A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

PubMed Central

2011-01-01

Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191

Broken flow symmetry explains the dynamics of small particles in deterministic lateral displacement arrays

PubMed Central

Kim, Sung-Cheol; Wunsch, Benjamin H.; Hu, Huan; Smith, Joshua T.; Stolovitzky, Gustavo

2017-01-01

Deterministic lateral displacement (DLD) is a technique for size fractionation of particles in continuous flow that has shown great potential for biological applications. Several theoretical models have been proposed, but experimental evidence has demonstrated that a rich class of intermediate migration behavior exists, which is not predicted. We present a unified theoretical framework to infer the path of particles in the whole array on the basis of trajectories in a unit cell. This framework explains many of the unexpected particle trajectories reported and can be used to design arrays for even nanoscale particle fractionation. We performed experiments that verify these predictions and used our model to develop a condenser array that achieves full particle separation with a single fluidic input. PMID:28607075

VirtualLeaf: an open-source framework for cell-based modeling of plant tissue growth and development.

PubMed

Merks, Roeland M H; Guravage, Michael; Inzé, Dirk; Beemster, Gerrit T S

2011-02-01

Plant organs, including leaves and roots, develop by means of a multilevel cross talk between gene regulation, patterned cell division and cell expansion, and tissue mechanics. The multilevel regulatory mechanisms complicate classic molecular genetics or functional genomics approaches to biological development, because these methodologies implicitly assume a direct relation between genes and traits at the level of the whole plant or organ. Instead, understanding gene function requires insight into the roles of gene products in regulatory networks, the conditions of gene expression, etc. This interplay is impossible to understand intuitively. Mathematical and computer modeling allows researchers to design new hypotheses and produce experimentally testable insights. However, the required mathematics and programming experience makes modeling poorly accessible to experimental biologists. Problem-solving environments provide biologically intuitive in silico objects ("cells", "regulation networks") required for setting up a simulation and present those to the user in terms of familiar, biological terminology. Here, we introduce the cell-based computer modeling framework VirtualLeaf for plant tissue morphogenesis. The current version defines a set of biologically intuitive C++ objects, including cells, cell walls, and diffusing and reacting chemicals, that provide useful abstractions for building biological simulations of developmental processes. We present a step-by-step introduction to building models with VirtualLeaf, providing basic example models of leaf venation and meristem development. VirtualLeaf-based models provide a means for plant researchers to analyze the function of developmental genes in the context of the biophysics of growth and patterning. VirtualLeaf is an ongoing open-source software project (http://virtualleaf.googlecode.com) that runs on Windows, Mac, and Linux.

Traits, properties, and performance: how woody plants combine hydraulic and mechanical functions in a cell, tissue, or whole plant.

PubMed

Lachenbruch, Barbara; McCulloh, Katherine A

2014-12-01

This review presents a framework for evaluating how cells, tissues, organs, and whole plants perform both hydraulic and mechanical functions. The morphological alterations that affect dual functionality are varied: individual cells can have altered morphology; tissues can have altered partitioning to functions or altered cell alignment; and organs and whole plants can differ in their allocation to different tissues, or in the geometric distribution of the tissues they have. A hierarchical model emphasizes that morphological traits influence the hydraulic or mechanical properties; the properties, combined with the plant unit's environment, then influence the performance of that plant unit. As a special case, we discuss the mechanisms by which the proxy property wood density has strong correlations to performance but without direct causality. Traits and properties influence multiple aspects of performance, and there can be mutual compensations such that similar performance occurs. This compensation emphasizes that natural selection acts on, and a plant's viability is determined by, its performance, rather than its contributing traits and properties. Continued research on the relationships among traits, and on their effects on multiple aspects of performance, will help us better predict, manage, and select plant material for success under multiple stresses in the future. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Supporting the Whole Child through Coordinated Policies, Processes, and Practices

ERIC Educational Resources Information Center

Murray, Sharon D.; Hurley, James; Ahmed, Shannon R.

2015-01-01

Background: The Whole School, Whole Community, Whole Child (WSCC) model provides a framework for promoting greater alignment, integration, and collaboration between health and education across the school setting and improving students' cognitive, physical, social, and emotional development. By providing a learning environment that ensures each…

A Learning Framework for Knowledge Building and Collective Wisdom Advancement in Virtual Learning Communities

ERIC Educational Resources Information Center

Gan, Yongcheng; Zhu, Zhiting

2007-01-01

This study represents an effort to construct a learning framework for knowledge building and collective wisdom advancement in a virtual learning community (VLC) from the perspectives of system wholeness, intelligence wholeness and dynamics, learning models, and knowledge management. It also tries to construct the zone of proximal development (ZPD)…

Plants in silico: why, why now and what?--an integrative platform for plant systems biology research.

PubMed

Zhu, Xin-Guang; Lynch, Jonathan P; LeBauer, David S; Millar, Andrew J; Stitt, Mark; Long, Stephen P

2016-05-01

A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels. © 2015 The Authors Plant, Cell & Environment Published by John Wiley & Sons Ltd.

Physiologically based pharmacokinetic modeling of polyethylene glycol-coated polyacrylamide nanoparticles in rats.

PubMed

Li, Dingsheng; Johanson, Gunnar; Emond, Claude; Carlander, Ulrika; Philbert, Martin; Jolliet, Olivier

2014-08-01

Nanoparticles' health risks depend on their biodistribution in the body. Phagocytosis may greatly affect this distribution but has not yet explicitly accounted for in whole body pharmacokinetic models. Here, we present a physiologically based pharmacokinetic model that includes phagocytosis of nanoparticles to explore the biodistribution of intravenously injected polyethylene glycol-coated polyacrylamide nanoparticles in rats. The model explains 97% of the observed variation in nanoparticles amounts across organs. According to the model, phagocytizing cells quickly capture nanoparticles until their saturation and thereby constitute a major reservoir in richly perfused organs (spleen, liver, bone marrow, lungs, heart and kidneys), storing 83% of the nanoparticles found in these organs 120 h after injection. Key determinants of the nanoparticles biodistribution are the uptake capacities of phagocytizing cells in organs, the partitioning between tissue and blood, and the permeability between capillary blood and tissues. This framework can be extended to other types of nanoparticles by adapting these determinants.

A Structural Framework for a Near-Minimal Form of Life: Mass and Compositional Analysis of the Helical Mollicute Spiroplasma melliferum BC3

PubMed Central

Trachtenberg, Shlomo; Schuck, Peter; Phillips, Terry M.; Andrews, S. Brian; Leapman, Richard D.

2014-01-01

Spiroplasma melliferum is a wall-less bacterium with dynamic helical geometry. This organism is geometrically well defined and internally well ordered, and has an exceedingly small genome. Individual cells are chemotactic, polar, and swim actively. Their dynamic helicity can be traced at the molecular level to a highly ordered linear motor (composed essentially of the proteins fib and MreB) that is positioned on a defined helical line along the internal face of the cell’s membrane. Using an array of complementary, informationally overlapping approaches, we have taken advantage of this uniquely simple, near-minimal life-form and its helical geometry to analyze the copy numbers of Spiroplasma’s essential parts, as well as to elucidate how these components are spatially organized to subserve the whole living cell. Scanning transmission electron microscopy (STEM) was used to measure the mass-per-length and mass-per-area of whole cells, membrane fractions, intact cytoskeletons and cytoskeletal components. These local data were fit into whole-cell geometric parameters determined by a variety of light microscopy modalities. Hydrodynamic data obtained by analytical ultracentrifugation allowed computation of the hydration state of whole living cells, for which the relative amounts of protein, lipid, carbohydrate, DNA, and RNA were also estimated analytically. Finally, ribosome and RNA content, genome size and gene expression were also estimated (using stereology, spectroscopy and 2D-gel analysis, respectively). Taken together, the results provide a general framework for a minimal inventory and arrangement of the major cellular components needed to support life. PMID:24586297

Sensitivity to sequencing depth in single-cell cancer genomics.

PubMed

Alves, João M; Posada, David

2018-04-16

Querying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed. Taking advantage of previously published single-cell whole-genome and whole-exome cancer datasets, we studied the impact of sequencing depth and sampling effort towards single-cell variant detection. Five single-cell whole-genome and whole-exome cancer datasets were independently downscaled to 25, 10, 5, and 1× sequencing depth. For each depth level, ten technical replicates were generated, resulting in a total of 6280 single-cell BAM files. The sensitivity of variant detection, including structural and driver mutations, genotyping, clonal inference, and phylogenetic reconstruction to sequencing depth was evaluated using recent tools specifically designed for single-cell data. Altogether, our results suggest that for relatively large sample sizes (25 or more cells) sequencing single tumor cells at depths > 5× does not drastically improve somatic variant discovery, characterization of clonal genotypes, or estimation of single-cell phylogenies. We suggest that sequencing multiple individual tumor cells at a modest depth represents an effective alternative to explore the mutational landscape and clonal evolutionary patterns of cancer genomes.

Guidance for the application of a population modeling framework in coordination with field based monitoring studies for multiple species and sites

EPA Science Inventory

A modeling framework was developed that can be applied in conjunction with field based monitoring efforts (e.g., through effects-based monitoring programs) to link chemically-induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and pop...

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

PubMed

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.

Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

PubMed

Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

Causes and correlations in cambium phenology: towards an integrated framework of xylogenesis.

PubMed

Rossi, Sergio; Morin, Hubert; Deslauriers, Annie

2012-03-01

Although habitually considered as a whole, xylogenesis is a complex process of division and maturation of a pool of cells where the relationship between the phenological phases generating such a growth pattern remains essentially unknown. This study investigated the causal relationships in cambium phenology of black spruce [Picea mariana (Mill.) BSP] monitored for 8 years on four sites of the boreal forest of Quebec, Canada. The dependency links connecting the timing of xylem cell differentiation and cell production were defined and the resulting causal model was analysed with d-sep tests and generalized mixed models with repeated measurements, and tested with Fisher's C statistics to determine whether and how causality propagates through the measured variables. The higher correlations were observed between the dates of emergence of the first developing cells and between the ending of the differentiation phases, while the number of cells was significantly correlated with all phenological phases. The model with eight dependency links was statistically valid for explaining the causes and correlations between the dynamics of cambium phenology. Causal modelling suggested that the phenological phases involved in xylogenesis are closely interconnected by complex relationships of cause and effect, with the onset of cell differentiation being the main factor directly or indirectly triggering all successive phases of xylem maturation.

Causes and correlations in cambium phenology: towards an integrated framework of xylogenesis

PubMed Central

Rossi, Sergio; Morin, Hubert; Deslauriers, Annie

2012-01-01

Although habitually considered as a whole, xylogenesis is a complex process of division and maturation of a pool of cells where the relationship between the phenological phases generating such a growth pattern remains essentially unknown. This study investigated the causal relationships in cambium phenology of black spruce [Picea mariana (Mill.) BSP] monitored for 8 years on four sites of the boreal forest of Quebec, Canada. The dependency links connecting the timing of xylem cell differentiation and cell production were defined and the resulting causal model was analysed with d-sep tests and generalized mixed models with repeated measurements, and tested with Fisher’s C statistics to determine whether and how causality propagates through the measured variables. The higher correlations were observed between the dates of emergence of the first developing cells and between the ending of the differentiation phases, while the number of cells was significantly correlated with all phenological phases. The model with eight dependency links was statistically valid for explaining the causes and correlations between the dynamics of cambium phenology. Causal modelling suggested that the phenological phases involved in xylogenesis are closely interconnected by complex relationships of cause and effect, with the onset of cell differentiation being the main factor directly or indirectly triggering all successive phases of xylem maturation. PMID:22174441

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Integrated lung tissue mechanics one piece at a time: Computational modeling across the scales of biology.

PubMed

Burrowes, Kelly S; Iravani, Amin; Kang, Wendy

2018-01-12

The lung is a delicately balanced and highly integrated mechanical system. Lung tissue is continuously exposed to the environment via the air we breathe, making it susceptible to damage. As a consequence, respiratory diseases present a huge burden on society and their prevalence continues to rise. Emergent function is produced not only by the sum of the function of its individual components but also by the complex feedback and interactions occurring across the biological scales - from genes to proteins, cells, tissue and whole organ - and back again. Computational modeling provides the necessary framework for pulling apart and putting back together the pieces of the body and organ systems so that we can fully understand how they function in both health and disease. In this review, we discuss models of lung tissue mechanics spanning from the protein level (the extracellular matrix) through to the level of cells, tissue and whole organ, many of which have been developed in isolation. This is a vital step in the process but to understand the emergent behavior of the lung, we must work towards integrating these component parts and accounting for feedback across the scales, such as mechanotransduction. These interactions will be key to unlocking the mechanisms occurring in disease and in seeking new pharmacological targets and improving personalized healthcare. Copyright © 2018 Elsevier Ltd. All rights reserved.

The OME Framework for genome-scale systems biology

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

Palsson, Bernhard O.; Ebrahim, Ali; Federowicz, Steve

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity ofmore » genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.« less

Feedback control in planarian stem cell systems.

PubMed

Mangel, Marc; Bonsall, Michael B; Aboobaker, Aziz

2016-02-13

In planarian flatworms, the mechanisms underlying the activity of collectively pluripotent adult stem cells (neoblasts) and their descendants can now be studied from the level of the individual gene to the entire animal. Flatworms maintain startling developmental plasticity and regenerative capacity in response to variable nutrient conditions or injury. We develop a model for cell dynamics in such animals, assuming that fully differentiated cells exert feedback control on neoblast activity. Our model predicts a number of whole organism level and general cell biological and behaviours, some of which have been empirically observed or inferred in planarians and others that have not. As previously observed empirically we find: 1) a curvilinear relationship between external food and planarian steady state size; 2) the fraction of neoblasts in the steady state is constant regardless of planarian size; 3) a burst of controlled apoptosis during regeneration after amputation as the number of differentiated cells are adjusted towards their homeostatic/steady state level. In addition our model describes the following properties that can inform and be tested by future experiments: 4) the strength of feedback control from differentiated cells to neoblasts (i.e. the activity of the signalling system) and from neoblasts on themselves in relation to absolute number depends upon the level of food in the environment; 5) planarians adjust size when food level reduces initially through increased apoptosis and then through a reduction in neoblast self-renewal activity; 6) following wounding or excision of differentiated cells, different time scales characterize both recovery of size and the two feedback functions; 7) the temporal pattern of feedback controls differs noticeably during recovery from a removal or neoblasts or a removal of differentiated cells; 8) the signaling strength for apoptosis of differentiated cells depends upon both the absolute and relative deviations of the number of differentiated cells from their homeostatic level; and 9) planaria prioritize resource use for cell divisions. We offer the first analytical framework for organizing experiments on planarian flatworm stem cell dynamics in a form that allows models to be compared with quantitative cell data based on underlying molecular mechanisms and thus facilitate the interplay between empirical studies and modeling. This framework is the foundation for studying cell migration during wound repair, the determination of homeostatic levels of differentiated cells by natural selection, and stochastic effects.

Whole systems shared governance: a model for the integrated health system.

PubMed

Evan, K; Aubry, K; Hawkins, M; Curley, T A; Porter-O'Grady, T

1995-05-01

The healthcare system is under renovation and renewal. In the process, roles and structures are shifting to support a subscriber-based continuum of care. Alliances and partnerships are emerging as the models of integration for the future. But how do we structure to support these emerging integrated partnerships? As the nurse executive expands the role and assumes increasing responsibility for creating new frameworks for care, a structure that sustains the point-of-care innovations and interdisciplinary relationships must be built. Whole systems models of organization, such as shared governance, are expanding as demand grows for a sustainable structure for horizontal and partnered systems of healthcare delivery. The executive will have to apply these newer frameworks to the delivery of care to provide adequate support for the clinically integrated environment.

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

Practical whole-tooth restoration utilizing autologous bioengineered tooth germ transplantation in a postnatal canine model

PubMed Central

Ono, Mitsuaki; Oshima, Masamitsu; Ogawa, Miho; Sonoyama, Wataru; Hara, Emilio Satoshi; Oida, Yasutaka; Shinkawa, Shigehiko; Nakajima, Ryu; Mine, Atsushi; Hayano, Satoru; Fukumoto, Satoshi; Kasugai, Shohei; Yamaguchi, Akira; Tsuji, Takashi; Kuboki, Takuo

2017-01-01

Whole-organ regeneration has great potential for the replacement of dysfunctional organs through the reconstruction of a fully functional bioengineered organ using three-dimensional cell manipulation in vitro. Recently, many basic studies of whole-tooth replacement using three-dimensional cell manipulation have been conducted in a mouse model. Further evidence of the practical application to human medicine is required to demonstrate tooth restoration by reconstructing bioengineered tooth germ using a postnatal large-animal model. Herein, we demonstrate functional tooth restoration through the autologous transplantation of bioengineered tooth germ in a postnatal canine model. The bioengineered tooth, which was reconstructed using permanent tooth germ cells, erupted into the jawbone after autologous transplantation and achieved physiological function equivalent to that of a natural tooth. This study represents a substantial advancement in whole-organ replacement therapy through the transplantation of bioengineered organ germ as a practical model for future clinical regenerative medicine. PMID:28300208

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

Simulating Heterogeneous Tumor Cell Populations

PubMed Central

Bar-Sagi, Dafna; Mishra, Bud

2016-01-01

Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor’s resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2—diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior. PMID:28030620

When 1+1 can be >2: Uncertainties compound when simulating climate, fisheries and marine ecosystems

NASA Astrophysics Data System (ADS)

Evans, Karen; Brown, Jaclyn N.; Sen Gupta, Alex; Nicol, Simon J.; Hoyle, Simon; Matear, Richard; Arrizabalaga, Haritz

2015-03-01

Multi-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty.

Framework of distributed coupled atmosphere-ocean-wave modeling system

NASA Astrophysics Data System (ADS)

Wen, Yuanqiao; Huang, Liwen; Deng, Jian; Zhang, Jinfeng; Wang, Sisi; Wang, Lijun

2006-05-01

In order to research the interactions between the atmosphere and ocean as well as their important role in the intensive weather systems of coastal areas, and to improve the forecasting ability of the hazardous weather processes of coastal areas, a coupled atmosphere-ocean-wave modeling system has been developed. The agent-based environment framework for linking models allows flexible and dynamic information exchange between models. For the purpose of flexibility, portability and scalability, the framework of the whole system takes a multi-layer architecture that includes a user interface layer, computational layer and service-enabling layer. The numerical experiment presented in this paper demonstrates the performance of the distributed coupled modeling system.

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components

PubMed Central

Gardiner, Bruce S.; Wong, Kelvin K. L.; Joldes, Grand R.; Rich, Addison J.; Tan, Chin Wee; Burgess, Antony W.; Smith, David W.

2015-01-01

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an ‘agent’, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory. PMID:26452000

Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components.

PubMed

Gardiner, Bruce S; Wong, Kelvin K L; Joldes, Grand R; Rich, Addison J; Tan, Chin Wee; Burgess, Antony W; Smith, David W

2015-10-01

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an 'agent', meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory.

A quantitative framework for whole-body coordination reveals specific deficits in freely walking ataxic mice

PubMed Central

Machado, Ana S; Darmohray, Dana M; Fayad, João; Marques, Hugo G; Carey, Megan R

2015-01-01

The coordination of movement across the body is a fundamental, yet poorly understood aspect of motor control. Mutant mice with cerebellar circuit defects exhibit characteristic impairments in locomotor coordination; however, the fundamental features of this gait ataxia have not been effectively isolated. Here we describe a novel system (LocoMouse) for analyzing limb, head, and tail kinematics of freely walking mice. Analysis of visibly ataxic Purkinje cell degeneration (pcd) mice reveals that while differences in the forward motion of individual paws are fully accounted for by changes in walking speed and body size, more complex 3D trajectories and, especially, inter-limb and whole-body coordination are specifically impaired. Moreover, the coordination deficits in pcd are consistent with a failure to predict and compensate for the consequences of movement across the body. These results isolate specific impairments in whole-body coordination in mice and provide a quantitative framework for understanding cerebellar contributions to coordinated locomotion. DOI: http://dx.doi.org/10.7554/eLife.07892.001 PMID:26433022

Twelve tips for implementing whole-task curricula: how to make it work.

PubMed

Dolmans, Diana H J M; Wolfhagen, Ineke H A P; Van Merriënboer, Jeroen J G

2013-10-01

Whole-task models of learning and instructional design, such as problem-based learning, are nowadays very popular. Schools regularly encounter large problems when they implement whole-task curricula. The main aim of this article is to provide 12 tips that may help to make the implementation of a whole-task curriculum successful. Implementing whole-task curricula fails when the implementation is not well prepared. Requirements that must be met to make the implementation of whole task models into a success are described as twelve tips. The tips are organized in four clusters and refer to (1) the infrastructure, (2) the teachers, (3) the students, and (4) the management of the educational organization. Finally, the presented framework will be critically discussed and the importance of shared values and a change of culture is emphasized.

Food Practices and School Connectedness: A Whole-School Approach

ERIC Educational Resources Information Center

Neely, Eva; Walton, Mat; Stephens, Christine

2016-01-01

Purpose: The health-promoting schools (HPSs) framework has emerged as a promising model for promoting school connectedness in the school setting. The purpose of this paper is to explore the potential for food practices to promote school connectedness within a HPSs framework. Design/methodology/approach: This study explores food practices within a…

Towards an integrative computational model for simulating tumor growth and response to radiation therapy

NASA Astrophysics Data System (ADS)

Marrero, Carlos Sosa; Aubert, Vivien; Ciferri, Nicolas; Hernández, Alfredo; de Crevoisier, Renaud; Acosta, Oscar

2017-11-01

Understanding the response to irradiation in cancer radiotherapy (RT) may help devising new strategies with improved tumor local control. Computational models may allow to unravel the underlying radiosensitive mechanisms intervening in the dose-response relationship. By using extensive simulations a wide range of parameters may be evaluated providing insights on tumor response thus generating useful data to plan modified treatments. We propose in this paper a computational model of tumor growth and radiation response which allows to simulate a whole RT protocol. Proliferation of tumor cells, cell life-cycle, oxygen diffusion, radiosensitivity, RT response and resorption of killed cells were implemented in a multiscale framework. The model was developed in C++, using the Multi-formalism Modeling and Simulation Library (M2SL). Radiosensitivity parameters extracted from literature enabled us to simulate in a regular grid (voxel-wise) a prostate cell tissue. Histopathological specimens with different aggressiveness levels extracted from patients after prostatectomy were used to initialize in silico simulations. Results on tumor growth exhibit a good agreement with data from in vitro studies. Moreover, standard fractionation of 2 Gy/fraction, with a total dose of 80 Gy as a real RT treatment was applied with varying radiosensitivity and oxygen diffusion parameters. As expected, the high influence of these parameters was observed by measuring the percentage of survival tumor cell after RT. This work paves the way to further models allowing to simulate increased doses in modified hypofractionated schemes and to develop new patient-specific combined therapies.

A hybrid model of cell cycle in mammals.

PubMed

Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck

2016-02-01

Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication.

Mechanistic links between cellular trade-offs, gene expression, and growth.

PubMed

Weiße, Andrea Y; Oyarzún, Diego A; Danos, Vincent; Swain, Peter S

2015-03-03

Intracellular processes rarely work in isolation but continually interact with the rest of the cell. In microbes, for example, we now know that gene expression across the whole genome typically changes with growth rate. The mechanisms driving such global regulation, however, are not well understood. Here we consider three trade-offs that, because of limitations in levels of cellular energy, free ribosomes, and proteins, are faced by all living cells and we construct a mechanistic model that comprises these trade-offs. Our model couples gene expression with growth rate and growth rate with a growing population of cells. We show that the model recovers Monod's law for the growth of microbes and two other empirical relationships connecting growth rate to the mass fraction of ribosomes. Further, we can explain growth-related effects in dosage compensation by paralogs and predict host-circuit interactions in synthetic biology. Simulating competitions between strains, we find that the regulation of metabolic pathways may have evolved not to match expression of enzymes to levels of extracellular substrates in changing environments but rather to balance a trade-off between exploiting one type of nutrient over another. Although coarse-grained, the trade-offs that the model embodies are fundamental, and, as such, our modeling framework has potentially wide application, including in both biotechnology and medicine.

Dynamics of blood flow in a microfluidic ladder network

NASA Astrophysics Data System (ADS)

Maddala, Jeevan; Zilberman-Rudenko, Jevgenia; McCarty, Owen

The dynamics of a complex mixture of cells and proteins, such as blood, in perturbed shear flow remains ill-defined. Microfluidics is a promising technology for improving the understanding of blood flow under complex conditions of shear; as found in stent implants and in tortuous blood vessels. We model the fluid dynamics of blood flow in a microfluidic ladder network with dimensions mimicking venules. Interaction of blood cells was modeled using multiagent framework, where cells of different diameters were treated as spheres. This model served as the basis for predicting transition regions, collision pathways, re-circulation zones and residence times of cells dependent on their diameters and device architecture. Based on these insights from the model, we were able to predict the clot formation configurations at various locations in the device. These predictions were supported by the experiments using whole blood. To facilitate platelet aggregation, the devices were coated with fibrillar collagen and tissue factor. Blood was perfused through the microfluidic device for 9 min at a physiologically relevant venous shear rate of 600 s-1. Using fluorescent microscopy, we observed flow transitions near the channel intersections and at the areas of blood flow obstruction, which promoted larger thrombus formation. This study of integrating model predictions with experimental design, aids in defining the dynamics of blood flow in microvasculature and in development of novel biomedical devices.

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

PubMed Central

Jones, Michael N.

2017-01-01

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

PubMed

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

Nanoparticle Distributions in Cancer and other Cells from Light Transmission Spectroscopy

NASA Astrophysics Data System (ADS)

Deatsch, Alison; Sun, Nan; Johnson, Jeffery; Stack, Sharon; Tanner, Carol; Ruggiero, Steven

We have measured the optical properties of whole cells and lysates using light transmission spectroscopy (LTS). LTS provides both the optical extinction coefficient in the wavelength range from 220 to 1100 nm and (by spectral inversion using a Mie model) the particle distribution density in the size range from 1 to 3000 nm. Our current work involves whole cells and lysates of cultured human oral cells and other plant and animal cells. We have found systematic differences in the optical extinction between cancer and normal whole cells and lysates, which translate to different particle size distributions (PSDs) for these materials. We have also found specific power-law dependences of particle density with particle diameter for cell lysates. This suggests a universality of the packing distribution in cells that can be compared to ideal Apollonian packing, with the cell modeled as a fractal body comprised of spheres on all size scales.

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

PubMed Central

Balakrishnan, Minimol; Chakravarthy, V. Srinivasa; Guhathakurta, Soma

2015-01-01

Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias. PMID:26733873

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

PubMed

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

2016-01-01

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

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

PubMed

Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S

2017-12-11

Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

Interactions of Condensed Tannins with Saccharomyces cerevisiae Yeast Cells and Cell Walls: Tannin Location by Microscopy.

PubMed

Mekoue Nguela, Julie; Vernhet, Aude; Sieczkowski, Nathalie; Brillouet, Jean-Marc

2015-09-02

Interactions between grape tannins/red wine polyphenols and yeast cells/cell walls was previously studied within the framework of red wine aging and the use of yeast-derived products as an alternative to aging on lees. Results evidenced a quite different behavior between whole cells (biomass grown to elaborate yeast-derived products, inactivated yeast, and yeast inactivated after autolysis) and yeast cell walls (obtained from mechanical disruption of the biomass). Briefly, whole cells exhibited a high capacity to irreversibly adsorb grape and wine tannins, whereas only weak interactions were observed for cell walls. This last point was quite unexpected considering the literature and called into question the real role of cell walls in yeasts' ability to fix tannins. In the present work, tannin location after interactions between grape and wine tannins and yeast cells and cell walls was studied by means of transmission electron microscopy, light epifluorescence, and confocal microscopy. Microscopy observations evidenced that if tannins interact with cell walls, and especially cell wall mannoproteins, they also diffuse freely through the walls of dead cells to interact with their plasma membrane and cytoplasmic components.

Willy Bernal Heredia | NREL

Science.gov Websites

, developing the framework to model whole-campus dynamics to coordinate and synchronize its multiple loads developing the controls for a self-balancing two-wheel electrical vehicle. Education M.S. Electrical

Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.

PubMed

Chew, Yin Hoon; Wenden, Bénédicte; Flis, Anna; Mengin, Virginie; Taylor, Jasper; Davey, Christopher L; Tindal, Christopher; Thomas, Howard; Ougham, Helen J; de Reffye, Philippe; Stitt, Mark; Williams, Mathew; Muetzelfeldt, Robert; Halliday, Karen J; Millar, Andrew J

2014-09-30

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Potency assays for therapeutic live whole cell cancer vaccines.

PubMed

Petricciani, John; Egan, William; Vicari, Giuseppe; Furesz, John; Schild, Geoffrey

2007-04-01

Therapeutic cancer vaccines are under development with the goal of enhancing the body's immune response to cancer cells sufficient to arrest cancer cell growth. Among the various approaches being used are those based on whole tumor cells. Developing a suitable measure of the potency of such vaccines presents a significant challenge because neither cellular associated markers nor in vivo biological responses that are correlated with efficacy have been identified; nevertheless, manufacturers and regulatory agencies will need to develop methods to evaluate these products. At this moment, the challenge for manufacturers who are developing whole cell vaccines is to demonstrate batch-to-batch consistency for the vaccine used in clinical studies and to show that comparable vaccine batches have the same capacity to achieve an acceptable level of biological activity that may be related to efficacy. This is particularly challenging in that animal models to test that activity do not exist and direct serological or immunological correlates of clinical protection are not available because protection has not yet been established in clinical trials. In the absence of well-defined biological markers and tests for manufacturing consistency, manufacturers and regulators will need to rely heavily on a highly reproducible manufacturing process--the consistency of the process therefore becomes critical. In developing regulatory approaches to whole cell cancer vaccines, the experience from the field of infectious disease vaccines should be examined for general guidance. A framework that draws heavily on the field of infectious disease vaccines is presented and suggests that at this point in the development of this new class of products, it is reasonable to develop data on quantitative antigen expression as a measure of potency with the expectation that when clinical efficacy has been established it will confirm the appropriateness of this approach. But because this will not be known until the end of a pivotal trial, a bioassay should be considered and run in parallel. Several examples of bioassays are presented along with their advantages and disadvantages. The final selection of a potency assay for use in lot release of a commercializable therapeutic whole cell vaccine ultimately will depend on the totality of the data available at the time of approval by regulatory agencies. Based on information currently available, it is likely that quantitative antigen expression or a bioassay could be used to measure potency. If both are determined to be acceptable, the use of quantitative antigen expression could be considered for routine lot release, while the bioassay could be reserved for use as one of the elements in establishing comparability when manufacturing changes are being considered after approval.

Efficiency Analysis and Mechanism Insight of that Whole-Cell Biocatalytic Production of Melibiose from Raffinose with Saccharomyces cerevisiae.

PubMed

Zhou, Yingbiao; Zhu, Yueming; Dai, Longhai; Men, Yan; Wu, Jinhai; Zhang, Juankun; Sun, Yuanxia

2017-01-01

Melibiose is widely used as a functional carbohydrate. Whole-cell biocatalytic production of melibiose from raffinose could reduce its cost. However, characteristics of strains for whole-cell biocatalysis and mechanism of such process are unclear. We compared three different Saccharomyces cerevisiae strains (liquor, wine, and baker's yeasts) in terms of concentration variations of substrate (raffinose), target product (melibiose), and by-products (fructose and galactose) in whole-cell biocatalysis process. Distinct difference was observed in whole-cell catalytic efficiency among three strains. Furthermore, activities of key enzymes (invertase, α-galactosidase, and fructose transporter) involved in process and expression levels of their coding genes (suc2, mel1, and fsy1) were investigated. Conservation of key genes in S. cerevisiae strains was also evaluated. Results show that whole-cell catalytic efficiency of S. cerevisiae in the raffinose substrate was closely related to activity of key enzymes and expression of their coding genes. Finally, we summarized characteristics of producing strain that offered advantages, as well as contributions of key genes to excellent strains. Furthermore, we presented a dynamic mechanism model to achieve some mechanism insight for this whole-cell biocatalytic process. This pioneering study should contribute to improvement of whole-cell biocatalytic production of melibiose from raffinose.

Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates

PubMed Central

Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda

2012-01-01

One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039

Learning situation models in a smart home.

PubMed

Brdiczka, Oliver; Crowley, James L; Reignier, Patrick

2009-02-01

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.

Interactive Exploration for Continuously Expanding Neuron Databases.

PubMed

Li, Zhongyu; Metaxas, Dimitris N; Lu, Aidong; Zhang, Shaoting

2017-02-15

This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to associate neuronal morphologies with their functional properties. We design a coarse-to-fine framework for efficient and effective data retrieval from large-scale neuron databases. In the coarse-level, for efficiency in large-scale, we employ a binary coding method to compress morphological features into binary codes of tens of bits. Short binary codes allow for real-time similarity searching in Hamming space. Because the neuron databases are continuously expanding, it is inefficient to re-train the binary coding model from scratch when adding new neurons. To solve this problem, we extend binary coding with online updating schemes, which only considers the newly added neurons and update the model on-the-fly, without accessing the whole neuron databases. In the fine-grained level, we introduce domain experts/users in the framework, which can give relevance feedback for the binary coding based retrieval results. This interactive strategy can improve the retrieval performance through re-ranking the above coarse results, where we design a new similarity measure and take the feedback into account. Our framework is validated on more than 17,000 neuron cells, showing promising retrieval accuracy and efficiency. Moreover, we demonstrate its use case in assisting biologists to identify and explore unknown neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

Epithelial cytoskeletal framework and nuclear matrix-intermediate filament scaffold: three-dimensional organization and protein composition.

