INIS)

Tobias, C.A.; Blakely, E.A.; Ngo, F.Q.H.

1980-01-01

During the last three years a new model, the repair-misrepair model (RMR) has been proposed, to interpret radiobiological experiments with heavy ions. In using the RMR model it became apparent that some of its features are suitable for handling the effects produced by a variety of environmental agents in addition to ionizing radiation. Two separate sequences of events are assumed to take place in an irradiated cell. The first sequence begins with an initial energy transfer consisting of ionizations and excitations, culminating via fast secondary physical and chemical processes in established macromolecular lesions in essential cell structures. The second sequence contains the responses of the cell to the lesions and consists of the processes of recognition and molecular repair. In normal cells there exists one repair process or at most a few enzymatic repair processes for each essential macromolecular lesion. The enzymatic repair processes may last for hours and minutes, and can be separated in time from the initial physicochemical and later genetic phases

Cell reprogramming modelled as transitions in a hierarchy of cell cycles

International Nuclear Information System (INIS)

Hannam, Ryan; Annibale, Alessia; Kühn, Reimer

2017-01-01

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. (paper)

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.

Consideration of time-evolving capacity distributions and improved degradation models for seismic fragility assessment of aging highway bridges

International Nuclear Information System (INIS)

Ghosh, Jayadipta; Sood, Piyush

2016-01-01

This paper presents a methodology to develop seismic fragility curves for deteriorating highway bridges by uniquely accounting for realistic pitting corrosion deterioration and time-dependent capacity distributions for reinforced concrete columns under chloride attacks. The proposed framework offers distinct improvements over state-of-the-art procedures for fragility assessment of degrading bridges which typically assume simplified uniform corrosion deterioration model and pristine limit state capacities. Depending on the time in service life and deterioration mechanism, this study finds that capacity limit states for deteriorating bridge columns follow either lognormal distribution or generalized extreme value distributions (particularly for pitting corrosion). Impact of column degradation mechanism on seismic response and fragility of bridge components and system is assessed using nonlinear time history analysis of three-dimensional finite element bridge models reflecting the uncertainties across structural modeling parameters, deterioration parameters and ground motion. Comparisons are drawn between the proposed methodology and traditional approaches to develop aging bridge fragility curves. Results indicate considerable underestimations of system level fragility across different damage states using the traditional approach compared to the proposed realistic pitting model for chloride induced corrosion. Time-dependent predictive functions are provided to interpolate logistic regression coefficients for continuous seismic reliability evaluation along the service life with reasonable accuracy. - Highlights: • Realistic modeling of chloride induced corrosion deterioration in the form of pitting. • Time-evolving capacity distribution for aging bridge columns under chloride attacks. • Time-dependent seismic fragility estimation of highway bridges at component and system level. • Mathematical functions for continuous tracking of seismic fragility along service

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.

Chemical Equilibrium Models for the S3 State of the Oxygen-Evolving Complex of Photosystem II.

Science.gov (United States)

Isobe, Hiroshi; Shoji, Mitsuo; Shen, Jian-Ren; Yamaguchi, Kizashi

2016-01-19

We have performed hybrid density functional theory (DFT) calculations to investigate how chemical equilibria can be described in the S3 state of the oxygen-evolving complex in photosystem II. For a chosen 340-atom model, 1 stable and 11 metastable intermediates have been identified within the range of 13 kcal mol(-1) that differ in protonation, charge, spin, and conformational states. The results imply that reversible interconversion of these intermediates gives rise to dynamic equilibria that involve processes with relocations of protons and electrons residing in the Mn4CaO5 cluster, as well as bound water ligands, with concomitant large changes in the cluster geometry. Such proton tautomerism and redox isomerism are responsible for reversible activation/deactivation processes of substrate oxygen species, through which Mn-O and O-O bonds are transiently ruptured and formed. These results may allow for a tentative interpretation of kinetic data on substrate water exchange on the order of seconds at room temperature, as measured by time-resolved mass spectrometry. The reliability of the hybrid DFT method for the multielectron redox reaction in such an intricate system is also addressed.

Symbiotic Composition and Evolvability

OpenAIRE

Watson, Richard A.; Pollack, Jordan B.

2001-01-01

Several of the Major Transitions in natural evolution, such as the symbiogenic origin of eukaryotes from prokaryotes, share the feature that existing entities became the components of composite entities at a higher level of organisation. This composition of pre-adapted extant entities into a new whole is a fundamentally different source of variation from the gradual accumulation of small random variations, and it has some interesting consequences for issues of evolvability. In this paper we p...

Cell-free DNA in a three-dimensional spheroid cell culture model

DEFF Research Database (Denmark)

Aucamp, Janine; Calitz, Carlemi; Bronkhorst, Abel J.

2017-01-01

Background Investigating the biological functions of cell-free DNA (cfDNA) is limited by the interference of vast numbers of putative sources and causes of DNA release into circulation. Utilization of three-dimensional (3D) spheroid cell cultures, models with characteristics closer to the in vivo...... cultures can serve as effective, simplified in vivo-simulating “closed-circuit” models since putative sources of cfDNA are limited to only the targeted cells. In addition, cfDNA can also serve as an alternative or auxiliary marker for tracking spheroid growth, development and culture stability. Biological...... significance 3D cell cultures can be used to translate “closed-circuit” in vitro model research into data that is relevant for in vivo studies and clinical applications. In turn, the utilization of cfDNA during 3D culture research can optimize sample collection without affecting the stability of the growth...

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...

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...

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

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.

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...... and transition probabilities using the classic Baum-Welch algorithm. The system is tested on the problem of finding the promoter and coding region of C. jejuni. The resulting HMM has a superior discrimination ability to a handcrafted model that has been published in the literature....

Numerical modelling of CIGS/CdS solar cell

Science.gov (United States)

Devi, Nisha; Aziz, Anver; Datta, Shouvik

2018-05-01

In this work, we design and analyze the Cu(In,Ga)Se2 (CIGS) solar cell using simulation software "Solar Cell Capacitance Simulator in One Dimension (SCAPS-1D)". The conventional CIGS solar cell uses various layers, like intrinsic ZnO/Aluminium doped ZnO as transparent oxide, antireflection layer MgF2, and electron back reflection (EBR) layer at CIGS/Mo interface for good power conversion efficiency. We replace this conventional model by a simple model which is easy to fabricate and also reduces the cost of this cell because of use of lesser materials. The new designed model of CIGS solar cell is ITO/CIGS/OVC/CdS/Metal contact, where OVC is ordered vacancy compound. From this simple structure, even at very low illumination we are getting good results. We simulate this CIGS solar cell model by varying various physical parameters of CIGS like thickness, carrier density, band gap and temperature.

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.

Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

Science.gov (United States)

Frost, S. A.; Balas, M. J.

2010-01-01

We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.

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...

Qualitative Functional Decomposition Analysis of Evolved Neuromorphic Flight Controllers

Directory of Open Access Journals (Sweden)

Sanjay K. Boddhu

2012-01-01

Full Text Available In the previous work, it was demonstrated that one can effectively employ CTRNN-EH (a neuromorphic variant of EH method methodology to evolve neuromorphic flight controllers for a flapping wing robot. This paper describes a novel frequency grouping-based analysis technique, developed to qualitatively decompose the evolved controllers into explainable functional control blocks. A summary of the previous work related to evolving flight controllers for two categories of the controller types, called autonomous and nonautonomous controllers, is provided, and the applicability of the newly developed decomposition analysis for both controller categories is demonstrated. Further, the paper concludes with appropriate discussion of ongoing work and implications for possible future work related to employing the CTRNN-EH methodology and the decomposition analysis techniques presented in this paper.

A mathematical model of cancer cells with phenotypic plasticity

Directory of Open Access Journals (Sweden)

Da Zhou

2015-12-01

Full Text Available Purpose: The phenotypic plasticity of cancer cells is recently becoming a cutting-edge research area in cancer, which challenges the cellular hierarchy proposed by the conventional cancer stem cell theory. In this study, we establish a mathematical model for describing the phenotypic plasticity of cancer cells, based on which we try to find some salient features that can characterize the dynamic behavior of the phenotypic plasticity especially in comparison to the hierarchical model of cancer cells. Methods: We model cancer as population dynamics composed of different phenotypes of cancer cells. In this model, not only can cancer cells divide (symmetrically and asymmetrically and die, but they can also convert into other cellular phenotypes. According to the Law of Mass Action, the cellular processes can be captured by a system of ordinary differential equations (ODEs. On one hand, we can analyze the long-term stability of the model by applying qualitative method of ODEs. On the other hand, we are also concerned about the short-term behavior of the model by studying its transient dynamics. Meanwhile, we validate our model to the cell-state dynamics in published experimental data.Results: Our results show that the phenotypic plasticity plays important roles in both stabilizing the distribution of different phenotypic mixture and maintaining the cancer stem cells proportion. In particular, the phenotypic plasticity model shows decided advantages over the hierarchical model in predicting the phenotypic equilibrium and cancer stem cells’ overshoot reported in previous biological experiments in cancer cell lines.Conclusion: Since the validity of the phenotypic plasticity paradigm and the conventional cancer stem cell theory is still debated in experimental biology, it is worthy of theoretically searching for good indicators to distinguish the two models through quantitative methods. According to our study, the phenotypic equilibrium and overshoot

A bistable model of cell polarity.

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Matteo Semplice

Full Text Available Ultrasensitivity, as described by Goldbeter and Koshland, has been considered for a long time as a way to realize bistable switches in biological systems. It is not as well recognized that when ultrasensitivity and reinforcing feedback loops are present in a spatially distributed system such as the cell plasmamembrane, they may induce bistability and spatial separation of the system into distinct signaling phases. Here we suggest that bistability of ultrasensitive signaling pathways in a diffusive environment provides a basic mechanism to realize cell membrane polarity. Cell membrane polarization is a fundamental process implicated in several basic biological phenomena, such as differentiation, proliferation, migration and morphogenesis of unicellular and multicellular organisms. We describe a simple, solvable model of cell membrane polarization based on the coupling of membrane diffusion with bistable enzymatic dynamics. The model can reproduce a broad range of symmetry-breaking events, such as those observed in eukaryotic directional sensing, the apico-basal polarization of epithelium cells, the polarization of budding and mating yeast, and the formation of Ras nanoclusters in several cell types.

Mechanisms of Cancer Cell Dormancy--Another Hallmark of Cancer?

Science.gov (United States)

Yeh, Albert C; Ramaswamy, Sridhar

2015-12-01

Disease relapse in cancer patients many years after clinical remission, often referred to as cancer dormancy, is well documented but remains an incompletely understood phenomenon on the biologic level. Recent reviews have summarized potential models that can explain this phenomenon, including angiogenic, immunologic, and cellular dormancy. We focus on mechanisms of cellular dormancy as newer biologic insights have enabled better understanding of this process. We provide a historical context, synthesize current advances in the field, and propose a mechanistic framework that treats cancer cell dormancy as a dynamic cell state conferring a fitness advantage to an evolving malignancy under stress. Cellular dormancy appears to be an active process that can be toggled through a variety of signaling mechanisms that ultimately downregulate the RAS/MAPK and PI(3)K/AKT pathways, an ability that is preserved even in cancers that constitutively depend on these pathways for their growth and survival. Just as unbridled proliferation is a key hallmark of cancer, the ability of cancer cells to become quiescent may be critical to evolving malignancies, with implications for understanding cancer initiation, progression, and treatment resistance. ©2015 American Association for Cancer Research.

A synergism between adaptive effects and evolvability drives whole genome duplication to fixation.

Science.gov (United States)

Cuypers, Thomas D; Hogeweg, Paulien

2014-04-01

Whole genome duplication has shaped eukaryotic evolutionary history and has been associated with drastic environmental change and species radiation. While the most common fate of WGD duplicates is a return to single copy, retained duplicates have been found enriched for highly interacting genes. This pattern has been explained by a neutral process of subfunctionalization and more recently, dosage balance selection. However, much about the relationship between environmental change, WGD and adaptation remains unknown. Here, we study the duplicate retention pattern postWGD, by letting virtual cells adapt to environmental changes. The virtual cells have structured genomes that encode a regulatory network and simple metabolism. Populations are under selection for homeostasis and evolve by point mutations, small indels and WGD. After populations had initially adapted fully to fluctuating resource conditions re-adaptation to a broad range of novel environments was studied by tracking mutations in the line of descent. WGD was established in a minority (≈30%) of lineages, yet, these were significantly more successful at re-adaptation. Unexpectedly, WGD lineages conserved more seemingly redundant genes, yet had higher per gene mutation rates. While WGD duplicates of all functional classes were significantly over-retained compared to a model of neutral losses, duplicate retention was clearly biased towards highly connected TFs. Importantly, no subfunctionalization occurred in conserved pairs, strongly suggesting that dosage balance shaped retention. Meanwhile, singles diverged significantly. WGD, therefore, is a powerful mechanism to cope with environmental change, allowing conservation of a core machinery, while adapting the peripheral network to accommodate change.

A synergism between adaptive effects and evolvability drives whole genome duplication to fixation.

Directory of Open Access Journals (Sweden)

Thomas D Cuypers

2014-04-01

Full Text Available Whole genome duplication has shaped eukaryotic evolutionary history and has been associated with drastic environmental change and species radiation. While the most common fate of WGD duplicates is a return to single copy, retained duplicates have been found enriched for highly interacting genes. This pattern has been explained by a neutral process of subfunctionalization and more recently, dosage balance selection. However, much about the relationship between environmental change, WGD and adaptation remains unknown. Here, we study the duplicate retention pattern postWGD, by letting virtual cells adapt to environmental changes. The virtual cells have structured genomes that encode a regulatory network and simple metabolism. Populations are under selection for homeostasis and evolve by point mutations, small indels and WGD. After populations had initially adapted fully to fluctuating resource conditions re-adaptation to a broad range of novel environments was studied by tracking mutations in the line of descent. WGD was established in a minority (≈30% of lineages, yet, these were significantly more successful at re-adaptation. Unexpectedly, WGD lineages conserved more seemingly redundant genes, yet had higher per gene mutation rates. While WGD duplicates of all functional classes were significantly over-retained compared to a model of neutral losses, duplicate retention was clearly biased towards highly connected TFs. Importantly, no subfunctionalization occurred in conserved pairs, strongly suggesting that dosage balance shaped retention. Meanwhile, singles diverged significantly. WGD, therefore, is a powerful mechanism to cope with environmental change, allowing conservation of a core machinery, while adapting the peripheral network to accommodate change.