PubMed

Fey, E G; Wan, K M; Penman, S

1984-06-01

Madin-Darby canine kidney (MDCK) cells grow as differentiated, epithelial colonies that display tissue-like organization. We examined the structural elements underlying the colony morphology in situ using three consecutive extractions that produce well-defined fractions for both microscopy and biochemical analysis. First, soluble proteins and phospholipid were removed with Triton X-100 in a physiological buffer. The resulting skeletal framework retained nuclei, dense cytoplasmic filament networks, intercellular junctional complexes, and apical microvillar structures. Scanning electron microscopy showed that the apical cell morphology is largely unaltered by detergent extraction. Residual desmosomes, as can be seen in thin sections, were also well-preserved. The skeletal framework was visualized in three dimensions as an unembedded whole mount that revealed the filament networks that were masked in Epon-embedded thin sections of the same preparation. The topography of cytoskeletal filaments was relatively constant throughout the epithelial sheet, particularly across intercellular borders. This ordering of epithelial skeletal filaments across contiguous cell boundaries was in sharp contrast to the more independent organization of networks in autonomous cells such as fibroblasts. Further extraction removed the proteins of the salt-labile cytoskeleton and the chromatin as separate fractions, and left the nuclear matrix-intermediate filament (NM-IF) scaffold. The NM-IF contained only 5% of total cellular protein, but whole mount transmission electron microscopy and immunofluorescence showed that this scaffold was organized as in the intact epithelium. Immunoblots demonstrate that vimentin, cytokeratins, desmosomal proteins, and a 52,000-mol-wt nuclear matrix protein were found almost exclusively in the NM-IF scaffold. Vimentin was largely perinuclear while the cytokeratins were localized at the cell borders. The 52,000-mol-wt nuclear matrix protein was confined to the chromatin-depleted matrix and the desmosomal proteins were observed in punctate polygonal arrays at intercellular junctions. The filaments of the NM-IF were seen to be interconnected, via the desmosomes, over the entire epithelial colony. The differentiated epithelial morphology was reflected in both the cytoskeletal framework and the NM-IF scaffold.

Epithelial cytoskeletal framework and nuclear matrix-intermediate filament scaffold: three-dimensional organization and protein composition

PubMed Central

1984-01-01

Madin-Darby canine kidney (MDCK) cells grow as differentiated, epithelial colonies that display tissue-like organization. We examined the structural elements underlying the colony morphology in situ using three consecutive extractions that produce well-defined fractions for both microscopy and biochemical analysis. First, soluble proteins and phospholipid were removed with Triton X-100 in a physiological buffer. The resulting skeletal framework retained nuclei, dense cytoplasmic filament networks, intercellular junctional complexes, and apical microvillar structures. Scanning electron microscopy showed that the apical cell morphology is largely unaltered by detergent extraction. Residual desmosomes, as can be seen in thin sections, were also well- preserved. The skeletal framework was visualized in three dimensions as an unembedded whole mount that revealed the filament networks that were masked in Epon-embedded thin sections of the same preparation. The topography of cytoskeletal filaments was relatively constant throughout the epithelial sheet, particularly across intercellular borders. This ordering of epithelial skeletal filaments across contiguous cell boundaries was in sharp contrast to the more independent organization of networks in autonomous cells such as fibroblasts. Further extraction removed the proteins of the salt-labile cytoskeleton and the chromatin as separate fractions, and left the nuclear matrix-intermediate filament (NM-IF) scaffold. The NM-IF contained only 5% of total cellular protein, but whole mount transmission electron microscopy and immunofluorescence showed that this scaffold was organized as in the intact epithelium. Immunoblots demonstrate that vimentin, cytokeratins, desmosomal proteins, and a 52,000-mol-wt nuclear matrix protein were found almost exclusively in the NM-IF scaffold. Vimentin was largely perinuclear while the cytokeratins were localized at the cell borders. The 52,000-mol-wt nuclear matrix protein was confined to the chromatin- depleted matrix and the desmosomal proteins were observed in punctate polygonal arrays at intercellular junctions. The filaments of the NM-IF were seen to be interconnected, via the desmosomes, over the entire epithelial colony. The differentiated epithelial morphology was reflected in both the cytoskeletal framework and the NM-IF scaffold. PMID:6202700

Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

NASA Astrophysics Data System (ADS)

Ellis, Michael; Dobrovolny, Hana

2014-03-01

One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

PubMed

Hansen, Jens; Meretzky, David; Woldesenbet, Simeneh; Stolovitzky, Gustavo; Iyengar, Ravi

2017-12-18

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the Molecular Biology of the Cell Ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,384 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed SCP networks for predictive modeling of emergent whole cell functions.

Repeated whole cigarette smoke exposure alters cell differentiation and augments secretion of inflammatory mediators in air-liquid interface three-dimensional co-culture model of human bronchial tissue.

PubMed

Ishikawa, Shinkichi; Ito, Shigeaki

2017-02-01

In vitro models of human bronchial epithelium are useful for toxicological testing because of their resemblance to in vivo tissue. We constructed a model of human bronchial tissue which has a fibroblast layer embedded in a collagen matrix directly below a fully-differentiated epithelial cell layer. The model was applied to whole cigarette smoke (CS) exposure repeatedly from an air-liquid interface culture while bronchial epithelial cells were differentiating. The effects of CS exposure on differentiation were determined by histological and gene expression analyses on culture day 21. We found a decrease in ciliated cells and perturbation of goblet cell differentiation. We also analyzed the effects of CS exposure on the inflammatory response, and observed a significant increase in secretion of IL-8, GRO-α, IL-1β, and GM-CSF. Interestingly, secretion of these mediators was augmented with repetition of whole CS exposure. Our data demonstrate the usefulness of our bronchial tissue model for in vitro testing and the importance of exposure repetition in perturbing the differentiation and inflammation processes. Copyright © 2016 Elsevier B.V. All rights reserved.

Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

PubMed

Hill, Deborah K; Orton, Matthew R; Mariotti, Erika; Boult, Jessica K R; Panek, Rafal; Jafar, Maysam; Parkes, Harold G; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M S; Beloueche-Babari, Mounia; Robinson, Simon P; Leach, Martin O; Chung, Yuen-Li; Eykyn, Thomas R

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic.

Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

PubMed Central

Mariotti, Erika; Boult, Jessica K. R.; Panek, Rafal; Jafar, Maysam; Parkes, Harold G.; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M. S.; Beloueche-Babari, Mounia; Robinson, Simon P.; Leach, Martin O.; Chung, Yuen-Li; Eykyn, Thomas R.

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic. PMID:24023724

TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data

PubMed Central

Roth, Andrew; Khattra, Jaswinder; Ho, Julie; Yap, Damian; Prentice, Leah M.; Melnyk, Nataliya; McPherson, Andrew; Bashashati, Ali; Laks, Emma; Biele, Justina; Ding, Jiarui; Le, Alan; Rosner, Jamie; Shumansky, Karey; Marra, Marco A.; Gilks, C. Blake; Huntsman, David G.; McAlpine, Jessica N.; Aparicio, Samuel

2014-01-01

The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN. PMID:25060187

Three-dimensional intracellular structure of a whole rice mesophyll cell observed with FIB-SEM.

PubMed

Oi, Takao; Enomoto, Sakiko; Nakao, Tomoyo; Arai, Shigeo; Yamane, Koji; Taniguchi, Mitsutaka

2017-07-01

Ultrathin sections of rice leaf blades observed two-dimensionally using a transmission electron microscope (TEM) show that the chlorenchyma is composed of lobed mesophyll cells, with intricate cell boundaries, and lined with chloroplasts. The lobed cell shape and chloroplast positioning are believed to enhance the area available for the gas exchange surface for photosynthesis in rice leaves. However, a cell image revealing the three-dimensional (3-D) ultrastructure of rice mesophyll cells has not been visualized. In this study, a whole rice mesophyll cell was observed using a focused ion beam scanning electron microscope (FIB-SEM), which provides many serial sections automatically, rapidly and correctly, thereby enabling 3-D cell structure reconstruction. Rice leaf blades were fixed chemically using the method for conventional TEM observation, embedded in resin and subsequently set in the FIB-SEM chamber. Specimen blocks were sectioned transversely using the FIB, and block-face images were captured using the SEM. The sectioning and imaging were repeated overnight for 200-500 slices (each 50 nm thick). The resultant large-volume image stacks ( x = 25 μm, y = 25 μm, z = 10-25 μm) contained one or two whole mesophyll cells. The 3-D models of whole mesophyll cells were reconstructed using image processing software. The reconstructed cell models were discoid shaped with several lobes around the cell periphery. The cell shape increased the surface area, and the ratio of surface area to volume was twice that of a cylinder having the same volume. The chloroplasts occupied half the cell volume and spread as sheets along the cell lobes, covering most of the inner cell surface, with adjacent chloroplasts in close contact with each other. Cellular and sub-cellular ultrastructures of a whole mesophyll cell in a rice leaf blade are demonstrated three-dimensionally using a FIB-SEM. The 3-D models and numerical information support the hypothesis that rice mesophyll cells enhance their CO 2 absorption with increased cell surface and sheet-shaped chloroplasts. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The Activation and Inactivation of Mature CD4 T cells: A Case for Peripheral Self–Nonself Discrimination

PubMed Central

Bretscher, P A

2014-01-01

The establishment of central tolerance to most self-antigens results in a repertoire of mature peripheral lymphocytes specific for foreign and peripheral self-antigens. The framework that single, mature lymphocytes are inactivated by antigen, whereas their activation requires lymphocyte cooperation, accounts for diverse observations and incorporates a mechanism of peripheral tolerance. This framework accounts for the generalizations that the sustained activation by antigen of most B cells and CD8 T cells requires CD4 T helper cells; in the absence of CD4 T cells, antigen can inactivate these B cells and CD8 T cells. In this sense, CD4 T cells are the guardians of the fate of most B cells and CD8 T cells when they encounter antigen. I argue here that the single-lymphocyte/multiple-lymphocyte framework for the inactivation/activation of lymphocytes also applies to CD4 T cells. I consider within this framework a model for the activation/inactivation of CD4 T cells that is consistent with the large majority of contemporary observations, including significant clinical observations. I outline the grounds why I feel this model is more plausible than the contemporary and predominant pathogen-associated molecular pattern (PAMP) and Danger Models for CD4 T cell activation. These models are based upon what I consider the radical premise that self–nonself discrimination does not exist at the level of mature CD4 T cells. I explain why I feel this feature renders the PAMP and Danger Models somewhat implausible. The model I propose, in contrast, is conservative in that it embodies such a process of self–nonself discrimination. PMID:24684567

EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos.

PubMed

Schott, Benjamin; Traub, Manuel; Schlagenhauf, Cornelia; Takamiya, Masanari; Antritter, Thomas; Bartschat, Andreas; Löffler, Katharina; Blessing, Denis; Otte, Jens C; Kobitski, Andrei Y; Nienhaus, G Ulrich; Strähle, Uwe; Mikut, Ralf; Stegmaier, Johannes

2018-04-01

State-of-the-art light-sheet and confocal microscopes allow recording of entire embryos in 3D and over time (3D+t) for many hours. Fluorescently labeled structures can be segmented and tracked automatically in these terabyte-scale 3D+t images, resulting in thousands of cell migration trajectories that provide detailed insights to large-scale tissue reorganization at the cellular level. Here we present EmbryoMiner, a new interactive open-source framework suitable for in-depth analyses and comparisons of entire embryos, including an extensive set of trajectory features. Starting at the whole-embryo level, the framework can be used to iteratively focus on a region of interest within the embryo, to investigate and test specific trajectory-based hypotheses and to extract quantitative features from the isolated trajectories. Thus, the new framework provides a valuable new way to quantitatively compare corresponding anatomical regions in different embryos that were manually selected based on biological prior knowledge. As a proof of concept, we analyzed 3D+t light-sheet microscopy images of zebrafish embryos, showcasing potential user applications that can be performed using the new framework.

Mathematical model of the glucose-insulin regulatory system: From the bursting electrical activity in pancreatic β-cells to the glucose dynamics in the whole body

NASA Astrophysics Data System (ADS)

Han, Kyungreem; Kang, Hyuk; Choi, M. Y.; Kim, Jinwoong; Lee, Myung-Shik

2012-10-01

A theoretical approach to the glucose-insulin regulatory system is presented. By means of integrated mathematical modeling and extensive numerical simulations, we probe the cell-level dynamics of the membrane potential, intracellular Ca2+ concentration, and insulin secretion in pancreatic β-cells, together with the whole-body level glucose-insulin dynamics in the liver, brain, muscle, and adipose tissues. In particular, the three oscillatory modes of insulin secretion are reproduced successfully. Such comprehensive mathematical modeling may provide a theoretical basis for the simultaneous assessment of the β-cell function and insulin resistance in clinical examination.

Implementing vertex dynamics models of cell populations in biology within a consistent computational framework.

PubMed

Fletcher, Alexander G; Osborne, James M; Maini, Philip K; Gavaghan, David J

2013-11-01

The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell-cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Computational Framework for Bioimaging Simulation.

PubMed

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

A multiscale computational model of spatially resolved calcium cycling in cardiac myocytes: from detailed cleft dynamics to the whole cell concentration profiles

PubMed Central

Vierheller, Janine; Neubert, Wilhelm; Falcke, Martin; Gilbert, Stephen H.; Chamakuri, Nagaiah

2015-01-01

Mathematical modeling of excitation-contraction coupling (ECC) in ventricular cardiac myocytes is a multiscale problem, and it is therefore difficult to develop spatially detailed simulation tools. ECC involves gradients on the length scale of 100 nm in dyadic spaces and concentration profiles along the 100 μm of the whole cell, as well as the sub-millisecond time scale of local concentration changes and the change of lumenal Ca2+ content within tens of seconds. Our concept for a multiscale mathematical model of Ca2+ -induced Ca2+ release (CICR) and whole cardiomyocyte electrophysiology incorporates stochastic simulation of individual LC- and RyR-channels, spatially detailed concentration dynamics in dyadic clefts, rabbit membrane potential dynamics, and a system of partial differential equations for myoplasmic and lumenal free Ca2+ and Ca2+-binding molecules in the bulk of the cell. We developed a novel computational approach to resolve the concentration gradients from dyadic space to cell level by using a quasistatic approximation within the dyad and finite element methods for integrating the partial differential equations. We show whole cell Ca2+-concentration profiles using three previously published RyR-channel Markov schemes. PMID:26441674

Field Markup Language: biological field representation in XML.

PubMed

Chang, David; Lovell, Nigel H; Dokos, Socrates

2007-01-01

With an ever increasing number of biological models available on the internet, a standardized modeling framework is required to allow information to be accessed or visualized. Based on the Physiome Modeling Framework, the Field Markup Language (FML) is being developed to describe and exchange field information for biological models. In this paper, we describe the basic features of FML, its supporting application framework and its ability to incorporate CellML models to construct tissue-scale biological models. As a typical application example, we present a spatially-heterogeneous cardiac pacemaker model which utilizes both FML and CellML to describe and solve the underlying equations of electrical activation and propagation.

A multiscale, model-based analysis of the multi-tissue interplay underlying blood glucose regulation in type I diabetes.

PubMed

Wadehn, Federico; Schaller, Stephan; Eissing, Thomas; Krauss, Markus; Kupfer, Lars

2016-08-01

A multiscale model for blood glucose regulation in diabetes type I patients is constructed by integrating detailed metabolic network models for fat, liver and muscle cells into a whole body physiologically-based pharmacokinetic/pharmacodynamic (pBPK/PD) model. The blood glucose regulation PBPK/PD model simulates the distribution and metabolization of glucose, insulin and glucagon on an organ and whole body level. The genome-scale metabolic networks in contrast describe intracellular reactions. The developed multiscale model is fitted to insulin, glucagon and glucose measurements of a 48h clinical trial featuring 6 subjects and is subsequently used to simulate (in silico) the influence of geneknockouts and drug-induced enzyme inhibitions on whole body blood glucose levels. Simulations of diabetes associated gene knockouts and impaired cellular glucose metabolism, resulted in elevated whole body blood-glucose levels, but also in a metabolic shift within the cell's reaction network. Such multiscale models have the potential to be employed in the exploration of novel drug-targets or to be integrated into control algorithms for artificial pancreas systems.

Bayesian calibration for electrochemical thermal model of lithium-ion cells

NASA Astrophysics Data System (ADS)

Tagade, Piyush; Hariharan, Krishnan S.; Basu, Suman; Verma, Mohan Kumar Singh; Kolake, Subramanya Mayya; Song, Taewon; Oh, Dukjin; Yeo, Taejung; Doo, Seokgwang

2016-07-01

Pseudo-two dimensional electrochemical thermal (P2D-ECT) model contains many parameters that are difficult to evaluate experimentally. Estimation of these model parameters is challenging due to computational cost and the transient model. Due to lack of complete physical understanding, this issue gets aggravated at extreme conditions like low temperature (LT) operations. This paper presents a Bayesian calibration framework for estimation of the P2D-ECT model parameters. The framework uses a matrix variate Gaussian process representation to obtain a computationally tractable formulation for calibration of the transient model. Performance of the framework is investigated for calibration of the P2D-ECT model across a range of temperatures (333 Ksbnd 263 K) and operating protocols. In the absence of complete physical understanding, the framework also quantifies structural uncertainty in the calibrated model. This information is used by the framework to test validity of the new physical phenomena before incorporation in the model. This capability is demonstrated by introducing temperature dependence on Bruggeman's coefficient and lithium plating formation at LT. With the incorporation of new physics, the calibrated P2D-ECT model accurately predicts the cell voltage with high confidence. The accurate predictions are used to obtain new insights into the low temperature lithium ion cell behavior.

Modular modelling with Physiome standards

PubMed Central

Nickerson, David P.; Nielsen, Poul M. F.; Hunter, Peter J.

2016-01-01

Key points The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models.We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML.By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity.We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology.The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. Abstract The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole‐cell models and linking such models in multi‐scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole‐cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles. PMID:27353233

Left Ventricular Endocardium Tracking by Fusion of Biomechanical and Deformable Models

PubMed Central

Gu, Jason

2014-01-01

This paper presents a framework for tracking left ventricular (LV) endocardium through 2D echocardiography image sequence. The framework is based on fusion of biomechanical (BM) model of the heart with the parametric deformable model. The BM model constitutive equation consists of passive and active strain energy functions. The deformations of the LV are obtained by solving the constitutive equations using ABAQUS FEM in each frame in the cardiac cycle. The strain energy functions are defined in two user subroutines for active and passive phases. Average fusion technique is used to fuse the BM and deformable model contours. Experimental results are conducted to verify the detected contours and the results are evaluated by comparing themto a created gold standard. The results and the evaluation proved that the framework has the tremendous potential to track and segment the LV through the whole cardiac cycle. PMID:24587814

Comparison of Three Whole-Cell Pertussis Vaccines in the Baboon Model of Pertussis

PubMed Central

Warfel, Jason M.; Zimmerman, Lindsey I.

2015-01-01

Pertussis is a highly contagious respiratory illness caused by the bacterial pathogen Bordetella pertussis. Pertussis rates in the United States have escalated since the 1990s and reached a 50-year high of 48,000 cases in 2012. While this pertussis resurgence is not completely understood, we previously showed that the current acellular pertussis vaccines do not prevent colonization or transmission following challenge. In contrast, a whole-cell pertussis vaccine accelerated the rate of clearance compared to rates in unvaccinated animals and animals treated with the acellular vaccine. In order to understand if these results are generalizable, we used our baboon model to compare immunity from whole-cell vaccines from three different manufacturers that are approved outside the United States. We found that, compared to clearance rates with no vaccine and with an acellular pertussis vaccine, immunization with any of the three whole-cell vaccines significantly accelerated the clearance of B. pertussis following challenge. Whole-cell vaccination also significantly reduced the total nasopharyngeal B. pertussis burden, suggesting that these vaccines reduce the opportunity for pertussis transmission. Meanwhile, there was no difference in either the duration or in B. pertussis burden between unvaccinated and acellular-pertussis-vaccinated animals, while previously infected animals were not colonized following reinfection. We also determined that transcription of the gene encoding interleukin-17 (IL-17) was increased in whole-cell-vaccinated and previously infected animals but not in acellular-pertussis-vaccinated animals following challenge. Together with our previous findings, these data are consistent with a role for Th17 responses in the clearance of B. pertussis infection. PMID:26561389

Physangulidines A, B, and C: three new antiproliferative withanolides from Physalis angulata L.

PubMed

Jin, Zhuang; Mashuta, Mark S; Stolowich, Neal J; Vaisberg, Abraham J; Stivers, Nicole S; Bates, Paula J; Lewis, Walter H; Hammond, Gerald B

2012-03-02

Bioassay-directed fractionation of the whole plant of Physalis angulata L. afforded three new antiproliferative withanolides with an unusual carbon framework: physangulidines A (1), B (2), and C (3). Structures of the three isomeric withanolides were determined by a combination of HRMS, NMR spectroscopic, and X-ray crystallographic methods. Each has shown significant antiproliferative activity against DU145 prostate cancer cells. Physangulidine A (1) was further tested against a wide range of additional cancer cell lines and found to exhibit significant antiproliferative activity. © 2012 American Chemical Society

A mathematical model for predicting the life of polymer electrolyte fuel cell membranes subjected to hydration cycling

NASA Astrophysics Data System (ADS)

Burlatsky, S. F.; Gummalla, M.; O'Neill, J.; Atrazhev, V. V.; Varyukhin, A. N.; Dmitriev, D. V.; Erikhman, N. S.

2012-10-01

Under typical Polymer Electrolyte Membrane Fuel Cell (PEMFC) fuel cell operating conditions, part of the membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEMFC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane lifetime. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.

TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.

PubMed

Ha, Gavin; Roth, Andrew; Khattra, Jaswinder; Ho, Julie; Yap, Damian; Prentice, Leah M; Melnyk, Nataliya; McPherson, Andrew; Bashashati, Ali; Laks, Emma; Biele, Justina; Ding, Jiarui; Le, Alan; Rosner, Jamie; Shumansky, Karey; Marra, Marco A; Gilks, C Blake; Huntsman, David G; McAlpine, Jessica N; Aparicio, Samuel; Shah, Sohrab P

2014-11-01

The evolution of cancer genomes within a single tumor creates mixed cell populations with divergent somatic mutational landscapes. Inference of tumor subpopulations has been disproportionately focused on the assessment of somatic point mutations, whereas computational methods targeting evolutionary dynamics of copy number alterations (CNA) and loss of heterozygosity (LOH) in whole-genome sequencing data remain underdeveloped. We present a novel probabilistic model, TITAN, to infer CNA and LOH events while accounting for mixtures of cell populations, thereby estimating the proportion of cells harboring each event. We evaluate TITAN on idealized mixtures, simulating clonal populations from whole-genome sequences taken from genomically heterogeneous ovarian tumor sites collected from the same patient. In addition, we show in 23 whole genomes of breast tumors that the inference of CNA and LOH using TITAN critically informs population structure and the nature of the evolving cancer genome. Finally, we experimentally validated subclonal predictions using fluorescence in situ hybridization (FISH) and single-cell sequencing from an ovarian cancer patient sample, thereby recapitulating the key modeling assumptions of TITAN. © 2014 Ha et al.; Published by Cold Spring Harbor Laboratory Press.

Evaluation of imaging biomarkers for identification of single cancer cells in blood

NASA Astrophysics Data System (ADS)

Odaka, Masao; Kim, Hyonchol; Girault, Mathias; Hattori, Akihiro; Terazono, Hideyuki; Matsuura, Kenji; Yasuda, Kenji

2015-06-01

A method of discriminating single cancer cells from whole blood cells based on their morphological visual characteristics (i.e., “imaging biomarker”) was examined. Cells in healthy rat blood, a cancer cell line (MAT-LyLu), and cells in cancer-cell-implanted rat blood were chosen as models, and their bright-field (BF, whole-cell morphology) and fluorescence (FL, nucleus morphology) images were taken by an on-chip multi-imaging flow cytometry system and compared. Eight imaging biomarker indices, i.e., cellular area in a BF image, nucleus area in an FL image, area ratio of a whole cell and its nucleus, distance of the mass center between a whole cell and nucleus, cellular and nucleus perimeter, and perimeter ratios were calculated and analyzed using the BF and FL images taken. Results show that cancer cells can be clearly distinguished from healthy blood cells using correlation diagrams for cellular and nucleus areas as two different categories. Moreover, a portion of cancer cells showed a low nucleus perimeter ratio less than 0.9 because of the irregular nucleus morphologies of cancer cells. These results indicate that the measurements of imaging biomarkers are practically applicable to identifying cancer cells in blood.

Whole-brain low-intensity pulsed ultrasound therapy markedly improves cognitive dysfunctions in mouse models of dementia - Crucial roles of endothelial nitric oxide synthase.

PubMed

Eguchi, Kumiko; Shindo, Tomohiko; Ito, Kenta; Ogata, Tsuyoshi; Kurosawa, Ryo; Kagaya, Yuta; Monma, Yuto; Ichijo, Sadamitsu; Kasukabe, Sachie; Miyata, Satoshi; Yoshikawa, Takeo; Yanai, Kazuhiko; Taki, Hirofumi; Kanai, Hiroshi; Osumi, Noriko; Shimokawa, Hiroaki

2018-05-22

Therapeutic focused-ultrasound to the hippocampus has been reported to exert neuroprotective effects on dementia. In the present study, we examined whether the whole-brain LIPUS (low-intensity pulsed ultrasound) therapy is effective and safe in 2 mouse models of dementia (vascular dementia, VaD and Alzheimer's disease, AD), and if so, to elucidate the common underlying mechanism(s) involved. We used bilateral carotid artery stenosis (BCAS) model with micro-coils in male C57BL/6 mice as a VaD model and 5XFAD transgenic mice as an AD model. We applied the LIPUS therapy (1.875 MHz, 6.0 kHz, 32cycles) to the whole brain. In both models, the LIPUS therapy markedly ameliorated cognitive impairments (Y-maze test and/or passive avoidance test) associated with improved cerebral blood flow (CBF). Mechanistically, the LIPUS therapy significantly increased CD31-positive endothelial cells and Olig2-positive oligodendrocyte precursor cells (OPCs) in the VaD model, while it reduced Iba-1-positive microglias and amyloid-β (Aβ) plaque in the AD model. In both models, endothelium-related genes were significantly upregulated in RNA-sequencing, and expressions of endothelial nitric oxide synthase (eNOS) and neurotrophins were upregulated in Western blotting. Interestingly, the increases in glia cells and neurotrophin expressions showed significant correlations with eNOS expression. Importantly, these beneficial effects of LIPUS were absent in eNOS-knockout mice. These results indicate that the whole-brain LIPUS is an effective and non-invasive therapy for dementia by activating specific cells corresponding to each pathology, for which eNOS activation plays an important role as a common mechanism. Copyright © 2018. Published by Elsevier Inc.

Translating Life Course Theory to Clinical Practice to Address Health Disparities

PubMed Central

Solomon, Barry S.

2013-01-01

Life Course Theory (LCT) is a framework that explains health and disease across populations and over time and in a powerful way, conceptualizes health and health disparities to guide improvements. It suggests a need to change priorities and paradigms in our healthcare delivery system. In “Rethinking Maternal and Child Health: The Life Course Model as an Organizing Framework,” Fine and Kotelchuck identify three areas of rethinking that have relevance to clinical care: (1) recognition of context and the “whole-person, whole-family, whole-community systems approach;” (2) longitudinal approach with “greater emphasis on early (“upstream”) determinants of health”; and (3) need for integration and “developing integrated, multi-sector service systems that become lifelong “pipelines” for healthy development”. This paper discusses promising clinical practice innovations in these three areas: addressing social influences on health in clinical practice, longitudinal and vertical integration of clinical services and horizontal integration with community services and resources. In addition, barriers and facilitators to implementation are reviewed. PMID:23677685

A Computational Framework for Bioimaging Simulation

PubMed Central

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood.

PubMed

Prauße, Maria T E; Lehnert, Teresa; Timme, Sandra; Hünniger, Kerstin; Leonhardt, Ines; Kurzai, Oliver; Figge, Marc Thilo

2018-01-01

Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with C. albicans to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either C. albicans or C. glabrata under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with C. albicans and C. glabrata . However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism.

Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood

PubMed Central

Prauße, Maria T. E.; Lehnert, Teresa; Timme, Sandra; Hünniger, Kerstin; Leonhardt, Ines; Kurzai, Oliver; Figge, Marc Thilo

2018-01-01

Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with C. albicans to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either C. albicans or C. glabrata under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with C. albicans and C. glabrata. However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism. PMID:29619027

Role of whole bone marrow, whole bone marrow cultured cells, and mesenchymal stem cells in chronic wound healing.

PubMed

Rodriguez-Menocal, Luis; Shareef, Shahjahan; Salgado, Marcela; Shabbir, Arsalan; Van Badiavas, Evangelos

2015-03-13

Recent evidence has shown that bone marrow cells play critical roles during the inflammatory, proliferative and remodeling phases of cutaneous wound healing. Among the bone marrow cells delivered to wounds are stem cells, which can differentiate into multiple tissue-forming cell lineages to effect, healing. Gaining insight into which lineages are most important in accelerating wound healing would be quite valuable in designing therapeutic approaches for difficult to heal wounds. In this report we compared the effect of different bone marrow preparations on established in vitro wound healing assays. The preparations examined were whole bone marrow (WBM), whole bone marrow (long term initiating/hematopoietic based) cultured cells (BMC), and bone marrow derived mesenchymal stem cells (BM-MSC). We also applied these bone marrow preparations in two murine models of radiation induced delayed wound healing to determine which had a greater effect on healing. Angiogenesis assays demonstrated that tube formation was stimulated by both WBM and BMC, with WBM having the greatest effect. Scratch wound assays showed higher fibroblast migration at 24, 48, and 72 hours in presence of WBM as compared to BM-MSC. WBM also appeared to stimulate a greater healing response than BMC and BM-MSC in a radiation induced delayed wound healing animal model. These studies promise to help elucidate the role of stem cells during repair of chronic wounds and reveal which cells present in bone marrow might contribute most to the wound healing process.

Quantitative analysis of drug effects at the whole-body level: a case study for glucose metabolism in malaria patients.

PubMed

Snoep, Jacky L; Green, Kathleen; Eicher, Johann; Palm, Daniel C; Penkler, Gerald; du Toit, Francois; Walters, Nicolas; Burger, Robert; Westerhoff, Hans V; van Niekerk, David D

2015-12-01

We propose a hierarchical modelling approach to construct models for disease states at the whole-body level. Such models can simulate effects of drug-induced inhibition of reaction steps on the whole-body physiology. We illustrate the approach for glucose metabolism in malaria patients, by merging two detailed kinetic models for glucose metabolism in the parasite Plasmodium falciparum and the human red blood cell with a coarse-grained model for whole-body glucose metabolism. In addition we use a genome-scale metabolic model for the parasite to predict amino acid production profiles by the malaria parasite that can be used as a complex biomarker. © 2015 Authors; published by Portland Press Limited.

Macrogenomic engineering via modulation of the scaling of chromatin packing density.

PubMed

Almassalha, Luay M; Bauer, Greta M; Wu, Wenli; Cherkezyan, Lusik; Zhang, Di; Kendra, Alexis; Gladstein, Scott; Chandler, John E; VanDerway, David; Seagle, Brandon-Luke L; Ugolkov, Andrey; Billadeau, Daniel D; O'Halloran, Thomas V; Mazar, Andrew P; Roy, Hemant K; Szleifer, Igal; Shahabi, Shohreh; Backman, Vadim

2017-11-01

Many human diseases result from the dysregulation of the complex interactions between tens to thousands of genes. However, approaches for the transcriptional modulation of many genes simultaneously in a predictive manner are lacking. Here, through the combination of simulations, systems modelling and in vitro experiments, we provide a physical regulatory framework based on chromatin packing-density heterogeneity for modulating the genomic information space. Because transcriptional interactions are essentially chemical reactions, they depend largely on the local physical nanoenvironment. We show that the regulation of the chromatin nanoenvironment allows for the predictable modulation of global patterns in gene expression. In particular, we show that the rational modulation of chromatin density fluctuations can lead to a decrease in global transcriptional activity and intercellular transcriptional heterogeneity in cancer cells during chemotherapeutic responses to achieve near-complete cancer cell killing in vitro. Our findings represent a 'macrogenomic engineering' approach to modulating the physical structure of chromatin for whole-scale transcriptional modulation.

SPY: a new scission-point model based on microscopic inputs to predict fission fragment properties

NASA Astrophysics Data System (ADS)

Panebianco, Stefano; Dubray, Nöel; Goriely, Stéphane; Hilaire, Stéphane; Lemaître, Jean-François; Sida, Jean-Luc

2014-04-01

Despite the difficulty in describing the whole fission dynamics, the main fragment characteristics can be determined in a static approach based on a so-called scission-point model. Within this framework, a new Scission-Point model for the calculations of fission fragment Yields (SPY) has been developed. This model, initially based on the approach developed by Wilkins in the late seventies, consists in performing a static energy balance at scission, where the two fragments are supposed to be completely separated so that their macroscopic properties (mass and charge) can be considered as fixed. Given the knowledge of the system state density, averaged quantities such as mass and charge yields, mean kinetic and excitation energy can then be extracted in the framework of a microcanonical statistical description. The main advantage of the SPY model is the introduction of one of the most up-to-date microscopic descriptions of the nucleus for the individual energy of each fragment and, in the future, for their state density. These quantities are obtained in the framework of HFB calculations using the Gogny nucleon-nucleon interaction, ensuring an overall coherence of the model. Starting from a description of the SPY model and its main features, a comparison between the SPY predictions and experimental data will be discussed for some specific cases, from light nuclei around mercury to major actinides. Moreover, extensive predictions over the whole chart of nuclides will be discussed, with particular attention to their implication in stellar nucleosynthesis. Finally, future developments, mainly concerning the introduction of microscopic state densities, will be briefly discussed.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

A hybrid computational model to explore the topological characteristics of epithelial tissues.