The gaseous haloes of evolving galaxies: a probe using the linear sizes of radio sources

International Nuclear Information System (INIS)

Subramanian, K.; Swarup, G.

1990-01-01

As galaxies form and evolve, their gaseous haloes are expected to undergo corresponding evolution. We examine here whether observations of the linear sizes of radio sources can be used to probe such evolution. For this purpose we first represent the gas density at various stages of galaxy formation and evolution by means of simple model density profiles, and then work out the expected linear sizes (l) of radio sources in these models. (author)

Evolving Spiking Neural Networks for Recognition of Aged Voices.

Science.gov (United States)

Silva, Marco; Vellasco, Marley M B R; Cataldo, Edson

2017-01-01

The aging of the voice, known as presbyphonia, is a natural process that can cause great change in vocal quality of the individual. This is a relevant problem to those people who use their voices professionally, and its early identification can help determine a suitable treatment to avoid its progress or even to eliminate the problem. This work focuses on the development of a new model for the identification of aging voices (independently of their chronological age), using as input attributes parameters extracted from the voice and glottal signals. The proposed model, named Quantum binary-real evolving Spiking Neural Network (QbrSNN), is based on spiking neural networks (SNNs), with an unsupervised training algorithm, and a Quantum-Inspired Evolutionary Algorithm that automatically determines the most relevant attributes and the optimal parameters that configure the SNN. The QbrSNN model was evaluated in a database composed of 120 records, containing samples from three groups of speakers. The results obtained indicate that the proposed model provides better accuracy than other approaches, with fewer input attributes. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Views on Evolvability of Embedded Systems

NARCIS (Netherlands)

Laar, P. van de; Punter, T.

2011-01-01

Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

Views on evolvability of embedded systems

NARCIS (Netherlands)

Laar, van de P.J.L.J.; Punter, H.T.

2011-01-01

Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

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.

; this was not observed with ovalbumin and blank solution. An example of the results is shown in Figure 2 for IL-17A. An established co-culture of Caco-2, THP-1 and MUTZ-3 cells showed promise as an in vitro model for testing of oral vaccine formulations. Mobility of co-culture immune cells as well as cytokine production......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...

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.

Modelling solar cells with thermal phenomena taken into account

International Nuclear Information System (INIS)

Górecki, K; Górecki, P; Paduch, K

2014-01-01

The paper is devoted to modelling properties of solar cells. The authors' electrothermal model of such cells is described. This model takes into account the influence of temperature on its characteristics. Some results of calculations and measurements of selected solar cells are presented and discussed. The good agreement between the results of calculations and measurements was obtained, which proves the correctness of the elaborated model.

Why did heterospory evolve?

Science.gov (United States)

Petersen, Kurt B; Burd, Martin

2017-08-01

The primitive land plant life cycle featured the production of spores of unimodal size, a condition called homospory. The evolution of bimodal size distributions with small male spores and large female spores, known as heterospory, was an innovation that occurred repeatedly in the history of land plants. The importance of desiccation-resistant spores for colonization of the land is well known, but the adaptive value of heterospory has never been well established. It was an addition to a sexual life cycle that already involved male and female gametes. Its role as a precursor to the evolution of seeds has received much attention, but this is an evolutionary consequence of heterospory that cannot explain the transition from homospory to heterospory (and the lack of evolutionary reversal from heterospory to homospory). Enforced outcrossing of gametophytes has often been mentioned in connection to heterospory, but we review the shortcomings of this argument as an explanation of the selective advantage of heterospory. Few alternative arguments concerning the selective forces favouring heterospory have been proposed, a paucity of attention that is surprising given the importance of this innovation in land plant evolution. In this review we highlight two ideas that may lead us to a better understanding of why heterospory evolved. First, models of optimal resource allocation - an approach that has been used for decades in evolutionary ecology to help understand parental investment and other life-history patterns - suggest that an evolutionary increase in spore size could reach a threshold at which small spores yielding small, sperm-producing gametophytes would return greater fitness per unit of resource investment than would large spores and bisexual gametophytes. With the advent of such microspores, megaspores would evolve under frequency-dependent selection. This argument can account for the appearance of heterospory in the Devonian, when increasingly tall and complex

Risk factors which cause senile cataract evolvement: outline

Directory of Open Access Journals (Sweden)

E.V. Bragin

2018-03-01

Full Text Available Examination of natural ageing processes including those caused by multiple external factors has been attracting re-searchers' attention over the last years. Senile cataract is a multi-factor disease. Expenditure on cataract surgery remain one of the greatest expenses items in public health care. Age is a basic factor which causes senile cataract. Morbidity with cataract doubles each 10 years of life. This outline considers some literature sources which describe research results on influence exerted on cataract evolvement by such risk factors as age, sex, race, smoking, alcohol intake, pancreatic diabetes, intake of certain medications, a number of environmental factors including ultraviolet and ionizing radiation. mane of these factors are shown to increase or reduce senile cataract risk; there are conflicting data on certain factors. The outline also contains quantitative characteristics of cataract risks which are given via odds relation and evolve due to age parameters impacts, alcohol intake, ionizing radiation, etc. The authors also state that still there is no answer to the question whether dose-effect relationship for cataract evolvement is a threshold or non-threshold.

THP-1 cell line: an in vitro cell model for immune modulation approach.

Science.gov (United States)

Chanput, Wasaporn; Mes, Jurriaan J; Wichers, Harry J

2014-11-01

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 attempts to summarize and discuss recent publications related to the THP-1 cell model. An overview on the biological similarities and dissimilarities between the THP-1 cell line and human peripheral blood mononuclear cell (PBMC) derived-monocytes and macrophages, as well as the advantages and disadvantages of the use of THP-1 cell line, is included. The review summarizes different published co-cultivation studies of THP-1 cells with other cell types, for instance, intestinal cells, adipocytes, T-lymphocytes, platelets, and vascular smooth muscle cells, which can be an option to study cell-cell interaction in vitro and can be an approach to better mimic in vivo conditions. Macrophage polarization is a relatively new topic which gains interest for which the THP-1 cell line also may be relevant. Besides that an overview of newly released commercial THP-1 engineered-reporter cells and THP-1 inflammasome test-cells is also given. Evaluation of recent papers leads to the conclusion that the THP-1 cell line has unique characteristics as a model to investigate/estimate immune-modulating effects of compounds in both activated and resting conditions of the cells. Although the THP-1 response can hint to potential responses that might occur ex vivo or in vivo, these should be, however, validated by in vivo studies to draw more definite conclusions. Copyright © 2013. Published by Elsevier B.V.

Extinction models for cancer stem cell therapy

Science.gov (United States)

Sehl, Mary; Zhou, Hua; Sinsheimer, Janet S.; Lange, Kenneth L.

2012-01-01

Cells with stem cell-like properties are now viewed as initiating and sustaining many cancers. This suggests that cancer can be cured by driving these cancer stem cells to extinction. The problem with this strategy is that ordinary stem cells are apt to be killed in the process. This paper sets bounds on the killing differential (difference between death rates of cancer stem cells and normal stem cells) that must exist for the survival of an adequate number of normal stem cells. Our main tools are birth–death Markov chains in continuous time. In this framework, we investigate the extinction times of cancer stem cells and normal stem cells. Application of extreme value theory from mathematical statistics yields an accurate asymptotic distribution and corresponding moments for both extinction times. We compare these distributions for the two cell populations as a function of the killing rates. Perhaps a more telling comparison involves the number of normal stem cells NH at the extinction time of the cancer stem cells. Conditioning on the asymptotic time to extinction of the cancer stem cells allows us to calculate the asymptotic mean and variance of NH. The full distribution of NH can be retrieved by the finite Fourier transform and, in some parameter regimes, by an eigenfunction expansion. Finally, we discuss the impact of quiescence (the resting state) on stem cell dynamics. Quiescence can act as a sanctuary for cancer stem cells and imperils the proposed therapy. We approach the complication of quiescence via multitype branching process models and stochastic simulation. Improvements to the τ-leaping method of stochastic simulation make it a versatile tool in this context. We conclude that the proposed therapy must target quiescent cancer stem cells as well as actively dividing cancer stem cells. The current cancer models demonstrate the virtue of attacking the same quantitative questions from a variety of modeling, mathematical, and computational perspectives

Cell plasticity and heterogeneity in cancer.

Science.gov (United States)

Marjanovic, Nemanja D; Weinberg, Robert A; Chaffer, Christine L

2013-01-01

Heterogeneity within a given cancer arises from diverse cell types recruited to the tumor and from genetic and/or epigenetic differences amongst the cancer cells themselves. These factors conspire to create a disease with various phenotypes. There are 2 established models of cancer development and progression to metastatic disease. These are the clonal evolution and cancer stem cell models. The clonal evolution theory suggests that successive mutations accumulating in a given cell generate clonal outgrowths that thrive in response to microenvironmental selection pressures, dictating the phenotype of the tumor. The alternative cancer stem cell (CSC) model suggests that cancer cells with similar genetic backgrounds can be hierarchically organized according to their tumorigenic potential. Accordingly, CSCs reside at the apex of the hierarchy and are thought to possess the majority of a cancer's tumor-initiating and metastatic ability. A defining feature of this model is its apparent unidirectional nature, whereby CSCs undergo symmetric division to replenish the CSC pool and irreversible asymmetric division to generate daughter cells (non-CSCs) with low tumorigenic potential. However, evolving evidence supports a new model of tumorigenicity, in which considerable plasticity exists between the non-CSC and CSC compartments, such that non-CSCs can reacquire a CSC phenotype. These findings suggest that some tumors may adhere to a plastic CSC model, in which bidirectional conversions are common and essential components of tumorigenicity. Accumulating evidence surrounding the plasticity of cancer cells, in particular, suggests that aggressive CSCs can be created de novo within a tumor. Given the current focus on therapeutic targeting of CSCs, we discuss the implications of non-CSC-to-CSC conversions on the development of future therapies. © 2012 American Association for Clinical Chemistry

A mathematical model for the iron/chromium redox battery

Science.gov (United States)

Fedkiw, P. S.; Watts, R. W.

1984-01-01

A mathematical model has been developed to describe the isothermal operation of a single anode-separator-cathode unit cell in a redox-flow battery and has been applied to the NASA iron/chromium system. The model, based on porous electrode theory, incorporates redox kinetics, mass transfer, and ohmic effects as well as the parasitic hydrogen reaction which occurs in the chromium electrode. A numerical parameter study was carried out to predict cell performance to aid in the rational design, scale-up, and operation of the flow battery. The calculations demonstrate: (1) an optimum electrode thickness and electrolyte flow rate exist; (2) the amount of hydrogen evolved and, hence, cycle faradaic efficiency, can be affected by cell geometry, flow rate, and charging procedure; (3) countercurrent flow results in enhanced cell performance over cocurrent flow; and (4) elevated temperature operation enhances cell performance.

Occurrence and characterisation of the hydrogen-evolving enzyme in Frankia sp.

Energy Technology Data Exchange (ETDEWEB)

Mohapatra, A.; Leul, M.; Sellstedt, A. [Umeaa Plant Science Centre, Department of Plant Physiology, Umeaa University, S-901 87 Umeaa (Sweden); Sandstroem, G. [Karolinska Institutet, Department of Laboratory Medicine, Division of Clinical Bacteriology, Karelinska University Hospital, Huddinge, S-141 86 Stockholm (Sweden)

2006-09-15

An increase in hydrogen evolution from the hydrogen-evolving enzyme in the actinomycete Frankia was recorded in the presence of nickel. Immunogold localisation analysis of the intracellular distribution of hydrogenase proteins indicated that they were evenly distributed in the membranes and cytosol of both hyphae and vesicles. In addition, molecular characterisation of the hydrogen-evolving enzyme at the proteomic level, using two-dimensional gel electrophoresis combined with mass spectrometry, confirmed that the Frankia hydrogen-evolving enzyme is similar to the cyanobacterial bidirectional hydrogenase of Anabena siamensis. (author)

Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability.

Directory of Open Access Journals (Sweden)

Kirsten H Ten Tusscher

2011-10-01

Full Text Available A major goal of evolutionary developmental biology (evo-devo is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs. This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy. In the second scenario segments and domains evolve simultaneously (SS strategy. We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation

Abundances of elements of the palladium group in the atmospheres of evolved stars. I. Molybdenum

International Nuclear Information System (INIS)

Orlov, M.Ya.; Shavrina, A.V.

1988-01-01

The abundance of molybdenum in the atmospheres of the K giants υ Ser, 9 Boo, and ρ Boo has been determined using spectra with reciprocal dispersion 6 angstrom/mm and the method of model atmospheres. Data on the abundance of this element in the atmospheres of other evolved stars are also given

How People Interact in Evolving Online Affiliation Networks

Science.gov (United States)

Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

2012-07-01

The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

Evolving autonomous learning in cognitive networks.

Science.gov (United States)

Sheneman, Leigh; Hintze, Arend

2017-12-01

There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

An Improved Model for FE Modeling and Simulation of Closed Cell Al-Alloy Foams

OpenAIRE

Hasan, MD. Anwarul

2010-01-01

Cell wall material properties of Al-alloy foams have been derived by a combination of nanoindentation experiment and numerical simulation. Using the derived material properties in FE (finite element) modeling of foams, the existing constitutive models of closed-cell Al-alloy foams have been evaluated against experimental results. An improved representative model has been proposed for FE analysis of closed-cell Al-alloy foams. The improved model consists of a combination of spherical and cruci...

PEM fuel cell model suitable for energy optimization purposes

International Nuclear Information System (INIS)

Caux, S.; Hankache, W.; Fadel, M.; Hissel, D.

2010-01-01

Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms.

PEM fuel cell model suitable for energy optimization purposes

Energy Technology Data Exchange (ETDEWEB)

Caux, S.; Hankache, W.; Fadel, M. [LAPLACE/CODIASE: UMR CNRS 5213, Universite de Toulouse - INPT, UPS, - ENSEEIHT: 2 rue Camichel BP7122, 31071 Toulouse (France); CNRS, LAPLACE, F-31071 Toulouse (France); Hissel, D. [FEMTO-ST ENISYS/FCLAB, UMR CNRS 6174, University of Franche-Comte, Rue Thierry Mieg, 90010 Belfort (France)

2010-02-15

Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms. (author)

The actual current density of gas-evolving electrodes—Notes on the bubble coverage

International Nuclear Information System (INIS)

Vogt, H.

2012-01-01

All investigations of electrochemical reactors with gas-evolving electrodes must take account of the fact that the actual current density controlling cell operation commonly differs substantially from the nominal current density used for practical purposes. Both quantities are interrelated by the fractional bubble coverage. This parameter is shown to be affected by a large number of operational quantities. However, available relationships of the bubble coverage take account only of the nominal current density. A further essential insufficiency is their inconsistency with reality for very large values of the bubble coverage being of relevance for operation conditions leading to anode effects. An improved relationship applicable to the total range is proposed.

Evolving Systems: An Outcome of Fondest Hopes and Wildest Dreams

Science.gov (United States)

Frost, Susan A.; Balas, Mark J.

2012-01-01

New theory is presented for evolving systems, which are autonomously controlled subsystems that self-assemble into a new evolved system with a higher purpose. Evolving systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control that operates through one specific component to maintain stability during the evolution. In addition, this control must often overcome persistent disturbances that occur while the evolution is in progress. Theoretical results will be presented for Adaptive Key Component control for persistent disturbance rejection. An illustrative example will demonstrate the Adaptive Key Component controller on a system composed of rigid body and flexible body modes.

Modelling transport-limited discharge capacity of lithium-sulfur cells

International Nuclear Information System (INIS)

Zhang, Teng; Marinescu, Monica; Walus, Sylwia; Offer, Gregory J.

2016-01-01

Highlights: • We modelled the rate capability of a Li-S cell based on mass-transport limitation • The model predicts a discharged Li-S cell to regain capacity upon short relaxation • Modelled rate capability and capacity recovery effect validated with measurements - Abstract: Lithium-sulfur (Li-S) battery could bring a step-change in battery technology with a potential specific energy density of 500 - 600 Wh/kg. A key challenge for further improving the specific energy-density of Li-S cells is to understand the mechanisms behind reduced sulfur utilisation at low electrolyte loadings and high discharge currents. While several Li-S models have been developed to explore the discharge mechanisms of Li-S cells, they so far fail to capture the discharge profiles at high currents. In this study, we propose that the slow ionic transport in concentrated electrolyte is limiting the rate capability of Li-S cells. This transport-limitation mechanism is demonstrated through a one-dimensional Li-S model which qualitatively captures the discharge capacities of a sulfolane-based Li-S cell at different currents. Furthermore, our model predicts that a discharged Li-S cell is able regain some capacity with a short period of relaxation. This capacity recovery phenomenon is validated experimentally for different discharge currents and relaxation durations. The transport-limited discharge behavior of Li-S cells highlights the importance of optimizing the electrolyte loading and electrolyte transport property in Li-S cells.

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 ...

Duplicate Abalone Egg Coat Proteins Bind Sperm Lysin Similarly, but Evolve Oppositely, Consistent with Molecular Mimicry at Fertilization

Science.gov (United States)

Aagaard, Jan E.; Springer, Stevan A.; Soelberg, Scott D.; Swanson, Willie J.

2013-01-01

Sperm and egg proteins constitute a remarkable paradigm in evolutionary biology: despite their fundamental role in mediating fertilization (suggesting stasis), some of these molecules are among the most rapidly evolving ones known, and their divergence can lead to reproductive isolation. Because of strong selection to maintain function among interbreeding individuals, interacting fertilization proteins should also exhibit a strong signal of correlated divergence among closely related species. We use evidence of such molecular co-evolution to target biochemical studies of fertilization in North Pacific abalone (Haliotis spp.), a model system of reproductive protein evolution. We test the evolutionary rates (d N/d S) of abalone sperm lysin and two duplicated egg coat proteins (VERL and VEZP14), and find a signal of co-evolution specific to ZP-N, a putative sperm binding motif previously identified by homology modeling. Positively selected residues in VERL and VEZP14 occur on the same face of the structural model, suggesting a common mode of interaction with sperm lysin. We test this computational prediction biochemically, confirming that the ZP-N motif is sufficient to bind lysin and that the affinities of VERL and VEZP14 are comparable. However, we also find that on phylogenetic lineages where lysin and VERL evolve rapidly, VEZP14 evolves slowly, and vice versa. We describe a model of sexual conflict that can recreate this pattern of anti-correlated evolution by assuming that VEZP14 acts as a VERL mimic, reducing the intensity of sexual conflict and slowing the co-evolution of lysin and VERL. PMID:23408913

Duplicate abalone egg coat proteins bind sperm lysin similarly, but evolve oppositely, consistent with molecular mimicry at fertilization.

Directory of Open Access Journals (Sweden)

Jan E Aagaard

Full Text Available Sperm and egg proteins constitute a remarkable paradigm in evolutionary biology: despite their fundamental role in mediating fertilization (suggesting stasis, some of these molecules are among the most rapidly evolving ones known, and their divergence can lead to reproductive isolation. Because of strong selection to maintain function among interbreeding individuals, interacting fertilization proteins should also exhibit a strong signal of correlated divergence among closely related species. We use evidence of such molecular co-evolution to target biochemical studies of fertilization in North Pacific abalone (Haliotis spp., a model system of reproductive protein evolution. We test the evolutionary rates (d(N/d(S of abalone sperm lysin and two duplicated egg coat proteins (VERL and VEZP14, and find a signal of co-evolution specific to ZP-N, a putative sperm binding motif previously identified by homology modeling. Positively selected residues in VERL and VEZP14 occur on the same face of the structural model, suggesting a common mode of interaction with sperm lysin. We test this computational prediction biochemically, confirming that the ZP-N motif is sufficient to bind lysin and that the affinities of VERL and VEZP14 are comparable. However, we also find that on phylogenetic lineages where lysin and VERL evolve rapidly, VEZP14 evolves slowly, and vice versa. We describe a model of sexual conflict that can recreate this pattern of anti-correlated evolution by assuming that VEZP14 acts as a VERL mimic, reducing the intensity of sexual conflict and slowing the co-evolution of lysin and VERL.

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.

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.

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.

Mechanisms of Cancer Cell Dormancy – Another Hallmark of Cancer?

Science.gov (United States)

Yeh, Albert C.; Ramaswamy, Sridhar

2015-01-01

Disease relapse in cancer patients many years after clinical remission, often referred to as cancer dormancy, is well documented but remains an incompletely understood phenomenon on the biological level. Recent reviews have summarized potential models that can explain this phenomenon, including angiogenic, immunologic, and cellular dormancy. We focus on mechanisms of cellular dormancy as newer biological insights have enabled better understanding of this process. We provide a historical context, synthesize current advances in the field, and propose a mechanistic framework that treats cancer cell dormancy as a dynamic cell state conferring a fitness advantage to an evolving malignancy under stress. Cellular dormancy appears to be an active process that can be toggled through a variety of signaling mechanisms that ultimately down-regulate the Ras/MAPK and PI(3)K/AKT pathways, an ability that is preserved even in cancers that constitutively depend on these pathways for their growth and survival. Just as unbridled proliferation is a key hallmark of cancer, the ability of cancer cells to become quiescent may be critical to evolving malignancies, with implications for understanding cancer initiation, progression, and treatment resistance. PMID:26354021

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.

Favorable Response of Metastatic Merkel Cell Carcinoma to Targeted 177Lu-DOTATATE Therapy: Will PRRT Evolve to Become an Important Approach in Receptor-Positive Cases?

Science.gov (United States)

Basu, Sandip; Ranade, Rohit

2016-06-01

This report illustrates an excellent partial response of Merkel cell carcinoma with multiple bilobar hepatic metastases to a single cycle of peptide receptor radionuclide therapy (PRRT) with (177)Lu-DOTATATE. This response, coupled with minimal side effects, warrants consideration of this therapy early in the disease course (rather than at an advanced stage after failure of other therapies) if the metastatic lesions exhibit adequate tracer avidity on somatostatin receptor-based imaging. Our patient showed progression of systemic disease after having undergone a second surgery and adjuvant radiotherapy to the head and neck, as well as chemotherapy, and hence was considered a candidate for PRRT. In a pretreatment study, the metastatic lesions demonstrated avidity to both somatostatin receptors and (18)F-FDG. Three months after the first cycle of treatment, when the patient was being evaluated for a second cycle, both imaging parameters showed evidence of a partial response that included nearly complete resolution of the two previously seen lesions. In view of the relatively good tolerability, minimal side effects, and targeted nature of the treatment, PRRT may evolve to become the first-line therapy for metastatic Merkel cell carcinoma and should be examined further in a larger number of patients. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

An Improved Model of Nonuniform Coleochaete Cell Division.

Science.gov (United States)

Wang, Yuandi; Cong, Jinyu

2016-08-01

Cell division is a key biological process in which cells divide forming new daughter cells. In the present study, we investigate continuously how a Coleochaete cell divides by introducing a modified differential equation model in parametric equation form. We discuss both the influence of "dead" cells and the effects of various end-points on the formation of the new cells' boundaries. We find that the boundary condition on the free end-point is different from that on the fixed end-point; the former has a direction perpendicular to the surface. It is also shown that the outer boundaries of new cells are arc-shaped. The numerical experiments and theoretical analyses for this model to construct the outer boundary are given.

What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast.

Directory of Open Access Journals (Sweden)

Artémis Llamosi

2016-02-01

Full Text Available Significant cell-to-cell heterogeneity is ubiquitously observed in isogenic cell populations. Consequently, parameters of models of intracellular processes, usually fitted to population-averaged data, should rather be fitted to individual cells to obtain a population of models of similar but non-identical individuals. Here, we propose a quantitative modeling framework that attributes specific parameter values to single cells for a standard model of gene expression. We combine high quality single-cell measurements of the response of yeast cells to repeated hyperosmotic shocks and state-of-the-art statistical inference approaches for mixed-effects models to infer multidimensional parameter distributions describing the population, and then derive specific parameters for individual cells. The analysis of single-cell parameters shows that single-cell identity (e.g. gene expression dynamics, cell size, growth rate, mother-daughter relationships is, at least partially, captured by the parameter values of gene expression models (e.g. rates of transcription, translation and degradation. Our approach shows how to use the rich information contained into longitudinal single-cell data to infer parameters that can faithfully represent single-cell identity.

WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions.

Science.gov (United States)

Karr, Jonathan R; Phillips, Nolan C; Covert, Markus W

2014-01-01

Mechanistic 'whole-cell' models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. http://www.wholecellsimdb.org SOURCE CODE REPOSITORY: URL: http://github.com/CovertLab/WholeCellSimDB. © The Author(s) 2014. Published by Oxford University Press.

Selfish cells in altruistic cell society - a theoretical oncology.

Science.gov (United States)

Chigira, M

1993-09-01

In multicellular organisms, internal evolution of individual cells is strictly forbidden and 'evolutional' DNA replication should be performed only by the sexual reproduction system. Wholistic negative control system called 'homeostasis' serves all service to germ line cells. All somatic cells are altruistic to the germ line cells. However, in malignant tumors, it seems that individual cells replicate and behave 'selfishly' and evolve against the internal microenvironment. Tumor cells only express the occult selfishness which is programmed in normal cells a priori. This phenomenon is based on the failure of identical DNA replication, and results in 'autonomy' and 'anomie' of cellular society as shown in tumor cells. Genetic programs of normal cells connote this cellular autonomy and anomie introduced by the deletion of regulators on structure genes. It is rather paradoxical that the somatic cells get their freedom from wholistic negative regulation programmed internally. However, this is not a true paradox, since multicellular organisms have clearly been evolved from 'monads' in which cells proliferate without wholistic regulation. Somatic cells revolt against germ cell DNA, called 'selfish replicator' by Dawkins. It is an inevitable destiny that the 'selfishness' coded in genome should be revenged by itself. Selfish replicator in germ cell line should be revolted by its selfishness in the expansion of somatic cells, since they have an orthogenesis to get more selfishness in order to increase their genome. Tumor heterogeneity and progression can be fully explained by this self-contradictory process which produces heterogeneous gene copies different from the original clone in the tumor, although 'selfish' gene replication is the final target of being. Furthermore, we have to discard the concept of clonality of tumor cells since genetic instability is a fundamental feature of tumors. Finally, tumor cells and proto-oncogenes can be considered as the ultimate parasite

Modeling universal dynamics of cell spreading on elastic substrates.

Science.gov (United States)

Fan, Houfu; Li, Shaofan

2015-11-01

A three-dimensional (3D) multiscale moving contact line model is combined with a soft matter cell model to study the universal dynamics of cell spreading over elastic substrates. We have studied both the early stage and the late stage cell spreading by taking into account the actin tension effect. In this work, the cell is modeled as an active nematic droplet, and the substrate is modeled as a St. Venant Kirchhoff elastic medium. A complete 3D simulation of cell spreading has been carried out. The simulation results show that the spreading area versus spreading time at different stages obeys specific power laws, which is in good agreement with experimental data and theoretical prediction reported in the literature. Moreover, the simulation results show that the substrate elasticity may affect force dipole distribution inside the cell. The advantage of this approach is that it combines the hydrodynamics of actin retrograde flow with moving contact line model so that it can naturally include actin tension effect resulting from actin polymerization and actomyosin contraction, and thus it might be capable of simulating complex cellular scale phenomenon, such as cell spreading or even crawling.