PubMed

González-Valverde, Ismael; García-Aznar, José Manuel

2017-11-01

Epithelial tissues show a particular topology where cells resemble a polygon-like shape, but some biological processes can alter this tissue topology. During cell proliferation, mitotic cell dilation deforms the tissue and modifies the tissue topology. Additionally, cells are reorganized in the epithelial layer and these rearrangements also alter the polygon distribution. We present here a computer-based hybrid framework focused on the simulation of epithelial layer dynamics that combines discrete and continuum numerical models. In this framework, we consider topological and mechanical aspects of the epithelial tissue. Individual cells in the tissue are simulated by an off-lattice agent-based model, which keeps the information of each cell. In addition, we model the cell-cell interaction forces and the cell cycle. Otherwise, we simulate the passive mechanical behaviour of the cell monolayer using a material that approximates the mechanical properties of the cell. This continuum approach is solved by the finite element method, which uses a dynamic mesh generated by the triangulation of cell polygons. Forces generated by cell-cell interaction in the agent-based model are also applied on the finite element mesh. Cell movement in the agent-based model is driven by the displacements obtained from the deformed finite element mesh of the continuum mechanical approach. We successfully compare the results of our simulations with some experiments about the topology of proliferating epithelial tissues in Drosophila. Our framework is able to model the emergent behaviour of the cell monolayer that is due to local cell-cell interactions, which have a direct influence on the dynamics of the epithelial tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Whole-cell based hybrid materials for green energy production, environmental remediation and smart cell-therapy.

PubMed

Léonard, Alexandre; Dandoy, Philippe; Danloy, Emeric; Leroux, Grégory; Meunier, Christophe F; Rooke, Joanna C; Su, Bao-Lian

2011-02-01

This critical review highlights the advances that have been made over recent years in the domain of whole-cell immobilisation and encapsulation for applications relating to the environment and human health, particularly focusing on examples of photosynthetic plant cells, bacteria and algae as well as animal cells. Evidence that encapsulated photosynthetic cells remain active in terms of CO(2) sequestration and biotransformation (solar driven conversion of CO(2) into biofuels, drugs, fine chemicals etc.), coupled with the most recent advances made in the field of cell therapy, reveals the need to develop novel devices based on the preservation of living cells within abiotic porous frameworks. This review shall corroborate this statement by selecting precise examples that unambiguously demonstrate the necessity and the benefits of such smart materials. As will be described, the handling and exploitation of photosynthetic cells are enhanced by entrapment or encapsulation since the cells are physically separated from the liquid medium, thereby facilitating the recovery of the metabolites produced. In the case of animal cells, their encapsulation within a matrix is essential in order to create a physical barrier that can protect the cells auto-immune defenders upon implantation into a living body. For these two research axes, the key parameters that have to be kept in mind when designing hybrid materials will be identified, concentrating on essential aspects such as biocompatibility, mechanical strength and controlled porosity (264 references).

Parsing multiple processes of high temperature impacts on corn/soybean yield using a newly developed CLM-APSIM modeling framework

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.

2016-12-01

Future agricultural production faces a grand challenge of higher temperature under climate change. There are multiple physiological or metabolic processes of how high temperature affects crop yield. Specifically, we consider the following major processes: (1) direct temperature effects on photosynthesis and respiration; (2) speed-up growth rate and the shortening of growing season; (3) heat stress during reproductive stage (flowering and grain-filling); (4) high-temperature induced increase of atmospheric water demands. In this work, we use a newly developed modeling framework (CLM-APSIM) to simulate the corn and soybean growth and explicitly parse the above four processes. By combining the strength of CLM in modeling surface biophysical (e.g., hydrology and energy balance) and biogeochemical (e.g., photosynthesis and carbon-nitrogen interactions), as well as that of APSIM in modeling crop phenology and reproductive stress, the newly developed CLM-APSIM modeling framework enables us to diagnose the impacts of high temperature stress through different processes at various crop phenology stages. Ground measurements from the advanced SoyFACE facility at University of Illinois is used here to calibrate, validate, and improve the CLM-APSIM modeling framework at the site level. We finally use the CLM-APSIM modeling framework to project crop yield for the whole US Corn Belt under different climate scenarios.

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making.

PubMed

Daniels, Bryan C; Flack, Jessica C; Krakauer, David C

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a "coding duality" in which there are accumulation and consensus formation processes distinguished by different timescales.

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making

PubMed Central

Daniels, Bryan C.; Flack, Jessica C.; Krakauer, David C.

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a “coding duality” in which there are accumulation and consensus formation processes distinguished by different timescales. PMID:28634436

Developing whole mycobacteria cell vaccines for tuberculosis: Workshop proceedings, Max Planck Institute for Infection Biology, Berlin, Germany, July 9, 2014.

PubMed

2015-06-12

On July 9, 2014, Aeras and the Max Planck Institute for Infection Biology convened a workshop entitled "Whole Mycobacteria Cell Vaccines for Tuberculosis" at the Max Planck Institute for Infection Biology on the grounds of the Charité Hospital in Berlin, Germany, close to the laboratory where, in 1882, Robert Koch first identified Mycobacterium tuberculosis (Mtb) as the pathogen responsible for tuberculosis (TB). The purpose of the meeting was to discuss progress in the development of TB vaccines based on whole mycobacteria cells. Live whole cell TB vaccines discussed at this meeting were derived from Mtb itself, from Bacille Calmette-Guérin (BCG), the only licensed vaccine against TB, which was genetically modified to reduce pathogenicity and increase immunogenicity, or from commensal non-tuberculous mycobacteria. Inactivated whole cell TB and non-tuberculous mycobacterial vaccines, intended as immunotherapy or as safer immunization alternatives for HIV+ individuals, also were discussed. Workshop participants agreed that TB vaccine development is significantly hampered by imperfect animal models, unknown immune correlates of protection and the absence of a human challenge model. Although a more effective TB vaccine is needed to replace or enhance the limited effectiveness of BCG in all age groups, members of the workshop concurred that an effective vaccine would have the greatest impact on TB control when administered to adolescents and adults, and that use of whole mycobacteria cells as TB vaccine candidates merits greater support, particularly given the limited understanding of the specific Mtb antigens necessary to generate an immune response capable of preventing Mtb infection and/or disease. Copyright © 2015. Published by Elsevier Ltd.. All rights reserved.

Combining Theory, Model, and Experiment to Explain How Intrinsic Theta Rhythms Are Generated in an In Vitro Whole Hippocampus Preparation without Oscillatory Inputs

PubMed Central

Ferguson, Katie A.

2017-01-01

Abstract Scientists have observed local field potential theta rhythms (3–12 Hz) in the hippocampus for decades, but understanding the mechanisms underlying their generation is complicated by their diversity in pharmacological and frequency profiles. In addition, interactions with other brain structures and oscillatory drives to the hippocampus during distinct brain states has made it difficult to identify hippocampus-specific properties directly involved in theta generation. To overcome this, we develop cellular-based network models using a whole hippocampus in vitro preparation that spontaneously generates theta rhythms. Building on theoretical and computational analyses, we find that spike frequency adaptation and postinhibitory rebound constitute a basis for theta generation in large, minimally connected CA1 pyramidal (PYR) cell network models with fast-firing parvalbumin-positive (PV+) inhibitory cells. Sparse firing of PYR cells and large excitatory currents onto PV+ cells are present as in experiments. The particular theta frequency is more controlled by PYR-to-PV+ cell interactions rather than PV+-to-PYR cell interactions. We identify two scenarios by which theta rhythms can emerge, and they can be differentiated by the ratio of excitatory to inhibitory currents to PV+ cells, but not to PYR cells. Only one of the scenarios is consistent with data from the whole hippocampus preparation, which leads to the prediction that the connection probability from PV+ to PYR cells needs to be larger than from PYR to PV+ cells. Our models can serve as a platform on which to build and develop an understanding of in vivo theta generation. PMID:28791333

Methane utilization in Methylomicrobium alcaliphilum 20ZR: a systems approach.

PubMed

Akberdin, Ilya R; Thompson, Merlin; Hamilton, Richard; Desai, Nalini; Alexander, Danny; Henard, Calvin A; Guarnieri, Michael T; Kalyuzhnaya, Marina G

2018-02-06

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13 C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20Z R . A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. The computational framework of C 1 -metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

Protective effects of vaccines against Bordetella parapertussis in a mouse intranasal challenge model.

PubMed

Komatsu, Eiji; Yamaguchi, Fuminori; Eguchi, Masahiro; Watanabe, Mineo

2010-06-17

Bordetella parapertussis causes typical whooping cough, as does Bordetella pertussis. However, current commercial vaccines are ineffective against B. parapertussis. In an effort to develop vaccines that are effective in protecting against both B. pertussis and B. parapertussis, we examined the protective effects of vaccines prepared from whole-cells and from recombinant proteins derived from B. parapertussis in a mouse intranasal challenge model. We confirmed current pertussis vaccines did not induce protective immunity against B. parapertussis in the mouse model. A whole-cell vaccine prepared from B. parapertussis induced protective immunity against B. parapertussis but not against B. pertussis, suggesting a combination of a current pertussis vaccine with a whole-cell parapertussis vaccine might prevent whooping cough caused by both species of Bordetella. We also found that filamentous hemagglutinin was a protective antigen of B. parapertussis. Our observations should lead to the development of new pertussis vaccines that can control the two prevalent forms of whooping cough.

A human ventricular cell model for investigation of cardiac arrhythmias under hyperkalaemic conditions.

PubMed

Carro, Jesús; Rodríguez, José Félix; Laguna, Pablo; Pueyo, Esther

2011-11-13

In this study, several modifications were introduced to a recently proposed human ventricular action potential (AP) model so as to render it suitable for the study of ventricular arrhythmias. These modifications were driven by new sets of experimental data available from the literature and the analysis of several well-established cellular arrhythmic risk biomarkers, namely AP duration at 90 per cent repolarization (APD(90)), AP triangulation, calcium dynamics, restitution properties, APD(90) adaptation to abrupt heart rate changes, and rate dependence of intracellular sodium and calcium concentrations. The proposed methodology represents a novel framework for the development of cardiac cell models. Five stimulation protocols were applied to the original model and the ventricular AP model developed here to compute the described arrhythmic risk biomarkers. In addition, those models were tested in a one-dimensional fibre in which hyperkalaemia was simulated by increasing the extracellular potassium concentration, [K(+)](o). The effective refractory period (ERP), conduction velocity (CV) and the occurrence of APD alternans were investigated. Results show that modifications improved model behaviour as verified by: (i) AP triangulation well within experimental limits (the difference between APD at 50 and 90 per cent repolarization being 78.1 ms); (ii) APD(90) rate adaptation dynamics characterized by fast and slow time constants within physiological ranges (10.1 and 105.9 s); and (iii) maximum S1S2 restitution slope in accordance with experimental data (S(S1S2)=1.0). In simulated tissues under hyperkalaemic conditions, APD(90) progressively shortened with the degree of hyperkalaemia, whereas ERP increased once a threshold in [K(+)](o) was reached ([K(+)](o)≈6 mM). CV decreased with [K(+)](o), and conduction was blocked for [K(+)](o)>10.4 mM. APD(90) alternans were observed for [K(+)](o)>9.8 mM. Those results adequately reproduce experimental observations. This study demonstrated the value of basing the development of AP models on the computation of arrhythmic risk biomarkers, as opposed to joining together independently derived ion channel descriptions to produce a whole-cell AP model, with the new framework providing a better picture of the model performance under a variety of stimulation conditions. On top of replicating experimental data at single-cell level, the model developed here was able to predict the occurrence of APD(90) alternans and areas of conduction block associated with high [K(+)](o) in tissue, which is of relevance for the investigation of the arrhythmogenic substrate in ischaemic hearts.

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

NASA Technical Reports Server (NTRS)

Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Votava, Petr; Roy, Anshuman; Mukhopadhyay, Supratik; Nemani, Ramakrishna

2015-01-01

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery using a Probabilistic Learning Framework

NASA Astrophysics Data System (ADS)

Basu, S.; Ganguly, S.; Michaelis, A.; Votava, P.; Roy, A.; Mukhopadhyay, S.; Nemani, R. R.

2015-12-01

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

A web-server of cell type discrimination system.

PubMed

Wang, Anyou; Zhong, Yan; Wang, Yanhua; He, Qianchuan

2014-01-01

Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells.

A Web-Server of Cell Type Discrimination System

PubMed Central

Zhong, Yan

2014-01-01

Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells. PMID:24578634

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Towards a Framework for Evolvable Network Design

NASA Astrophysics Data System (ADS)

Hassan, Hoda; Eltarras, Ramy; Eltoweissy, Mohamed

The layered Internet architecture that had long guided network design and protocol engineering was an “interconnection architecture” defining a framework for interconnecting networks rather than a model for generic network structuring and engineering. We claim that the approach of abstracting the network in terms of an internetwork hinders the thorough understanding of the network salient characteristics and emergent behavior resulting in impeding design evolution required to address extreme scale, heterogeneity, and complexity. This paper reports on our work in progress that aims to: 1) Investigate the problem space in terms of the factors and decisions that influenced the design and development of computer networks; 2) Sketch the core principles for designing complex computer networks; and 3) Propose a model and related framework for building evolvable, adaptable and self organizing networks We will adopt a bottom up strategy primarily focusing on the building unit of the network model, which we call the “network cell”. The model is inspired by natural complex systems. A network cell is intrinsically capable of specialization, adaptation and evolution. Subsequently, we propose CellNet; a framework for evolvable network design. We outline scenarios for using the CellNet framework to enhance legacy Internet protocol stack.

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays

PubMed Central

Li, Ao; Liu, Zongzhi; Lezon-Geyda, Kimberly; Sarkar, Sudipa; Lannin, Donald; Schulz, Vincent; Krop, Ian; Winer, Eric; Harris, Lyndsay; Tuck, David

2011-01-01

There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies. PMID:21398628

An Integrated Platform for Isolation, Processing, and Mass Spectrometry-based Proteomic Profiling of Rare Cells in Whole Blood*

PubMed Central

Li, Siyang; Plouffe, Brian D.; Belov, Arseniy M.; Ray, Somak; Wang, Xianzhe; Murthy, Shashi K.; Karger, Barry L.; Ivanov, Alexander R.

2015-01-01

Isolation and molecular characterization of rare cells (e.g. circulating tumor and stem cells) within biological fluids and tissues has significant potential in clinical diagnostics and personalized medicine. The present work describes an integrated platform of sample procurement, preparation, and analysis for deep proteomic profiling of rare cells in blood. Microfluidic magnetophoretic isolation of target cells spiked into 1 ml of blood at the level of 1000–2000 cells/ml, followed by focused acoustics-assisted sample preparation has been coupled with one-dimensional PLOT-LC-MS methodology. The resulting zeptomole detection sensitivity enabled identification of ∼4000 proteins with injection of the equivalent of only 100–200 cells per analysis. The characterization of rare cells in limited volumes of physiological fluids is shown by the isolation and quantitative proteomic profiling of first MCF-7 cells spiked into whole blood as a model system and then two CD133+ endothelial progenitor and hematopoietic cells in whole blood from volunteers. PMID:25755294

Three-dimensional simulation of pseudopod-driven swimming of amoeboid cells

NASA Astrophysics Data System (ADS)

Campbell, Eric; Bagchi, Prosenjit

2016-11-01

Pseudopod-driven locomotion is common in eukaryotic cells, such as amoeba, neutrophils, and cancer cells. Pseudopods are protrusions of the cell body that grow, bifurcate, and retract. Due to the dynamic nature of pseudopods, the shape of a motile cell constantly changes. The actin-myosin protein dynamics is a likely mechanism for pseudopod growth. Existing theoretical models often focus on the acto-myosin dynamics, and not the whole cell shape dynamics. Here we present a full 3D simulation of pseudopod-driven motility by coupling a surface-bound reaction-diffusion (RD) model for the acto-myosin dynamics, a continuum model for the cell membrane deformation, and flow of the cytoplasmic and extracellular fluids. The whole cell is represented as a viscous fluid surrounded by a membrane. A finite-element method is used to solve the membrane deformation, and the RD model on the deforming membrane, while a finite-difference/spectral method is used to solve the flow fields inside and outside the cell. The fluid flow and cell deformation are coupled by the immersed-boundary method. The model predicts pseudopod growth, bifurcation, and retraction as observed for a swimming amoeba. The work provides insights on the role of membrane stiffness and cytoplasmic viscosity on amoeboid swimming. Funded by NSF CBET 1438255.

Efficient breaking of water/oil emulsions by a newly isolated de-emulsifying bacterium, Ochrobactrum anthropi strain RIPI5-1.

PubMed

Mohebali, Ghasemali; Kaytash, Ashk; Etemadi, Narges

2012-10-01

Water-oil emulsions occur throughout oil production, transportation, and processing. The breaking of the water/oil emulsion improves oil quality and as a consequence chemically synthesized de-emulsifiers are commonly used in the petroleum industries. Microbial de-emulsifiers represent potential alternatives to the chemicals and may become important products for petroleum industries. The main goal of this work was isolation, identification, and characterization of an efficient de-emulsifying bacterium. Following a multi-step enrichment programme a de-emulsifying bacterium, Ochrobactrum anthropi strain RIPI5-1was isolated from the oil-polluted sandy bank of Siri Island, Iran. The presence of an oil phase in growth medium was found to be unnecessary for production of the de-emulsifier. The de-emulsifying activity of both the whole culture and the cells of this strain was examined using a model multiple water-crude oil (w/o/w) emulsion. This w/o/w emulsion was used for the first time in microbial de-emulsification research. Whole cells of strain RIPI5-1 exhibited high de-emulsifying activity during the late-exponential growth and stationary phases; de-emulsifying activity of the whole culture was highest during the early-exponential growth phase. The time course of de-emulsification by whole culture and whole cells of strain RIPI5-1 was investigated; the initial rate (DeI(1)) of breaking of the multiple water-crude oil emulsion by whole culture and whole cells was calculated as 11% and 54%, respectively. However, overall de-emulsification (DeI(8.5)) for whole culture and whole cells was calculated as 63% and 72%, respectively. A clear correlation was observed between cell surface hydrophobicity and the de-emulsifying activity of whole cells. With the water/kerosene emulsion, emulsion half-life (t(1/2)) was found to be <0.5h. The potential activity of this strain was also explained using a complex oilfield emulsion. Copyright © 2012 Elsevier B.V. All rights reserved.

Design and modeling of a measuring device for a TIR-R concentrator

NASA Astrophysics Data System (ADS)

Calero, Daniel Pérez; Miñano, Juan Carlos; Benitez, Pablo; Hernandez, Maikel; Cvetkovic, Aleksandra

2006-08-01

One of the most usual procedures to measure a concentrator optical efficiency is by direct comparison between the photocurrent generated by the compound concentrator/solar cell and photocurrent that single cell would generate under identical radiation conditions. Unfortunately, such procedure can give a good idea of the generator final performance, but can not indicate the real amount of radiation that will impinge over the cell. This apparent contradiction is based on the fact that once the cell is coupled with the concentrator, rays incidence is not perpendicular, but highly oblique, with an angle that can reach 70 ° or even greater for high concentration devices. The antireflective coating of the cell does not perform well enough for the whole incidence angle and frequency ranges because low cost is other important requirement for the solar cells. In consequence, the generated photocurrent drops for large incidence angles. In our case, a 70% incidence angle could, in the worst case, mean a 34% loss on generated photocurrent. With the aim of correcting such problem a special device has been designed in the framework of a EU funded project called HAMLET. The concept of the device is to substitute the concentrator receptor by a system formed by an optical collimator that would reduce concentration and incidence angle, and a characterized solar cell. The paper gives the results of this measuring procedure.

Global Perspective on School Leadership.

ERIC Educational Resources Information Center

Thomas, M. Donald; Bainbridge, William L.

The complexity of educational leadership belies simple models and must be examined holistically and historically. Leadership has a setting, a historical framework, a wholeness of meaning, and a diversity of influences. Effective leaders must both articulate the values of society and go beyond them. Most agree leadership: (1) is situational and…

Statistical label fusion with hierarchical performance models

PubMed Central

Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.

2014-01-01

Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809

Structure of 98Ru in the IBA-2 interacting boson model

NASA Astrophysics Data System (ADS)

Giannatiempo, A.

2017-10-01

The 98Ru structure has been investigated in the framework of the IBA-2 model, extending previous works to exploit the whole set of new spectroscopic data. The occurrence of states of mixed symmetry character in the proton and neutron degrees of freedom is of prominent importance in enlightening the structure of this nucleus, which displays features close to those of the Uπ ,ν(5) limit of the model.

SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering

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

Bush, B.; Melaina, M.; Penev, M.

This report describes the development and analysis of detailed temporal and spatial scenarios for early market hydrogen fueling infrastructure clustering and fuel cell electric vehicle rollout using the Scenario Evaluation, Regionalization and Analysis (SERA) model. The report provides an overview of the SERA scenario development framework and discusses the approach used to develop the nationwidescenario.

Modeling of cryopreservation of engineered tissues with one-dimensional geometry.

PubMed

Cui, Z F; Dykhuizen, R C; Nerem, R M; Sembanis, A

2002-01-01

Long-term storage of engineered bio-artificial tissues is required to ensure the off-the-shelf availability to clinicians due to their long production cycle. Cryopreservation is likely the choice for long-term preservation. Although the cryopreservation of cells is well established for many cell types, cryopreservation of tissues is far more complicated. Cells at different locations in the tissue could experience very different local environmental changes, i.e., the change of concentration of cryoprotecting chemicals (CPA) and temperature, during the addition/removal of CPA and cooling/warming, which leads to nonuniformity in cell survival in the tissue. This is due to the limitation of mass and heat transfer within the tissue. A specific aim of cryopreservation of tissue is to ensure a maximum recovery of cells and their functionality throughout a tissue. Cells at all locations should be protected adequately by the CPA and frozen at rates conducive to survival. It is hence highly desirable to know the cell transient and final states during cryopreservation within the whole tissue, which can be best studied by mathematical modeling. In this work, a model framework for cryopreservation of one-dimensional artificial tissues is developed on the basis of solving the coupled equations to describe the mass and heat transfer within the tissue and osmotic transport through the cell membrane. Using an artificial pancreas as an example, we carried out a simulation to examine the temperature history, cell volume, solute redistribution, and other state parameters during the freezing of the spherical heterogeneous construct (a single bead). It is found that the parameters affecting the mass transfer of CPA in tissue and through the cell membrane and the freezing rate play dominant roles in affecting the cell volume transient and extracellular ice formation. Thermal conductivity and extracellular ice formation kinetics, on the other hand, have little effect on cell transient and final states, as the heat transfer rate is much faster than mass diffusion. The outcome of such a model study can be used to evaluate the construct design on its survivability during cryopreservation and to select a cryopreservation protocol to achieve maximum cell survival.

Whole-cell bioreporters and risk assessment of environmental pollution: A proof-of-concept study using lead.

PubMed

Zhang, Xiaokai; Qin, Boqiang; Deng, Jianming; Wells, Mona

2017-10-01

As the world burden of environmental contamination increases, it is of the utmost importance to develop streamlined approaches to environmental risk assessment in order to prioritize mitigation measures. Whole-cell biosensors or bioreporters and speciation modeling have both become of increasing interest to determine the bioavailability of pollutants, as bioavailability is increasingly in use as an indicator of risk. Herein, we examine whether bioreporter results are able to reflect expectations based on chemical reactivity and speciation modeling, with the hope to extend the research into a wider framework of risk assessment. We study a specific test case concerning the bioavailability of lead (Pb) in aqueous environments containing Pb-complexing ligands. Ligands studied include ethylene diamine tetra-acetic acid (EDTA), meso-2,3 dimercaptosuccinic acid (DMSA), leucine, methionine, cysteine, glutathione, and humic acid (HA), and we also performed experiments using natural water samples from Lake Tai (Taihu), the third largest lake in China. We find that EDTA, DMSA, cysteine, glutathione, and HA amendment significantly reduced Pb bioavailability with increasing ligand concentration according to a log-sigmoid trend. Increasing dissolved organic carbon in Taihu water also had the same effect, whereas leucine and methionine had no notable effect on bioavailability at the concentrations tested. We find that bioreporter results are in accord with the reduction of aqueous Pb 2+ that we expect from the relative complexation affinities of the different ligands tested. For EDTA and HA, for which reasonably accurate ionization and complexation constants are known, speciation modeling is in agreement with bioreporter response to within the level of uncertainty recognised as reasonable by the United States Environmental Protection Agency for speciation-based risk assessment applications. These findings represent a first step toward using bioreporter technology to streamline the biological confirmation or validation of speciation modeling for use in environmental risk assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiscale Models in the Biomechanics of Plant Growth

PubMed Central

Fozard, John A.

2015-01-01

Plant growth occurs through the coordinated expansion of tightly adherent cells, driven by regulated softening of cell walls. It is an intrinsically multiscale process, with the integrated properties of multiple cell walls shaping the whole tissue. Multiscale models encode physical relationships to bring new understanding to plant physiology and development. PMID:25729061

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

Analysis of Traffic Crashes Involving Pedestrians Using Big Data: Investigation of Contributing Factors and Identification of Hotspots.

PubMed

Xie, Kun; Ozbay, Kaan; Kurkcu, Abdullah; Yang, Hong

2017-08-01

This study aims to explore the potential of using big data in advancing the pedestrian risk analysis including the investigation of contributing factors and the hotspot identification. Massive amounts of data of Manhattan from a variety of sources were collected, integrated, and processed, including taxi trips, subway turnstile counts, traffic volumes, road network, land use, sociodemographic, and social media data. The whole study area was uniformly split into grid cells as the basic geographical units of analysis. The cell-structured framework makes it easy to incorporate rich and diversified data into risk analysis. The cost of each crash, weighted by injury severity, was assigned to the cells based on the relative distance to the crash site using a kernel density function. A tobit model was developed to relate grid-cell-specific contributing factors to crash costs that are left-censored at zero. The potential for safety improvement (PSI) that could be obtained by using the actual crash cost minus the cost of "similar" sites estimated by the tobit model was used as a measure to identify and rank pedestrian crash hotspots. The proposed hotspot identification method takes into account two important factors that are generally ignored, i.e., injury severity and effects of exposure indicators. Big data, on the one hand, enable more precise estimation of the effects of risk factors by providing richer data for modeling, and on the other hand, enable large-scale hotspot identification with higher resolution than conventional methods based on census tracts or traffic analysis zones. © 2017 Society for Risk Analysis.

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

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

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) has developed a vehicle framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE’s Technical Targets using four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework model for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be easily estimated. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. Additionally, this design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the framework model and compare it to the DOE Technical Targets. These models will be explained and exercised with existing hydrogen storage materials.« less

Population Density and Moment-based Approaches to Modeling Domain Calcium-mediated Inactivation of L-type Calcium Channels.

PubMed

Wang, Xiao; Hardcastle, Kiah; Weinberg, Seth H; Smith, Gregory D

2016-03-01

We present a population density and moment-based description of the stochastic dynamics of domain [Formula: see text]-mediated inactivation of L-type [Formula: see text] channels. Our approach accounts for the effect of heterogeneity of local [Formula: see text] signals on whole cell [Formula: see text] currents; however, in contrast with prior work, e.g., Sherman et al. (Biophys J 58(4):985-995, 1990), we do not assume that [Formula: see text] domain formation and collapse are fast compared to channel gating. We demonstrate the population density and moment-based modeling approaches using a 12-state Markov chain model of an L-type [Formula: see text] channel introduced by Greenstein and Winslow (Biophys J 83(6):2918-2945, 2002). Simulated whole cell voltage clamp responses yield an inactivation function for the whole cell [Formula: see text] current that agrees with the traditional approach when domain dynamics are fast. We analyze the voltage-dependence of [Formula: see text] inactivation that may occur via slow heterogeneous domain [[Formula: see text

Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

PubMed Central

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

2014-01-01

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

k-space image correlation to probe the intracellular dynamics of gold nanoparticles

NASA Astrophysics Data System (ADS)

Bouzin, M.; Sironi, L.; Chirico, G.; D'Alfonso, L.; Inverso, D.; Pallavicini, P.; Collini, M.

2016-04-01

The collective action of dynein, kinesin and myosin molecular motors is responsible for the intracellular active transport of cargoes, vesicles and organelles along the semi-flexible oriented filaments of the cytoskeleton. The overall mobility of the cargoes upon binding and unbinding to motor proteins can be modeled as an intermittency between Brownian diffusion in the cell cytoplasm and active ballistic excursions along actin filaments or microtubules. Such an intermittent intracellular active transport, exhibited by star-shaped gold nanoparticles (GNSs, Gold Nanostars) upon internalization in HeLa cancer cells, is investigated here by combining live-cell time-lapse confocal reflectance microscopy and the spatio-temporal correlation, in the reciprocal Fourier space, of the acquired image sequences. At first, the analytical theoretical framework for the investigation of a two-state intermittent dynamics is presented for Fourier-space Image Correlation Spectroscopy (kICS). Then simulated kICS correlation functions are employed to evaluate the influence of, and sensitivity to, all the kinetic and dynamic parameters the model involves (the transition rates between the diffusive and the active transport states, the diffusion coefficient and drift velocity of the imaged particles). The optimal procedure for the analysis of the experimental data is outlined and finally exploited to derive whole-cell maps for the parameters underlying the GNSs super-diffusive dynamics. Applied here to the GNSs subcellular trafficking, the proposed kICS analysis can be adopted for the characterization of the intracellular (super-) diffusive dynamics of any fluorescent or scattering biological macromolecule.

Probing eukaryotic cell mechanics via mesoscopic simulations

NASA Astrophysics Data System (ADS)

Pivkin, Igor V.; Lykov, Kirill; Nematbakhsh, Yasaman; Shang, Menglin; Lim, Chwee Teck

2017-11-01

We developed a new mesoscopic particle based eukaryotic cell model which takes into account cell membrane, cytoskeleton and nucleus. The breast epithelial cells were used in our studies. To estimate the viscoelastic properties of cells and to calibrate the computational model, we performed micropipette aspiration experiments. The model was then validated using data from microfluidic experiments. Using the validated model, we probed contributions of sub-cellular components to whole cell mechanics in micropipette aspiration and microfluidics experiments. We believe that the new model will allow to study in silico numerous problems in the context of cell biomechanics in flows in complex domains, such as capillary networks and microfluidic devices.

Modelling cell motility and chemotaxis with evolving surface finite elements

PubMed Central

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

2012-01-01

We present a mathematical and a computational framework for the modelling of cell motility. The cell membrane is represented by an evolving surface, with the movement of the cell determined by the interaction of various forces that act normal to the surface. We consider external forces such as those that may arise owing to inhomogeneities in the medium and a pressure that constrains the enclosed volume, as well as internal forces that arise from the reaction of the cells' surface to stretching and bending. We also consider a protrusive force associated with a reaction–diffusion system (RDS) posed on the cell membrane, with cell polarization modelled by this surface RDS. The computational method is based on an evolving surface finite-element method. The general method can account for the large deformations that arise in cell motility and allows the simulation of cell migration in three dimensions. We illustrate applications of the proposed modelling framework and numerical method by reporting on numerical simulations of a model for eukaryotic chemotaxis and a model for the persistent movement of keratocytes in two and three space dimensions. Movies of the simulated cells can be obtained from http://homepages.warwick.ac.uk/∼maskae/CV_Warwick/Chemotaxis.html. PMID:22675164

High-throughput PBPK and Microdosimetry: Cell-level Exposures in a Virtual Tissue Context (WC9)

EPA Science Inventory

Toxicokinetic (TK) models can determine whether chemical exposures produce potentially hazardous tissue concentrations. Tissue microdosimetry TK models relate whole-body chemical exposures to cell-scale concentrations. As a proof of concept, we approximated the micro-anatomic arc...

FPGA implemented testbed in 8-by-8 and 2-by-2 OFDM-MIMO channel estimation and design of baseband transceiver.

PubMed

Ramesh, S; Seshasayanan, R

2016-01-01

In this study, a baseband OFDM-MIMO framework with channel timing and estimation synchronization is composed and executed utilizing the FPGA innovation. The framework is prototyped in light of the IEEE 802.11a standard and the signals transmitted and received utilizing a data transmission of 20 MHz. With the assistance of the QPSK tweak, the framework can accomplish a throughput of 24 Mbps. Besides, the LS formula is executed and the estimation of a frequency-specific fading channel is illustrated. For the rough estimation of timing, MNC plan is examined and actualized. Above all else, the whole framework is demonstrated in MATLAB and a drifting point model is set up. At that point, the altered point model is made with the assistance of Simulink and Xilinx's System Generator for DSP. In this way, the framework is incorporated and actualized inside of Xilinx's ISE tools and focused to Xilinx Virtex 5 board. In addition, an equipment co-simulation is contrived to decrease the preparing time while figuring the BER of the fixed point model. The work concentrates on above all else venture for further examination of planning creative channel estimation strategies towards applications in the fourth era (4G) mobile correspondence frameworks.

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

ERIC Educational Resources Information Center

Cohen, Joel I.

2014-01-01

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

A generative model of whole-brain effective connectivity.

PubMed

Frässle, Stefan; Lomakina, Ekaterina I; Kasper, Lars; Manjaly, Zina M; Leff, Alex; Pruessmann, Klaas P; Buhmann, Joachim M; Stephan, Klaas E

2018-05-25

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure. Copyright © 2018. Published by Elsevier Inc.

Higher bioavailability of iron from whole wheat bread compared with iron-fortified white breads in caco-2 cell model: an experimental study.

PubMed

Nikooyeh, Bahareh; Neyestani, Tirang R

2017-06-01

Bread, as the staple food of Iranians, with average per capita consumption of 300 g d -1 , could potentially be a good vehicle for many fortificants, including iron. In this study, iron bioavailability from flat breads (three fortified and one whole wheat unfortified) was investigated using in vitro simulation of gastrointestinal digestion and absorption in a caco-2 cell model. Despite having a lower ferritin/protein ratio in comparison with fortified breads, whole wheat bread showed higher iron bioavailability than the other three types of bread. Assuming iron bioavailability from the ferrous sulfate supplement used as standard was about 10%, the estimated bioavailability of iron from the test breads was calculated as 5.0-8.0%. Whole wheat bread (∼8%), as compared with the fortified breads (∼5-6.5%), had higher iron bioavailability. Iron from unfortified whole wheat bread is more bioavailable than from three types of iron-fortified breads. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Calibrating genomic and allelic coverage bias in single-cell sequencing.

PubMed

Zhang, Cheng-Zhong; Adalsteinsson, Viktor A; Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L; Meyerson, Matthew; Love, J Christopher

2015-04-16

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.

Calibrating genomic and allelic coverage bias in single-cell sequencing

PubMed Central

Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L.; Meyerson, Matthew; Love, J. Christopher

2016-01-01

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1–10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (~0.1 ×) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples. PMID:25879913

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

Full allogeneic fusion of embryos in a holothuroid echinoderm.

PubMed

Gianasi, Bruno L; Hamel, Jean-François; Mercier, Annie

2018-05-30

Whole-body chimaeras (organisms composed of genetically distinct cells) have been directly observed in modular/colonial organisms (e.g. corals, sponges, ascidians); whereas in unitary deuterostosmes (including mammals) they have only been detected indirectly through molecular analysis. Here, we document for the first time the step-by-step development of whole-body chimaeras in the holothuroid Cucumaria frondosa , a unitary deuterostome belonging to the phylum Echinodermata. To the best of our knowledge, this is the most derived unitary metazoan in which direct investigation of zygote fusibility has been undertaken. Fusion occurred among hatched blastulae, never during earlier (unhatched) or later (larval) stages. The fully fused chimaeric propagules were two to five times larger than non-chimaeric embryos. Fusion was positively correlated with propagule density and facilitated by the natural tendency of early embryos to agglomerate. The discovery of natural chimaerism in a unitary deuterostome that possesses large externally fertilized eggs provides a framework to explore key aspects of evolutionary biology, histocompatibility and cell transplantation in biomedical research. © 2018 The Author(s).

Geometry can provide long-range mechanical guidance for embryogenesis

PubMed Central

Dicko, Mahamar; Saramito, Pierre

2017-01-01

Downstream of gene expression, effectors such as the actomyosin contractile machinery drive embryo morphogenesis. During Drosophila embryonic axis extension, actomyosin has a specific planar-polarised organisation, which is responsible for oriented cell intercalation. In addition to these cell rearrangements, cell shape changes also contribute to tissue deformation. While cell-autonomous dynamics are well described, understanding the tissue-scale behaviour challenges us to solve the corresponding mechanical problem at the scale of the whole embryo, since mechanical resistance of all neighbouring epithelia will feedback on individual cells. Here we propose a novel numerical approach to compute the whole-embryo dynamics of the actomyosin-rich apical epithelial surface. We input in the model specific patterns of actomyosin contractility, such as the planar-polarisation of actomyosin in defined ventro-lateral regions of the embryo. Tissue strain rates and displacements are then predicted over the whole embryo surface according to the global balance of stresses and the material behaviour of the epithelium. Epithelia are modelled using a rheological law that relates the rate of deformation to the local stresses and actomyosin anisotropic contractility. Predicted flow patterns are consistent with the cell flows observed when imaging Drosophila axis extension in toto, using light sheet microscopy. The agreement between model and experimental data indicates that the anisotropic contractility of planar-polarised actomyosin in the ventro-lateral germband tissue can directly cause the tissue-scale deformations of the whole embryo. The three-dimensional mechanical balance is dependent on the geometry of the embryo, whose curved surface is taken into account in the simulations. Importantly, we find that to reproduce experimental flows, the model requires the presence of the cephalic furrow, a fold located anteriorly of the extending tissues. The presence of this geometric feature, through the global mechanical balance, guides the flow and orients extension towards the posterior end. PMID:28346461

Modelling cell wall growth using a fibre-reinforced hyperelastic-viscoplastic constitutive law

NASA Astrophysics Data System (ADS)

Huang, R.; Becker, A. A.; Jones, I. A.

2012-04-01

A fibre-reinforced hyperelastic-viscoplastic model using a finite strain Finite Element (FE) analysis is presented to study the expansive growth of cell walls. Based on the connections between biological concepts and plasticity theory, e.g. wall-loosening and plastic yield, wall-stiffening and plastic hardening, the modelling of cell wall growth is established within a framework of anisotropic viscoplasticity aiming to represent the corresponding biology-controlled behaviour of a cell wall. In order to model in vivo growth, special attention is paid to the differences between a living cell and an isolated wall. The proposed hyperelastic-viscoplastic theory provides a unique framework to clarify the interplay between cellulose microfibrils and cell wall matrix and how this interplay regulates sustainable growth in a particular direction while maintaining the mechanical strength of the cell walls by new material deposition. Moreover, the effect of temperature is taken into account. A numerical scheme is suggested and FE case studies are presented and compared with experimental data.

VAMPnets for deep learning of molecular kinetics.

PubMed

Mardt, Andreas; Pasquali, Luca; Wu, Hao; Noé, Frank

2018-01-02

There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transformation of simulated coordinates into structural features, dimension reduction, clustering the dimension-reduced data, and estimation of a Markov state model or related model of the interconversion rates between molecular structures. This handcrafted approach demands a substantial amount of modeling expertise, as poor decisions at any step will lead to large modeling errors. Here we employ the variational approach for Markov processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks, dubbed VAMPnets. A VAMPnet encodes the entire mapping from molecular coordinates to Markov states, thus combining the whole data processing pipeline in a single end-to-end framework. Our method performs equally or better than state-of-the-art Markov modeling methods and provides easily interpretable few-state kinetic models.

A Bayesian Framework for Generalized Linear Mixed Modeling Identifies New Candidate Loci for Late-Onset Alzheimer’s Disease

PubMed Central

Wang, Xulong; Philip, Vivek M.; Ananda, Guruprasad; White, Charles C.; Malhotra, Ankit; Michalski, Paul J.; Karuturi, Krishna R. Murthy; Chintalapudi, Sumana R.; Acklin, Casey; Sasner, Michael; Bennett, David A.; De Jager, Philip L.; Howell, Gareth R.; Carter, Gregory W.

2018-01-01

Recent technical and methodological advances have greatly enhanced genome-wide association studies (GWAS). The advent of low-cost, whole-genome sequencing facilitates high-resolution variant identification, and the development of linear mixed models (LMM) allows improved identification of putatively causal variants. While essential for correcting false positive associations due to sample relatedness and population stratification, LMMs have commonly been restricted to quantitative variables. However, phenotypic traits in association studies are often categorical, coded as binary case-control or ordered variables describing disease stages. To address these issues, we have devised a method for genomic association studies that implements a generalized LMM (GLMM) in a Bayesian framework, called Bayes-GLMM. Bayes-GLMM has four major features: (1) support of categorical, binary, and quantitative variables; (2) cohesive integration of previous GWAS results for related traits; (3) correction for sample relatedness by mixed modeling; and (4) model estimation by both Markov chain Monte Carlo sampling and maximal likelihood estimation. We applied Bayes-GLMM to the whole-genome sequencing cohort of the Alzheimer’s Disease Sequencing Project. This study contains 570 individuals from 111 families, each with Alzheimer’s disease diagnosed at one of four confidence levels. Using Bayes-GLMM we identified four variants in three loci significantly associated with Alzheimer’s disease. Two variants, rs140233081 and rs149372995, lie between PRKAR1B and PDGFA. The coded proteins are localized to the glial-vascular unit, and PDGFA transcript levels are associated with Alzheimer’s disease-related neuropathology. In summary, this work provides implementation of a flexible, generalized mixed-model approach in a Bayesian framework for association studies. PMID:29507048

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a “Lung Physiome”

PubMed Central

Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.

2011-01-01

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236

Methane utilization in Methylomicrobium alcaliphilum 20Z R: a systems approach

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

Akberdin, Ilya R.; Thompson, Merlin; Hamilton, Richard

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization inmore » M. alcaliphilum 20Z R. A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C 1-metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.« less

Methane utilization in Methylomicrobium alcaliphilum 20Z R: a systems approach

DOE PAGES

Akberdin, Ilya R.; Thompson, Merlin; Hamilton, Richard; ...

2018-02-06

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization inmore » M. alcaliphilum 20Z R. A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C 1-metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.« less

Sustainability assessment framework for scenarios – SAFS

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

Arushanyan, Yevgeniya, E-mail: yevgeniya.arushanyan@abe.kth.se; KTH Royal Institute of Technology, Centre for Sustainable Communications; Ekener, Elisabeth

To address current challenges regarding sustainable development and support planning for this form of development, new learning about different possible futures and their potential sustainability implications is needed. One way of facilitating this learning is by combining the futures studies and sustainability assessment (SA) research fields. This paper presents the sustainability assessment framework for scenarios (SAFS), a method developed for assessing the environmental and social risks and opportunities of future scenarios, provides guidelines for its application and demonstrates how the framework can be applied. SAFS suggests assessing environmental and social aspects using a consumption perspective and a life cycle approach,more » and provides qualitative results. SAFS does not suggest any modelling using precise data, but instead offers guidelines on how to carry out a qualitative assessment, where both the process of assessing and the outcome of the assessment are valuable and can be used as a basis for discussion. The benefits, drawbacks and potential challenges of applying SAFS are also discussed in the paper. SAFS uses systems thinking looking at future societies as a whole, considering both environmental and social consequences. This encourages researchers and decision-makers to consider the whole picture, and not just individual elements, when considering different futures. - Highlights: • The paper presents a new methodological framework for qualitative sustainability assessment of future scenarios with transformative changes. • The framework suggests qualitative assessment with consumption perspective and a life cycle approach. • The paper presents the framework and provides guidelines for its application. • The paper demonstrates on an example how the framework can be applied. • The benefits, drawbacks and challenges of the framework application and the need for further development are discussed.« less

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

A Framework of Teachers' Coping Strategies for a Whole School Stress Management Policy.

ERIC Educational Resources Information Center

Dunham, Jack

1994-01-01

Educators possess a wealth of understanding and experience that can help colleagues deal with heavy work pressures more effectively within the framework of a whole school policy for stress management. The coping strategies discussed embrace a wide range of skills, knowledge, techniques, relationships, thoughts, and activities that may be…

Can dendritic cells improve whole cancer cell vaccines based on immunogenically killed cancer cells?

PubMed Central

Cicchelero, Laetitia; Denies, Sofie; Devriendt, Bert; de Rooster, Hilde; Sanders, Niek N

2015-01-01

Immunogenic cell death (ICD) offers interesting opportunities in cancer cell (CC) vaccine manufacture, as it increases the immunogenicity of the dead CC. Furthermore, fusion of CCs with dendritic cells (DCs) is considered a superior method for generating whole CC vaccines. Therefore, in this work, we determined in naive mice whether immunogenically killed CCs per se (CC vaccine) elicit an antitumoral immune response different from the response observed when immunogenically killed CCs are associated with DCs through fusion (fusion vaccine) or through co-incubation (co-incubation vaccine). After tumor inoculation, the type of immune response in the prophylactically vaccinated mice differed between the groups. In more detail, fusion vaccines elicited a humoral anticancer response, whereas the co-incubation and CC vaccine mainly induced a cellular response. Despite these differences, all three approaches offered a prophylactic protection against tumor development in the murine mammary carcinoma model. In summary, it can be concluded that whole CC vaccines based on immunogenically killed CCs may not necessarily require association with DCs to elicit a protective anticancer immune response. If this finding can be endorsed in other cancer models, the manufacture of CC vaccines would greatly benefit from this new insight, as production of DC-based vaccines is laborious, time-consuming and expensive. PMID:26587315

A mathematical model and computational framework for three-dimensional chondrocyte cell growth in a porous tissue scaffold placed inside a bi-directional flow perfusion bioreactor.

PubMed

Shakhawath Hossain, Md; Bergstrom, D J; Chen, X B

2015-12-01

The in vitro chondrocyte cell culture for cartilage tissue regeneration in a perfusion bioreactor is a complex process. Mathematical modeling and computational simulation can provide important insights into the culture process, which would be helpful for selecting culture conditions to improve the quality of the developed tissue constructs. However, simulation of the cell culture process is a challenging task due to the complicated interaction between the cells and local fluid flow and nutrient transport inside the complex porous scaffolds. In this study, a mathematical model and computational framework has been developed to simulate the three-dimensional (3D) cell growth in a porous scaffold placed inside a bi-directional flow perfusion bioreactor. The model was developed by taking into account the two-way coupling between the cell growth and local flow field and associated glucose concentration, and then used to perform a resolved-scale simulation based on the lattice Boltzmann method (LBM). The simulation predicts the local shear stress, glucose concentration, and 3D cell growth inside the porous scaffold for a period of 30 days of cell culture. The predicted cell growth rate was in good overall agreement with the experimental results available in the literature. This study demonstrates that the bi-directional flow perfusion culture system can enhance the homogeneity of the cell growth inside the scaffold. The model and computational framework developed is capable of providing significant insight into the culture process, thus providing a powerful tool for the design and optimization of the cell culture process. © 2015 Wiley Periodicals, Inc.

Process-to-Panel Modeling and Multiprobe Characterization of Silicon Heterojunction Solar Cell Technology

NASA Astrophysics Data System (ADS)

Chavali, Raghu Vamsi Krishna

The large-scale deployment of PV technology is very sensitive to the material and process costs. There are several potential candidates among p-n heterojunction (HJ) solar cells competing for higher efficiencies at lower material and process costs. These systems are, however, generally complex, involve diverse materials, and are not well understood. The direct translation of classical p-n homojunction theory to p-n HJ cells may not always be self-consistent and can lead, therefore, to misinterpretation of experimental results. Ultimately, this translation may not be useful for modeling and characterization of these solar cells. Hence, there is a strong need to redefine/reinterpret the modeling/characterization methodologies for HJ solar cells to produce a self-consistent framework for optimizing HJ solar cell designs. Towards this goal, we explore the physics and interpret characterization experiments of p-n HJs using Silicon HJ (HIT) solar cells. We will: (1) identify the key HJ properties that affect the cell efficiency; (2) analyze the dependence of key HJ properties on the carrier transport under light and dark conditions; (3) provide a selfconsistent multi-probe approach to extract the HJ parameters using several characterization techniques including dark I-V, light I-V, C-V, impedance spectroscopy, and Suns-Voc; (4) propose design guidelines to address the HJ bottlenecks of HIT cells; and (5) develop a process-to-module modeling framework to establish the module performance limits. The guidelines resulting from this multi-scale and self-consistent framework can be used to improve performance of HIT cells as well as other HJ based solar cells.

How causal analysis can reveal autonomy in models of biological systems

NASA Astrophysics Data System (ADS)

Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

2017-11-01

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

The ontology model of FrontCRM framework

NASA Astrophysics Data System (ADS)

Budiardjo, Eko K.; Perdana, Wira; Franshisca, Felicia

2013-03-01

Adoption and implementation of Customer Relationship Management (CRM) is not merely a technological installation, but the emphasis is more on the application of customer-centric philosophy and culture as a whole. CRM must begin at the level of business strategy, the only level that thorough organizational changes are possible to be done. Changes agenda can be directed to each departmental plans, and supported by information technology. Work processes related to CRM concept include marketing, sales, and services. FrontCRM is developed as framework to guide in identifying business processes related to CRM in which based on the concept of strategic planning approach. This leads to processes and practices identification in every process area related to marketing, sales, and services. The Ontology model presented on this paper by means serves as tools to avoid framework misunderstanding, to define practices systematically within process area and to find CRM software features related to those practices.

Multiscale Modeling of Hematologic Disorders

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

Fedosov, Dmitry A.; Pivkin, Igor; Pan, Wenxiao

Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain perfusion, as in the case of cerebral malaria. Modeling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangianmore » method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behavior of whole healthy blood and compare with experimental results. The same procedure is applied to modeling malaria, and results for infected single RBCs and whole blood are presented.« less

A Flexible Electronic Commerce Recommendation System

NASA Astrophysics Data System (ADS)

Gong, Songjie

Recommendation systems have become very popular in E-commerce websites. Many of the largest commerce websites are already using recommender technologies to help their customers find products to purchase. An electronic commerce recommendation system learns from a customer and recommends products that the customer will find most valuable from among the available products. But most recommendation methods are hard-wired into the system and they support only fixed recommendations. This paper presented a framework of flexible electronic commerce recommendation system. The framework is composed by user model interface, recommendation engine, recommendation strategy model, recommendation technology group, user interest model and database interface. In the recommender strategy model, the method can be collaborative filtering, content-based filtering, mining associate rules method, knowledge-based filtering method or the mixed method. The system mapped the implementation and demand through strategy model, and the whole system would be design as standard parts to adapt to the change of the recommendation strategy.

The Internal Coherence Assessment Protocol & Developmental Framework: Building the Organizational Capacity for Instructional Improvement in Schools. Research Paper

ERIC Educational Resources Information Center

Elmore, Richard F.; Forman, Michelle L.; Stosich, Elizabeth L.; Bocala, Candice

2014-01-01

Purpose: In this paper we describe the Internal Coherence (IC) model of assessment and professional development, a set of clinical tools and practices designed to help practitioners foster the organizational conditions required for whole-school instructional improvement. Proposed Conceptual Argument: We argue that the data captured by the IC…

Chinese medicine and biomodulation in cancer patients—Part one

PubMed Central

Sagar, S.M.; Wong, R.K.

2008-01-01

Traditional Chinese Medicine (tcm) may be integrated with conventional Western medicine to enhance the care of patients with cancer. Although tcm is normally implemented as a whole system, recent reductionist research suggests mechanisms for the effects of acupuncture, herbs, and nutrition within the scientific model of biomedicine. The health model of Chinese medicine accommodates physical and pharmacologic interventions within the framework of a body–mind network. A Cartesian split does not occur within this model, but to allow for scientific exploration within the restrictions of positivism, reductionism, and controls for confounding factors, the components must necessarily be separated. Still, whole-systems research is important to evaluate effectiveness when applying the full model in clinical practice. Scientific analysis provides a mechanistic understanding of the processes that will improve the design of clinical studies and enhance safety. Enough preliminary evidence is available to encourage quality clinical trials to evaluate the efficacy of integrating tcm into Western cancer care. PMID:18317584

Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations

PubMed Central

Schwen, Lars Ole; Schenk, Arne; Kreutz, Clemens; Timmer, Jens; Bartolomé Rodríguez, María Matilde; Kuepfer, Lars; Preusser, Tobias

2015-01-01

The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale. PMID:26222615

Process change evaluation framework for allogeneic cell therapies: impact on drug development and commercialization.

PubMed

Hassan, Sally; Huang, Hsini; Warren, Kim; Mahdavi, Behzad; Smith, David; Jong, Simcha; Farid, Suzanne S

2016-04-01

Some allogeneic cell therapies requiring a high dose of cells for large indication groups demand a change in cell expansion technology, from planar units to microcarriers in single-use bioreactors for the market phase. The aim was to model the optimal timing for making this change. A development lifecycle cash flow framework was created to examine the implications of process changes to microcarrier cultures at different stages of a cell therapy's lifecycle. The analysis performed under assumptions used in the framework predicted that making this switch earlier in development is optimal from a total expected out-of-pocket cost perspective. From a risk-adjusted net present value view, switching at Phase I is economically competitive but a post-approval switch can offer the highest risk-adjusted net present value as the cost of switching is offset by initial market penetration with planar technologies. The framework can facilitate early decision-making during process development.

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE PAGES

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.; ...

2018-04-07

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

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

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less

Automated analysis and classification of melanocytic tumor on skin whole slide images.

PubMed

Xu, Hongming; Lu, Cheng; Berendt, Richard; Jha, Naresh; Mandal, Mrinal

2018-06-01

This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synthesis of MSnO{sub 3} (M = Ba, Sr) nanoparticles by reverse micelle method and particle size distribution analysis by whole powder pattern modeling

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

Ahmed, Jahangeer; Blakely, Colin K.; Bruno, Shaun R.

2012-09-15

Highlights: ► BaSnO{sub 3} and SrSnO{sub 3} nanoparticles synthesized using the reverse micelle method. ► Particle size and size distribution studied by whole powder pattern modeling. ► Nanoparticles are of optimal size for investigation in dye-sensitized solar cells. -- Abstract: Light-to-electricity conversion efficiency in dye-sensitized solar cells critically depends not only on the dye molecule, semiconducting material and redox shuttle selection but also on the particle size and particle size distribution of the semiconducting photoanode. In this study, nanocrystalline BaSnO{sub 3} and SrSnO{sub 3} particles have been synthesized using the microemulsion method. Particle size distribution was studied by whole powdermore » pattern modeling which confirmed narrow particle size distribution with an average size of 18.4 ± 8.3 nm for SrSnO{sub 3} and 15.8 ± 4.2 nm for BaSnO{sub 3}. These values are in close agreement with results of transmission electron microscopy. The prepared materials have optimal microstructure for successive investigation in dye-sensitized solar cells.« less

Preliminary model of fluid and solute distribution and transport during hemorrhage.

PubMed

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

2003-01-01

The distribution and transport of fluid, ions, and other solutes (plasma proteins and glucose) are described in a mathematical model of unresuscitated hemorrhage. The model is based on balances of each material in both the circulation and its red blood cells, as well as in a whole-body tissue compartment along with its cells. Exchange between these four compartments occurs by a number of different mechanisms. The hemorrhage model has as its basis a validated model, due to Gyenge et al., of fluid and solute exchange in the whole body of a standard human. Hypothetical but physiologically based features such as glucose and small ion releases along with cell membrane changes are incorporated into the hemorrhage model to describe the system behavior, particularly during larger hemorrhages. Moderate (10%-30% blood volume loss) and large (> 30% blood loss) hemorrhage dynamics are simulated and compared with available data. The model predictions compare well with the available information for both types of hemorrhages and provide a reasonable description of the progression of a large hemorrhage from the compensatory phase through vascular collapse.

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

Aggressive natural killer-cell leukemia mutational landscape and drug profiling highlight JAK-STAT signaling as therapeutic target.

PubMed

Dufva, Olli; Kankainen, Matti; Kelkka, Tiina; Sekiguchi, Nodoka; Awad, Shady Adnan; Eldfors, Samuli; Yadav, Bhagwan; Kuusanmäki, Heikki; Malani, Disha; Andersson, Emma I; Pietarinen, Paavo; Saikko, Leena; Kovanen, Panu E; Ojala, Teija; Lee, Dean A; Loughran, Thomas P; Nakazawa, Hideyuki; Suzumiya, Junji; Suzuki, Ritsuro; Ko, Young Hyeh; Kim, Won Seog; Chuang, Shih-Sung; Aittokallio, Tero; Chan, Wing C; Ohshima, Koichi; Ishida, Fumihiro; Mustjoki, Satu

2018-04-19

Aggressive natural killer-cell (NK-cell) leukemia (ANKL) is an extremely aggressive malignancy with dismal prognosis and lack of targeted therapies. Here, we elucidate the molecular pathogenesis of ANKL using a combination of genomic and drug sensitivity profiling. We study 14 ANKL patients using whole-exome sequencing (WES) and identify mutations in STAT3 (21%) and RAS-MAPK pathway genes (21%) as well as in DDX3X (29%) and epigenetic modifiers (50%). Additional alterations include JAK-STAT copy gains and tyrosine phosphatase mutations, which we show recurrent also in extranodal NK/T-cell lymphoma, nasal type (NKTCL) through integration of public genomic data. Drug sensitivity profiling further demonstrates the role of the JAK-STAT pathway in the pathogenesis of NK-cell malignancies, identifying NK cells to be highly sensitive to JAK and BCL2 inhibition compared to other hematopoietic cell lineages. Our results provide insight into ANKL genetics and a framework for application of targeted therapies in NK-cell malignancies.

Expression of a Dianthus flavonoid glucosyltransferase in Saccharomyces cerevisiae for whole-cell biocatalysis.

PubMed

Werner, Sean R; Morgan, John A

2009-07-15

Glycosyltransferases are promising biocatalysts for the synthesis of small molecule glycosides. In this study, Saccharomyces cerevisiae expressing a flavonoid glucosyltransferase (GT) from Dianthus caryophyllus (carnation) was investigated as a whole-cell biocatalyst. Two yeast expression systems were compared using the flavonoid naringenin as a model substrate. Under in vitro conditions, naringenin-7-O-glucoside was formed and a higher specific glucosyl transfer activity was found using a galactose inducible expression system compared to a constitutive expression system. However, S. cerevisiae expressing the GT constitutively was significantly more productive than the galactose inducible system under in vivo conditions. Interestingly, the glycosides were recovered directly from the culture broth and did not accumulate intracellularly. A previously uncharacterized naringenin glycoside formed using the D. caryophyllus GT was identified as naringenin-4'-O-glucoside. It was found that S. cerevisiae cells hydrolyze naringenin-7-O-glucoside during whole-cell biocatalysis, resulting in a low final glycoside titer. When phloretin was added as a substrate to the yeast strain expressing the GT constitutively, the natural product phlorizin was formed. This study demonstrates S. cerevisiae is a promising whole-cell biocatalyst host for the production of valuable glycosides.

Mathematical Model Formulation And Validation Of Water And Solute Transport In Whole Hamster Pancreatic Islets

PubMed Central

Benson, Charles T.; Critser, John K.

2014-01-01

Optimization of cryopreservation protocols for cells and tissues requires accurate models of heat and mass transport. Model selection often depends on the configuration of the tissue. Here, a mathematical and conceptual model of water and solute transport for whole hamster pancreatic islets has been developed and experimentally validated incorporating fundamental biophysical data from previous studies on individual hamster islet cells while retaining whole-islet structural information. It describes coupled transport of water and solutes through the islet by three methods: intracellularly, intercellularly, and in combination. In particular we use domain decomposition techniques to couple a transmembrane flux model with an interstitial mass transfer model. The only significant undetermined variable is the cellular surface area which is in contact with the intercellularly transported solutes, Ais. The model was validated and Ais determined using a 3 × 3 factorial experimental design blocked for experimental day. Whole islet physical experiments were compared with model predictions at three temperatures, three perfusing solutions, and three islet size groups. A mean of 4.4 islets were compared at each of the 27 experimental conditions and found to correlate with a coefficient of determination of 0.87 ± 0.06 (mean ± S.D.). Only the treatment variable of perfusing solution was found to be significant (p < 0.05). We have devised a model that retains much of the intrinsic geometric configuration of the system, and thus fewer laboratory experiments are needed to determine model parameters and thus to develop new optimized cryopreservation protocols. Additionally, extensions to ovarian follicles and other concentric tissue structures may be made. PMID:24950195

A novel mechanistic modeling framework for analysis of electrode balancing and degradation modes in commercial lithium-ion cells

NASA Astrophysics Data System (ADS)

Schindler, Stefan; Danzer, Michael A.

2017-03-01

Aiming at a long-term stable and safe operation of rechargeable lithium-ion cells, elementary design aspects and degradation phenomena have to be considered depending on the specific application. Among the degrees of freedom in cell design, electrode balancing is of particular interest and has a distinct effect on useable capacity and voltage range. Concerning intrinsic degradation modes, understanding the underlying electrochemical processes and tracing the overall degradation history are the most crucial tasks. In this study, a model-based, minimal parameter framework for combined elucidation of electrode balancing and degradation pathways in commercial lithium-ion cells is introduced. The framework rests upon the simulation of full cell voltage profiles from the superposition of equivalent, artificially degraded half-cell profiles and allows to separate aging contributions from loss of available lithium and active materials in both electrodes. A physically meaningful coupling between thermodynamic and kinetic degradation modes based on the correlation between altered impedance features and loss of available lithium as well as loss of active material is proposed and validated by a low temperature degradation profile examined in one of our recent publications. The coupled framework is able to determine the electrode balancing within an error range of < 1% and the projected cell degradation is qualitatively and quantitatively in line with experimental observations.

Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.

PubMed

Watanabe, Leandro; Myers, Chris J

2016-08-19

The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime.

The structure of disaster resilience: a framework for simulations and policy recommendations

NASA Astrophysics Data System (ADS)

Edwards, J. H. Y.

2015-04-01

In this era of rapid climate change there is an urgent need for interdisciplinary collaboration and understanding in the study of what determines resistance to disasters and recovery speed. This paper is an economist's contribution to that effort. It traces the entrance of the word "resilience" from ecology into the social science literature on disasters, provides a formal economic definition of resilience that can be used in mathematical modeling, incorporates this definition into a multilevel model that suggests appropriate policy roles and targets at each level, and draws on the recent empirical literature on the economics of disaster, searching for policy handles that can stimulate higher resilience. On the whole it provides a framework for simulations and for formulating disaster resilience policies.

The structure of disaster resilience: a framework for simulations and policy recommendations

NASA Astrophysics Data System (ADS)

Edwards, J. H. Y.

2014-09-01

In this era of rapid climate change there is an urgent need for interdisciplinary collaboration and understanding in the study of what determines resistance to disasters and recovery speed. This paper is an economist's contribution to that effort. It traces the entrance of the word "resilience" from ecology into the social science literature on disasters, provides a formal economic definition of resilience that can be used in mathematical modeling, incorporates this definition into a multilevel model that suggests appropriate policy roles and targets at each level, and draws on the recent empirical literature on the economics of disaster searching for policy handles that can stimulate higher resilience. On the whole it provides a framework for simulations and for formulating disaster resilience policies.

Prediction and Informative Risk Factor Selection of Bone Diseases.

PubMed

Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong

2015-01-01

With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.

Clonal Expansion (CE) Models in Cancer Risk Assessment

EPA Science Inventory

Cancer arises when cells accumulate sufficient critical mutations. Carcinogens increase the probability of mutation during cell division or promote clonal expansion within stages. Multistage CE models recapitulate this process and provide a framework for incorporating relevant da...

Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity

PubMed Central

Cheng, Leo K; Komuro, Rie; Austin, Travis M; Buist, Martin L; Pullan, Andrew J

2007-01-01

One of the major aims of the International Union of Physiological Sciences (IUPS) Physiome Project is to develop multiscale mathematical and computer models that can be used to help understand human health. We present here a small facet of this broad plan that applies to the gastrointestinal system. Specifically, we present an anatomically and physiologically based modelling framework that is capable of simulating normal and pathological electrical activity within the stomach and small intestine. The continuum models used within this framework have been created using anatomical information derived from common medical imaging modalities and data from the Visible Human Project. These models explicitly incorporate the various smooth muscle layers and networks of interstitial cells of Cajal (ICC) that are known to exist within the walls of the stomach and small bowel. Electrical activity within individual ICCs and smooth muscle cells is simulated using a previously published simplified representation of the cell level electrical activity. This simulated cell level activity is incorporated into a bidomain representation of the tissue, allowing electrical activity of the entire stomach or intestine to be simulated in the anatomically derived models. This electrical modelling framework successfully replicates many of the qualitative features of the slow wave activity within the stomach and intestine and has also been used to investigate activity associated with functional uncoupling of the stomach. PMID:17457969

A Note on the Bogdanov-Takens Bifurcation in the Romer Model with Learning by Doing

NASA Astrophysics Data System (ADS)

Bella, Giovanni

This paper is aimed at describing the whole set of necessary and sufficient conditions for the emergence of multiple equilibria and global indeterminacy in the standard endogenous growth framework with learning by doing. The novelty of this paper relies on the application of the original Bogdanov-Takens bifurcation theorem, which allows us to characterize the full dynamics of the model, and determine the emergence of an unavoidable poverty trap.

Application of agent-based system for bioprocess description and process improvement.

PubMed

Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

2010-01-01

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. Copyright 2009 American Institute of Chemical Engineers

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

PubMed

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.

A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis.

PubMed

Uriu, Koichiro; Bhavna, Rajasekaran; Oates, Andrew C; Morelli, Luis G

2017-08-15

In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a 'segmentation clock', in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease. © 2017. Published by The Company of Biologists Ltd.

A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis

PubMed Central

Bhavna, Rajasekaran; Oates, Andrew C.; Morelli, Luis G.

2017-01-01

ABSTRACT In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease. PMID:28652318

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

PubMed

Giridhar, Karthik V; Sosa, Carlos P; Hillman, David W; Sanhueza, Cristobal; Dalpiaz, Candace L; Costello, Brian A; Quevedo, Fernando J; Pitot, Henry C; Dronca, Roxana S; Ertz, Donna; Cheville, John C; Donkena, Krishna Vanaja; Kohli, Manish

2017-11-03

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04-0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05-0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only ( p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies.