Evolving ATLAS Computing For Today’s Networks

CERN Document Server

Campana, S; The ATLAS collaboration; Jezequel, S; Negri, G; Serfon, C; Ueda, I

2012-01-01

The ATLAS computing infrastructure was designed many years ago based on the assumption of rather limited network connectivity between computing centres. ATLAS sites have been organized in a hierarchical model, where only a static subset of all possible network links can be exploited and a static subset of well connected sites (CERN and the T1s) can cover important functional roles such as hosting master copies of the data. The pragmatic adoption of such simplified approach, in respect of a more relaxed scenario interconnecting all sites, was very beneficial during the commissioning of the ATLAS distributed computing system and essential in reducing the operational cost during the first two years of LHC data taking. In the mean time, networks evolved far beyond this initial scenario: while a few countries are still poorly connected with the rest of the WLCG infrastructure, most of the ATLAS computing centres are now efficiently interlinked. Our operational experience in running the computing infrastructure in ...

Development and the evolvability of human limbs.

Science.gov (United States)

Young, Nathan M; Wagner, Günter P; Hallgrímsson, Benedikt

2010-02-23

The long legs and short arms of humans are distinctive for a primate, the result of selection acting in opposite directions on each limb at different points in our evolutionary history. This mosaic pattern challenges our understanding of the relationship of development and evolvability because limbs are serially homologous and genetic correlations should act as a significant constraint on their independent evolution. Here we test a developmental model of limb covariation in anthropoid primates and demonstrate that both humans and apes exhibit significantly reduced integration between limbs when compared to quadrupedal monkeys. This result indicates that fossil hominins likely escaped constraints on independent limb variation via reductions to genetic pleiotropy in an ape-like last common ancestor (LCA). This critical change in integration among hominoids, which is reflected in macroevolutionary differences in the disparity between limb lengths, facilitated selection for modern human limb proportions and demonstrates how development helps shape evolutionary change.

Complement and the control of HIV infection: an evolving story.

Science.gov (United States)

Frank, Michael M; Hester, Christopher; Jiang, Haixiang

2014-05-01

Thirty years ago, investigators isolated and later determined the structure of HIV-1 and its envelope proteins. Using techniques that were effective with other viruses, they prepared vaccines designed to generate antibody or T-cell responses, but they were ineffective in clinical trials. In this article, we consider the role of complement in host defense against enveloped viruses, the role it might play in the antibody response and why complement has not controlled HIV-1 infection. Complement consists of a large group of cell-bound and plasma proteins that are an integral part of the innate immune system. They provide a first line of defense against microbes and also play a role in the immune response. Here we review the studies of complement-mediated HIV destruction and the role of complement in the HIV antibody response. HIV-1 has evolved a complex defense to prevent complement-mediated killing reviewed here. As part of these studies, we have discovered that HIV-1 envelope, on administration into animals, is rapidly broken down into small peptides that may prove to be very inefficient at provident the type of antigenic stimulation that leads to an effective immune response. Improving complement binding and stabilizing envelope may improve the vaccine response.

Incorporating pushing in exclusion-process models of cell migration.

Science.gov (United States)

Yates, Christian A; Parker, Andrew; Baker, Ruth E

2015-05-01

The macroscale movement behavior of a wide range of isolated migrating cells has been well characterized experimentally. Recently, attention has turned to understanding the behavior of cells in crowded environments. In such scenarios it is possible for cells to interact, inducing neighboring cells to move in order to make room for their own movements or progeny. Although the behavior of interacting cells has been modeled extensively through volume-exclusion processes, few models, thus far, have explicitly accounted for the ability of cells to actively displace each other in order to create space for themselves. In this work we consider both on- and off-lattice volume-exclusion position-jump processes in which cells are explicitly allowed to induce movements in their near neighbors in order to create space for themselves to move or proliferate into. We refer to this behavior as pushing. From these simple individual-level representations we derive continuum partial differential equations for the average occupancy of the domain. We find that, for limited amounts of pushing, comparison between the averaged individual-level simulations and the population-level model is nearly as good as in the scenario without pushing. Interestingly, we find that, in the on-lattice case, the diffusion coefficient of the population-level model is increased by pushing, whereas, for the particular off-lattice model that we investigate, the diffusion coefficient is reduced. We conclude, therefore, that it is important to consider carefully the appropriate individual-level model to use when representing complex cell-cell interactions such as pushing.

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.

Slowly evolving connectivity in recurrent neural networks: I. The extreme dilution regime

International Nuclear Information System (INIS)

Wemmenhove, B; Skantzos, N S; Coolen, A C C

2004-01-01

We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the 'condensed' pattern are locally stable, so the associative memory character of our model is preserved

MarCell trademark software for modeling bone marrow radiation cell kinetics

International Nuclear Information System (INIS)

Hasan, J.S.; Jones, T.D.; Morris, M.D.

1997-01-01

Differential equations were used to model cellular injury, repair, and compensatory proliferation in the irradiated bone marrow. Recently, that model was implemented as MarCell trademark, a user-friendly MS-DOS computer program that allows users from a variety of technical disciplines to evaluate complex radiation exposure. The software allows menu selections for different sources of ionizing radiation. Choices for cell lineages include progenitor, stroma, and malignant, and the available species include mouse, rat, dog, sheep, swine, burro, and man. An attractive feature is that any protracted irradiation can be compared with an equivalent prompt dose (EPD) in terms of cell kinetics for either the source used or for a reference such as 250 kVp x rays or 60 Co. EPD is used to mean a dose rate for which no meaningful biological recovery occurs during the period of irradiation. For human as species, output from MarCell trademark includes: risk of 30-day mortality; risk of whole-body cancer and leukemia based either on radiation-induced cytopenia or compensatory cell proliferation; cell survival and repopulation plots as functions of time or dose; and 4-week recovery following treatment. copyright 1997 American Association of Physicists in Medicine

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.

Cosmic Biology How Life Could Evolve on Other Worlds

CERN Document Server

Irwin, Louis Neil

2011-01-01

It is very unlikely that little green humanoids are living on Mars. But what are the possible life forms that might exist in our Solar System and how might they have evolved? This uniquely authoritative and imaginative book on the possibilties for alien life addresses the intrinsic interest that we have about life on other worlds - reinforcing some of our assumptions and reshaping others. It introduces new possibilties that will enlarge our understanding of the issue overall, in particular the enormous range of environments and planetary conditions within which life might evolve. Cosmic Biology -discusses a broad range of possible environments where alien life might have evolved; -explains why carbon-based, water-borne life is more likely that its alternatives, but is not the only possiblity; -applies the principles of planetary science and modern biology to evolutionary scenarios on other worlds; -looks at the future fates of living systems, including those on Earth.

PI5P Triggers ICAM-1 Degradation in Shigella Infected Cells, Thus Dampening Immune Cell Recruitment

Directory of Open Access Journals (Sweden)

Frédéric Boal

2016-02-01

Full Text Available Shigella flexneri, the pathogen responsible for bacillary dysentery, has evolved multiple strategies to control the inflammatory response. Here, we show that Shigella subverts the subcellular trafficking of the intercellular adhesion molecule-1 (ICAM-1, a key molecule in immune cell recruitment, in a mechanism dependent on the injected bacterial enzyme IpgD and its product, the lipid mediator PI5P. Overexpression of IpgD, but not a phosphatase dead mutant, induced the internalization and the degradation of ICAM-1 in intestinal epithelial cells. Remarkably, addition of permeant PI5P reproduced IpgD effects and led to the inhibition of neutrophil recruitment. Finally, these results were confirmed in an in vivo model of Shigella infection where IpgD-dependent ICAM-1 internalization reduced neutrophil adhesion. In conclusion, we describe here an immune evasion mechanism used by the pathogen Shigella to divert the host cell trafficking machinery in order to reduce immune cell recruitment.

Voronoi cell patterns: Theoretical model and applications

Science.gov (United States)

González, Diego Luis; Einstein, T. L.

2011-11-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

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

Open Science and Open Data: Evolving Business Models

OpenAIRE

Melero, Remedios

2013-01-01

The rise of ICT has changed the way scientific inputs and outputs are disseminated and diffused. As a consequence, new business models for open access to Scientific publications and datasets are emerging. This session will explore the new features of the business models for open access and open data as well as the associated benefits and risks.

Dynamical principles of cell-cycle arrest: Reversible, irreversible, and mixed strategies

Science.gov (United States)

Pfeuty, Benjamin

2012-08-01

Living cells often alternate between proliferating and nonproliferating states as part of individual or collective strategies to adapt to complex and changing environments. To this aim, they have evolved a biochemical regulatory network enabling them to switch between cell-division cycles (i.e., oscillatory state) and cell-cycle arrests (i.e., steady state) in response to extracellular cues. This can be achieved by means of a variety of bifurcation mechanisms that potentially give rise to qualitatively distinct cell-cycle arrest properties. In this paper, we study the dynamics of a minimal biochemical network model in which a cell-division oscillator and a differentiation switch mutually antagonize. We identify the existence of three biologically plausible bifurcation scenarios organized around a codimension-four swallowtail-homoclinic singularity. As a result, the model exhibits a broad repertoire of cell-cycle arrest properties in terms of reversibility of these arrests, tunability of interdivision time, and ability to track time-varying signals. This dynamic versatility would explain the diversity of cell-cycle arrest strategies developed in different living species and functional contexts.

An evolving systems-based methodology for healthcare planning.

Science.gov (United States)

Warwick, Jon; Bell, Gary

2007-01-01

Healthcare planning seems beset with problems at all hierarchical levels. These are caused by the 'soft' nature of many of the issues present in healthcare planning and the high levels of complexity inherent in healthcare services. There has, in recent years, been a move to utilize systems thinking ideas in an effort to gain a better understanding of the forces at work within the healthcare environment and these have had some success. This paper argues that systems-based methodologies can be further enhanced by metrication and modeling which assist in exploring the changed emergent behavior of a system resulting from management intervention. The paper describes the Holon Framework as an evolving systems-based approach that has been used to help clients understand complex systems (in the education domain) that would have application in the analysis of healthcare problems.

Advanced impedance modeling of solid oxide electrochemical cells

DEFF Research Database (Denmark)

Graves, Christopher R.; Hjelm, Johan

2014-01-01

Impedance spectroscopy is a powerful technique for detailed study of the electrochemical and transport processes that take place in fuel cells and electrolysis cells, including solid oxide cells (SOCs). Meaningful analysis of impedance measurements is nontrivial, however, because a large number...... techniques to provide good guesses for the modeling parameters, like transforming the impedance data to the distribution of relaxation times (DRT), together with experimental parameter sensitivity studies, is the state-of-the-art approach to achieve good EC model fits. Here we present new impedance modeling...... electrode and 2-D gas transport models which have fewer unknown parameters for the same number of processes, (ii) use of a new model fitting algorithm, “multi-fitting”, in which multiple impedance spectra are fit simultaneously with parameters linked based on the variation of measurement conditions, (iii...

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

Revealing evolved massive stars with Spitzer

Science.gov (United States)

Gvaramadze, V. V.; Kniazev, A. Y.; Fabrika, S.

2010-06-01

Massive evolved stars lose a large fraction of their mass via copious stellar wind or instant outbursts. During certain evolutionary phases, they can be identified by the presence of their circumstellar nebulae. In this paper, we present the results of a search for compact nebulae (reminiscent of circumstellar nebulae around evolved massive stars) using archival 24-μm data obtained with the Multiband Imaging Photometer for Spitzer. We have discovered 115 nebulae, most of which bear a striking resemblance to the circumstellar nebulae associated with luminous blue variables (LBVs) and late WN-type (WNL) Wolf-Rayet (WR) stars in the Milky Way and the Large Magellanic Cloud (LMC). We interpret this similarity as an indication that the central stars of detected nebulae are either LBVs or related evolved massive stars. Our interpretation is supported by follow-up spectroscopy of two dozen of these central stars, most of which turn out to be either candidate LBVs (cLBVs), blue supergiants or WNL stars. We expect that the forthcoming spectroscopy of the remaining objects from our list, accompanied by the spectrophotometric monitoring of the already discovered cLBVs, will further increase the known population of Galactic LBVs. This, in turn, will have profound consequences for better understanding the LBV phenomenon and its role in the transition between hydrogen-burning O stars and helium-burning WR stars. We also report on the detection of an arc-like structure attached to the cLBV HD 326823 and an arc associated with the LBV R99 (HD 269445) in the LMC. Partially based on observations collected at the German-Spanish Astronomical Centre, Calar Alto, jointly operated by the Max-Planck-Institut für Astronomie Heidelberg and the Instituto de Astrofísica de Andalucía (CSIC). E-mail: vgvaram@mx.iki.rssi.ru (VVG); akniazev@saao.ac.za (AYK); fabrika@sao.ru (SF)

Stem Cell Models: A Guide to Understand and Mitigate Aging?

Science.gov (United States)

Brunauer, Regina; Alavez, Silvestre; Kennedy, Brian K

2017-01-01

Aging is studied either on a systemic level using life span and health span of animal models, or on the cellular level using replicative life span of yeast or mammalian cells. While useful in identifying general and conserved pathways of aging, both approaches provide only limited information about cell-type specific causes and mechanisms of aging. Stem cells are the regenerative units of multicellular life, and stem cell aging might be a major cause for organismal aging. Using the examples of hematopoietic stem cell aging and human pluripotent stem cell models, we propose that stem cell models of aging are valuable for studying tissue-specific causes and mechanisms of aging and can provide unique insights into the mammalian aging process that may be inaccessible in simple model organisms. © 2016 S. Karger AG, Basel.