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma

PubMed Central

Sosa, Carlos P.; Hillman, David W.; Sanhueza, Cristobal; Dalpiaz, Candace L.; Costello, Brian A.; Quevedo, Fernando J.; Pitot, Henry C.; Dronca, Roxana S.; Ertz, Donna; Cheville, John C.; Donkena, Krishna Vanaja; Kohli, Manish

2017-01-01

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04–0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05–0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only (p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies. PMID:29099775

A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

PubMed Central

2012-01-01

Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

Comparing the Achievement of Urban Ninth Graders in Schools Using External Vendors for Whole School Reform

ERIC Educational Resources Information Center

Lynch, Virginia N.

2013-01-01

Use of external vendors to implement school reform and address student achievement in urban secondary schools has not been studied. This quasi-experimental longitudinal study focused on changes in student achievement among urban 9th grade students during the 2010-2011 school year. The theoretical framework was the transformational model of using…

Ribosome biogenesis in replicating cells: Integration of experiment and theory.

PubMed

Earnest, Tyler M; Cole, John A; Peterson, Joseph R; Hallock, Michael J; Kuhlman, Thomas E; Luthey-Schulten, Zaida

2016-10-01

Ribosomes-the primary macromolecular machines responsible for translating the genetic code into proteins-are complexes of precisely folded RNA and proteins. The ways in which their production and assembly are managed by the living cell is of deep biological importance. Here we extend a recent spatially resolved whole-cell model of ribosome biogenesis in a fixed volume [Earnest et al., Biophys J 2015, 109, 1117-1135] to include the effects of growth, DNA replication, and cell division. All biological processes are described in terms of reaction-diffusion master equations and solved stochastically using the Lattice Microbes simulation software. In order to determine the replication parameters, we construct and analyze a series of Escherichia coli strains with fluorescently labeled genes distributed evenly throughout their chromosomes. By measuring these cells' lengths and number of gene copies at the single-cell level, we could fit a statistical model of the initiation and duration of chromosome replication. We found that for our slow-growing (120 min doubling time) E. coli cells, replication was initiated 42 min into the cell cycle and completed after an additional 42 min. While simulations of the biogenesis model produce the correct ribosome and mRNA counts over the cell cycle, the kinetic parameters for transcription and degradation are lower than anticipated from a recent analytical time dependent model of in vivo mRNA production. Describing expression in terms of a simple chemical master equation, we show that the discrepancies are due to the lack of nonribosomal genes in the extended biogenesis model which effects the competition of mRNA for ribosome binding, and suggest corrections to parameters to be used in the whole-cell model when modeling expression of the entire transcriptome. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 735-751, 2016. © 2016 Wiley Periodicals, Inc.

New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.

PubMed

Tummler, Katja; Lubitz, Timo; Schelker, Max; Klipp, Edda

2014-01-01

Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms. © 2013 FEBS.

A hybrid parallel framework for the cellular Potts model simulations

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

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

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

A Whole Brain Staining, Embedding, and Clearing Pipeline for Adult Zebrafish to Visualize Cell Proliferation and Morphology in 3-Dimensions.

PubMed

Lindsey, Benjamin W; Douek, Alon M; Loosli, Felix; Kaslin, Jan

2017-01-01

The field of macro-imaging has grown considerably with the appearance of innovative clearing methods and confocal microscopes with lasers capable of penetrating increasing tissue depths. The ability to visualize and model the growth of whole organs as they develop from birth, or with manipulation, disease or injury, provides new ways of thinking about development, tissue-wide signaling, and cell-to-cell interactions. The zebrafish ( Danio rerio ) has ascended from a predominantly developmental model to a leading adult model of tissue regeneration. The unmatched neurogenic and regenerative capacity of the mature central nervous system, in particular, has received much attention, however tools to interrogate the adult brain are sparse. At present there exists no straightforward methods of visualizing changes in the whole adult brain in 3-dimensions (3-D) to examine systemic patterns of cell proliferation or cell populations of interest under physiological, injury, or diseased conditions. The method presented here is the first of its kind to offer an efficient step-by-step pipeline from intraperitoneal injections of the proliferative marker, 5-ethynyl-2'-deoxyuridine (EdU), to whole brain labeling, to a final embedded and cleared brain sample suitable for 3-D imaging using optical projection tomography (OPT). Moreover, this method allows potential for imaging GFP-reporter lines and cell-specific antibodies in the presence or absence of EdU. The small size of the adult zebrafish brain, the highly consistent degree of EdU labeling, and the use of basic clearing agents, benzyl benzoate, and benzyl alcohol, makes this method highly tractable for most laboratories interested in understanding the vertebrate central nervous system in health and disease. Post-processing of OPT-imaged adult zebrafish brains injected with EdU illustrate that proliferative patterns in EdU can readily be observed and analyzed using IMARIS and/or FIJI/IMAGEJ software. This protocol will be a valuable tool to unlock new ways of understanding systemic patterns in cell proliferation in the healthy and injured brain, brain-wide cellular interactions, stem cell niche development, and changes in brain morphology.

A Whole Brain Staining, Embedding, and Clearing Pipeline for Adult Zebrafish to Visualize Cell Proliferation and Morphology in 3-Dimensions

PubMed Central

Lindsey, Benjamin W.; Douek, Alon M.; Loosli, Felix; Kaslin, Jan

2018-01-01

The field of macro-imaging has grown considerably with the appearance of innovative clearing methods and confocal microscopes with lasers capable of penetrating increasing tissue depths. The ability to visualize and model the growth of whole organs as they develop from birth, or with manipulation, disease or injury, provides new ways of thinking about development, tissue-wide signaling, and cell-to-cell interactions. The zebrafish (Danio rerio) has ascended from a predominantly developmental model to a leading adult model of tissue regeneration. The unmatched neurogenic and regenerative capacity of the mature central nervous system, in particular, has received much attention, however tools to interrogate the adult brain are sparse. At present there exists no straightforward methods of visualizing changes in the whole adult brain in 3-dimensions (3-D) to examine systemic patterns of cell proliferation or cell populations of interest under physiological, injury, or diseased conditions. The method presented here is the first of its kind to offer an efficient step-by-step pipeline from intraperitoneal injections of the proliferative marker, 5-ethynyl-2′-deoxyuridine (EdU), to whole brain labeling, to a final embedded and cleared brain sample suitable for 3-D imaging using optical projection tomography (OPT). Moreover, this method allows potential for imaging GFP-reporter lines and cell-specific antibodies in the presence or absence of EdU. The small size of the adult zebrafish brain, the highly consistent degree of EdU labeling, and the use of basic clearing agents, benzyl benzoate, and benzyl alcohol, makes this method highly tractable for most laboratories interested in understanding the vertebrate central nervous system in health and disease. Post-processing of OPT-imaged adult zebrafish brains injected with EdU illustrate that proliferative patterns in EdU can readily be observed and analyzed using IMARIS and/or FIJI/IMAGEJ software. This protocol will be a valuable tool to unlock new ways of understanding systemic patterns in cell proliferation in the healthy and injured brain, brain-wide cellular interactions, stem cell niche development, and changes in brain morphology. PMID:29386991

Evaluation of 309 environmental chemicals using a mouse embryonic stem cell adherent cell differentiation and cytotoxicity assay

EPA Science Inventory

The vast landscape of environmental chemicals has motivated the need for alternative methods to traditional whole-animal bioassays in toxicity testing. Embryonic stem (ES) cells provide an in vitro model of embryonic development and an alternative method for assessing development...

Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection

PubMed Central

Su, Hai; Xing, Fuyong; Yang, Lin

2016-01-01

Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96. PMID:26812706

Accounting for cell lineage and sex effects in the identification of cell-specific DNA methylation using a Bayesian model selection algorithm.

PubMed

White, Nicole; Benton, Miles; Kennedy, Daniel; Fox, Andrew; Griffiths, Lyn; Lea, Rodney; Mengersen, Kerrie

2017-01-01

Cell- and sex-specific differences in DNA methylation are major sources of epigenetic variation in whole blood. Heterogeneity attributable to cell type has motivated the identification of cell-specific methylation at the CpG level, however statistical methods for this purpose have been limited to pairwise comparisons between cell types or between the cell type of interest and whole blood. We developed a Bayesian model selection algorithm for the identification of cell-specific methylation profiles that incorporates knowledge of shared cell lineage and allows for the identification of differential methylation profiles in one or more cell types simultaneously. Under the proposed methodology, sex-specific differences in methylation by cell type are also assessed. Using publicly available, cell-sorted methylation data, we show that 51.3% of female CpG markers and 61.4% of male CpG markers identified were associated with differential methylation in more than one cell type. The impact of cell lineage on differential methylation was also highlighted. An evaluation of sex-specific differences revealed differences in CD56+NK methylation, within both single and multi- cell dependent methylation patterns. Our findings demonstrate the need to account for cell lineage in studies of differential methylation and associated sex effects.

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

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

Smith, Daniel L.; Debeb, Bisrat G.; Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, Texas

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. Anmore » independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.« less

Density functional study on the structural and thermodynamic properties of aqueous DNA-electrolyte solution in the framework of cell model.

PubMed

Wang, Ke; Yu, Yang-Xin; Gao, Guang-Hua

2008-05-14

A density functional theory (DFT) in the framework of cell model is proposed to calculate the structural and thermodynamic properties of aqueous DNA-electrolyte solution with finite DNA concentrations. The hard-sphere contribution to the excess Helmholtz energy functional is derived from the modified fundamental measure theory, and the electrostatic interaction is evaluated through a quadratic functional Taylor expansion around a uniform fluid. The electroneutrality in the cell leads to a variational equation with a constraint. Since the reference fluid is selected to be a bulk phase, the Lagrange multiplier proves to be the potential drop across the cell boundary (Donnan potential). The ion profiles and electrostatic potential profiles in the cell are calculated from the present DFT-cell model. Our DFT-cell model gives better prediction of ion profiles than the Poisson-Boltzmann (PB)- or modified PB-cell models when compared to the molecular simulation data. The effects of polyelectrolyte concentration, ion size, and added-salt concentration on the electrostatic potential difference between the DNA surface and the cell boundary are investigated. The expression of osmotic coefficient is derived from the general formula of grand potential. The osmotic coefficients predicted by the DFT are lower than the PB results and are closer to the simulation results and experimental data.

Chemoprophylaxis with sporozoite immunization in P. knowlesi rhesus monkeys confers protection and elicits sporozoite-specific memory T cells in the liver

PubMed Central

Spring, Michele D.; Yongvanitchit, Kosol; Kum-Arb, Utaiwan; Limsalakpetch, Amporn; Im-Erbsin, Rawiwan; Ubalee, Ratawan; Vanachayangkul, Pattaraporn; Remarque, Edmond J.; Angov, Evelina; Smith, Philip L.; Saunders, David L.

2017-01-01

Whole malaria sporozoite vaccine regimens are promising new strategies, and some candidates have demonstrated high rates of durable clinical protection associated with memory T cell responses. Little is known about the anatomical distribution of memory T cells following whole sporozoite vaccines, and immunization of nonhuman primates can be used as a relevant model for humans. We conducted a chemoprophylaxis with sporozoite (CPS) immunization in P. knowlesi rhesus monkeys and challenged via mosquito bites. Half of CPS immunized animals developed complete protection, with a marked delay in parasitemia demonstrated in the other half. Antibody responses to whole sporozoites, CSP, and AMA1, but not CelTOS were detected. Peripheral blood T cell responses to whole sporozoites, but not CSP and AMA1 peptides were observed. Unlike peripheral blood, there was a high frequency of sporozoite-specific memory T cells observed in the liver and bone marrow. Interestingly, sporozoite-specific CD4+ and CD8+ memory T cells in the liver highly expressed chemokine receptors CCR5 and CXCR6, both of which are known for liver sinusoid homing. The majority of liver sporozoite-specific memory T cells expressed CD69, a phenotypic marker of tissue-resident memory (TRM) cells, which are well positioned to rapidly control liver-stage infection. Vaccine strategies that aim to elicit large number of liver TRM cells may efficiently increase the efficacy and durability of response against pre-erythrocytic parasites. PMID:28182750

Testing the Role of p21-Activated Kinases in Schwannoma Formation Using a Novel Genetically Engineered Murine Model that Closely Phenocopies Human NF2 Disease

DTIC Science & Technology

2015-06-01

preclinical models of NF1? Can whole kinome analysis predict pathways for drug resistance in treated mice? Procuring Contracting/Grants Officer: Emily...cells. b) Evaluate transduction of hydroxyethyl starch (HES)-processed hematopoietic cells. c) Monitor gene transfer in primary FANCC-/- progenitors

Limit of a nonpreferential attachment multitype network model

NASA Astrophysics Data System (ADS)

Shang, Yilun

2017-02-01

Here, we deal with a model of multitype network with nonpreferential attachment growth. The connection between two nodes depends asymmetrically on their types, reflecting the implication of time order in temporal networks. Based upon graph limit theory, we analytically determined the limit of the network model characterized by a kernel, in the sense that the number of copies of any fixed subgraph converges when network size tends to infinity. The results are confirmed by extensive simulations. Our work thus provides a theoretical framework for quantitatively understanding grown temporal complex networks as a whole.

Framework for cascade size calculations on random networks

NASA Astrophysics Data System (ADS)

Burkholz, Rebekka; Schweitzer, Frank

2018-04-01

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

Active immunotherapy for mouse breast cancer with irradiated whole-cell vaccine expressing VEGFR2.

PubMed

Yan, Heng-Xiu; Cheng, Ping; Wei, Hai-Yan; Shen, Guo-Bo; Fu, Li-Xin; Ni, Jie; Wu, Yang; Wei, Yu-Quan

2013-04-01

As tumor-associated antigens are not well characterized for the majority of human tumors, polyvalent vaccines prepared with whole-tumor antigens are an attractive approach for tumor vaccination. Vascular endothelial growth factor receptor-2 (VEGFR2), as a model antigen with which to explore the feasibility of immunotherapy, has shown great promise as a tumor vaccine. However, the efficacy of immunotherapy is often not ideal when used alone. In this study, we explored the therapeutic efficacy of an irradiated AdVEGFR2-infected cell vaccine-based immunotherapy in the weakly immunogenic and highly metastatic 4T1 murine mammary cancer model. An adenovirus encoding the VEGFR2 gene (AdVEGFR2) was constructed. Lethally irradiated, virus-infected 4T1 cells were used as vaccines. Vaccination with lethally irradiated AdVEGFR2-infected 4T1 cells inhibited subsequent tumor growth and pulmonary metastasis compared with challenge inoculations. Angiogenesis was inhibited, and the number of CD8+ T lymphocytes was increased within the tumors. Antitumor activity was also caused by the adoptive transfer of isolated spleen lymphocytes. In vitro, the expression of HMGB1 and HSP70 in the AdVEGFR2‑infected 4T1 cells was increased, and was involved in the activation of tumor antigen-specific T-cell immunity. Our results indicate that the immunotherapy based on irradiated AdVEGFR2-infected whole-cancer cell vaccines may be a potentially effective strategy for 4T1 cancer treatment.

Elementary Introduction to the Green Management of the Construction in Whole Process

NASA Astrophysics Data System (ADS)

Na), Wu Y. N.(Yun; Yu), Yan H. Y.(Hong; Jun), Huang Z. J.(Zhi

Construction industries consume more energy resources than necessary. it is essential to establish a management system with all pollution problems resolved to construct green buildings. By applying the theory of whole life cycle, this paper divides the whole process of construction into four sub-phases, which will also be subdivided into more concrete working procedures. Based on this, a systematic framework is promoted for the green management of the construction, especially and creatively, considering the green aims as important as the traditional three aims-"quality aim, schedule aim and cost aim". This framework, adhering to the integration idea-"customers first, whole optimal", regards the green control and workflow as an organic whole in order to build green, sustainable and healthy architecture, and then provide a perfect guide and reference to the green management.

On the causes and consequences of the uncoupler-like effects of quercetin and dehydrosilybin in H9c2 cells

PubMed Central

Mouithys-Mickalad, Ange; Dostal, Zdenek; Serteyn, Didier; Modriansky, Martin

2017-01-01

Quercetin and dehydrosilybin are polyphenols which are known to behave like uncouplers of respiration in isolated mitochondria. Here we investigated whether the effect is conserved in whole cells. Following short term incubation, neither compound uncouples mitochondrial respiration in whole H9c2 cells below 50μM. However, following hypoxia, or long term incubation, leak (state IV with oligomycin) oxygen consumption is increased by quercetin. Both compounds partially protected complex I respiration, but not complex II in H9c2 cells following hypoxia. In a permeabilised H9c2 cell model, the increase in leak respiration caused by quercetin is lowered by increased [ADP] and is increased by adenine nucleotide transporter inhibitor, atractyloside, but not bongkrekic acid. Both quercetin and dehydrosilybin dissipate mitochondrial membrane potential in whole cells. In the case of quercetin, the effect is potentiated post hypoxia. Genetically encoded Ca++ sensors, targeted to the mitochondria, enabled the use of fluorescence microscopy to show that quercetin decreased mitochondrial [Ca++] while dehydrosilybin did not. Likewise, quercetin decreases accumulation of [Ca++] in mitochondria following hypoxia. Fluorescent probes were used to show that both compounds decrease plasma membrane potential and increase cytosolic [Ca++]. We conclude that the uncoupler-like effects of these polyphenols are attenuated in whole cells compared to isolated mitochondria, but downstream effects are nevertheless apparent. Results suggest that the effect of quercetin observed in whole and permeabilised cells may originate in the mitochondria, while the mechanism of action of cardioprotection by dehydrosilybin may be less dependent on mitochondrial uncoupling than originally thought. Rather, protective effects may originate due to interactions at the plasma membrane. PMID:28977033

Systems biology of the structural proteome.

PubMed

Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan; Zhang, Zhen; O'Brien, Edward J; Bliven, Spencer E; Chen, Ke; Chang, Roger L; Bourne, Philip E; Palsson, Bernhard O

2016-03-11

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Selectivity in associative learning: a cognitive stage framework for blocking and cue competition phenomena

PubMed Central

Boddez, Yannick; Haesen, Kim; Baeyens, Frank; Beckers, Tom

2014-01-01

Blocking is the most important phenomenon in the history of associative learning theory: for over 40 years, blocking has inspired a whole generation of learning models. Blocking is part of a family of effects that are typically termed “cue competition” effects. Common amongst all cue competition effects is that a cue-outcome relation is poorly learned or poorly expressed because the cue is trained in the presence of an alternative predictor or cause of the outcome. We provide an overview of the cognitive processes involved in cue competition effects in humans and propose a stage framework that brings these processes together. The framework contends that the behavioral display of cue competition is cognitively construed following three stages that include (1) an encoding stage, (2) a retention stage, and (3) a performance stage. We argue that the stage framework supports a comprehensive understanding of cue competition effects. PMID:25429280

Mathematical model formulation and validation of water and solute transport in whole hamster pancreatic islets.

PubMed

Benson, James D; Benson, Charles T; Critser, John K

2014-08-01

Optimization of cryopreservation protocols for cells and tissues requires accurate models of heat and mass transport. Model selection often depends on the configuration of the tissue. Here, a mathematical and conceptual model of water and solute transport for whole hamster pancreatic islets has been developed and experimentally validated incorporating fundamental biophysical data from previous studies on individual hamster islet cells while retaining whole-islet structural information. It describes coupled transport of water and solutes through the islet by three methods: intracellularly, intercellularly, and in combination. In particular we use domain decomposition techniques to couple a transmembrane flux model with an interstitial mass transfer model. The only significant undetermined variable is the cellular surface area which is in contact with the intercellularly transported solutes, Ais. The model was validated and Ais determined using a 3×3 factorial experimental design blocked for experimental day. Whole islet physical experiments were compared with model predictions at three temperatures, three perfusing solutions, and three islet size groups. A mean of 4.4 islets were compared at each of the 27 experimental conditions and found to correlate with a coefficient of determination of 0.87±0.06 (mean ± SD). Only the treatment variable of perfusing solution was found to be significant (p<0.05). We have devised a model that retains much of the intrinsic geometric configuration of the system, and thus fewer laboratory experiments are needed to determine model parameters and thus to develop new optimized cryopreservation protocols. Additionally, extensions to ovarian follicles and other concentric tissue structures may be made. Copyright © 2014 Elsevier Inc. All rights reserved.

A Computational Framework for 3D Mechanical Modeling of Plant Morphogenesis with Cellular Resolution

PubMed Central

Gilles, Benjamin; Hamant, Olivier; Boudaoud, Arezki; Traas, Jan; Godin, Christophe

2015-01-01

The link between genetic regulation and the definition of form and size during morphogenesis remains largely an open question in both plant and animal biology. This is partially due to the complexity of the process, involving extensive molecular networks, multiple feedbacks between different scales of organization and physical forces operating at multiple levels. Here we present a conceptual and modeling framework aimed at generating an integrated understanding of morphogenesis in plants. This framework is based on the biophysical properties of plant cells, which are under high internal turgor pressure, and are prevented from bursting because of the presence of a rigid cell wall. To control cell growth, the underlying molecular networks must interfere locally with the elastic and/or plastic extensibility of this cell wall. We present a model in the form of a three dimensional (3D) virtual tissue, where growth depends on the local modulation of wall mechanical properties and turgor pressure. The model shows how forces generated by turgor-pressure can act both cell autonomously and non-cell autonomously to drive growth in different directions. We use simulations to explore lateral organ formation at the shoot apical meristem. Although different scenarios lead to similar shape changes, they are not equivalent and lead to different, testable predictions regarding the mechanical and geometrical properties of the growing lateral organs. Using flower development as an example, we further show how a limited number of gene activities can explain the complex shape changes that accompany organ outgrowth. PMID:25569615

Voxel2MCNP: a framework for modeling, simulation and evaluation of radiation transport scenarios for Monte Carlo codes.

PubMed

Pölz, Stefan; Laubersheimer, Sven; Eberhardt, Jakob S; Harrendorf, Marco A; Keck, Thomas; Benzler, Andreas; Breustedt, Bastian

2013-08-21

The basic idea of Voxel2MCNP is to provide a framework supporting users in modeling radiation transport scenarios using voxel phantoms and other geometric models, generating corresponding input for the Monte Carlo code MCNPX, and evaluating simulation output. Applications at Karlsruhe Institute of Technology are primarily whole and partial body counter calibration and calculation of dose conversion coefficients. A new generic data model describing data related to radiation transport, including phantom and detector geometries and their properties, sources, tallies and materials, has been developed. It is modular and generally independent of the targeted Monte Carlo code. The data model has been implemented as an XML-based file format to facilitate data exchange, and integrated with Voxel2MCNP to provide a common interface for modeling, visualization, and evaluation of data. Also, extensions to allow compatibility with several file formats, such as ENSDF for nuclear structure properties and radioactive decay data, SimpleGeo for solid geometry modeling, ImageJ for voxel lattices, and MCNPX's MCTAL for simulation results have been added. The framework is presented and discussed in this paper and example workflows for body counter calibration and calculation of dose conversion coefficients is given to illustrate its application.

Compensation for Lithography Induced Process Variations during Physical Design

NASA Astrophysics Data System (ADS)

Chin, Eric Yiow-Bing

This dissertation addresses the challenge of designing robust integrated circuits in the deep sub micron regime in the presence of lithography process variability. By extending and combining existing process and circuit analysis techniques, flexible software frameworks are developed to provide detailed studies of circuit performance in the presence of lithography variations such as focus and exposure. Applications of these software frameworks to select circuits demonstrate the electrical impact of these variations and provide insight into variability aware compact models that capture the process dependent circuit behavior. These variability aware timing models abstract lithography variability from the process level to the circuit level and are used to estimate path level circuit performance with high accuracy with very little overhead in runtime. The Interconnect Variability Characterization (IVC) framework maps lithography induced geometrical variations at the interconnect level to electrical delay variations. This framework is applied to one dimensional repeater circuits patterned with both 90nm single patterning and 32nm double patterning technologies, under the presence of focus, exposure, and overlay variability. Studies indicate that single and double patterning layouts generally exhibit small variations in delay (between 1--3%) due to self compensating RC effects associated with dense layouts and overlay errors for layouts without self-compensating RC effects. The delay response of each double patterned interconnect structure is fit with a second order polynomial model with focus, exposure, and misalignment parameters with 12 coefficients and residuals of less than 0.1ps. The IVC framework is also applied to a repeater circuit with cascaded interconnect structures to emulate more complex layout scenarios, and it is observed that the variations on each segment average out to reduce the overall delay variation. The Standard Cell Variability Characterization (SCVC) framework advances existing layout-level lithography aware circuit analysis by extending it to cell-level applications utilizing a physically accurate approach that integrates process simulation, compact transistor models, and circuit simulation to characterize electrical cell behavior. This framework is applied to combinational and sequential cells in the Nangate 45nm Open Cell Library, and the timing response of these cells to lithography focus and exposure variations demonstrate Bossung like behavior. This behavior permits the process parameter dependent response to be captured in a nine term variability aware compact model based on Bossung fitting equations. For a two input NAND gate, the variability aware compact model captures the simulated response to an accuracy of 0.3%. The SCVC framework is also applied to investigate advanced process effects including misalignment and layout proximity. The abstraction of process variability from the layout level to the cell level opens up an entire new realm of circuit analysis and optimization and provides a foundation for path level variability analysis without the computationally expensive costs associated with joint process and circuit simulation. The SCVC framework is used with slight modification to illustrate the speedup and accuracy tradeoffs of using compact models. With variability aware compact models, the process dependent performance of a three stage logic circuit can be estimated to an accuracy of 0.7% with a speedup of over 50,000. Path level variability analysis also provides an accurate estimate (within 1%) of ring oscillator period in well under a second. Another significant advantage of variability aware compact models is that they can be easily incorporated into existing design methodologies for design optimization. This is demonstrated by applying cell swapping on a logic circuit to reduce the overall delay variability along a circuit path. By including these variability aware compact models in cell characterization libraries, design metrics such as circuit timing, power, area, and delay variability can be quickly assessed to optimize for the correct balance of all design metrics, including delay variability. Deterministic lithography variations can be easily captured using the variability aware compact models described in this dissertation. However, another prominent source of variability is random dopant fluctuations, which affect transistor threshold voltage and in turn circuit performance. The SCVC framework is utilized to investigate the interactions between deterministic lithography variations and random dopant fluctuations. Monte Carlo studies show that the output delay distribution in the presence of random dopant fluctuations is dependent on lithography focus and exposure conditions, with a 3.6 ps change in standard deviation across the focus exposure process window. This indicates that the electrical impact of random variations is dependent on systematic lithography variations, and this dependency should be included for precise analysis.

Diffuse large B-cell lymphoma patient-derived xenograft models capture the molecular and biological heterogeneity of the disease.

PubMed

Chapuy, Bjoern; Cheng, Hongwei; Watahiki, Akira; Ducar, Matthew D; Tan, Yuxiang; Chen, Linfeng; Roemer, Margaretha G M; Ouyang, Jing; Christie, Amanda L; Zhang, Liye; Gusenleitner, Daniel; Abo, Ryan P; Farinha, Pedro; von Bonin, Frederike; Thorner, Aaron R; Sun, Heather H; Gascoyne, Randy D; Pinkus, Geraldine S; van Hummelen, Paul; Wulf, Gerald G; Aster, Jon C; Weinstock, David M; Monti, Stefano; Rodig, Scott J; Wang, Yuzhuo; Shipp, Margaret A

2016-05-05

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined by transcriptional classifications, specific signaling and survival pathways, and multiple low-frequency genetic alterations. Preclinical model systems that capture the genetic and functional heterogeneity of DLBCL are urgently needed. Here, we generated and characterized a panel of large B-cell lymphoma (LBCL) patient-derived xenograft (PDX) models, including 8 that reflect the immunophenotypic, transcriptional, genetic, and functional heterogeneity of primary DLBCL and 1 that is a plasmablastic lymphoma. All LBCL PDX models were subjected to whole-transcriptome sequencing to classify cell of origin and consensus clustering classification (CCC) subtypes. Mutations and chromosomal rearrangements were evaluated by whole-exome sequencing with an extended bait set. Six of the 8 DLBCL models were activated B-cell (ABC)-type tumors that exhibited ABC-associated mutations such as MYD88, CD79B, CARD11, and PIM1. The remaining 2 DLBCL models were germinal B-cell type, with characteristic alterations of GNA13, CREBBP, and EZH2, and chromosomal translocations involving IgH and either BCL2 or MYC Only 25% of the DLBCL PDX models harbored inactivating TP53 mutations, whereas 75% exhibited copy number alterations of TP53 or its upstream modifier, CDKN2A, consistent with the reported incidence and type of p53 pathway alterations in primary DLBCL. By CCC criteria, 6 of 8 DLBCL PDX models were B-cell receptor (BCR)-type tumors that exhibited selective surface immunoglobulin expression and sensitivity to entospletinib, a recently developed spleen tyrosine kinase inhibitor. In summary, we have established and characterized faithful PDX models of DLBCL and demonstrated their usefulness in functional analyses of proximal BCR pathway inhibition. © 2016 by The American Society of Hematology.

Quantitative impact of small angle forward scatter on whole blood oximetry using a Beer-Lambert absorbance model.

PubMed

LeBlanc, Serge Emile; Atanya, Monica; Burns, Kevin; Munger, Rejean

2011-04-21

It is well known that red blood cell scattering has an impact on whole blood oximetry as well as in vivo retinal oxygen saturation measurements. The goal of this study was to quantify the impact of small angle forward scatter on whole blood oximetry for scattering angles found in retinal oximetry light paths. Transmittance spectra of whole blood were measured in two different experimental setups: one that included small angle scatter in the transmitted signal and one that measured the transmitted signal only, at absorbance path lengths of 25, 50, 100, 250 and 500 µm. Oxygen saturation was determined by multiple linear regression in the 520-600 nm wavelength range and compared between path lengths and experimental setups. Mean calculated oxygen saturation differences between setups were greater than 10% at every absorbance path length. The deviations to the Beer-Lambert absorbance model had different spectral dependences between experimental setups, with the highest deviations found in the 520-540 nm range when scatter was added to the transmitted signal. These results are consistent with other models of forward scatter that predict different spectral dependences of the red blood cell scattering cross-section and haemoglobin extinction coefficients in this wavelength range.

Whole-Mount Adult Ear Skin Imaging Reveals Defective Neuro-Vascular Branching Morphogenesis in Obese and Type 2 Diabetic Mouse Models.

PubMed

Yamazaki, Tomoko; Li, Wenling; Yang, Ling; Li, Ping; Cao, Haiming; Motegi, Sei-Ichiro; Udey, Mark C; Bernhard, Elise; Nakamura, Takahisa; Mukouyama, Yoh-Suke

2018-01-11

Obesity and type 2 diabetes are frequently associated with peripheral neuropathy. Though there are multiple methods for diagnosis and analysis of morphological changes of peripheral nerves and blood vessels, three-dimensional high-resolution imaging is necessary to appreciate the pathogenesis with an anatomically recognizable branching morphogenesis and patterning. Here we established a novel technique for whole-mount imaging of adult mouse ear skin to visualize branching morphogenesis and patterning of peripheral nerves and blood vessels. Whole-mount immunostaining of adult mouse ear skin showed that peripheral sensory and sympathetic nerves align with large-diameter blood vessels. Diet-induced obesity (DIO) mice exhibit defective vascular smooth muscle cells (VSMCs) coverage, while there is no significant change in the amount of peripheral nerves. The leptin receptor-deficient db/db mice, a severe obese and type 2 diabetic mouse model, exhibit defective VSMC coverage and a large increase in the amount of smaller-diameter nerve bundles with myelin sheath and unmyelinated nerve fibers. Interestingly, an increase in the amount of myeloid immune cells was observed in the DIO but not db/db mouse skin. These data suggest that our whole-mount imaging method enables us to investigate the neuro-vascular and neuro-immune phenotypes in the animal models of obesity and diabetes.

Transdimensional Seismic Tomography

NASA Astrophysics Data System (ADS)

Bodin, T.; Sambridge, M.

2009-12-01

In seismic imaging the degree of model complexity is usually determined by manually tuning damping parameters within a fixed parameterization chosen in advance. Here we present an alternative methodology for seismic travel time tomography where the model complexity is controlled automatically by the data. In particular we use a variable parametrization consisting of Voronoi cells with mobile geometry, shape and number, all treated as unknowns in the inversion. The reversible jump algorithm is used to sample the transdimensional model space within a Bayesian framework which avoids global damping procedures and the need to tune regularisation parameters. The method is an ensemble inference approach, as many potential solutions are generated with variable numbers of cells. Information is extracted from the ensemble as a whole by performing Monte Carlo integration to produce the expected Earth model. The ensemble of models can also be used to produce velocity uncertainty estimates and experiments with synthetic data suggest they represent actual uncertainty surprisingly well. In a transdimensional approach, the level of data uncertainty directly determines the model complexity needed to satisfy the data. Intriguingly, the Bayesian formulation can be extended to the case where data uncertainty is also uncertain. Experiments show that it is possible to recover data noise estimate while at the same time controlling model complexity in an automated fashion. The method is tested on synthetic data in a 2-D application and compared with a more standard matrix based inversion scheme. The method has also been applied to real data obtained from cross correlation of ambient noise where little is known about the size of the errors associated with the travel times. As an example, a tomographic image of Rayleigh wave group velocity for the Australian continent is constructed for 5s data together with uncertainty estimates.

The practice of quality-associated costing: application to transfusion manufacturing processes.

PubMed

Trenchard, P M; Dixon, R

1997-01-01

This article applies the new method of quality-associated costing (QAC) to the mixture of processes that create red cell and plasma products from whole blood donations. The article compares QAC with two commonly encountered but arbitrary models and illustrates the invalidity of clinical cost-benefit analysis based on these models. The first, an "isolated" cost model, seeks to allocate each whole process cost to only one product class. The other is a "shared" cost model, and it seeks to allocate an approximately equal share of all process costs to all associated products.

Computational model of chromosome aberration yield induced by high- and low-LET radiation exposures.

PubMed

Ponomarev, Artem L; George, Kerry; Cucinotta, Francis A

2012-06-01

We present a computational model for calculating the yield of radiation-induced chromosomal aberrations in human cells based on a stochastic Monte Carlo approach and calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. A previously developed DNA-fragmentation model for high- and low-LET radiation called the NASARadiationTrackImage model was enhanced to simulate a stochastic process of the formation of chromosomal aberrations from DNA fragments. The current version of the model gives predictions of the yields and sizes of translocations, dicentrics, rings, and more complex-type aberrations formed in the G(0)/G(1) cell cycle phase during the first cell division after irradiation. As the model can predict smaller-sized deletions and rings (<3 Mbp) that are below the resolution limits of current cytogenetic analysis techniques, we present predictions of hypothesized small deletions that may be produced as a byproduct of properly repaired DNA double-strand breaks (DSB) by nonhomologous end-joining. Additionally, the model was used to scale chromosomal exchanges in two or three chromosomes that were obtained from whole-chromosome FISH painting analysis techniques to whole-genome equivalent values.

Lessons in Building Capacity in Sexuality Education Using the Health Promoting School Framework: From Planning to Implementation

ERIC Educational Resources Information Center

Ollis, Debbie; Harrison, Lyn

2016-01-01

Purpose: The health promoting school model is rarely implemented in relation to sexuality education. This paper reports on data collected as part of a five-year project designed to implement a health promoting and whole school approach to sexuality education in a five campus year 1-12 college in regional Victoria, Australia. Using a community…

Bridging American Indian Culture and the New Science Paradigm. Science of Alcohol Curriculum for American Indians. Training Unit [and] Participant Booklet.

ERIC Educational Resources Information Center

Jacobs, Cecelia; Smiley-Marquez, Carolyna

People generally learn best when information is presented to them in a culturally and socially relevant context or framework. This issue is addressed by the Science of Alcohol Curriculum for American Indians through the use of the Medicine Circle, a model that represents the concepts of wholeness, interconnectedness, and balance in a manner…

Whole-mount Confocal Microscopy for Adult Ear Skin: A Model System to Study Neuro-vascular Branching Morphogenesis and Immune Cell Distribution.

PubMed

Yamazaki, Tomoko; Li, Wenling; Mukouyama, Yoh-Suke

2018-03-29

Here, we present a protocol of a whole-mount adult ear skin imaging technique to study comprehensive three-dimensional neuro-vascular branching morphogenesis and patterning, as well as immune cell distribution at a cellular level. The analysis of peripheral nerve and blood vessel anatomical structures in adult tissues provides some insights into the understanding of functional neuro-vascular wiring and neuro-vascular degeneration in pathological conditions such as wound healing. As a highly informative model system, we have focused our studies on adult ear skin, which is readily accessible for dissection. Our simple and reproducible protocol provides an accurate depiction of the cellular components in the entire skin, such as peripheral nerves (sensory axons, sympathetic axons, and Schwann cells), blood vessels (endothelial cells and vascular smooth muscle cells), and inflammatory cells. We believe this protocol will pave the way to investigate morphological abnormalities in peripheral nerves and blood vessels as well as the inflammation in the adult ear skin under different pathological conditions.

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis shows that terrestrial carbon and water cycle simulations in monsoon Asia were greatly improved, and the use of multiple satellite observations with this framework is an effective way for improving terrestrial biosphere models.

Simulation of Blast Loading on an Ultrastructurally-based Computational Model of the Ocular Lens

DTIC Science & Technology

2016-12-01

organelles. Additionally, the cell membranes demonstrated the classic ball-and-socket loops . For the SEM images, they were placed in two fixatives and mounted...considered (fibrous network and matrix), both components are modelled using a hyper - elastic framework, and the resulting constitutive model is embedded in a...within the framework of hyper - elasticity). Full details on the linearization procedures that were adopted in these previous models or the convergence

Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

PubMed

Başar, Erol

2005-01-01

According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

Sovereign Challenge Conference (6th). Borders & Security: Similarities, Differences and Shared Affinities. Held in El Paso, Texas on November 7-10, 2010

DTIC Science & Technology

2010-11-01

protection and to isolate threats in order to survive and develop. The cell model implies osmosis , allowing flows to take place across the borders and the...relationships to new levels, much as cell phone technology replaces the laying of copper wire for traditional telephone service. Whole-of-Government/Whole...in urban, rural, and remote environments. This practical experience with the men and women of the U.S. Border Patrol animated many of the concepts

Immunoreactive Coxiella burnetii Nine Mile proteins separated by 2D electrophoresis and identified by tandem mass spectrometry

PubMed Central

Deringer, James R.; Chen, Chen; Samuel, James E.; Brown, Wendy C.

2011-01-01

Coxiella burnetii is a Gram-negative obligate intracellular pathogen and the causative agent of Q fever in humans. Q fever causes acute flu-like symptoms and may develop into a chronic disease leading to endocarditis. Its potential as a bioweapon has led to its classification as a category B select agent. An effective inactivated whole-cell vaccine (WCV) currently exists but causes severe granulomatous/necrotizing reactions in individuals with prior exposure, and is not licensed for use in most countries. Current efforts to reduce or eliminate the deleterious reactions associated with WCVs have focused on identifying potential subunit vaccine candidates. Both humoral and T cell-mediated responses are required for protection in animal models. In this study, nine novel immunogenic C. burnetii proteins were identified in extracted whole-cell lysates using 2D electrophoresis, immunoblotting with immune guinea pig sera, and tandem MS. The immunogenic C. burnetii proteins elicited antigen-specific IgG in guinea pigs vaccinated with whole-cell killed Nine Mile phase I vaccine, suggesting a T cell-dependent response. Eleven additional proteins previously shown to react with immune human sera were also antigenic in guinea pigs, showing the relevance of the guinea pig immunization model for antigen discovery. The antigens described here warrant further investigation to validate their potential use as subunit vaccine candidates. PMID:21030434

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Treesearch

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia Wang

2014-01-01

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

Distinct embryotoxic effects of lithium appeared in a new assessment model of the sea urchin: the whole embryo assay and the blastomere culture assay.

PubMed

Kiyomoto, Masato; Morinaga, Seiko; Ooi, Nagisa

2010-03-01

Early embryogenesis is one of the most sensitive and critical stages in animal development. Here we propose a new assessment model on the effect of pollutant to multicellular organism development. That is a comparison between the whole embryo assay and the blastomere culture assay. We examined the LiCl effect on the sea urchin early development in both of whole embryos and the culture of isolated blastomeres. The mesoderm and endoderm region were capable to differentiate into skeletogenic cells when they were isolated at 60-cell stage and cultured in vitro. The embryo developed to exogastrula by the vegetalizing effect of the same LiCl condition where ectodermal region changed their fate to endoderm, while the isolated blastomeres from the presumptive ectoderm region differentiated into skeletogenic cells in the culture with LiCl. The effect of LiCl to the sea urchin embryo and to the dissociated blastomere is a unique example where same cells response distinctly to the same agent depend on the condition around them. Present results show the importance of examining the process in cellular and tissue levels for the exact understanding on the morphological effect of chemicals and metals.

Comparative proteomics analysis of oral cancer cell lines: identification of cancer associated proteins

PubMed Central

2014-01-01

Background A limiting factor in performing proteomics analysis on cancerous cells is the difficulty in obtaining sufficient amounts of starting material. Cell lines can be used as a simplified model system for studying changes that accompany tumorigenesis. This study used two-dimensional gel electrophoresis (2DE) to compare the whole cell proteome of oral cancer cell lines vs normal cells in an attempt to identify cancer associated proteins. Results Three primary cell cultures of normal cells with a limited lifespan without hTERT immortalization have been successfully established. 2DE was used to compare the whole cell proteome of these cells with that of three oral cancer cell lines. Twenty four protein spots were found to have changed in abundance. MALDI TOF/TOF was then used to determine the identity of these proteins. Identified proteins were classified into seven functional categories – structural proteins, enzymes, regulatory proteins, chaperones and others. IPA core analysis predicted that 18 proteins were related to cancer with involvements in hyperplasia, metastasis, invasion, growth and tumorigenesis. The mRNA expressions of two proteins – 14-3-3 protein sigma and Stress-induced-phosphoprotein 1 – were found to correlate with the corresponding proteins’ abundance. Conclusions The outcome of this analysis demonstrated that a comparative study of whole cell proteome of cancer versus normal cell lines can be used to identify cancer associated proteins. PMID:24422745

Transcutaneous photodynamic therapy delays the onset of paralysis in a murine multiple sclerosis model

NASA Astrophysics Data System (ADS)

Hunt, David W. C.; Leong, Simon; Levy, Julia G.; Chan, Agnes H.

1995-03-01

Photodynamic therapy (PDT) using benzoporphyrin derivative (BPD, Verteporfin) and whole body irradiation, can affect the course of adoptively transferred experimental allergic (autoimmune) encephalomyelitis (EAE) in PL mice. Murine EAE is a T cell-mediated autoimmune disease which serves as a model for human multiple sclerosis. Using a novel disease induction protocol, we found that mice characteristically developed EAE within 3 weeks of receipt of myelin basic protein (MBP)-sensitized, in vitro-cultured spleen or lymph node cells. However, if animals were treated with PDT (1 mg BPD/kg bodyweight and exposed to whole body 15 Joules cm2 of LED light) 24 hours after receiving these cells, disease onset time was significantly delayed. PDT-treated mice developed disease symptoms 45 +/- 3 days following cell administration whereas untreated controls were affected within 23 +/- 2 days. In contrast, application of PDT 48 or 120 hours following injection of the pathogenic cells had no significant effect upon the development of EAE. Experiments are in progress to account for the protective effect of PDT in this animal model. These studies should provide evidence on the feasibility of PDT as a treatment for human autoimmune disease.

Microfluidic devices for label-free separation of cells through transient interaction with asymmetric receptor patterns

NASA Astrophysics Data System (ADS)

Bose, S.; Singh, R.; Hollatz, M. H.; Lee, C.-H.; Karp, J.; Karnik, R.

2012-02-01

Cell sorting serves an important role in clinical diagnosis and biological research. Most of the existing microscale sorting techniques are either non-specific to antigen type or rely on capturing cells making sample recovery difficult. We demonstrate a simple; yet effective technique for isolating cells in an antigen specific manner by using transient interactions of the cell surface antigens with asymmetric receptor patterned surface. Using microfluidic devices incorporating P-selectin patterns we demonstrate separation of HL60 cells from K562 cells. We achieved a sorting purity above 90% and efficiency greater than 85% with this system. We also present a mathematical model incorporating flow mediated and adhesion mediated transport of cells in the microchannel that can be used to predict the performance of these devices. Lastly, we demonstrate the clinical significance of the method by demonstrating single step separation of neutrophils from whole blood. When whole blood is introduced in the device, the granulocyte population gets separated exclusively yielding neutrophils of high purity (<10% RBC contamination). To our knowledge, this is the first ever demonstration of continuous label free sorting of neutrophils from whole blood. We believe this technology will be useful in developing point-of-care diagnostic devices and also for a host of cell sorting applications.

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

PubMed Central

Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad

2017-01-01

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001 PMID:28296635

Multiscale smeared finite element model for mass transport in biological tissue: From blood vessels to cells and cellular organelles.

PubMed

Kojic, M; Milosevic, M; Simic, V; Koay, E J; Kojic, N; Ziemys, A; Ferrari, M

2018-05-21

One of the basic and vital processes in living organisms is mass exchange, which occurs on several levels: it goes from blood vessels to cells and organelles within cells. On that path, molecules, as oxygen, metabolic products, drugs, etc. Traverse different macro and micro environments - blood, extracellular/intracellular space, and interior of organelles; and also biological barriers such as walls of blood vessels and membranes of cells and organelles. Many aspects of this mass transport remain unknown, particularly the biophysical mechanisms governing drug delivery. The main research approach relies on laboratory and clinical investigations. In parallel, considerable efforts have been directed to develop computational tools for additional insight into the intricate process of mass exchange and transport. Along these lines, we have recently formulated a composite smeared finite element (CSFE) which is composed of the smeared continuum pressure and concentration fields of the capillary and lymphatic system, and of these fields within tissue. The element offers an elegant and simple procedure which opens up new lines of inquiry and can be applied to large systems such as organs and tumors models. Here, we extend this concept to a multiscale scheme which concurrently couples domains that span from large blood vessels, capillaries and lymph, to cell cytosol and further to organelles of nanometer size. These spatial physical domains are coupled by the appropriate connectivity elements representing biological barriers. The composite finite element has "degrees of freedom" which include pressures and concentrations of all compartments of the vessels-tissue assemblage. The overall model uses the standard, measurable material properties of the continuum biological environments and biological barriers. It can be considered as a framework into which we can incorporate various additional effects (such as electrical or biochemical) for transport through membranes or within cells. This concept and the developed FE software within our package PAK offers a computational tool that can be applied to whole-organ systems, while also including specific domains such as tumors. The solved examples demonstrate the accuracy of this model and its applicability to large biological systems. Copyright © 2018. Published by Elsevier Ltd.

Micro-scale blood particulate dynamics using a non-uniform rational B-spline-based isogeometric analysis.

PubMed

Chivukula, V; Mousel, J; Lu, J; Vigmostad, S

2014-12-01

The current research presents a novel method in which blood particulates - biconcave red blood cells (RBCs) and spherical cells are modeled using isogeometric analysis, specifically Non-Uniform Rational B-Splines (NURBS) in 3-D. The use of NURBS ensures that even with a coarse representation, the geometry of the blood particulates maintains an accurate description when subjected to large deformations. The fundamental advantage of this method is the coupling of the geometrical description and the stress analysis of the cell membrane into a single, unified framework. Details on the modeling approach, implementation of boundary conditions and the membrane mechanics analysis using isogeometric modeling are presented, along with validation cases for spherical and biconcave cells. Using NURBS - based isogeometric analysis, the behavior of individual cells in fluid flow is presented and analyzed in different flow regimes using as few as 176 elements for a spherical cell and 220 elements for a biconcave RBC. This work provides a framework for modeling a large number of 3-D deformable biological cells, each with its own geometric description and membrane properties. To the best knowledge of the authors, this is the first application of the NURBS - based isogeometric analysis to model and simulate blood particulates in flow in 3D. Copyright © 2014 John Wiley & Sons, Ltd.

SPH simulations of WBC adhesion to the endothelium: the role of haemodynamics and endothelial binding kinetics.

PubMed

Gholami, Babak; Comerford, Andrew; Ellero, Marco

2015-11-01

A multiscale Lagrangian particle solver introduced in our previous work is extended to model physiologically realistic near-wall cell dynamics. Three-dimensional simulation of particle trajectories is combined with realistic receptor-ligand adhesion behaviour to cover full cell interactions in the vicinity of the endothelium. The selected stochastic adhesion model, which is based on a Monte Carlo acceptance-rejection method, fits in our Lagrangian framework and does not compromise performance. Additionally, appropriate inflow/outflow boundary conditions are implemented for our SPH solver to enable realistic pulsatile flow simulation. The model is tested against in-vitro data from a 3D geometry with a stenosis and sudden expansion. In both steady and pulsatile flow conditions, results show close agreement with the experimental ones. Furthermore we demonstrate, in agreement with experimental observations, that haemodynamics alone does not account for adhesion of white blood cells, in this case U937 monocytic human cells. Our findings suggest that the current framework is fully capable of modelling cell dynamics in large arteries in a realistic and efficient manner.

Myxobacteria Fruiting Body Formation

NASA Astrophysics Data System (ADS)

Jiang, Yi

2006-03-01

Myxobacteria are social bacteria that swarm and glide on surfaces, and feed cooperatively. When starved, tens of thousands of cells change their movement pattern from outward spreading to inward concentration; they form aggregates that become fruiting bodies, inside which cells differentiate into nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis, a long-range cell interaction mediated by diffusing chemicals. However, myxobacteria aggregation is the consequence of direct cell-contact interactions. I will review our recent efforts in modeling the fruiting body formation of Myxobacteria, using lattice gas cellular automata models that are based on local cell-cell contact signaling. These models have reproduced the individual phases in Myxobacteria development such as the rippling, streaming, early aggregation and the final sporulation; the models can be unified to simulate the whole developmental process of Myxobacteria.

A proposed analytic framework for determining the impact of an antimicrobial resistance intervention.

PubMed

Grohn, Yrjo T; Carson, Carolee; Lanzas, Cristina; Pullum, Laura; Stanhope, Michael; Volkova, Victoriya

2017-06-01

Antimicrobial use (AMU) is increasingly threatened by antimicrobial resistance (AMR). The FDA is implementing risk mitigation measures promoting prudent AMU in food animals. Their evaluation is crucial: the AMU/AMR relationship is complex; a suitable framework to analyze interventions is unavailable. Systems science analysis, depicting variables and their associations, would help integrate mathematics/epidemiology to evaluate the relationship. This would identify informative data and models to evaluate interventions. This National Institute for Mathematical and Biological Synthesis AMR Working Group's report proposes a system framework to address the methodological gap linking livestock AMU and AMR in foodborne bacteria. It could evaluate how AMU (and interventions) impact AMR. We will evaluate pharmacokinetic/dynamic modeling techniques for projecting AMR selection pressure on enteric bacteria. We study two methods to model phenotypic AMR changes in bacteria in the food supply and evolutionary genotypic analyses determining molecular changes in phenotypic AMR. Systems science analysis integrates the methods, showing how resistance in the food supply is explained by AMU and concurrent factors influencing the whole system. This process is updated with data and techniques to improve prediction and inform improvements for AMU/AMR surveillance. Our proposed framework reflects both the AMR system's complexity, and desire for simple, reliable conclusions.

Modelling and simulation of thermal behaviour of vanadium redox flow battery

NASA Astrophysics Data System (ADS)

Yan, Yitao; Li, Yifeng; Skyllas-Kazacos, Maria; Bao, Jie

2016-08-01

This paper extends previous thermal models of the vanadium redox flow battery to predict temperature profiles within multi-cell stacks. This involves modelling the thermal characteristics of the stack as a whole to modelling each individual cell. The study investigates the thermal behaviour for two different scenarios: during standby periods when the pumps are turned off, and in a residential power arbitrage scenario for two types of membranes. It was found that the temperature gradient across the cells is most significant during the standby case, with the simulation results showing completely different thermal behaviours between the two systems.

Potent Innate Immune Response to Pathogenic Leptospira in Human Whole Blood

PubMed Central

Hartskeerl, Rudy A.; van Gorp, Eric C. M.; Schuller, Simone; Monahan, Avril M.; Nally, Jarlath E.; van der Poll, Tom; van 't Veer, Cornelis

2011-01-01

Background Leptospirosis is caused by pathogenic spirochetes of the genus Leptospira. The bacteria enter the human body via abraded skin or mucous membranes and may disseminate throughout. In general the clinical picture is mild but some patients develop rapidly progressive, severe disease with a high case fatality rate. Not much is known about the innate immune response to leptospires during haematogenous dissemination. Previous work showed that a human THP-1 cell line recognized heat-killed leptospires and leptospiral LPS through TLR2 instead of TLR4. The LPS of virulent leptospires displayed a lower potency to trigger TNF production by THP-1 cells compared to LPS of non-virulent leptospires. Methodology/Principal Findings We investigated the host response and killing of virulent and non-virulent Leptospira of different serovars by human THP-1 cells, human PBMC's and human whole blood. Virulence of each leptospiral strain was tested in a well accepted standard guinea pig model. Virulent leptospires displayed complement resistance in human serum and whole blood while in-vitro attenuated non-virulent leptospires were rapidly killed in a complement dependent manner. In vitro stimulation of THP-1 and PBMC's with heat-killed and living leptospires showed differential serovar and cell type dependence of cytokine induction. However, at low, physiological, leptospiral dose, living virulent complement resistant strains were consistently more potent in whole blood stimulations than the corresponding non-virulent complement sensitive strains. At higher dose living virulent and non-virulent leptospires were equipotent in whole blood. Inhibition of different TLRs indicated that both TLR2 and TLR4 as well as TLR5 play a role in the whole blood cytokine response to living leptospires. Conclusions/Significance Thus, in a minimally altered system as human whole blood, highly virulent Leptospira are potent inducers of the cytokine response. PMID:21483834

Potent innate immune response to pathogenic leptospira in human whole blood.

PubMed

Goris, Marga G A; Wagenaar, Jiri F P; Hartskeerl, Rudy A; van Gorp, Eric C M; Schuller, Simone; Monahan, Avril M; Nally, Jarlath E; van der Poll, Tom; van 't Veer, Cornelis

2011-03-31

Leptospirosis is caused by pathogenic spirochetes of the genus Leptospira. The bacteria enter the human body via abraded skin or mucous membranes and may disseminate throughout. In general the clinical picture is mild but some patients develop rapidly progressive, severe disease with a high case fatality rate. Not much is known about the innate immune response to leptospires during haematogenous dissemination. Previous work showed that a human THP-1 cell line recognized heat-killed leptospires and leptospiral LPS through TLR2 instead of TLR4. The LPS of virulent leptospires displayed a lower potency to trigger TNF production by THP-1 cells compared to LPS of non-virulent leptospires. We investigated the host response and killing of virulent and non-virulent Leptospira of different serovars by human THP-1 cells, human PBMC's and human whole blood. Virulence of each leptospiral strain was tested in a well accepted standard guinea pig model. Virulent leptospires displayed complement resistance in human serum and whole blood while in-vitro attenuated non-virulent leptospires were rapidly killed in a complement dependent manner. In vitro stimulation of THP-1 and PBMC's with heat-killed and living leptospires showed differential serovar and cell type dependence of cytokine induction. However, at low, physiological, leptospiral dose, living virulent complement resistant strains were consistently more potent in whole blood stimulations than the corresponding non-virulent complement sensitive strains. At higher dose living virulent and non-virulent leptospires were equipotent in whole blood. Inhibition of different TLRs indicated that both TLR2 and TLR4 as well as TLR5 play a role in the whole blood cytokine response to living leptospires. Thus, in a minimally altered system as human whole blood, highly virulent Leptospira are potent inducers of the cytokine response.

The neuron classification problem

PubMed Central

Bota, Mihail; Swanson, Larry W.

2007-01-01

A systematic account of neuron cell types is a basic prerequisite for determining the vertebrate nervous system global wiring diagram. With comprehensive lineage and phylogenetic information unavailable, a general ontology based on structure-function taxonomy is proposed and implemented in a knowledge management system, and a prototype analysis of select regions (including retina, cerebellum, and hypothalamus) presented. The supporting Brain Architecture Knowledge Management System (BAMS) Neuron ontology is online and its user interface allows queries about terms and their definitions, classification criteria based on the original literature and “Petilla Convention” guidelines, hierarchies, and relations—with annotations documenting each ontology entry. Combined with three BAMS modules for neural regions, connections between regions and neuron types, and molecules, the Neuron ontology provides a general framework for physical descriptions and computational modeling of neural systems. The knowledge management system interacts with other web resources, is accessible in both XML and RDF/OWL, is extendible to the whole body, and awaits large-scale data population requiring community participation for timely implementation. PMID:17582506

Pseudomonas fluorescens HK44: Lessons Learned from a Model Whole-Cell Bioreporter with a Broad Application History

PubMed Central

Trögl, Josef; Chauhan, Archana; Ripp, Steven; Layton, Alice C.; Kuncová, Gabriela; Sayler, Gary S.

2012-01-01

Initially described in 1990, Pseudomonas fluorescens HK44 served as the first whole-cell bioreporter genetically endowed with a bioluminescent (luxCDABE) phenotype directly linked to a catabolic (naphthalene degradative) pathway. HK44 was the first genetically engineered microorganism to be released in the field to monitor bioremediation potential. Subsequent to that release, strain HK44 had been introduced into other solids (soils, sands), liquid (water, wastewater), and volatile environments. In these matrices, it has functioned as one of the best characterized chemically-responsive environmental bioreporters and as a model organism for understanding bacterial colonization and transport, cell immobilization strategies, and the kinetics of cellular bioluminescent emission. This review summarizes the characteristics of P. fluorescens HK44 and the extensive range of its applications with special focus on the monitoring of bioremediation processes and biosensing of environmental pollution. PMID:22438725

A Statistical Framework for the Functional Analysis of Metagenomes

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

Sharon, Itai; Pati, Amrita; Markowitz, Victor

2008-10-01

Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements.more » They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.« less

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

PubMed Central

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

2012-01-01

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

Experimental Clostridium perfringens type D enterotoxemia in goats.

PubMed

Uzal, F A; Kelly, W R

1998-03-01

The effects of intraduodenal administration of Clostridium perfringens cultures and culture products in goats were evaluated to develop a reliable experimental model of enterotoxemia in this species. Five conventionally reared, 11-16-week-old Angora goat kids were dosed intraduodenally with whole cultures of C. perfringens type D; five similar animals were dosed with C. perfringens type D filtered culture supernatant; and a third group of five kids was dosed with C. perfringens type D washed cells. Two kids were used as controls and received sterile, nontoxic culture medium intraduodenally. All animals received starch solution into the abomasum. All five kids inoculated with whole culture and three of five dosed with culture supernatant and with washed cells developed central nervous system signs. Diarrhea was observed in two of five kids inoculated with whole culture, in all five of those dosed with culture supernatant, and in three of five of those that received washed cells. The most striking postmortem findings consisted of lung edema, necrotizing pseudomembranous colitis, and cerebral vasogenic edema. The protocol thus provided a reasonable model of naturally occurring enterotoxemia in goats, producing a range of clinical signs and postmortem changes similar to those observed in the natural disease.

Effect of whole yeast cell product supplementation (CitriStim®) on immune responses and cecal microflora species in pullet and layer chickens during an experimental coccidial challenge.

PubMed

Markazi, Ashley D; Perez, Victor; Sifri, Mamduh; Shanmugasundaram, Revathi; Selvaraj, Ramesh K

2017-07-01

Three separate experiments were conducted to study the effects of whole yeast cell product supplementation in pullets and layer hens. Body weight gain, fecal and intestinal coccidial oocyst counts, cecal microflora species, cytokine mRNA amounts, and CD4+ and CD8+ T-cell populations in the cecal tonsils were analyzed following an experimental coccidial infection. In Experiment I, day-old Leghorn layer chicks were fed 3 experimental diets with 0, 0.1, or 0.2% whole yeast cell product (CitriStim®, ADM, Decatur, IL). At 21 d of age, birds were challenged with 1 × 105 live coccidial oocysts. Supplementation with whole yeast cell product decreased the fecal coccidial oocyst count at 7 (P = 0.05) and 8 (P < 0.01) d post-challenge. In Experiment II, 27-week old Leghorn layer hens were fed 3 experimental diets with 0, 0.05 or 0.1% whole yeast cell product and challenged with 1 × 105 live coccidial oocysts on d 25 of whole yeast cell product feeding. Supplementation with whole yeast cell product decreased the coccidial oocyst count in the intestinal content (P < 0.01) at 5, 13, and 38 d post-coccidial challenge. Supplementation with whole yeast cell product increased relative proportion of Lactobacillus (P < 0.01) in the cecal tonsils 13 d post-coccidial challenge. Supplementation with whole yeast cell product decreased CD8+ T cell percentages (P < 0.05) in the cecal tonsils at 5 d post-coccidial challenge. In Experiment III, 32-week-old Leghorn layer hens were fed 3 experimental diets with 0, 0.1, or 0.2% whole yeast cell product and challenged with 1 × 105 live coccidial oocysts on d 66 of whole yeast cell product feeding. At 5 d post-coccidial challenge, whole yeast cell product supplementation down-regulated (P = 0.01) IL-10 mRNA amount. It could be concluded that supplementing whole yeast cell product can help minimize coccidial infection in both growing pullets and layer chickens. © 2017 Poultry Science Association Inc.

A proposed route to independent measurements of tight junction conductance at discrete cell junctions

PubMed Central

Zhou, Lushan; Zeng, Yuhan; Baker, Lane A; Hou, Jianghui

2015-01-01

Direct recording of tight junction permeability is of pivotal importance to many biologic fields. Previous approaches bear an intrinsic disadvantage due to the difficulty of separating tight junction conductance from nearby membrane conductance. Here, we propose the design of Double whole-cell Voltage Clamp - Ion Conductance Microscopy (DVC-ICM) based on previously demonstrated potentiometric scanning of local conductive pathways. As proposed, DVC-ICM utilizes two coordinated whole-cell patch-clamps to neutralize the apical membrane current during potentiometric scanning, which in models described here will profoundly enhance the specificity of tight junction recording. Several potential pitfalls are considered, evaluated and addressed with alternative countermeasures. PMID:26716077

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).

PubMed

Koestler, Devin C; Jones, Meaghan J; Usset, Joseph; Christensen, Brock C; Butler, Rondi A; Kobor, Michael S; Wiencke, John K; Kelsey, Karl T

2016-03-08

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution. Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R (2)>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R (2)>0.90 and R M S E<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large publicly available HM450 data sets. Despite consisting of half as many CpGs compared to existing libraries for whole blood mixture deconvolution, the optimized IDOL library identified herein resulted in outstanding prediction performance across all considered data sets and demonstrated potential to improve the operating characteristics of EWAS involving adjustments for cell distribution. In addition to providing the EWAS community with an optimized library for whole blood mixture deconvolution, our work establishes a systematic and generalizable framework for the assembly of libraries that improve the accuracy of cell mixture deconvolution.

Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell line.

PubMed

Lakatos, Eszter; Salehi-Reyhani, Ali; Barclay, Michael; Stumpf, Michael P H; Klug, David R

2017-01-01

We determine p53 protein abundances and cell to cell variation in two human cancer cell lines with single cell resolution, and show that the fractional width of the distributions is the same in both cases despite a large difference in average protein copy number. We developed a computational framework to identify dominant mechanisms controlling the variation of protein abundance in a simple model of gene expression from the summary statistics of single cell steady state protein expression distributions. Our results, based on single cell data analysed in a Bayesian framework, lends strong support to a model in which variation in the basal p53 protein abundance may be best explained by variations in the rate of p53 protein degradation. This is supported by measurements of the relative average levels of mRNA which are very similar despite large variation in the level of protein.

A Simulation Framework for Battery Cell Impact Safety Modeling Using LS-DYNA

DOE PAGES

Marcicki, James; Zhu, Min; Bartlett, Alexander; ...

2017-02-04

The development process of electrified vehicles can benefit significantly from computer-aided engineering tools that predict themultiphysics response of batteries during abusive events. A coupled structural, electrical, electrochemical, and thermal model framework has been developed within the commercially available LS-DYNA software. The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components. The mechanical solver predicts the distributed stress and strain response with failure thresholds leading to the onset of an internal short circuit. In this implementation, an arbitrary compressive strain criterion is applied locally to each unit cell. A spatially distributed equivalent circuit model providesmore » an empirical representation of the electrochemical responsewith minimal computational complexity.The thermalmodel provides state information to index the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation. The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response. The ability to predict the distributed thermal response of the cell as its stored energy is completely discharged through the short circuit enables an engineering safety assessment. A parametric analysis of an exemplary model is used to demonstrate the simulation capabilities.« less

Microfluidic immunomagnetic cell separation from whole blood.

PubMed

Bhuvanendran Nair Gourikutty, Sajay; Chang, Chia-Pin; Puiu, Poenar Daniel

2016-02-01

Immunomagnetic-based separation has become a viable technique for the separation of cells and biomolecules. Here we report on the design and analysis of a simple and efficient microfluidic device for high throughput and high efficiency capture of cells tagged with magnetic particles. This is made possible by using a microfluidic chip integrated with customized arrays of permanent magnets capable of creating large magnetic field gradients, which determine the effective capturing of the tagged cells. This method is based on manipulating the cells which are under the influence of a combination of magnetic and fluid dynamic forces in a fluid under laminar flow through a microfluidic chip. A finite element analysis (FEA) model is developed to analyze the cell separation process and predict its behavior, which is validated subsequently by the experimental results. The magnetic field gradients created by various arrangements of magnetic arrays have been simulated using FEA and the influence of these field gradients on cell separation has been studied with the design of our microfluidic chip. The proof-of-concept for the proposed technique is demonstrated by capturing white blood cells (WBCs) from whole human blood. CD45-conjugated magnetic particles were added into whole blood samples to label WBCs and the mixture was flown through our microfluidic device to separate the labeled cells. After the separation process, the remaining WBCs in the elute were counted to determine the capture efficiency, and it was found that more than 99.9% WBCs have been successfully separated from whole blood. The proposed design can be used for positive selection as well as for negative enrichment of rare cells. Copyright © 2015 Elsevier B.V. All rights reserved.

Managing risks in the fisheries supply chain using House of Risk Framework (HOR) and Interpretive Structural Modeling (ISM)

NASA Astrophysics Data System (ADS)

Nguyen, T. L. T.; Tran, T. T.; Huynh, T. P.; Ho, T. K. D.; Le, A. T.; Do, T. K. H.

2018-04-01

One of the sectors which contributes importantly to the development of Vietnam economy is fishery industry. However, during recent year, it has been witnessed many difficulties on managing the performance of the fishery supply chain operations as a whole. In this paper, a framework for supply chain risk management (SCRM) is proposed. Initially, all the activities are mapped by using Supply Chain Operations Reference (SCOR) model. Next, the risk ranking is analyzed in House of Risk. Furthermore, interpretive structural modeling (ISM) is used to identify inter-relationships among supply chain risks and to visualize the risks according to their levels. For illustration, the model has been tested in several case studies with fishery companies in Can Tho, Mekong Delta. This study identifies 22 risk events and 20 risk agents through the supply chain. Also, the risk priority could be used for further House of Risk with proactive actions in future studies.