Evolving NASA's Earth Science Data Systems

Science.gov (United States)

Walter, J.; Behnke, J.; Murphy, K. J.; Lowe, D. R.

2013-12-01

NASA's Earth Science Data and Information System Project (ESDIS) is charged with managing, maintaining, and evolving NASA's Earth Observing System Data and Information System (EOSDIS) and is responsible for processing, archiving, and distributing NASA Earth science data. The system supports a multitude of missions and serves diverse science research and other user communities. Keeping up with ever-changing information technology and figuring out how to leverage those changes across such a large system in order to continuously improve and meet the needs of a diverse user community is a significant challenge. Maintaining and evolving the system architecture and infrastructure is a continuous and multi-layered effort. It requires a balance between a "top down" management paradigm that provides a coherent system view and maintaining the managerial, technological, and functional independence of the individual system elements. This presentation will describe some of the key elements of the current system architecture, some of the strategies and processes we employ to meet these challenges, current and future challenges, and some ideas for meeting those challenges.

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.

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

T cell immunity

OpenAIRE

Emel Bülbül Başkan

2013-01-01

Since birth, our immune system is constantly bombarded with self-antigens and foreign pathogens. To stay healthy, complex immune strategies have evolved in our immune system to maintain self-tolerance and to defend against foreign pathogens. Effector T cells are the key players in steering the immune responses to execute immune functions. While effector T cells were initially identified to be immune promoting, recent studies unraveled negative regulatory functions of effector T cells...

Sex determination: ways to evolve a hermaphrodite.

OpenAIRE

Braendle , Christian; Félix , Marie-Anne

2006-01-01

Most species of the nematode genus Caenorhabditis reproduce through males and females; C. elegans and C. briggsae, however, produce self-fertile hermaphrodites instead of females. These transitions to hermaphroditism evolved convergently through distinct modifications of germline sex determination mechanisms.

Fusomorphogenesis: cell fusion in organ formation.

Science.gov (United States)

Shemer, G; Podbilewicz, B

2000-05-01

Cell fusion is a universal process that occurs during fertilization and in the formation of organs such as muscles, placenta, and bones. Very little is known about the molecular and cellular mechanisms of cell fusion during pattern formation. Here we review the dynamic anatomy of all cell fusions during embryonic and postembryonic development in an organism. Nearly all the cell fates and cell lineages are invariant in the nematode C. elegans and one third of the cells that are born fuse to form 44 syncytia in a reproducible and stereotyped way. To explain the function of cell fusion in organ formation we propose the fusomorphogenetic model as a simple cellular mechanism to efficiently redistribute membranes using a combination of cell fusion and polarized membrane recycling during morphogenesis. Thus, regulated intercellular and intracellular membrane fusion processes may drive elongation of the embryo as well as postembryonic organ formation in C. elegans. Finally, we use the fusomorphogenetic hypothesis to explain the role of cell fusion in the formation of organs like muscles, bones, and placenta in mammals and other species and to speculate on how the intracellular machinery that drive fusomorphogenesis may have evolved.

A mathematical model for eph/ephrin-directed segregation of intermingled cells.

Directory of Open Access Journals (Sweden)

Rotem Aharon

Full Text Available Eph receptors, the largest family of receptor tyrosine kinases, control cell-cell adhesion/de-adhesion, cell morphology and cell positioning through interaction with cell surface ephrin ligands. Bi-directional signalling from the Eph and ephrin complexes on interacting cells have a significant role in controlling normal tissue development and oncogenic tissue patterning. Eph-mediated tissue patterning is based on the fine-tuned balance of adhesion and de-adhesion reactions between distinct Eph- and ephrin-expressing cell populations, and adhesion within like populations (expressing either Eph or ephrin. Here we develop a stochastic, Lagrangian model that is based on Eph/ephrin biology: incorporating independent Brownian motion to describe cell movement and a deterministic term (the drift term to represent repulsive and adhesive interactions between neighbouring cells. Comparison between the experimental and computer simulated Eph/ephrin cell patterning events shows that the model recapitulates the dynamics of cell-cell segregation and cell cluster formation. Moreover, by modulating the term for Eph/ephrin-mediated repulsion, the model can be tuned to match the actual behaviour of cells with different levels of Eph expression or activity. Together the results of our experiments and modelling suggest that the complexity of Eph/ephrin signalling mechanisms that control cell-cell interactions can be described well by a mathematical model with a single term balancing adhesion and de-adhesion between interacting cells. This model allows reliable prediction of Eph/ephrin-dependent control of cell patterning behaviour.

Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

Science.gov (United States)

Kasabov, Nikola; Dhoble, Kshitij; Nuntalid, Nuttapod; Indiveri, Giacomo

2013-05-01

On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass rank-order learning mechanism and a strategy to evolve a new spiking neuron and new connections to learn new patterns from incoming data. So far these networks have been mainly used for fast image and speech frame-based recognition. Alternative spike-time learning methods, such as Spike-Timing Dependent Plasticity (STDP) and its variant Spike Driven Synaptic Plasticity (SDSP), can also be used to learn spatio-temporal representations, but they usually require many iterations in an unsupervised or semi-supervised mode of learning. This paper introduces a new class of eSNN, dynamic eSNN, that utilise both rank-order learning and dynamic synapses to learn SSTD in a fast, on-line mode. The paper also introduces a new model called deSNN, that utilises rank-order learning and SDSP spike-time learning in unsupervised, supervised, or semi-supervised modes. The SDSP learning is used to evolve dynamically the network changing connection weights that capture spatio-temporal spike data clusters both during training and during recall. The new deSNN model is first illustrated on simple examples and then applied on two case study applications: (1) moving object recognition using address-event representation (AER) with data collected using a silicon retina device; (2) EEG SSTD recognition for brain-computer interfaces. The deSNN models resulted in a superior performance in terms of accuracy and speed when compared with other SNN models that use either rank-order or STDP learning. The reason is that the deSNN makes use of both the information contained in the order of the first input spikes

Modelling spatio-temporal interactions within the cell

Indian Academy of Sciences (India)

Prakash

Cell signalling pathways make up the regulatory systems of mammalian cells. ... This organization makes it possible to study the signalling networks in a modelling ..... energy transfer (FRET) and fluorescence recovery after photobleaching ...

A comparative study of approaches to direct methanol fuel cells modelling

Energy Technology Data Exchange (ETDEWEB)

Oliveira, V.B.; Falcao, D.S.; Pinto, A.M.F.R. [Centro de Estudos de Fenomenos de Transporte, Departamento de Eng. Quimica, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto (Portugal); Rangel, C.M. [Instituto Nacional de Engenharia, Tecnologia e Inovacao, Paco do Lumiar, 22,1649-038 (Portugal)

2007-03-15

Fuel cell modelling has received much attention over the past decade in an attempt to better understand the phenomena occurring within the cell. Mathematical models and simulation are needed as tools for design optimization of fuel cells, stacks and fuel cell power systems. Analytical, semi-empirical and mechanistic models for direct methanol fuel cells (DMFC) are reviewed. Effective models were until now developed describing the fundamental electrochemical and transport phenomena taking place in the cell. More research is required to develop models that can account for the two-phase flows occurring in the anode and cathode of the DMFC. The merits and demerits of the models are presented. Selected models of different categories are implemented and discussed. Finally, one of the selected simplified models is proposed as a computer-aided tool for real-time system level DMFC calculations. (author)

Trapping planets in an evolving protoplanetary disk: preferred time, locations and planet mass

OpenAIRE

Baillié, Kévin; Charnoz, Sébastien; Pantin, Éric

2016-01-01

Planet traps are necessary to prevent forming planets from falling onto their host star by type I migration. Surface mass density and temperature gradient irregularities favor the apparition of traps and deserts. Such features are found at the dust sublimation lines and heat transition barriers. We study how planets may remain trapped or escape as they grow and as the disk evolves. We model the temporal viscous evolution of a protoplanetary disk by coupling its dynamics, thermodynamics, geome...

Satcom access in the Evolved Packet Core

NARCIS (Netherlands)

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

2011-01-01

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

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

A mechanistic model for the evolution of multicellularity

Science.gov (United States)

Amado, André; Batista, Carlos; Campos, Paulo R. A.

2018-02-01

Through a mechanistic approach we investigate the formation of aggregates of variable sizes, accounting mechanisms of aggregation, dissociation, death and reproduction. In our model, cells can produce two metabolites, but the simultaneous production of both metabolites is costly in terms of fitness. Thus, the formation of larger groups can favor the aggregates to evolve to a configuration where division of labor arises. It is assumed that the states of the cells in a group are those that maximize organismal fitness. In the model it is considered that the groups can grow linearly, forming a chain, or compactly keeping a roughly spherical shape. Starting from a population consisting of single-celled organisms, we observe the formation of groups with variable sizes and usually much larger than two-cell aggregates. Natural selection can favor the formation of large groups, which allows the system to achieve new and larger fitness maxima.

Real-time evolvable pulse shaper for radiation measurements

Energy Technology Data Exchange (ETDEWEB)

Lanchares, Juan, E-mail: julandan@dacya.ucm.es [Facultad de Informática, Universidad Complutense de Madrid (UCM), C/Prof. José García Santesmases s/n, 28040 Madrid (Spain); Garnica, Oscar, E-mail: ogarnica@dacya.ucm.es [Facultad de Informática, Universidad Complutense de Madrid (UCM), C/Prof. José García Santesmases s/n, 28040 Madrid (Spain); Risco-Martín, José L., E-mail: jlrisco@dacya.ucm.es [Facultad de Informática, Universidad Complutense de Madrid (UCM), C/Prof. José García Santesmases s/n, 28040 Madrid (Spain); Ignacio Hidalgo, J., E-mail: hidalgo@dacya.ucm.es [Facultad de Informática, Universidad Complutense de Madrid (UCM), C/Prof. José García Santesmases s/n, 28040 Madrid (Spain); Regadío, Alberto, E-mail: alberto.regadio@insa.es [Área de Tecnologías Electrónicas, Instituto Nacional de Técnica Aeroespacial (INTA), 28850 Torrejón de Ardoz, Madrid (Spain)

2013-11-01

In the last two decades, recursive algorithms for real-time digital pulse shaping in pulse height measurements have been developed and published in number of articles and textbooks. All these algorithms try to synthesize in real time optimum or near optimum shapes in the presence of noise. Even though some of these shapers can be considered effective designs, some side effects like aging cannot be ignored. We may observe that after sensors degradation, the signal obtained is not valid. In this regard, we present in this paper a novel technique that, based on evolvable hardware concepts, is able to evolve the degenerated shaper into a new design with better performance than the original one under the new sensor features.

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

Modeling human neurological disorders with induced pluripotent stem cells.

Science.gov (United States)

Imaizumi, Yoichi; Okano, Hideyuki

2014-05-01

Human induced pluripotent stem (iPS) cells obtained by reprogramming technology are a source of great hope, not only in terms of applications in regenerative medicine, such as cell transplantation therapy, but also for modeling human diseases and new drug development. In particular, the production of iPS cells from the somatic cells of patients with intractable diseases and their subsequent differentiation into cells at affected sites (e.g., neurons, cardiomyocytes, hepatocytes, and myocytes) has permitted the in vitro construction of disease models that contain patient-specific genetic information. For example, disease-specific iPS cells have been established from patients with neuropsychiatric disorders, including schizophrenia and autism, as well as from those with neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. A multi-omics analysis of neural cells originating from patient-derived iPS cells may thus enable investigators to elucidate the pathogenic mechanisms of neurological diseases that have heretofore been unknown. In addition, large-scale screening of chemical libraries with disease-specific iPS cells is currently underway and is expected to lead to new drug discovery. Accordingly, this review outlines the progress made via the use of patient-derived iPS cells toward the modeling of neurological disorders, the testing of existing drugs, and the discovery of new drugs. The production of human induced pluripotent stem (iPS) cells from the patients' somatic cells and their subsequent differentiation into specific cells have permitted the in vitro construction of disease models that contain patient-specific genetic information. Furthermore, innovations of gene-editing technologies on iPS cells are enabling new approaches for illuminating the pathogenic mechanisms of human diseases. In this review article, we outlined the current status of neurological diseases-specific iPS cell research and described recently obtained

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...... the possibilities of generating three-dimensional (3D) models using the iPSCs-derived cells and compare their advantages and disadvantages to conventional two-dimensional (2D) models....

Do motifs reflect evolved function?--No convergent evolution of genetic regulatory network subgraph topologies.

Science.gov (United States)

Knabe, Johannes F; Nehaniv, Chrystopher L; Schilstra, Maria J

2008-01-01

Methods that analyse the topological structure of networks have recently become quite popular. Whether motifs (subgraph patterns that occur more often than in randomized networks) have specific functions as elementary computational circuits has been cause for debate. As the question is difficult to resolve with currently available biological data, we approach the issue using networks that abstractly model natural genetic regulatory networks (GRNs) which are evolved to show dynamical behaviors. Specifically one group of networks was evolved to be capable of exhibiting two different behaviors ("differentiation") in contrast to a group with a single target behavior. In both groups we find motif distribution differences within the groups to be larger than differences between them, indicating that evolutionary niches (target functions) do not necessarily mold network structure uniquely. These results show that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Moreover, analysis of motif functional relevance by lesioning did not suggest that motifs were of greater importance to the functioning of the network than arbitrary subgraph patterns. Only when drastically restricting network size, so that one motif corresponds to a whole functionally evolved network, was preference for particular connection patterns found. This suggests that in non-restricted, bigger networks, entanglement with the rest of the network hinders topological subgraph analysis.

Replaying Evolution to Test the Cause of Extinction of One Ecotype in an Experimentally Evolved Population.