Nature as a network of morphological infocomputational processes for cognitive agents

NASA Astrophysics Data System (ADS)

Dodig-Crnkovic, Gordana

2017-01-01

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted.

Coupling between a multi-physics workflow engine and an optimization framework

NASA Astrophysics Data System (ADS)

Di Gallo, L.; Reux, C.; Imbeaux, F.; Artaud, J.-F.; Owsiak, M.; Saoutic, B.; Aiello, G.; Bernardi, P.; Ciraolo, G.; Bucalossi, J.; Duchateau, J.-L.; Fausser, C.; Galassi, D.; Hertout, P.; Jaboulay, J.-C.; Li-Puma, A.; Zani, L.

2016-03-01

A generic coupling method between a multi-physics workflow engine and an optimization framework is presented in this paper. The coupling architecture has been developed in order to preserve the integrity of the two frameworks. The objective is to provide the possibility to replace a framework, a workflow or an optimizer by another one without changing the whole coupling procedure or modifying the main content in each framework. The coupling is achieved by using a socket-based communication library for exchanging data between the two frameworks. Among a number of algorithms provided by optimization frameworks, Genetic Algorithms (GAs) have demonstrated their efficiency on single and multiple criteria optimization. Additionally to their robustness, GAs can handle non-valid data which may appear during the optimization. Consequently GAs work on most general cases. A parallelized framework has been developed to reduce the time spent for optimizations and evaluation of large samples. A test has shown a good scaling efficiency of this parallelized framework. This coupling method has been applied to the case of SYCOMORE (SYstem COde for MOdeling tokamak REactor) which is a system code developed in form of a modular workflow for designing magnetic fusion reactors. The coupling of SYCOMORE with the optimization platform URANIE enables design optimization along various figures of merit and constraints.

A general framework for updating belief distributions.

PubMed

Bissiri, P G; Holmes, C C; Walker, S G

2016-11-01

We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such as a mean or median, it is cumbersome to have to achieve this via a complete model for the whole data distribution. More importantly, there are settings where the parameter of interest does not directly index a family of density functions and thus the Bayesian approach to learning about such parameters is currently regarded as problematic. Our framework uses loss functions to connect information in the data to functionals of interest. The updating of beliefs then follows from a decision theoretic approach involving cumulative loss functions. Importantly, the procedure coincides with Bayesian updating when a true likelihood is known yet provides coherent subjective inference in much more general settings. Connections to other inference frameworks are highlighted.

A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms.

PubMed

Balbi, Pietro; Massobrio, Paolo; Hellgren Kotaleski, Jeanette

2017-09-01

Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.

A quantitative framework to evaluate modeling of cortical development by neural stem cells

PubMed Central

Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.

2014-01-01

Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955

Safety modelling and testing of lithium-ion batteries in electrified vehicles

NASA Astrophysics Data System (ADS)

Deng, Jie; Bae, Chulheung; Marcicki, James; Masias, Alvaro; Miller, Theodore

2018-04-01

To optimize the safety of batteries, it is important to understand their behaviours when subjected to abuse conditions. Most early efforts in battery safety modelling focused on either one battery cell or a single field of interest such as mechanical or thermal failure. These efforts may not completely reflect the failure of batteries in automotive applications, where various physical processes can take place in a large number of cells simultaneously. In this Perspective, we review modelling and testing approaches for battery safety under abuse conditions. We then propose a general framework for large-scale multi-physics modelling and experimental work to address safety issues of automotive batteries in real-world applications. In particular, we consider modelling coupled mechanical, electrical, electrochemical and thermal behaviours of batteries, and explore strategies to extend simulations to the battery module and pack level. Moreover, we evaluate safety test approaches for an entire range of automotive hardware sets from cell to pack. We also discuss challenges in building this framework and directions for its future development.

Developing Highly Sensitive Micro-Biosensors for in-situ Monitoring Mercury and Chromium(IV) Contaminants by Genetically-evolving and Computer-designing Metal-binding Proteins

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

Wang, Qinghong; Fang, Xiangdong; Goddard, William

2013-10-17

Mercury has been well known as an environmental pollutant to the environment and to cause serious effects on human health for several decades. To effectively control mercury pollution and reduce mercury damages, the sensitive determination of mercury is essential. Currently, many different types of sensor-based assays have been developed, while the whole-cell biosensor has been gaining increasingly attentions due to its easy reproducibility and the possibility to greatly reduce the cost. However, significant improvements on the specificity, sensitivity, stability and simplicity of the whole-cell biosensor are still needed prior to its eventual commercialization. Sponsored by US Department of Energy undermore » the contract agreement DE-FG02-07ER64410, we applied the special synthetic biology and directed evolution strategies to improve the effectiveness and performance of whole-cell biosensors. We have constructed different whole-cell biosensors for the mercuric ion and methylmercury detection with metalloregulator MerR, fluorescent protein mCherry and organomercurial lyase MerB. By introducing the mercuric transporter MerT, we were able to increase the detection sensitivity of whole-cell biosensors by at least one fold. By introducing the bio-amplification genetic circuit based on the gene cascade expression system of PRM-cI from bacteriophage l and Pm-XylS2 from Pseudomonas putida, we have increased the detection sensitivity of whole-cell biosensors by 1~2 folds in our tested conditions. With the directed evolution of MerR and subsequent high-throughput screening via color assay and microplate screening, we have dramatically increased the detection sensitivity by up to 10 folds at low concentration of mercury (II) of 1-10nM. Structural modeling and computational analysis of the mutated MerR showed that many mutations could cause the change of a loop to helix, which could be responsible for the increased mercury sensitivity.« less

Modeling intrinsic electrophysiology of AII amacrine cells: preliminary results.

PubMed

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

2013-01-01

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

Running and rotating: modelling the dynamics of migrating cell clusters

NASA Astrophysics Data System (ADS)

Copenhagen, Katherine; Gov, Nir; Gopinathan, Ajay

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

Multi-flexible-body analysis for application to wind turbine control design

NASA Astrophysics Data System (ADS)

Lee, Donghoon

The objective of the present research is to build a theoretical and computational framework for the aeroelastic analysis of flexible rotating systems, more specifically with special application to a wind turbine control design. The methodology is based on the integration of Kane's approach for the analysis of the multi-rigid-body subsystem and a mixed finite element method for the analysis of the flexible-body subsystem. The combined analysis is then strongly coupled with an aerodynamic model based on Blade Element Momentum theory for inflow model. The unified framework from the analysis of subsystems is represented as, in a symbolic manner, a set of nonlinear ordinary differential equations with time-variant, periodic coefficients, which describe the aeroelastic behavior of whole system. The framework can be directly applied to control design due to its symbolic characteristics. The solution procedures for the equations are presented for the study of nonlinear simulation, periodic steady-state solution, and Floquet stability of the linearized system about the steady-state solution. Finally the linear periodic system equation can be obtained with both system and control matrices as explicit functions of time, which can be directly applicable to control design. The structural model is validated by comparison of its results with those from software, some of which is commercial. The stability of the linearized system about periodic steady-state solution is different from that obtained about a constant steady-state solution, which have been conventional in the field of wind turbine dynamics. Parametric studies are performed on a wind turbine model with various pitch angles, precone angles, and rotor speeds. Combined with composite material, their effects on wind turbine aeroelastic stability are investigated. Finally it is suggested that the aeroelastic stability analysis and control design for the whole system is crucial for the design of wind turbines, and the present research breaks new ground in the ability to treat the issue.

Cell-type-specific modelling of intracellular calcium signalling: a urothelial cell model.

PubMed

Appleby, Peter A; Shabir, Saqib; Southgate, Jennifer; Walker, Dawn

2013-09-06

Calcium signalling plays a central role in regulating a wide variety of cell processes. A number of calcium signalling models exist in the literature that are capable of reproducing a variety of experimentally observed calcium transients. These models have been used to examine in more detail the mechanisms underlying calcium transients, but very rarely has a model been directly linked to a particular cell type and experimentally verified. It is important to show that this can be achieved within the general theoretical framework adopted by these models. Here, we develop a framework designed specifically for modelling cytosolic calcium transients in urothelial cells. Where possible, we draw upon existing calcium signalling models, integrating descriptions of components known to be important in this cell type from a number of studies in the literature. We then add descriptions of several additional pathways that play a specific role in urothelial cell signalling, including an explicit ionic influx term and an active pumping mechanism that drives the cytosolic calcium concentration to a target equilibrium. The resulting one-pool model of endoplasmic reticulum (ER)-dependent calcium signalling relates the cytosolic, extracellular and ER calcium concentrations and can generate a wide range of calcium transients, including spikes, bursts, oscillations and sustained elevations in the cytosolic calcium concentration. Using single-variate robustness and multivariate sensitivity analyses, we quantify how varying each of the parameters of the model leads to changes in key features of the calcium transient, such as initial peak amplitude and the frequency of bursting or spiking, and in the transitions between bursting- and plateau-dominated modes. We also show that, novel to our urothelial cell model, the ionic and purinergic P2Y pathways make distinct contributions to the calcium transient. We then validate the model using human bladder epithelial cells grown in monolayer cell culture and show that the model robustly captures the key features of the experimental data in a way that is not possible using more generic calcium models from the literature.

Toward a Whole-Cell Model of Ribosome Biogenesis: Kinetic Modeling of SSU Assembly

PubMed Central

Earnest, Tyler M.; Lai, Jonathan; Chen, Ke; Hallock, Michael J.; Williamson, James R.; Luthey-Schulten, Zaida

2015-01-01

Central to all life is the assembly of the ribosome: a coordinated process involving the hierarchical association of ribosomal proteins to the RNAs forming the small and large ribosomal subunits. The process is further complicated by effects arising from the intracellular heterogeneous environment and the location of ribosomal operons within the cell. We provide a simplified model of ribosome biogenesis in slow-growing Escherichia coli. Kinetic models of in vitro small-subunit reconstitution at the level of individual protein/ribosomal RNA interactions are developed for two temperature regimes. The model at low temperatures predicts the existence of a novel 5′→3′→central assembly pathway, which we investigate further using molecular dynamics. The high-temperature assembly network is incorporated into a model of in vivo ribosome biogenesis in slow-growing E. coli. The model, described in terms of reaction-diffusion master equations, contains 1336 reactions and 251 species that dynamically couple transcription and translation to ribosome assembly. We use the Lattice Microbes software package to simulate the stochastic production of mRNA, proteins, and ribosome intermediates over a full cell cycle of 120 min. The whole-cell model captures the correct growth rate of ribosomes, predicts the localization of early assembly intermediates to the nucleoid region, and reproduces the known assembly timescales for the small subunit with no modifications made to the embedded in vitro assembly network. PMID:26333594

Determination of EGFR mutations in single cells microdissected from enriched lung tumor cells in peripheral blood.

PubMed

Ran, Ran; Li, Longyun; Wang, Mengzhao; Wang, Shulan; Zheng, Zhi; Lin, Peter Ping

2013-09-01

A minimally invasive and repeatable approach for real-time epidermal growth factor receptor (EGFR) mutation surveillance would be highly beneficial for individualized therapy of late stage lung cancer patients whose surgical specimens are often not available. We aim to develop a viable method to detect EGFR mutations in single circulating tumor cells (CTCs). Using a model CTC system of spiked tumor cells in whole blood, we evaluated EGFR mutation determination in single tumor cells enriched from blood. We used magnetic beads labeled with antibody against leukocyte surface antigens to deplete leukocytes and enrich native CTCs independent of epithelial marker expression level. We then used laser cell microdissection (LCM) to isolate individual CTCs, followed by whole-genome amplification of the DNA for exon 19 microdeletion, L858R and T790M mutation detection by PCR sequencing. EGFR mutations were successfully measured in individual spiked tumor cells enriched from 7.5 ml whole blood. Whole-genome amplification provided sufficient DNA for mutation determination at multiple sites. Ninety-five percent of the single CTCs microdissected by LCM (19/20) yielded PCR amplicons for at least one of the three mutation sites. The amplification success rates were 55 % (11/20) for exon 19 deletion, 45 % (9/20) for T790M, and 85 % (17/20) for L858R. Sequencing of the amplicons showed allele dropout in the amplification reactions, but mutations were correctly identified in 80 % of the amplicons. EGFR mutation determination from single captured tumor cells from blood is feasible with the approach described here. However, to overcome allele dropout and to obtain reliable information about the tumor's EGFR status, multiple individual tumor cells should be assayed.

Non-Gaussian spatiotemporal simulation of multisite daily precipitation: downscaling framework

NASA Astrophysics Data System (ADS)

Ben Alaya, M. A.; Ouarda, T. B. M. J.; Chebana, F.

2018-01-01

Probabilistic regression approaches for downscaling daily precipitation are very useful. They provide the whole conditional distribution at each forecast step to better represent the temporal variability. The question addressed in this paper is: how to simulate spatiotemporal characteristics of multisite daily precipitation from probabilistic regression models? Recent publications point out the complexity of multisite properties of daily precipitation and highlight the need for using a non-Gaussian flexible tool. This work proposes a reasonable compromise between simplicity and flexibility avoiding model misspecification. A suitable nonparametric bootstrapping (NB) technique is adopted. A downscaling model which merges a vector generalized linear model (VGLM as a probabilistic regression tool) and the proposed bootstrapping technique is introduced to simulate realistic multisite precipitation series. The model is applied to data sets from the southern part of the province of Quebec, Canada. It is shown that the model is capable of reproducing both at-site properties and the spatial structure of daily precipitations. Results indicate the superiority of the proposed NB technique, over a multivariate autoregressive Gaussian framework (i.e. Gaussian copula).

Registering Cortical Surfaces Based on Whole-Brain Structural Connectivity and Continuous Connectivity Analysis

PubMed Central

Gutman, Boris; Leonardo, Cassandra; Jahanshad, Neda; Hibar, Derrek; Eschen-burg, Kristian; Nir, Talia; Villalon, Julio; Thompson, Paul

2014-01-01

We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains’ continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer’s patients and controls. Our measures show significant differences between the two groups. PMID:25320795

Switching LPV Control with Double-Layer LPV Model for Aero-Engines

NASA Astrophysics Data System (ADS)

Tang, Lili; Huang, Jinquan; Pan, Muxuan

2017-11-01

To cover the whole range of operating conditions of aero-engine, a double-layer LPV model is built so as to take into account of the variability due to the flight altitude, Mach number and the rotational speed. With this framework, the problem of designing LPV state-feedback robust controller that guarantees desired bounds on both H_∞ and H_2 performances is considered. Besides this, to reduce the conservativeness caused by a single LPV controller of the whole flight envelope and the common Lyapunov function method, a new method is proposed to design a family of LPV switching controllers. The switching LPV controllers can ensure that the closed-loop system remains stable in the sense of Lyapunov under arbitrary switching logic. Meanwhile, the switching LPV controllers can ensure the parameters change smoothly. The validity and performance of the theoretical results are demonstrated through a numerical example.

Optical and electrical interfacing technologies for living cell bio-chips.

PubMed

Shacham-Diamand, Y; Belkin, S; Rishpon, J; Elad, T; Melamed, S; Biran, A; Yagur-Kroll, S; Almog, R; Daniel, R; Ben-Yoav, H; Rabner, A; Vernick, S; Elman, N; Popovtzer, R

2010-06-01

Whole-cell bio-chips for functional sensing integrate living cells on miniaturized platforms made by micro-system-technologies (MST). The cells are integrated, deposited or immersed in a media which is in contact with the chip. The cells behavior is monitored via electrical, electrochemical or optical methods. In this paper we describe such whole-cell biochips where the signal is generated due to the genetic response of the cells. The solid-state platform hosts the biological component, i.e. the living cells, and integrates all the required micro-system technologies, i.e. the micro-electronics, micro-electro optics, micro-electro or magneto mechanics and micro-fluidics. The genetic response of the cells expresses proteins that generate: a. light by photo-luminescence or bioluminescence, b. electrochemical signal by interaction with a substrate, or c. change in the cell impedance. The cell response is detected by a front end unit that converts it to current or voltage amplifies and filters it. The resultant signal is analyzed and stored for further processing. In this paper we describe three examples of whole-cell bio chips, photo-luminescent, bioluminescent and electrochemical, which are based on the genetic response of genetically modified E. coli microbes integrated on a micro-fluidics MEMS platform. We describe the chip outline as well as the basic modeling scheme of such sensors. We discuss the highlights and problems of such system, from the point of view of micro-system-technology.

The effect of burn injury on CD8+ and CD4+ T cells in an irradiation model of homeostatic proliferation.

PubMed

Buchanan, Ian B; Maile, Robert; Frelinger, Jeffrey A; Fair, Jeffrey H; Meyer, Anthony A; Cairns, Bruce A

2006-11-01

Homeostatic proliferation of T cells has recently been shown to be an important mechanism in the host response to infection. However, its role in the T cell response to burn injury is unknown. In this study, we examine the effect of burn injury on CD4+ and CD8+ T cell homeostatic proliferation after irradiation. Wild-type C57BL/6 female mice were irradiated with six grays ionizing radiation and 48 hours later, syngeneic whole splenocytes or purified CD4+ or CD8+ T cells labeled with carboxy-fluorescein diacetate, succinimidyl ester were adoptively transferred. Two days later, mice underwent a 20% burn injury, followed by splenocyte harvest 3 and 10 days after injury. Burn mice demonstrate increased splenic cellularity and CD8+ T cell proliferation after adoptive transfer of either purified CD8+ cells or whole spleen populations compared with unburned (sham) mice. In contrast, CD4+ T cell proliferation after burn injury is unchanged after adoptive transfer of whole spleen cells and drastically decreased after adoptive transfer of a purified CD4+ population compared with sham mice. Ten days after burn injury CD8+ T cells continue to demonstrate greater proliferation than CD4+ T cells. CD8+ T cells are more robust than CD4+ T cells in their proliferative response after burn injury. In addition, CD8+ T cell proliferation appears less reliant on other immune cells than purified CD4+ T cell proliferation. These data reiterate the importance of CD8+ T cells in the initial immune response to burn injury.

Modeling and simulation of an unmanned ground vehicle power system

NASA Astrophysics Data System (ADS)

Broderick, John; Hartner, Jack; Tilbury, Dawn M.; Atkins, Ella M.

2014-06-01

Long-duration missions challenge ground robot systems with respect to energy storage and efficient conversion to power on demand. Ground robot systems can contain multiple power sources such as fuel cell, battery and/or ultra-capacitor. This paper presents a hybrid systems framework for collectively modeling the dynamics and switching between these different power components. The hybrid system allows modeling power source on/off switching and different regimes of operation, together with continuous parameters such as state of charge, temperature, and power output. We apply this modeling framework to a fuel cell/battery power system applicable to unmanned ground vehicles such as Packbot or TALON. A simulation comparison of different control strategies is presented. These strategies are compared based on maximizing energy efficiency and meeting thermal constraints.

A novel way to go whole-cell in patch-clamp experiments.

PubMed

Inayat, Samsoon; Zhao, Yan; Cantrell, Donal R; Dikin, Dmitryi; Pinto, Lawrence H; Troy, John B

2010-11-01

With a conventional patch-clamp electrode, an Ag/AgCl wire sits stationary inside the pipette. To move from the gigaseal cell-attached configuration to whole-cell recording, suction is applied inside the pipette. We have designed and developed a novel Pushpen patch-clamp electrode, in which a W wire insulated and wound with Ag/AgCl wire can move linearly inside the pipette. The W wire has a conical tip, which can protrude from the pipette tip like a push pen, a procedure we call the Pushpen Operation. We use the Pushpen operation to impale the cell membrane in cell-attached configuration to go whole-cell without disruption of the gigaseal. We successfully recorded whole-cell currents from chinese hamster ovarian cells expressing influenza A virus protein A/M2, after obtaining whole-cell configuration with the Pushpen operation. This novel method of achieving whole-cell configuration may have a higher success rate than is the case with the conventional patch clamp technique.

The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.

Complementary and alternative medicine whole systems research: beyond identification of inadequacies of the RCT.

PubMed

Verhoef, Marja J; Lewith, George; Ritenbaugh, Cheryl; Boon, Heather; Fleishman, Susan; Leis, Anne

2005-09-01

Complementary and alternative medicine (CAM) often consists of whole systems of care (such as naturopathic medicine or traditional Chinese medicine (TCM)) that combine a wide range of modalities to provide individualised treatment. The complexity of these interventions and their potential synergistic effect requires innovative evaluative approaches. Model validity, which encompasses the need for research to adequately address the unique healing theory and therapeutic context of the intervention, is central to whole systems research (WSR). Classical randomised controlled trials (RCTs) are limited in their ability to address this need. Therefore, we propose a mixed methods approach that includes a range of relevant and holistic outcome measures. As the individual components of most whole systems are inseparable, complementary and synergistic, WSR must not focus only on the "active" ingredients of a system. An emerging WSR framework must be non-hierarchical, cyclical, flexible and adaptive, as knowledge creation is continuous, evolutionary and necessitates a continuous interplay between research methods and "phases" of knowledge. Finally, WSR must hold qualitative and quantitative research methods in equal esteem to realize their unique research contribution. Whole systems are complex and therefore no one method can adequately capture the meaning, process and outcomes of these interventions.

Buder revisited: cell and organ polarity during phototropism.

PubMed

Nick, P; Furuya, M

1996-10-01

The induction of a radial polarity by environmental stimuli was studied at the cellular and organ levels, with phototropism chosen as a model. The light gradient acting on the whole coleoptile was opposed to the light direction acting upon individual cells in the classical Buder experiment, irradiating from the inside out. Alternatively, the stimulus was administered to the coleoptile tip with a microbeam-irradiation device. Tropistic curvature was assayed as a marker for the response of the whole organ, whereas cell elongation and the orientation of cortical microtubules were taken as markers for the responses of individual cells. Upon tip irradiation, signals much faster than basipetal auxin transport migrate towards the base. The data are discussed in terms of an organ polarity that is the primary result of the asymmetric light signal and affects, in a second step, an endogenous radial polarity of epidermal cells.

Polyploidy can drive rapid adaptation in yeast

NASA Astrophysics Data System (ADS)

Selmecki, Anna M.; Maruvka, Yosef E.; Richmond, Phillip A.; Guillet, Marie; Shoresh, Noam; Sorenson, Amber L.; de, Subhajyoti; Kishony, Roy; Michor, Franziska; Dowell, Robin; Pellman, David

2015-03-01

Polyploidy is observed across the tree of life, yet its influence on evolution remains incompletely understood. Polyploidy, usually whole-genome duplication, is proposed to alter the rate of evolutionary adaptation. This could occur through complex effects on the frequency or fitness of beneficial mutations. For example, in diverse cell types and organisms, immediately after a whole-genome duplication, newly formed polyploids missegregate chromosomes and undergo genetic instability. The instability following whole-genome duplications is thought to provide adaptive mutations in microorganisms and can promote tumorigenesis in mammalian cells. Polyploidy may also affect adaptation independently of beneficial mutations through ploidy-specific changes in cell physiology. Here we perform in vitro evolution experiments to test directly whether polyploidy can accelerate evolutionary adaptation. Compared with haploids and diploids, tetraploids undergo significantly faster adaptation. Mathematical modelling suggests that rapid adaptation of tetraploids is driven by higher rates of beneficial mutations with stronger fitness effects, which is supported by whole-genome sequencing and phenotypic analyses of evolved clones. Chromosome aneuploidy, concerted chromosome loss, and point mutations all provide large fitness gains. We identify several mutations whose beneficial effects are manifest specifically in the tetraploid strains. Together, these results provide direct quantitative evidence that in some environments polyploidy can accelerate evolutionary adaptation.

Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.

Harnessing the Flow of Excitation: TRP, Voltage-Gated Na(+), and Voltage-Gated Ca(2+) Channels in Contemporary Medicine.

PubMed

Frolov, Roman V; Weckström, Matti

2016-01-01

Cellular signaling in both excitable and nonexcitable cells involves several classes of ion channels. Some of them are of minor importance, with very specialized roles in physiology, but here we concentrate on three major channel classes: TRP (transient receptor potential channels), voltage-gated sodium channels (Nav), and voltage-gated calcium channels (Cav). Here, we first propose a conceptual framework binding together all three classes of ion channels, a "flow-of-excitation model" that takes into account the inputs mediated by TRP and other similar channels, the outputs invariably provided by Cav channels, and the regenerative transmission of signals in the neural networks, for which Nav channels are responsible. We use this framework to examine the function, structure, and pharmacology of these channel classes both at cellular and also at whole-body physiological level. Building on that basis we go through the pathologies arising from the direct or indirect malfunction of the channels, utilizing ion channel defects, the channelopathies. The pharmacological interventions affecting these channels are numerous. Part of those are well-established treatments, like treatment of hypertension or some forms of epilepsy, but many other are deeply problematic due to poor drug specificity, ion channel diversity, and widespread expression of the channels in tissues other than those actually targeted. © 2016 Elsevier Inc. All rights reserved.

Muver, a computational framework for accurately calling accumulated mutations.

PubMed

Burkholder, Adam B; Lujan, Scott A; Lavender, Christopher A; Grimm, Sara A; Kunkel, Thomas A; Fargo, David C

2018-05-09

Identification of mutations from next-generation sequencing data typically requires a balance between sensitivity and accuracy. This is particularly true of DNA insertions and deletions (indels), that can impart significant phenotypic consequences on cells but are harder to call than substitution mutations from whole genome mutation accumulation experiments. To overcome these difficulties, we present muver, a computational framework that integrates established bioinformatics tools with novel analytical methods to generate mutation calls with the extremely low false positive rates and high sensitivity required for accurate mutation rate determination and comparison. Muver uses statistical comparison of ancestral and descendant allelic frequencies to identify variant loci and assigns genotypes with models that include per-sample assessments of sequencing errors by mutation type and repeat context. Muver identifies maximally parsimonious mutation pathways that connect these genotypes, differentiating potential allelic conversion events and delineating ambiguities in mutation location, type, and size. Benchmarking with a human gold standard father-son pair demonstrates muver's sensitivity and low false positive rates. In DNA mismatch repair (MMR) deficient Saccharomyces cerevisiae, muver detects multi-base deletions in homopolymers longer than the replicative polymerase footprint at rates greater than predicted for sequential single-base deletions, implying a novel multi-repeat-unit slippage mechanism. Benchmarking results demonstrate the high accuracy and sensitivity achieved with muver, particularly for indels, relative to available tools. Applied to an MMR-deficient Saccharomyces cerevisiae system, muver mutation calls facilitate mechanistic insights into DNA replication fidelity.

Colaborated Architechture Framework for Composition UML 2.0 in Zachman Framework

NASA Astrophysics Data System (ADS)

Hermawan; Hastarista, Fika

2016-01-01

Zachman Framework (ZF) is the framework of enterprise architechture that most widely adopted in the Enterprise Information System (EIS) development. In this study, has been developed Colaborated Architechture Framework (CAF) to collaborate ZF with Unified Modeling Language (UML) 2.0 modeling. The CAF provides the composition of ZF matrix that each cell is consist of the Model Driven architechture (MDA) from the various UML models and many Software Requirement Specification (SRS) documents. Implementation of this modeling is used to develops Enterprise Resource Planning (ERP). Because ERP have a coverage of applications in large numbers and complexly relations, it is necessary to use Agile Model Driven Design (AMDD) approach as an advanced method to transforms MDA into components of application modules with efficiently and accurately. Finally, through the using of the CAF, give good achievement in fullfilment the needs from all stakeholders that are involved in the overall process stage of Rational Unified Process (RUP), and also obtaining a high satisfaction to fullfiled the functionality features of the ERP software in PT. Iglas (Persero) Gresik.

Retinal cell responses to elevated intraocular pressure: a gene array comparison between the whole retina and retinal ganglion cell layer.

PubMed

Guo, Ying; Cepurna, William O; Dyck, Jennifer A; Doser, Tom A; Johnson, Elaine C; Morrison, John C

2010-06-01

To determine and compare gene expression patterns in the whole retina and retinal ganglion cell layer (RGCL) in a rodent glaucoma model. IOP was unilaterally elevated in Brown Norway rats (N = 26) by injection of hypertonic saline and monitored for 5 weeks. A cDNA microarray was used on whole retinas from one group of eyes with extensive optic nerve injury and on RGCL isolated by laser capture microdissection (LCM) from another group with comparable injury, to determine the significantly up- or downregulated genes and gene categories in both groups. Expression changes of selected genes were examined by quantitative reverse transcription-PCR (qPCR) to verify microarray results. Microarray analysis of the whole retina identified 632 genes with significantly changed expression (335 up, 297 down), associated with 9 upregulated and 3 downregulated biological processes. In contrast, the RGCL microarray yielded 3726 genes with significantly changed expression (2003 up, 1723 down), including 60% of those found in whole retina. Thirteen distinct upregulated biological processes were identified in the RGCL, dominated by protein synthesis. Among 11 downregulated processes, axon extension and dendrite morphogenesis and generation of precursor metabolism and energy were uniquely identified in the RGCL. qPCR confirmed significant changes in 6 selected messages in whole retina and 11 in RGCL. Increased Atf3, the most upregulated gene in the RGCL, was confirmed by immunohistochemistry of RGCs. Isolation of RGCL by LCM allows a more refined detection of gene response to elevated pressure and improves the potential of determining cellular mechanisms in RGCs and their supporting cells that could be targets for enhancing RGC survival.

Niche construction game cancer cells play

NASA Astrophysics Data System (ADS)

Bergman, Aviv; Gligorijevic, Bojana

2015-10-01

Niche construction concept was originally defined in evolutionary biology as the continuous interplay between natural selection via environmental conditions and the modification of these conditions by the organism itself. Processes unraveling during cancer metastasis include construction of niches, which cancer cells use towards more efficient survival, transport into new environments and preparation of the remote sites for their arrival. Many elegant experiments were done lately illustrating, for example, the premetastatic niche construction, but there is practically no mathematical modeling done which would apply the niche construction framework. To create models useful for understanding niche construction role in cancer progression, we argue that a) genetic, b) phenotypic and c) ecological levels are to be included. While the model proposed here is phenomenological in its current form, it can be converted into a predictive outcome model via experimental measurement of the model parameters. Here we give an overview of an experimentally formulated problem in cancer metastasis and propose how niche construction framework can be utilized and broadened to model it. Other life science disciplines, such as host-parasite coevolution, may also benefit from niche construction framework adaptation, to satisfy growing need for theoretical considerations of data collected by experimental biology.

Niche construction game cancer cells play.

PubMed

Bergman, Aviv; Gligorijevic, Bojana

2015-10-01

Niche construction concept was originally defined in evolutionary biology as the continuous interplay between natural selection via environmental conditions and the modification of these conditions by the organism itself. Processes unraveling during cancer metastasis include construction of niches, which cancer cells use towards more efficient survival, transport into new environments and preparation of the remote sites for their arrival. Many elegant experiments were done lately illustrating, for example, the premetastatic niche construction, but there is practically no mathematical modeling done which would apply the niche construction framework. To create models useful for understanding niche construction role in cancer progression, we argue that a) genetic, b) phenotypic and c) ecological levels are to be included. While the model proposed here is phenomenological in its current form, it can be converted into a predictive outcome model via experimental measurement of the model parameters. Here we give an overview of an experimentally formulated problem in cancer metastasis and propose how niche construction framework can be utilized and broadened to model it. Other life science disciplines, such as host-parasite coevolution, may also benefit from niche construction framework adaptation, to satisfy growing need for theoretical considerations of data collected by experimental biology.

Whole-body irradiation increases the magnitude and persistence of adoptively transferred T cells associated with tumor regression in a mouse model of prostate cancer

PubMed Central

Ward-Kavanagh, Lindsay K.; Zhu, Junjia; Cooper, Timothy K.; Schell, Todd D.

2014-01-01

Adoptive immunotherapy has demonstrated efficacy in a subset of clinical and preclinical studies, but the T cells used for therapy often are rendered rapidly non-functional in tumor-bearing hosts. Recent evidence indicates that prostate cancer can be susceptible to immunotherapy, but most studies using autochthonous tumor models demonstrate only short-lived T-cell responses in the tolerogenic prostate microenvironment. Here, we assessed the efficacy of sublethal whole-body irradiation (WBI) to enhance the magnitude and duration of adoptively transferred CD8+ T cells in the transgenic adenocarcinoma of the mouse prostate (TRAMP) model. We demonstrate that WBI promoted high-level accumulation of granzyme B (GzB)-expressing donor T cells both in lymphoid organs and in the prostate of TRAMP mice. Donor T cells remained responsive to vaccination in irradiated recipients, but a single round of WBI-enhanced adoptive immunotherapy failed to impact significantly the existing disease. Addition of a second round of immunotherapy promoted regression of established disease in half of the treated mice, with no progressions observed. Regression was associated with long-term persistence of effector/memory phenotype CD8+ donor cells. Administration of the second round of adoptive immunotherapy led to reacquisition of GzB expression by persistent T cells from the first transfer. These results indicate that WBI conditioning amplifies tumor-specific T cells in the TRAMP prostate and lymphoid tissue, and suggest that the initial treatment alters the tolerogenic microenvironment to increase antitumor activity by a second wave of donor cells. PMID:24801834

Modeling Bacteria Surface Acid-Base Properties: The Overprint Of Biology

NASA Astrophysics Data System (ADS)

Amores, D. R.; Smith, S.; Warren, L. A.