Directory of Open Access Journals (Sweden)

Caroline B Turner

Full Text Available In a long-term evolution experiment with Escherichia coli, bacteria in one of twelve populations evolved the ability to consume citrate, a previously unexploited resource in a glucose-limited medium. This innovation led to the frequency-dependent coexistence of citrate-consuming (Cit+ and non-consuming (Cit- ecotypes, with Cit-bacteria persisting on the exogenously supplied glucose as well as other carbon molecules released by the Cit+ bacteria. After more than 10,000 generations of coexistence, however, the Cit-lineage went extinct; cells with the Cit-phenotype dropped to levels below detection, and the Cit-clade could not be detected by molecular assays based on its unique genotype. We hypothesized that this extinction was a deterministic outcome of evolutionary change within the population, specifically the appearance of a more-fit Cit+ ecotype that competitively excluded the Cit-ecotype. We tested this hypothesis by re-evolving the population from a frozen population sample taken within 500 generations of the extinction and from another sample taken several thousand generations earlier, in each case for 500 generations and with 20-fold replication. To our surprise, the Cit-type did not go extinct in any of these replays, and Cit-cells also persisted in a single replicate that was propagated for 2,500 generations. Even more unexpectedly, we showed that the Cit-ecotype could reinvade the Cit+ population after its extinction. Taken together, these results indicate that the extinction of the Cit-ecotype was not a deterministic outcome driven by competitive exclusion by the Cit+ ecotype. The extinction also cannot be explained by demographic stochasticity alone, as the population size of the Cit-ecotype should have been many thousands of cells even during the daily transfer events. Instead, we infer that the extinction must have been caused by a rare chance event in which some aspect of the experimental conditions was inadvertently perturbed.

Sextant: Visualizing time-evolving linked geospatial data

NARCIS (Netherlands)

C. Nikolaou (Charalampos); K. Dogani (Kallirroi); K. Bereta (Konstantina); G. Garbis (George); M. Karpathiotakis (Manos); K. Kyzirakos (Konstantinos); M. Koubarakis (Manolis)

2015-01-01

textabstractThe linked open data cloud is constantly evolving as datasets get continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone

Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials

OpenAIRE

K. S. Reddy; P Karthikeyan

2010-01-01

A model to predict the effective thermal conductivity of heterogeneous materials is proposed based on unit cell approach. The model is combined with four fundamental effective thermal conductivity models (Parallel, Series, Maxwell-Eucken-I, and Maxwell-Eucken-II) to evolve a unifying equation for the estimation of effective thermal conductivity of porous and nonporous food materials. The effect of volume fraction (ν) on the structure composition factor (ψ) of the food materials is studied. Th...

Inhibition of BACE1 Activity by a DNA Aptamer in an Alzheimer's Disease Cell Model.

Directory of Open Access Journals (Sweden)

Huiyu Liang

Full Text Available An initial step in amyloid-β (Aβ production includes amyloid precursor protein (APP cleavage via β-Site amyloid precursor protein cleaving enzyme 1 (BACE1. Increased levels of brain Aβ have been implicated in the pathogenesis of Alzheimer's disease (AD. Thus, β-secretase represents a primary target for inhibitor drug development in AD. In this study, aptamers were obtained from combinatorial oligonucleotide libraries using a technology referred to as systematic evolution of ligands by exponential enrichment (SELEX. A purified human BACE1 extracellular domain was used as a target to conduct an in vitro selection process using SELEX. Two DNA aptamers were capable of binding to BACE1 with high affinity and good specificity, with Kd values in the nanomolar range. We subsequently confirmed that one aptamer, A1, exhibited a distinct inhibitory effect on BACE1 activity in an AD cell model. We detected the effects of M17-APPsw cells that stably expressed Swedish mutant APP after aptamer A1 treatment. Aβ40 and Aβ42 concentrations secreted by M17-APPsw cells decreased intracellularly and in culture media. Furthermore, Western blot analysis indicated that sAPPβ expression significantly decreased in the A1 treated versus control groups. These findings support the preliminary feasibility of an aptamer evolved from a SELEX strategy to function as a potential BACE1 inhibitor. To our knowledge, this is the first study to acquire a DNA aptamer that exhibited binding specificity to BACE1 and inhibited its activity.

Time Evolving Fission Chain Theory and Fast Neutron and Gamma-Ray Counting Distributions

International Nuclear Information System (INIS)

Kim, K. S.; Nakae, L. F.; Prasad, M. K.; Snyderman, N. J.; Verbeke, J. M.

2015-01-01

Here, we solve a simple theoretical model of time evolving fission chains due to Feynman that generalizes and asymptotically approaches the point model theory. The point model theory has been used to analyze thermal neutron counting data. This extension of the theory underlies fast counting data for both neutrons and gamma rays from metal systems. Fast neutron and gamma-ray counting is now possible using liquid scintillator arrays with nanosecond time resolution. For individual fission chains, the differential equations describing three correlated probability distributions are solved: the time-dependent internal neutron population, accumulation of fissions in time, and accumulation of leaked neutrons in time. Explicit analytic formulas are given for correlated moments of the time evolving chain populations. The equations for random time gate fast neutron and gamma-ray counting distributions, due to randomly initiated chains, are presented. Correlated moment equations are given for both random time gate and triggered time gate counting. There are explicit formulas for all correlated moments are given up to triple order, for all combinations of correlated fast neutrons and gamma rays. The nonlinear differential equations for probabilities for time dependent fission chain populations have a remarkably simple Monte Carlo realization. A Monte Carlo code was developed for this theory and is shown to statistically realize the solutions to the fission chain theory probability distributions. Combined with random initiation of chains and detection of external quanta, the Monte Carlo code generates time tagged data for neutron and gamma-ray counting and from these data the counting distributions.

Beta-Poisson model for single-cell RNA-seq data analyses.

Science.gov (United States)

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Radiation damage, repopulation and cell recovery analysis of in vitro tumour cell megacolony culture data using a non-Poissonian cell repopulation TCP model

International Nuclear Information System (INIS)

Stavrev, P; Weldon, M; Warkentin, B; Stavreva, N; Fallone, B G

2005-01-01

The effects of radiation damage, tumour repopulation and cell sublethal damage repair and the possibility of extracting information about the model parameters describing them are investigated in this work. Previously published data on two different cultured cell lines were analysed with the help of a tumour control probability (TCP) model that describes tumour cell dynamics properly. Different versions of a TCP model representing the cases of full or partial cell recovery between fractions of radiation, accompanied by repopulation or no repopulation were used to fit the data and were ranked according to statistical criteria. The data analysis shows the importance of the linear-quadratic mechanism of cell damage for the description of the in vitro cell dynamics. In a previous work where in vivo data were analysed, the employment of the single hit model of cell kill and cell repopulation produced the best fit, while ignoring the quadratic term of cell damage in the current analysis leads to poor fits. It is also concluded that more experiments using different fractionation regimes producing diverse data are needed to help model analysis and better ranking of the models

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

Science.gov (United States)

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

2012-12-07

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

Mechanistic modelling of a cathode-supported tubular solid oxide fuel cell

Science.gov (United States)

Suwanwarangkul, R.; Croiset, E.; Pritzker, M. D.; Fowler, M. W.; Douglas, P. L.; Entchev, E.

A two-dimensional mechanistic model of a tubular solid oxide fuel cell (SOFC) considering momentum, energy, mass and charge transport is developed. The model geometry of a single cell comprises an air-preheating tube, air channel, fuel channel, anode, cathode and electrolyte layers. The heat radiation between cell and air-preheating tube is also incorporated into the model. This allows the model to predict heat transfer between the cell and air-preheating tube accurately. The model is validated and shows good agreement with literature data. It is anticipated that this model can be used to help develop efficient fuel cell designs and set operating variables under practical conditions. The transport phenomena inside the cell, including gas flow behaviour, temperature, overpotential, current density and species concentration, are analysed and discussed in detail. Fuel and air velocities are found to vary along flow passages depending on the local temperature and species concentrations. This model demonstrates the importance of incorporating heat radiation into a tubular SOFC model. Furthermore, the model shows that the overall cell performance is limited by O 2 diffusion through the thick porous cathode and points to the development of new cathode materials and designs being important avenues to enhance cell performance.

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

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...

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

Science.gov (United States)

Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

2016-01-01

Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

Directory of Open Access Journals (Sweden)

Arno Steinacher

Full Text Available Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

KAUST Repository

Kachalo, Sëma

2015-05-14

Geometric and mechanical properties of individual cells and interactions among neighboring cells are the basis of formation of tissue patterns. Understanding the complex interplay of cells is essential for gaining insight into embryogenesis, tissue development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating properties of individual cells as well as detailed description of the dynamic growth process, with all topological changes accounted for. Cell size, shape, and division plane orientation are modeled realistically. In addition, cell birth, cell growth, cell shrinkage, cell death, cell division, cell collision, and cell rearrangements are now fully accounted for. Different models of cell-cell interactions, such as lateral inhibition during the process of growth, can be studied in detail. Cellular pattern formation for monolayered tissues from arbitrary initial conditions, including that of a single cell, can also be studied in detail. Computational efficiency is achieved through the employment of a special data structure that ensures access to neighboring cells in constant time, without additional space requirement. We have successfully generated tissues consisting of more than 20,000 cells starting from 2 cells within 1 hour. We show that our model can be used to study embryogenesis, tissue fusion, and cell apoptosis. We give detailed study of the classical developmental process of bristle formation on the epidermis of D. melanogaster and the fundamental problem of homeostatic size control in epithelial tissues. Simulation results reveal significant roles of solubility of secreted factors in both the bristle formation and the homeostatic control of tissue size. Our method can be used to study broad problems in monolayered tissue formation. Our software is publicly

Feathers and fins: non-mammalian models for hair cell regeneration.

Science.gov (United States)

Brignull, Heather R; Raible, David W; Stone, Jennifer S

2009-06-24

Death of mechanosensory cells in the inner ear results in two profound disabilities: hearing loss and balance disorders. Although mammals lack the capacity to regenerate hair cells, recent studies in mice and other rodents have offered valuable insight into strategies for stimulating hair cell regeneration in mammals. Investigations of model organisms that retain the ability to form new hair cells after embryogenesis, such as fish and birds, are equally important and have provided clues as to the cellular and molecular mechanisms that may block hair cell regeneration in mammals. Here, we summarize studies on hair cell regeneration in the chicken and the zebrafish, discuss specific advantages of each model, and propose future directions for the use of non-mammalian models in understanding hair cell regeneration.

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

Science.gov (United States)

Patou, François; AlZahra’a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E.

2016-01-01

The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods. PMID:27598208

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications.

Science.gov (United States)

Patou, François; AlZahra'a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E

2016-09-03

The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

Directory of Open Access Journals (Sweden)

François Patou

2016-09-01

Full Text Available The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

Programmatic access to logical models in the Cell Collective modeling environment via a REST API.

Science.gov (United States)

Kowal, Bryan M; Schreier, Travis R; Dauer, Joseph T; Helikar, Tomáš

2016-01-01

Cell Collective (www.cellcollective.org) is a web-based interactive environment for constructing, simulating and analyzing logical models of biological systems. Herein, we present a Web service to access models, annotations, and simulation data in the Cell Collective platform through the Representational State Transfer (REST) Application Programming Interface (API). The REST API provides a convenient method for obtaining Cell Collective data through almost any programming language. To ensure easy processing of the retrieved data, the request output from the API is available in a standard JSON format. The Cell Collective REST API is freely available at http://thecellcollective.org/tccapi. All public models in Cell Collective are available through the REST API. For users interested in creating and accessing their own models through the REST API first need to create an account in Cell Collective (http://thecellcollective.org). thelikar2@unl.edu. Technical user documentation: https://goo.gl/U52GWo. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Concerted evolution of body mass and cell size: similar patterns among species of birds (Galliformes) and mammals (Rodentia)

Science.gov (United States)

Dragosz-Kluska, Dominika; Pis, Tomasz; Pawlik, Katarzyna; Kapustka, Filip; Kilarski, Wincenty M.; Kozłowski, Jan

2018-01-01

ABSTRACT Cell size plays a role in body size evolution and environmental adaptations. Addressing these roles, we studied body mass and cell size in Galliformes birds and Rodentia mammals, and collected published data on their genome sizes. In birds, we measured erythrocyte nuclei and basal metabolic rates (BMRs). In birds and mammals, larger species consistently evolved larger cells for five cell types (erythrocytes, enterocytes, chondrocytes, skin epithelial cells, and kidney proximal tubule cells) and evolved smaller hepatocytes. We found no evidence that cell size differences originated through genome size changes. We conclude that the organism-wide coordination of cell size changes might be an evolutionarily conservative characteristic, and the convergent evolutionary body size and cell size changes in Galliformes and Rodentia suggest the adaptive significance of cell size. Recent theory predicts that species evolving larger cells waste less energy on tissue maintenance but have reduced capacities to deliver oxygen to mitochondria and metabolize resources. Indeed, birds with larger size of the abovementioned cell types and smaller hepatocytes have evolved lower mass-specific BMRs. We propose that the inconsistent pattern in hepatocytes derives from the efficient delivery system to hepatocytes, combined with their intense involvement in supracellular function and anabolic activity. PMID:29540429

Concerted evolution of body mass and cell size: similar patterns among species of birds (Galliformes and mammals (Rodentia

Directory of Open Access Journals (Sweden)

Marcin Czarnoleski

2018-04-01

Full Text Available Cell size plays a role in body size evolution and environmental adaptations. Addressing these roles, we studied body mass and cell size in Galliformes birds and Rodentia mammals, and collected published data on their genome sizes. In birds, we measured erythrocyte nuclei and basal metabolic rates (BMRs. In birds and mammals, larger species consistently evolved larger cells for five cell types (erythrocytes, enterocytes, chondrocytes, skin epithelial cells, and kidney proximal tubule cells and evolved smaller hepatocytes. We found no evidence that cell size differences originated through genome size changes. We conclude that the organism-wide coordination of cell size changes might be an evolutionarily conservative characteristic, and the convergent evolutionary body size and cell size changes in Galliformes and Rodentia suggest the adaptive significance of cell size. Recent theory predicts that species evolving larger cells waste less energy on tissue maintenance but have reduced capacities to deliver oxygen to mitochondria and metabolize resources. Indeed, birds with larger size of the abovementioned cell types and smaller hepatocytes have evolved lower mass-specific BMRs. We propose that the inconsistent pattern in hepatocytes derives from the efficient delivery system to hepatocytes, combined with their intense involvement in supracellular function and anabolic activity.

A mathematical model of a lithium/thionyl chloride primary cell

Science.gov (United States)

Evans, T. I.; Nguyen, T. V.; White, R. E.

1987-08-01

A 1-D mathematical model for the lithium/thionyl chloride primary cell was developed to investigate methods of improving its performance and safety. The model includes many of the components of a typical lithium/thionyl chloride cell such as the porous lithium chloride film which forms on the lithium anode surface. The governing equations are formulated from fundamental conservation laws using porous electrode theory and concentrated solution theory. The model is used to predict 1-D, time dependent profiles of concentration, porosity, current, and potential as well as cell temperature and voltage. When a certain discharge rate is required, the model can be used to determine the design criteria and operating variables which yield high cell capacities. Model predictions can be used to establish operational and design limits within which the thermal runaway problem, inherent in these cells, can be avoided.

Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model.

Science.gov (United States)

Pepe, Daniele; Do, Jin Hwan

2015-12-16

Increasing evidence indicates that different morphological types of cell death coexist in the brain of patients with Parkinson's disease (PD), but the molecular explanation for this is still under investigation. In this study, we identified perturbed pathways in two different cell models for PD through the following procedures: (1) enrichment pathway analysis with differentially expressed genes and the Reactome pathway database, and (2) construction of the shortest path model for the enriched pathway and detection of significant shortest path model with fitting time-course microarray data of each PD cell model to structural equation model. Two PD cell models constructed by the same neurotoxin showed different perturbed pathways. That is, one showed perturbation of three Reactome pathways, including cellular senescence, chromatin modifying enzymes, and chromatin organization, while six modules within metabolism pathway represented perturbation in the other. This suggests that the activation of common upstream cell death pathways in PD may result in various down-stream processes, which might be associated with different morphological types of cell death. In addition, our results might provide molecular clues for coexistence of different morphological types of cell death in PD patients.

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.

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......, 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.......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...

Evolved Cas9 variants with broad PAM compatibility and high DNA specificity.

Science.gov (United States)

Hu, Johnny H; Miller, Shannon M; Geurts, Maarten H; Tang, Weixin; Chen, Liwei; Sun, Ning; Zeina, Christina M; Gao, Xue; Rees, Holly A; Lin, Zhi; Liu, David R

2018-04-05

A key limitation of the use of the CRISPR-Cas9 system for genome editing and other applications is the requirement that a protospacer adjacent motif (PAM) be present at the target site. For the most commonly used Cas9 from Streptococcus pyogenes (SpCas9), the required PAM sequence is NGG. No natural or engineered Cas9 variants that have been shown to function efficiently in mammalian cells offer a PAM less restrictive than NGG. Here we use phage-assisted continuous evolution to evolve an expanded PAM SpCas9 variant (xCas9) that can recognize a broad range of PAM sequences including NG, GAA and GAT. The PAM compatibility of xCas9 is the broadest reported, to our knowledge, among Cas9 proteins that are active in mammalian cells, and supports applications in human cells including targeted transcriptional activation, nuclease-mediated gene disruption, and cytidine and adenine base editing. Notably, despite its broadened PAM compatibility, xCas9 has much greater DNA specificity than SpCas9, with substantially lower genome-wide off-target activity at all NGG target sites tested, as well as minimal off-target activity when targeting genomic sites with non-NGG PAMs. These findings expand the DNA targeting scope of CRISPR systems and establish that there is no necessary trade-off between Cas9 editing efficiency, PAM compatibility and DNA specificity.

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.

Setting FIRES to Stem Cell Research

Science.gov (United States)

Miller, Roxanne Grietz

2005-01-01

The goal of this lesson is to present the basic scientific knowledge about stem cells, the promise of stem cell research to medicine, and the ethical considerations and arguments involved. One of the challenges of discussing stem cell research is that the field is constantly evolving and the most current information changes almost daily. Few…

Knowledge extraction from evolving spiking neural networks with rank order population coding.

Science.gov (United States)

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

CellML, SED-ML, and the Physiome Model Repository

OpenAIRE

Nickerson, David

2016-01-01

Invited presentation delivered at COMBINE 2016.CellML, SED-ML, and the Physiome Model Repository.David Nickerson, Auckland Bioengineering Institute, University of Auckland, New Zealand.CellML is an XML-based protocol for storing and exchanging computer-based mathematical models in an unambiguous, modular, and reusable manner. In addition to introducing CellML, in this presentation I will provide some of physiological examples that have help drive the development and adoption of CellML. I will...

A new level set model for cell image segmentation

Science.gov (United States)

Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

2011-02-01

In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

Continual Learning through Evolvable Neural Turing Machines

DEFF Research Database (Denmark)

Lüders, Benno; Schläger, Mikkel; Risi, Sebastian

2016-01-01

Continual learning, i.e. the ability to sequentially learn tasks without catastrophic forgetting of previously learned ones, is an important open challenge in machine learning. In this paper we take a step in this direction by showing that the recently proposed Evolving Neural Turing Machine (ENTM...

Identification of dual-tropic HIV-1 using evolved neural networks.

Science.gov (United States)

Fogel, Gary B; Lamers, Susanna L; Liu, Enoch S; Salemi, Marco; McGrath, Michael S

2015-11-01

Blocking the binding of the envelope HIV-1 protein to immune cells is a popular concept for development of anti-HIV therapeutics. R5 HIV-1 binds CCR5, X4 HIV-1 binds CXCR4, and dual-tropic HIV-1 can bind either coreceptor for cellular entry. R5 viruses are associated with early infection and over time can evolve to X4 viruses that are associated with immune failure. Dual-tropic HIV-1 is less studied; however, it represents functional antigenic intermediates during the transition of R5 to X4 viruses. Viral tropism is linked partly to the HIV-1 envelope V3 domain, where the amino acid sequence helps dictate the receptor a particular virus will target; however, using V3 sequence information to identify dual-tropic HIV-1 isolates has remained difficult. Our goal in this study was to elucidate features of dual-tropic HIV-1 isolates that assist in the biological understanding of dual-tropism and develop an approach for their detection. Over 1559 HIV-1 subtype B sequences with known tropisms were analyzed. Each sequence was represented by 73 structural, biochemical and regional features. These features were provided to an evolved neural network classifier and evaluated using balanced and unbalanced data sets. The study resolved R5X4 viruses from R5 with an accuracy of 81.8% and from X4 with an accuracy of 78.8%. The approach also identified a set of V3 features (hydrophobicity, structural and polarity) that are associated with tropism transitions. The ability to distinguish R5X4 isolates will improve computational tropism decisions for R5 vs. X4 and assist in HIV-1 research and drug development efforts. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Dental pulp stem cells promote regeneration of damaged neuron cells on the cellular model of Alzheimer's disease.

Science.gov (United States)

Wang, Feixiang; Jia, Yali; Liu, Jiajing; Zhai, Jinglei; Cao, Ning; Yue, Wen; He, Huixia; Pei, Xuetao

2017-06-01

Alzheimer's disease (AD) is an incurable neurodegenerative disease and many types of stem cells have been used in AD therapy with some favorable effects. In this study, we investigated the potential therapeutical effects of human dental pulp stem cells (hDPSCs) on AD cellular model which established by okadaic acid (OA)-induced damage to human neuroblastoma cell line, SH-SY5Y, in vitro for 24 h. After confirmed the AD cellular model, the cells were co-culture with hDPSCs by transwell co-culture system till 24 h for treatment. Then the cytomorphology of the hDPSCs-treated cells were found to restore gradually with re-elongation of retracted dendrites. Meanwhile, Cell Counting Kit-8 assay and Hoechst 33258 staining showed that hDPSCs caused significant increase in the viability and decrease in apoptosis of the model cells, respectively. Observation of DiI labeling also exhibited the prolongation dendrites in hDPSCs-treated cells which were obviously different from the retraction dendrites in AD model cells. Furthermore, specific staining of α-tubulin and F-actin demonstrated that the hDPSCs-treated cells had the morphology of restored neurons, with elongated dendrites, densely arranged microfilaments, and thickened microtubular fibrils. In addition, results from western blotting revealed that phosphorylation at Ser 396 of Tau protein was significantly suppressed by adding of hDPSCs. These results indicate that hDPSCs may promote regeneration of damaged neuron cells in vitro model of AD and may serve as a useful cell source for treatment of AD. © 2017 International Federation for Cell Biology.

Designing Garments to Evolve Over Time

DEFF Research Database (Denmark)

Riisberg, Vibeke; Grose, Lynda

2017-01-01

This paper proposes a REDO of the current fashion paradigm by investigating how garments might be designed to evolve over time. The purpose is to discuss ways of expanding the traditional role of the designer to include temporal dimensions of creating, producing and using clothes and to suggest...... to a REDO of design education, to further research and the future fashion and textile industry....

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…

The utility of dermoscopy in the diagnosis of evolving lesions of vitiligo

Directory of Open Access Journals (Sweden)

Sarvesh S Thatte

2014-01-01

Full Text Available Background: Early lesions of vitiligo can be confused with various other causes of hypopigmentation and depigmentation. Few workers have utilized dermoscopy for the diagnosis of evolving lesions of vitiligo. Aim: To analyze the dermoscopic findings of evolving lesions in diagnosed cases of vitiligo and to correlate them histopathologically. Methods: Dermoscopy of evolving lesions in 30 diagnosed cases of vitiligo was performed using both polarized light and ultraviolet light. Result: On polarized light examination, the pigmentary network was found to be reduced in 12 (40% of 30 patients, absent in 9 (30%, and reversed in 6 (20% patients; 2 patients (6.7% showed perifollicular hyperpigmentation and 1 (3.3% had perilesional hyperpigmentation. A diffuse white glow was demonstrable in 27 (90% of 30 patients on ultraviolet light examination. Melanocytes were either reduced in number or absent in 12 (40% of 30 patients on histopathology. Conclusion: Pigmentary network changes, and perifollicular and perilesional hyperpigmentation on polarized light examination, and a diffuse white glow on ultraviolet light examination were noted in evolving vitiligo lesions. Histopathological examination was comparatively less reliable. Dermoscopy appears to be better than routine histopathology in the diagnosis of evolving lesions of vitiligo and can obviate the need for a skin biopsy.

Evolvement simulation of the probability of neutron-initiating persistent fission chain

International Nuclear Information System (INIS)

Wang Zhe; Hong Zhenying

2014-01-01

Background: Probability of neutron-initiating persistent fission chain, which has to be calculated in analysis of critical safety, start-up of reactor, burst waiting time on pulse reactor, bursting time on pulse reactor, etc., is an inherent parameter in a multiplying assembly. Purpose: We aim to derive time-dependent integro-differential equation for such probability in relative velocity space according to the probability conservation, and develop the deterministic code Dynamic Segment Number Probability (DSNP) based on the multi-group S N method. Methods: The reliable convergence of dynamic calculation was analyzed and numerical simulation of the evolvement process of dynamic probability for varying concentration was performed under different initial conditions. Results: On Highly Enriched Uranium (HEU) Bare Spheres, when the time is long enough, the results of dynamic calculation approach to those of static calculation. The most difference of such results between DSNP and Partisn code is less than 2%. On Baker model, over the range of about 1 μs after the first criticality, the most difference between the dynamic and static calculation is about 300%. As for a super critical system, the finite fission chains decrease and the persistent fission chains increase as the reactivity aggrandizes, the dynamic evolvement curve of initiation probability is close to the static curve within the difference of 5% when the K eff is more than 1.2. The cumulative probability curve also indicates that the difference of integral results between the dynamic calculation and the static calculation decreases from 35% to 5% as the K eff increases. This demonstrated that the ability of initiating a self-sustaining fission chain reaction approaches stabilization, while the former difference (35%) showed the important difference of the dynamic results near the first criticality with the static ones. The DSNP code agrees well with Partisn code. Conclusions: There are large numbers of

A minimal physical model for crawling cells

Science.gov (United States)

Tiribocchi, Adriano; Tjhung, Elsen; Marenduzzo, Davide; Cates, Michael E.

Cell motility in higher organisms (eukaryotes) is fundamental to biological functions such as wound healing or immune response, and is also implicated in diseases such as cancer. For cells crawling on solid surfaces, considerable insights into motility have been gained from experiments replicating such motion in vitro. Such experiments show that crawling uses a combination of actin treadmilling (polymerization), which pushes the front of a cell forward, and myosin-induced stress (contractility), which retracts the rear. We present a simplified physical model of a crawling cell, consisting of a droplet of active polar fluid with contractility throughout, but treadmilling connected to a thin layer near the supporting wall. The model shows a variety of shapes and/or motility regimes, some closely resembling cases seen experimentally. Our work supports the view that cellular motility exploits autonomous physical mechanisms whose operation does not need continuous regulatory effort.

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

On a poroviscoelastic model for cell crawling

KAUST Repository

Kimpton, L. S.; Whiteley, J. P.; Waters, S. L.; Oliver, J. M.

2014-01-01

-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

Qualitative analysis of an integro-differential equation model of periodic chemotherapy

KAUST Repository

Jain, Harsh Vardhan

2012-12-01

An existing model of tumor growth that accounts for cell cycle arrest and cell death induced by chemotherapy is extended to simulate the response to treatment of a tumor growing in vivo. The tumor is assumed to undergo logistic growth in the absence of therapy, and treatment is administered periodically rather than continuously. Necessary and sufficient conditions for the global stability of the cancer-free equilibrium are derived and conditions under which the system evolves to periodic solutions are determined. © 2012 Elsevier Ltd. All rights reserved.

Modelling radiation-induced cell death and tumour re-oxygenation: local versus global and instant versus delayed cell death

International Nuclear Information System (INIS)

Gago-Arias, Araceli; Espinoza, Ignacio; Sánchez-Nieto, Beatriz; Aguiar, Pablo; Pardo-Montero, Juan

2016-01-01

The resistance of hypoxic cells to radiation, due to the oxygen dependence of radiosensitivity, is well known and must be taken into account to accurately calculate the radiation induced cell death. A proper modelling of the response of tumours to radiation requires deriving the distribution of oxygen at a microscopic scale. This usually involves solving the reaction-diffusion equation in tumour voxels using a vascularization distribution model. Moreover, re-oxygenation arises during the course of radiotherapy, one reason being the increase of available oxygen caused by cell killing, which can turn hypoxic tumours into oxic. In this work we study the effect of cell death kinetics in tumour oxygenation modelling, analysing how it affects the timing of re-oxygenation, surviving fraction and tumour control. Two models of cell death are compared, an instantaneous cell killing, mimicking early apoptosis, and a delayed cell death scenario in which cells can die shortly after being damaged, as well as long after irradiation. For each of these scenarios, the decrease in oxygen consumption due to cell death can be computed globally (macroscopic voxel average) or locally (microscopic). A re-oxygenation model already used in the literature, the so called full re-oxygenation, is also considered. The impact of cell death kinetics and re-oxygenation on tumour responses is illustrated for two radiotherapy fractionation schemes: a conventional schedule, and a hypofractionated treatment. The results show large differences in the doses needed to achieve 50% tumour control for the investigated cell death models. Moreover, the models affect the tumour responses differently depending on the treatment schedule. This corroborates the complex nature of re-oxygenation, showing the need to take into account the kinetics of cell death in radiation response models. (paper)

A polynomial based model for cell fate prediction in human diseases.

Science.gov (United States)

Ma, Lichun; Zheng, Jie

2017-12-21

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development. In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable. Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

Structural evolvement and the capability of resistance to γ-ray irradiation on zircon originating from nyainqentanglha granite

International Nuclear Information System (INIS)

Cui Chunlong; Zhang Dong; Kang Houjun; Wang Xiaoli; Zhou Yulin; Yi Facheng; Lu Xirui; Tang Jingyou

2010-01-01

In order to investigate the structural evolvement and the capability of resistance to γ-ray irradiation on zircon as mothball waste forms of radionuclide, the zircon crystals (11.01±0.24 M) were studied as investigative object, which were collected from nyainqentanglha granite. All the samples were irradiated using a 60 Co y-ray source with 576 kGy doses. Phases, structures and microstructures of the as-gained samples before and after y-ray irradiation were characterized by means of a multi-functional microscope, cathodoluminescence (CL), backscattered electron microprobe (BEM), X-ray diffraction (XRD), Raman spectroscopy (Raman), infrared spectroscopy (IR) and scanning electron microscopy (SEM), and so on. Moreover, the geological backgrounds and chemical compositions of zircons originating from natural rocks were analyzed as well. The results indicated that the as-gained crystals came from magmatic rock which undergone near 11 million years geological evolvement and still contain UO 2 and ThO 2 with the contents of 0.5729 wt%. The alteration of 10 -3 nm magnitude in the crystal cell parameters was measured (of the standard XRD card of zircon). The irradiation on the crystalline samples using γ-ray induced to the alteration of 10 -4 nm magnitude for their crystal cell parameters. The conclusion shows that zircon crystals with a certain amount of UO 2 and ThO 2 have better structural stability for the y-ray irradiation. (authors)

The bankfull hydraulic geometry of evolving meander bends

Science.gov (United States)

Monegaglia, F.; Tubino, M.; Zolezzi, G.

2017-12-01

Changes in the bankfull hydraulic geometry of meandering rivers associated with meander growth from incipient meandering to cutoffs have seldom been analysed in detail. Such information is also needed by meander morphodynamic models, most of which simulate the evolution of bankfull channel geometry by simply accounting for channel slope reduction inversely proportional to elongation, while changes in bankfull channel width are often neglected or, when they are considered, they are not consistent with the few available observations. To address these gaps we first perform an extensive, systematic, bend-scale evolutionary analysis of bankfull channel widths in several large meandering rivers in the Amazon basin, over a three decades time period, from remotely sensed field data. The analysis consistently show a slight decreasing trend of the bankfull channel width during the planform evolution towards cutoff. Furthermore, we develop a physically based model for the evolution of bankfull channel geometry during the planform development of meandering rivers. The model is based on the conservation of sediment discharge. An integrated one-dimensional Exner equation that accounts for meander elongation, sediment supply conservation and sediment income from the channel banks, allows us to predict the evolution of the channel slope. The evolution of the channel width is modeled through a threshold equation. The model correctly predicts the slight variability of channel width during meander development and a gentler reduction of the channel slope, which is mitigated by the conservation of sediment supply. The bankfull geometry of highly dynamic meandering rivers is predicted to be elongation-dominated, while the one related to slowly evolving meandering rivers is sediment supply-dominated. Finally, we discuss the implications of the proposed modeling framework in terms of planform structure, meander shape and morphodynamic influence.

Evolving lithospheric flexure and paleotopography of the Pyrenean Orogen from 3D flexural modeling and basin analysis

Science.gov (United States)

Curry, M. E.; van der Beek, P.; Huismans, R. S.; Muñoz, J. A.

2017-12-01

The Pyrenees are an asymmetric, doubly-vergent orogen with retro- and pro- foreland basins that preserve a record of deformation since the Mesozoic. The extensive research and exploration efforts on the mountain belt and flanking foreland basins provide an exceptional dataset for investigating geodynamics and surface processes over large spatial and temporal scales in western Europe. We present the results of a numerical modeling study investigating the spatio-temporal variation in lithospheric flexure in response to the developing orogen. We employ a finite element method to model the 3D flexural deformation of the lithosphere beneath the Pyrenean orogen since the onset of convergence in the late Cretaceous. Using subsurface, geophysical, and structural data, we describe the evolving geometry of both the French Aquitaine and Spanish Ebro foreland basins at the present (post-orogenic), the mid-Eocene (peak orogenic), the Paleocene (early orogenic), and the end of the Cretaceous (pre- to early orogenic). The flexural modeling provides insight into how both the rigidity of the lithosphere and the paleotopographic load have varied over the course of orogenesis to shape the basin geometry. We find that the overriding European plate has higher rigidity than the subducting Iberian plate, with modern Effective Elastic Thickness (EET) values of 20 ± 2 and 12 ± 2 km, respectively. Modeling indicates that the modern rigidity of both plates decreases westward towards the Bay of Biscay. The lithospheric rigidity has increased by 50% since the Mesozoic with early Cenozoic EET values of 13 ± 2 and 8 ± 1 km for the European and Iberian plates, respectively. The topographic load began increasing with convergence in the late Cretaceous, reaching modern levels in the central and eastern Pyrenees by the Eocene. In contrast, the topographic load in the western Pyrenees was 70% of the modern value in the Eocene, and experienced topographic growth through the Oligo-Miocene. The

Development of a real-time fuel cell stack modelling solution with integrated test rig interface for the generic fuel cell modelling environment (GenFC) software

Energy Technology Data Exchange (ETDEWEB)

Fraser, S.D.; Monsberger, M.; Hacker, V. [Graz Univ. of Technology, Graz (Austria). Christian Doppler Laboratory for Fuel Cell Systems; Gubner, A.; Reimer, U. [Forschungszentrum Julich, Julich (Germany)

2007-07-01

Since the late 1980s, numerous FC models have been developed by scientists and engineers worldwide to design, control and optimize fuel cells (FCs) and fuel cell (FC) power systems. However, state-of-the-art FC models have only a small range of applications within the versatile field of FC modelling. As fuel cell technology approaches commercialization, the scientific community is faced with the challenge of providing robust fuel cell models that are compatible with established processes in industrial product development. One such process, known as Hardware in the Loop (HiL), requires real-time modelling capability. HiL is used for developing and testing hardware components by adding the complexity of the related dynamic systems with mathematical representations. Sensors and actuators are used to interface simulated and actual hardware components. As such, real-time fuel cell models are among the key elements in the development of the Generic Fuel Cell Modelling Environment (GenFC) software. Six European partners are developing GenFC under the support of the Sixth European Framework Programme for Research and Technological Development (FP6). GenFC is meant to increase the use of fuel cell modelling for systems design and to enable cost- and time-efficient virtual experiments for optimizing operating parameters. This paper presented an overview of the GenFC software and the GenFC HiL functionality. It was concluded that GenFC is going to be an extendable software tool providing FC modelling techniques and solutions to a wide range of different FC modelling applications. By combining the flexibility of the GenFC software with this HiL-specific functionality, GenFC is going to promote the use of FC model-based HiL technology in FC system development. 9 figs.

FY1995 evolvable hardware chip; 1995 nendo shinkasuru hardware chip

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This project aims at the development of 'Evolvable Hardware' (EHW) which can adapt its hardware structure to the environment to attain better hardware performance, under the control of genetic algorithms. EHW is a key technology to explore the new application area requiring real-time performance and on-line adaptation. 1. Development of EHW-LSI for function level hardware evolution, which includes 15 DSPs in one chip. 2. Application of the EHW to the practical industrial applications such as data compression, ATM control, digital mobile communication. 3. Two patents : (1) the architecture and the processing method for programmable EHW-LSI. (2) The method of data compression for loss-less data, using EHW. 4. The first international conference for evolvable hardware was held by authors: Intl. Conf. on Evolvable Systems (ICES96). It was determined at ICES96 that ICES will be held every two years between Japan and Europe. So the new society has been established by us. (NEDO)

FY1995 evolvable hardware chip; 1995 nendo shinkasuru hardware chip

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This project aims at the development of 'Evolvable Hardware' (EHW) which can adapt its hardware structure to the environment to attain better hardware performance, under the control of genetic algorithms. EHW is a key technology to explore the new application area requiring real-time performance and on-line adaptation. 1. Development of EHW-LSI for function level hardware evolution, which includes 15 DSPs in one chip. 2. Application of the EHW to the practical industrial applications such as data compression, ATM control, digital mobile communication. 3. Two patents : (1) the architecture and the processing method for programmable EHW-LSI. (2) The method of data compression for loss-less data, using EHW. 4. The first international conference for evolvable hardware was held by authors: Intl. Conf. on Evolvable Systems (ICES96). It was determined at ICES96 that ICES will be held every two years between Japan and Europe. So the new society has been established by us. (NEDO)

Evolvability of thermophilic proteins from archaea and bacteria.

Science.gov (United States)

Takano, Kazufumi; Aoi, Atsushi; Koga, Yuichi; Kanaya, Shigenori

2013-07-16

Proteins from thermophiles possess high thermostability. The stabilization mechanisms differ between archaeal and bacterial proteins, whereby archaeal proteins are mainly stabilized via hydrophobic interactions and bacterial proteins by ion pairs. High stability is an important factor in promoting protein evolution, but the precise means by which different stabilization mechanisms affect the evolution process remain unclear. In this study, we investigated a random mutational drift of esterases from thermophilic archaea and bacteria at high temperatures. Our results indicate that mutations in archaeal proteins lead to improved function with no loss of stability, while mutant bacterial proteins are largely destabilized with decreased activity at high temperatures. On the basis of these findings, we suggest that archaeal proteins possess higher "evolvability" than bacterial proteins under temperature selection and are additionally able to evolve into eukaryotic proteins.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

Directory of Open Access Journals (Sweden)

Julie Behr

Full Text Available This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC and substrate adherent polymorphonuclear neutrophils (PMN is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

Science.gov (United States)

Behr, Julie; Gaskin, Byron; Fu, Changliang; Dong, Cheng; Kunz, Robert

2015-01-01

This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC) and substrate adherent polymorphonuclear neutrophils (PMN) is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD) framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

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.

Design, Modeling, Fabrication & Characterization of Industrial Si Solar Cells

Science.gov (United States)

Chowdhury, Ahrar Ahmed

Photovoltaic is a viable solution towards meeting the energy demand in an ecofriendly environment. To ensure the mass access in photovoltaic electricity, cost effective approach needs to be adapted. This thesis aims towards substrate independent fabrication process in order to achieve high efficiency cost effective industrial Silicon (Si) solar cells. Most cost-effective structures, such as, Al-BSF (Aluminum Back Surface Field), FSF (Front Surface Field) and bifacial cells are investigated in detail to exploit the efficiency potentials. First off, we introduced two-dimensional simulation model to design and modeling of most commonly used Si solar cells in today's PV arena. Best modelled results of high efficiency Al-BSF, FSF and bifacial cells are 20.50%, 22% and 21.68% respectively. Special attentions are given on the metallization design on all the structures in order to reduce the Ag cost. Furthermore, detail design and modeling were performed on FSF and bifacial cells. The FSF cells has potentials to gain 0.42%abs efficiency by combining the emitter design and front surface passivation. The prospects of bifacial cells can be revealed with the optimization of gridline widths and gridline numbers. Since, bifacial cells have metallization on both sides, a double fold cost saving is possible via innovative metallization design. Following modeling an effort is undertaken to reach the modelled result in fabrication the process. We proposed substrate independent fabrication process aiming towards establishing simultaneous processing sequences for both monofacial and bifacial cells. Subsequently, for the contact formation cost effective screen-printed technology is utilized throughout this thesis. The best Al-BSF cell attained efficiency ˜19.40%. Detail characterization was carried out to find a roadmap of achieving >20.50% efficiency Al-BSF cell. Since, n-type cell is free from Light Induced degradation (LID), recently there is a growing interest on FSF cell. Our