2009-05-01

Bacteria are ubiquitous in the environment and are important repositories for metals as well as nucleation templates for a myriad of secondary minerals due to an abundance of reactive surface binding sites. Model elucidation of whole cell surface reactivity simplifies bacteria as viable but static, i.e., no metabolic activity, to enable fits of microbial data sets from models derived from mineral surfaces. Here we investigate the surface proton charging behavior of live and dead whole cell cyanobacteria (Synechococcus sp.) harvested from a single parent culture by acid-base titration using a Fully Optimized ContinUouS (FOCUS) pKa spectrum method. Viability of live cells was verified by successful recultivation post experimentation, whereas dead cells were consistently non-recultivable. Surface site identities derived from binding constants determined for both the live and dead cells are consistent with molecular analogs for organic functional groups known to occur on microbial surfaces: carboxylic (pKa = 2.87-3.11), phosphoryl (pKa = 6.01-6.92) and amine/hydroxyl groups (pKa = 9.56-9.99). However, variability in total ligand concentration among the live cells is greater than those between the live and dead. The total ligand concentrations (LT, mol- mg-1 dry solid) derived from the live cell titrations (n=12) clustered into two sub-populations: high (LT = 24.4) and low (LT = 5.8), compared to the single concentration for the dead cell titrations (LT = 18.8; n=5). We infer from these results that metabolic activity can substantively impact surface reactivity of morphologically identical cells. These results and their modeling implications for bacteria surface reactivities will be discussed.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

PubMed Central

Almquist, Joachim; Bendrioua, Loubna; Adiels, Caroline Beck; Goksör, Mattias; Hohmann, Stefan; Jirstrand, Mats

2015-01-01

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability. PMID:25893847

Modeling the complex activity of sickle cell and thalassemia specialist nurses in England.

PubMed

Leary, Alison; Anionwu, Elizabeth N

2014-01-01

Specialist advanced practice nursing in hemoglobinopathies has a rich historical and descriptive literature. Subsequent work has shown that the role is valued by patients and families and also by other professionals. However, there is little empirical research on the complexity of activity of these services in terms of interventions offered. In addition, the work of clinical nurse specialists in England has been devalued through a perception of oversimplification. The purpose of this study was to understand the complexity of expert nursing practice in sickle cell and thalassemia. The approach taken to modeling complexity was used from common methods in mathematical modeling and computational mathematics. Knowledge discovery through data was the underpinning framework used in this study using a priori mined data. This allowed categorization of activity and articulation of complexity. In total, 8966 nursing events were captured over 1639 hours from a total of 22.8 whole time equivalents, and several data sources were mined. The work of specialist nurses in this area is complex in terms of the physical and psychosocial care they provide. The nurses also undertook case management activity such as utilizing a very large network of professionals, and others participated in admission avoidance work and education of patients' families and other staff. The work of nurses specializing in hemoglobinopathy care is complex and multidimensional and is likely to contribute to the quality of care in a cost-effective way. An understanding of this complexity can be used as an underpinning to establishing key performance indicators, optimum caseload calculations, and economic evaluation.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

There is an increasing demand to run environmental models on a big scale: simulations over large areas at high resolution. The heterogeneity of available computing hardware such as multi-core CPUs, GPUs or supercomputer potentially provides significant computing power to fulfil this demand. However, this requires detailed knowledge of the underlying hardware, parallel algorithm design and the implementation thereof in an efficient system programming language. Domain scientists such as hydrologists or ecologists often lack this specific software engineering knowledge, their emphasis is (and should be) on exploratory building and analysis of simulation models. As a result, models constructed by domain specialists mostly do not take full advantage of the available hardware. A promising solution is to separate the model building activity from software engineering by offering domain specialists a model building framework with pre-programmed building blocks that they combine to construct a model. The model building framework, consequently, needs to have built-in capabilities to make full usage of the available hardware. Developing such a framework providing understandable code for domain scientists and being runtime efficient at the same time poses several challenges on developers of such a framework. For example, optimisations can be performed on individual operations or the whole model, or tasks need to be generated for a well-balanced execution without explicitly knowing the complexity of the domain problem provided by the modeller. Ideally, a modelling framework supports the optimal use of available hardware whichsoever combination of model building blocks scientists use. We demonstrate our ongoing work on developing parallel algorithms for spatio-temporal modelling and demonstrate 1) PCRaster, an environmental software framework (http://www.pcraster.eu) providing spatio-temporal model building blocks and 2) parallelisation of about 50 of these building blocks using the new Fern library (https://github.com/geoneric/fern/), an independent generic raster processing library. Fern is a highly generic software library and its algorithms can be configured according to the configuration of a modelling framework. With manageable programming effort (e.g. matching data types between programming and domain language) we created a binding between Fern and PCRaster. The resulting PCRaster Python multicore module can be used to execute existing PCRaster models without having to make any changes to the model code. We show initial results on synthetic and geoscientific models indicating significant runtime improvements provided by parallel local and focal operations. We further outline challenges in improving remaining algorithms such as flow operations over digital elevation maps and further potential improvements like enhancing disk I/O.

Decellularized scaffold of cryopreserved rat kidney retains its recellularization potential.

PubMed

Chani, Baldeep; Puri, Veena; Sobti, Ranbir C; Jha, Vivekanand; Puri, Sanjeev

2017-01-01

The multi-cellular nature of renal tissue makes it the most challenging organ for regeneration. Therefore, till date whole organ transplantations remain the definitive treatment for the end stage renal disease (ESRD). The shortage of available organs for the transplantation has, thus, remained a major concern as well as an unsolved problem. In this regard generation of whole organ scaffold through decellularization followed by regeneration of the whole organ by recellularization is being viewed as a potential alternative for generating functional tissues. Despite its growing interest, the optimal processing to achieve functional organ still remains unsolved. The biggest challenge remains is the time line for obtaining kidney. Keeping these facts in mind, we have assessed the effects of cryostorage (3 months) on renal tissue architecture and its potential for decellularization and recellularization in comparison to the freshly isolated kidneys. The light microscopy exploiting different microscopic stains as well as immuno-histochemistry and Scanning electron microscopy (SEM) demonstrated that ECM framework is well retained following kidney cryopreservation. The strength of these structures was reinforced by calculating mechanical stress which confirmed the similarity between the freshly isolated and cryopreserved tissue. The recellularization of these bio-scaffolds, with mesenchymal stem cells quickly repopulated the decellularized structures irrespective of the kidneys status, i.e. freshly isolated or the cryopreserved. The growth pattern employing mesenchymal stem cells demonstrated their equivalent recellularization potential. Based on these observations, it may be concluded that cryopreserved kidneys can be exploited as scaffolds for future development of functional organ.

A closer look at the FTEM framework. Response to "More of the same? Comment on 'An integrated framework for the optimisation of sport and athlete development: a practitioner approach'".

PubMed

Gulbin, Jason P; Croser, Morag J; Morley, Elissa J; Weissensteiner, Juanita R

2014-01-01

The Foundations, Talent, Elite and Mastery (FTEM) framework was designed through the lens of a world leading high-performance sport agency to assist sporting stakeholders operationalise and research their whole of sport development pathways (Gulbin, J. P., Croser, M. J., Morley, E. J., & Weissensteiner, J. R. (2013). An integrated framework for the optimisation of sport and athlete development: A practitioner approach. Journal of Sport Sciences, 31, 1319-1331). In response to the commentary by MacNamara and Collins (2013) (Journal of Sports Sciences, doi:10.1080/02640414.2013. 855805), it was possible to document many inaccurate, false and misleading statements based on inattentive reading of the original article. We reinforce that: FTEM is a holistic framework of sport and athlete development and not a surrogate for a talent identification ( TID) model; bio-psycho-social components of development are liberally embedded throughout the FTEM framework; and the combined research and applied insights of development practitioners provide strong ecological validity for the consideration of stakeholders looking to explore applied approaches to athlete pathway management.

A novel approach for pilot error detection using Dynamic Bayesian Networks.

PubMed

Saada, Mohamad; Meng, Qinggang; Huang, Tingwen

2014-06-01

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment's data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.

Biomechanics of Single Cortical Neurons

PubMed Central

Bernick, Kristin B.; Prevost, Thibault P.; Suresh, Subra; Socrate, Simona

2011-01-01

This study presents experimental results and computational analysis of the large strain dynamic behavior of single neurons in vitro with the objective of formulating a novel quantitative framework for the biomechanics of cortical neurons. Relying on the atomic force microscopy (AFM) technique, novel testing protocols are developed to enable the characterization of neural soma deformability over a range of indentation rates spanning three orders of magnitude – 10, 1, and 0.1 μm/s. Modified spherical AFM probes were utilized to compress the cell bodies of neonatal rat cortical neurons in load, unload, reload and relaxation conditions. The cell response showed marked hysteretic features, strong non-linearities, and substantial time/rate dependencies. The rheological data were complemented with geometrical measurements of cell body morphology, i.e. cross-diameter and height estimates. A constitutive model, validated by the present experiments, is proposed to quantify the mechanical behavior of cortical neurons. The model aimed to correlate empirical findings with measurable degrees of (hyper-) elastic resilience and viscosity at the cell level. The proposed formulation, predicated upon previous constitutive model developments undertaken at the cortical tissue level, was implemented into a three-dimensional finite element framework. The simulated cell response was calibrated to the experimental measurements under the selected test conditions, providing a novel single cell model that could form the basis for further refinements. PMID:20971217

Applying the Transactional Stress and Coping Model to Sickle Cell Disorder and Insulin-Dependent Diabetes Mellitus: Identifying Psychosocial Variables Related to Adjustment and Intervention

ERIC Educational Resources Information Center

Hocking, Matthew C.; Lochman, John E.

2005-01-01

This review paper examines the literature on psychosocial factors associated with adjustment to sickle cell disease and insulin-dependent diabetes mellitus in children through the framework of the transactional stress and coping (TSC) model. The transactional stress and coping model views adaptation to a childhood chronic illness as mediated by…

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

PubMed Central

Rahman, M. M.; Antani, S. K.; Thoma, G. R.

2011-01-01

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

Membrane potential dynamics of grid cells

PubMed Central

Domnisoru, Cristina; Kinkhabwala, Amina A.; Tank, David W.

2014-01-01

During navigation, grid cells increase their spike rates in firing fields arranged on a strikingly regular triangular lattice, while their spike timing is often modulated by theta oscillations. Oscillatory interference models of grid cells predict theta amplitude modulations of membrane potential during firing field traversals, while competing attractor network models predict slow depolarizing ramps. Here, using in-vivo whole-cell recordings, we tested these models by directly measuring grid cell intracellular potentials in mice running along linear tracks in virtual reality. Grid cells had large and reproducible ramps of membrane potential depolarization that were the characteristic signature tightly correlated with firing fields. Grid cells also exhibited intracellular theta oscillations that influenced their spike timing. However, the properties of theta amplitude modulations were not consistent with the view that they determine firing field locations. Our results support cellular and network mechanisms in which grid fields are produced by slow ramps, as in attractor models, while theta oscillations control spike timing. PMID:23395984

Effects of stiffness and volume on the transit time of an erythrocyte through a slit.

PubMed

Salehyar, Sara; Zhu, Qiang

2017-06-01

By using a fully coupled fluid-cell interaction model, we numerically simulate the dynamic process of a red blood cell passing through a slit driven by an incoming flow. The model is achieved by combining a multiscale model of the composite cell membrane with a boundary element fluid dynamics model based on the Stokes flow assumption. Our concentration is on the correlation between the transit time (the time it takes to finish the whole translocation process) and different conditions (flow speed, cell orientation, cell stiffness, cell volume, etc.) that are involved. According to the numerical prediction (with some exceptions), the transit time rises as the cell is stiffened. It is also highly sensitive to volume increase inside the cell. In general, even slightly swollen cells (i.e., the internal volume is increased while the surface area of the cell kept unchanged) travel dramatically slower through the slit. For these cells, there is also an increased chance of blockage.

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

DOE PAGES

Nguyen, Marcus; Brettin, Thomas; Long, S. Wesley; ...

2018-01-11

Here, antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to rapidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within ± 1 two-fold dilution factor, is 92%. Individual accuracies aremore » >= 90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.« less

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

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

Nguyen, Marcus; Brettin, Thomas; Long, S. Wesley

Here, antimicrobial resistant infections are a serious public health threat worldwide. Whole genome sequencing approaches to rapidly identify pathogens and predict antibiotic resistance phenotypes are becoming more feasible and may offer a way to reduce clinical test turnaround times compared to conventional culture-based methods, and in turn, improve patient outcomes. In this study, we use whole genome sequence data from 1668 clinical isolates of Klebsiella pneumoniae to develop a XGBoost-based machine learning model that accurately predicts minimum inhibitory concentrations (MICs) for 20 antibiotics. The overall accuracy of the model, within ± 1 two-fold dilution factor, is 92%. Individual accuracies aremore » >= 90% for 15/20 antibiotics. We show that the MICs predicted by the model correlate with known antimicrobial resistance genes. Importantly, the genome-wide approach described in this study offers a way to predict MICs for isolates without knowledge of the underlying gene content. This study shows that machine learning can be used to build a complete in silico MIC prediction panel for K. pneumoniae and provides a framework for building MIC prediction models for other pathogenic bacteria.« less

Targeting Phosphatidylserine for Radioimmunotherapy of Breast Cancer Brain Metastasis

DTIC Science & Technology

2015-12-01

response. e. Correlate imaging findings with histological studies of vascular damage, tumor cell and endothelial cell apoptosis or necrosis and vascular ...phosphatidylserine (PS) is exposed exclusively on tumor vascular endothelium of brain metastases in mouse models. A novel PS-targeting antibody, PGN635... vascular endothelial cells in multi-focal brain metastases throughout the whole mouse brain. Vascular endothelium in normal brain tissues is negative

The sweet taste of death: glucose triggers apoptosis during yeast chronological aging.

PubMed

Ruckenstuhl, Christoph; Carmona-Gutierrez, Didac; Madeo, Frank

2010-10-01

As time goes by, a postmitotic cell ages following a degeneration process ultimately ending in cell death. This phenomenon is evolutionary conserved and present in unicellular eukaryotes as well, making the yeast chronological aging system an appreciated model. Here, single cells die in a programmed fashion (both by apoptosis and necrosis) for the benefit of the whole population. Besides its meaning for aging and cell death research, age-induced programmed cell death represents the first experimental proof for the so-called group selection theory: Apoptotic genes became selected during evolution because of the benefits they might render to the whole cell culture and not to the individual cell. Many anti‐aging stimuli have been discovered in the yeast chronological aging system and have afterwards been confirmed in higher cells or organisms. New work from the Burhans group (this issue) now demonstrates that glucose signaling has a progeriatric effect on chronologically aged yeast cells: Glucose administration results in a diminished efficacy of cells to enter quiescence, finally causing superoxide‐mediated replication stress and apoptosis.

Choosing an Appropriate Modelling Framework for Analysing Multispecies Co-culture Cell Biology Experiments.

PubMed

Markham, Deborah C; Simpson, Matthew J; Baker, Ruth E

2015-04-01

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

NASA Astrophysics Data System (ADS)

Eftimie, Raluca

2015-03-01

One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

Orthographic Software Modelling: A Novel Approach to View-Based Software Engineering

NASA Astrophysics Data System (ADS)

Atkinson, Colin

The need to support multiple views of complex software architectures, each capturing a different aspect of the system under development, has been recognized for a long time. Even the very first object-oriented analysis/design methods such as the Booch method and OMT supported a number of different diagram types (e.g. structural, behavioral, operational) and subsequent methods such as Fusion, Kruchten's 4+1 views and the Rational Unified Process (RUP) have added many more views over time. Today's leading modeling languages such as the UML and SysML, are also oriented towards supporting different views (i.e. diagram types) each able to portray a different facets of a system's architecture. More recently, so called enterprise architecture frameworks such as the Zachman Framework, TOGAF and RM-ODP have become popular. These add a whole set of new non-functional views to the views typically emphasized in traditional software engineering environments.

SPIRIT: Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data. A Conceptual Best-practice Framework and Procedure Model.

PubMed

Hackl, W O; Ammenwerth, E

2016-01-01

Secondary use of clinical routine data is receiving an increasing amount of attention in biomedicine and healthcare. However, building and analysing integrated clinical routine data repositories are nontrivial, challenging tasks. As in most evolving fields, recognized standards, well-proven methodological frameworks, or accurately described best-practice approaches for the systematic planning of solutions for secondary use of routine medical record data are missing. We propose a conceptual best-practice framework and procedure model for the systematic planning of intelligent reuse of integrated clinical routine data (SPIRIT). SPIRIT was developed based on a broad literature overview and further refined in two case studies with different kinds of clinical routine data, including process-oriented nursing data from a large hospital group and high-volume multimodal clinical data from a neurologic intensive care unit. SPIRIT aims at tailoring secondary use solutions to specific needs of single departments without losing sight of the institution as a whole. It provides a general conceptual best-practice framework consisting of three parts: First, a secondary use strategy for the whole organization is determined. Second, comprehensive analyses are conducted from two different viewpoints to define the requirements regarding a clinical routine data reuse solution at the system level from the data perspective (BOTTOM UP) and at the strategic level from the future users perspective (TOP DOWN). An obligatory clinical context analysis (IN BETWEEN) facilitates refinement, combination, and integration of the different requirements. The third part of SPIRIT is dedicated to implementation, which comprises design and realization of clinical data integration and management as well as data analysis solutions. The SPIRIT framework is intended to be used to systematically plan the intelligent reuse of clinical routine data for multiple purposes, which often was not intended when the primary clinical documentation systems were implemented. SPIRIT helps to overcome this gap. It can be applied in healthcare institutions of any size or specialization and allows a stepwise setup and evolution of holistic clinical routine data reuse solutions.

Describing complex cells in primary visual cortex: a comparison of context and multi-filter LN models.

PubMed

Westö, Johan; May, Patrick J C

2018-05-02

Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multi-filter linear-nonlinear (LN) models and context models. Models are, however, never correct and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: First, we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions. Second, we evaluate context models and multi-filter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multi-filter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multi-filter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior.

Application of a disturbance-rejection controller for robotic-enhanced limb rehabilitation trainings.

PubMed

Madoński, R; Kordasz, M; Sauer, P

2014-07-01

The paper presents an application of a special case of an Active Disturbance Rejection Controller (ADRC) in governing a proper realization of basic limb rehabilitation trainings. The experimental study is performed on a model of a flexible joint manipulator, whose behavior resembles a real robotic rehabilitation device. The multidimensional character of the considered assisting mechanism makes it a nontrivial modeling and control problem. However, by the use of the ADRC approach, the modeling uncertainty in the plant is partially decoupled from the system, which increases the robustness of the whole control framework against both internal and external disturbances. © 2013 ISA. Published by ISA. All rights reserved.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Managing changes in the enterprise architecture modelling context

NASA Astrophysics Data System (ADS)

Khanh Dam, Hoa; Lê, Lam-Son; Ghose, Aditya

2016-07-01

Enterprise architecture (EA) models the whole enterprise in various aspects regarding both business processes and information technology resources. As the organisation grows, the architecture of its systems and processes must also evolve to meet the demands of the business environment. Evolving an EA model may involve making changes to various components across different levels of the EA. As a result, an important issue before making a change to an EA model is assessing the ripple effect of the change, i.e. change impact analysis. Another critical issue is change propagation: given a set of primary changes that have been made to the EA model, what additional secondary changes are needed to maintain consistency across multiple levels of the EA. There has been however limited work on supporting the maintenance and evolution of EA models. This article proposes an EA description language, namely ChangeAwareHierarchicalEA, integrated with an evolution framework to support both change impact analysis and change propagation within an EA model. The core part of our framework is a technique for computing the impact of a change and a new method for generating interactive repair plans from Alloy consistency rules that constrain the EA model.

Molecular identification of lipase LipA from Pseudomonas protegens Pf-5 and characterization of two whole-cell biocatalysts Pf-5 and Top10lipA.

PubMed

Zha, Daiming; Xu, Li; Zhang, Houjin; Yan, Yunjun

2014-05-01

To identify lipase LipA (PFL_0617) from Pseudomonas protegens Pf-5, a lipA deletion mutant (Pf0617) and a complementary strain (Pf0617lipA) were constructed, and their effects on the lipase production were examined. Pf0617 remarkably decreased its whole-cell lipase activity, whereas Pf0617lipA made its whole-cell lipase activity not only restore to wild-type level but also get a further increment. However, the deletion and overexpression of lipA did not affect the extracellular lipase activity. In addition, the unbroken whole cells of these strains were able to catalyze the hydrolysis of membrane-permeable p-nitrophenyl esters, but could not hydrolyze the membrane-impermeable olive oil. These results confirmed that LipA was an intracellular lipase and Pf-5 could also be used as a natural whole-cell biocatalyst. To evaluate the potential of Pf-5 as a whole-cell biocatalyst and separately characterize the whole-cell LipA, the properties of the whole-cell lipases from Pf-5 and Top10lipA were characterized. The results demonstrated that both Pf-5 and Top10lipA exhibited high tolerance to alkaline condition, high temperature, heavy metal ions, surfactants, and organic solvents. Taken together, lipA can realize functional expression in E. coli Top10, and Pf-5 and Top10lipA as whole-cell biocatalysts may have enormous potential in applications.

Supervised graph hashing for histopathology image retrieval and classification.

PubMed

Shi, Xiaoshuang; Xing, Fuyong; Xu, KaiDi; Xie, Yuanpu; Su, Hai; Yang, Lin

2017-12-01

In pathology image analysis, morphological characteristics of cells are critical to grade many diseases. With the development of cell detection and segmentation techniques, it is possible to extract cell-level information for further analysis in pathology images. However, it is challenging to conduct efficient analysis of cell-level information on a large-scale image dataset because each image usually contains hundreds or thousands of cells. In this paper, we propose a novel image retrieval based framework for large-scale pathology image analysis. For each image, we encode each cell into binary codes to generate image representation using a novel graph based hashing model and then conduct image retrieval by applying a group-to-group matching method to similarity measurement. In order to improve both computational efficiency and memory requirement, we further introduce matrix factorization into the hashing model for scalable image retrieval. The proposed framework is extensively validated with thousands of lung cancer images, and it achieves 97.98% classification accuracy and 97.50% retrieval precision with all cells of each query image used. Copyright © 2017 Elsevier B.V. All rights reserved.

Mechanochemical models of processive molecular motors

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Sun, Sean X.

2012-05-01

Motor proteins are the molecular engines powering the living cell. These nanometre-sized molecules convert chemical energy, both enthalpic and entropic, into useful mechanical work. High resolution single molecule experiments can now observe motor protein movement with increasing precision. The emerging data must be combined with structural and kinetic measurements to develop a quantitative mechanism. This article describes a modelling framework where quantitative understanding of motor behaviour can be developed based on the protein structure. The framework is applied to myosin motors, with emphasis on how synchrony between motor domains give rise to processive unidirectional movement. The modelling approach shows that the elasticity of protein domains are important in regulating motor function. Simple models of protein domain elasticity are presented. The framework can be generalized to other motor systems, or an ensemble of motors such as muscle contraction. Indeed, for hundreds of myosins, our framework can be reduced to the Huxely-Simmons description of muscle movement in the mean-field limit.

Diffusion-convection effects on drug distribution at the cell membrane level in a patch-clamp setup.

PubMed

Baran, Irina; Iftime, Adrian; Popescu, Anca

2010-01-01

We present a model-based method for estimating the effective concentration of the active drug applied by a pressure pulse to an individual cell in a patch-clamp setup, which could be of practical use in the analysis of ligand-induced whole-cell currents recorded in patch-clamp experiments. Our modelling results outline several important factors which may be involved in the high variability of the electric response of the cells, and indicate that with a pressure pulse duration of 1s and diameter of the perfusion tip of 600 μm, elevated amounts of drug can accumulate locally between the pipette tip and the cell. Hence, the effective agonist concentration at the cell membrane level can be consistently higher than the initial concentration inside the perfusion tubes. We performed finite-difference and finite-element simulations to investigate the diffusion/convection effects on the agonist distribution on the cell membrane. Our model can explain the delay between the commencement of acetylcholine application and the onset of the whole-cell current that we recorded on human rhabdomyosarcoma TE671 cells, and reproduce quantitatively the decrease of signal latency with the concentration of agonist in the pipette. Results also show that not only the geometry of the bath chamber and pipette tip, but also the transport parameters of the diffusive and convective phenomena in the bath solution are determinant for the amplitude and kinetics of the recorded currents and have to be accounted for when analyzing patch-clamp data. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

NASA Astrophysics Data System (ADS)

Comi, Troy J.; Neumann, Elizabeth K.; Do, Thanh D.; Sweedler, Jonathan V.

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. [Figure not available: see fulltext.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

PubMed

Comi, Troy J; Neumann, Elizabeth K; Do, Thanh D; Sweedler, Jonathan V

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ.

An ice sheet model validation framework for the Greenland ice sheet.

PubMed

Price, Stephen F; Hoffman, Matthew J; Bonin, Jennifer A; Howat, Ian M; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P; Evans, Katherine J; Kennedy, Joseph H; Lenaerts, Jan; Lipscomb, William H; Perego, Mauro; Salinger, Andrew G; Tuminaro, Raymond S; van den Broeke, Michiel R; Nowicki, Sophie M J

2017-01-01

We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

NASA Astrophysics Data System (ADS)

Delile, Julien; Herrmann, Matthieu; Peyriéras, Nadine; Doursat, René

2017-01-01

The study of multicellular development is grounded in two complementary domains: cell biomechanics, which examines how physical forces shape the embryo, and genetic regulation and molecular signalling, which concern how cells determine their states and behaviours. Integrating both sides into a unified framework is crucial to fully understand the self-organized dynamics of morphogenesis. Here we introduce MecaGen, an integrative modelling platform enabling the hypothesis-driven simulation of these dual processes via the coupling between mechanical and chemical variables. Our approach relies upon a minimal `cell behaviour ontology' comprising mesenchymal and epithelial cells and their associated behaviours. MecaGen enables the specification and control of complex collective movements in 3D space through a biologically relevant gene regulatory network and parameter space exploration. Three case studies investigating pattern formation, epithelial differentiation and tissue tectonics in zebrafish early embryogenesis, the latter with quantitative comparison to live imaging data, demonstrate the validity and usefulness of our framework.

Probing eukaryotic cell mechanics via mesoscopic simulations

PubMed Central

Shang, Menglin; Lim, Chwee Teck

2017-01-01

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

Evolutionary scalpels for dissecting tumor ecosystems

PubMed Central

Rosenbloom, Daniel I. S.; Camara, Pablo G.; Chu, Tim; Rabadan, Raul

2017-01-01

Amidst the growing literature on cancer genomics and intratumor heterogeneity, essential principles in evolutionary biology recur time and time again. Here we use these principles to guide the reader through major advances in cancer research, highlighting issues of “hit hard, hit early” treatment strategies, drug resistance, and metastasis. We distinguish between two frameworks for understanding heterogeneous tumors, both of which can inform treatment strategies: (1) The tumor as diverse ecosystem, a Darwinian population of sometimes-competing, sometimes-cooperating cells; (2) The tumor as tightly integrated, self-regulating organ, which may hijack developmental signals to restore functional heterogeneity after treatment. While the first framework dominates literature on cancer evolution, the second framework enjoys support as well. Throughout this review, we illustrate how mathematical models inform understanding of tumor progression and treatment outcomes. Connecting models to genomic data faces computational and technical hurdles, but high-throughput single-cell technologies show promise to clear these hurdles. PMID:27923679

Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation: Report of an FDA Public Workshop.

PubMed

Zhang, X; Duan, J; Kesisoglou, F; Novakovic, J; Amidon, G L; Jamei, M; Lukacova, V; Eissing, T; Tsakalozou, E; Zhao, L; Lionberger, R

2017-08-01

On May 19, 2016, the US Food and Drug Administration (FDA) hosted a public workshop, entitled "Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation." The topic of mechanistic oral absorption modeling, which is one of the major applications of physiologically based pharmacokinetic (PBPK) modeling and simulation, focuses on predicting oral absorption by mechanistically integrating gastrointestinal transit, dissolution, and permeation processes, incorporating systems, active pharmaceutical ingredient (API), and the drug product information, into a systemic mathematical whole-body framework. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Identification and characterization of Vibrio cholerae surface proteins by radioiodination.

PubMed Central

Richardson, K; Parker, C D

1985-01-01

Whole cells and isolated outer membrane from Vibrio cholerae (Classical, Inaba) were radiolabeled with Iodogen or Iodo-beads as catalyst. Radiolabeling of whole cells was shown to be surface specific by sodium dodecyl sulfate-urea polyacrylamide gel electrophoresis of whole cells and cell fractions. Surface-labeled whole cells regularly showed 16 distinguishable protein species, of which nine were found in radiolabeled outer membrane preparations obtained by a lithium chloride-lithium acetate procedure. Eight of these proteins were found in outer membranes prepared by sucrose density gradient centrifugation and Triton X-100 extraction of radiolabeled whole cells. The mobility of several proteins was shown to be affected by temperature, and the major protein species exposed on the cell surface was shown to consist of at least two different peptides. Images PMID:3980099

Highly dense, optically inactive silica microbeads for the isolation and identification of circulating tumor cells.

PubMed

Yoo, Chang Eun; Moon, Hui-Sung; Kim, Yeon Jeong; Park, Jong-Myeon; Park, Donghyun; Han, Kyung-Yeon; Park, Keunchil; Sun, Jong-Mu; Park, Woong-Yang

2016-01-01

Efficient isolation of circulating tumor cells (CTCs) from whole blood is a major challenge for the clinical application of CTCs. Here, we report an efficient method to isolate CTCs from whole blood using highly dense and transparent silica microbeads. The surfaces of silica microbeads were fully covered with an antibody to capture CTCs, and blocked by zwitterionic moieties to prevent the non-specific adsorption of blood cells. Owing to the high density of the silica microbeads, the complexation of CTCs with silica microbeads resulted in the efficient sedimentation of CTC-microbead complexes, which enabled their discrimination from other blood cells in density gradient media. Model CTCs (MCF-7, HCC827, and SHP-77) with various levels of epithelial cell adhesion molecule (EpCAM) were isolated efficiently, especially those with low EpCAM expression (SHP-77). Moreover, the transparency of silica microbeads enabled CTCs to be clearly identified without interference caused by microbeads. The improved sensitivity resulted in increased CTC recovery from patient samples compared with the FDA-approved CellSearch system (14/15 using our method; 5/15 using the CellSearch system). These results indicate that the isolation method described in this report constitutes a powerful tool for the isolation of CTCs from whole blood, which has important applications in clinical practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nitric oxide measurements in hTERT-RPE cells and subcellular fractions exposed to low levels of red light

NASA Astrophysics Data System (ADS)

Wigle, Jeffrey C.; Castellanos, Cherry C.; Denton, Michael L.; Holwitt, Eric A.

2014-02-01

Cells in a tissue culture model for laser eye injury exhibit increased resistance to a lethal pulse of 2.0-μm laser radiation if the cells are first exposed to 2.88 J/cm2 of red light 24 hr prior to the lethal laser exposure. Changes in expression of various genes associated with apoptosis have been observed, but the biochemical link between light absorption and gene expression remains unknown. Cytochome c oxidase (CCOX), in the electron transport chain, is the currentlyhypothesized absorber. Absorption of the red light by CCOX is thought to facilitate displacement of nitric oxide (NO) by O2 in the active site, increasing cellular respiration and intracellular ATP. However, NO is also an important regulator and mediator of numerous physiological processes in a variety of cell and tissue types that is synthesized from l-arginine by NO synthases. In an effort to determine the relative NO contributions from these competing pathways, we measured NO levels in whole cells and subcellular fractions, with and without exposure to red light, using DAF-FM, a fluorescent dye that stoichiometrically reacts with NO. Red light induced a small, but consistently reproducible, increase in fluorescence intensity in whole cells and some subcellular fractions. Whole cells exhibited the highest overall fluorescence intensity followed by (in order) cytosolic proteins, microsomes, then nuclei and mitochondria.

[Multilocus genotyping of polymorphous STR-loci of chromosomal DNA in individual cells: technical difficulties].

PubMed

Ivanov, P L; Leonov, S N; Zemskova, E Iu; Kobylianskiĭ, A G; Dziubenko, E V

2013-01-01

This study was designed to estimate the effectiveness of special technical procedures for the enhancement of sensitivity of multiplex analysis of DNA, such as the use of low-plexity PCR systems and the whole genome preamplification technology, and the possibility of their application for the purpose of forensic medical genotyping of polymorphous STR-loci of chromosomal DNA in individual cells. The authors refused to use the imitation model (equivalent DNA dilutions) for the sake of obtaining the maximally informative data and chose to work with real preparations of solitary buccal epithelial cells isolated by the laser microdissection technique. It was shown that neither the use of the low-plexity multilocus PCR systems nor the whole genome pre-amplification technology makes possible reliable genotyping of STR-loci of chromosomal DNA in individual cells. The proposed techniques allow for DNA genotyping in preparations consisting of 10 diploid cells whereas the methods for reliable genotyping of STR-loci of chromosomal DNA in individual cells remains to be developed.

Magnetic fingerprints of rolling cells for quantitative flow cytometry in whole blood

NASA Astrophysics Data System (ADS)

Reisbeck, Mathias; Helou, Michael Johannes; Richter, Lukas; Kappes, Barbara; Friedrich, Oliver; Hayden, Oliver

2016-09-01

Over the past 50 years, flow cytometry has had a profound impact on preclinical and clinical applications requiring single cell function information for counting, sub-typing and quantification of epitope expression. At the same time, the workflow complexity and high costs of such optical systems still limit flow cytometry applications to specialized laboratories. Here, we present a quantitative magnetic flow cytometer that incorporates in situ magnetophoretic cell focusing for highly accurate and reproducible rolling of the cellular targets over giant magnetoresistance sensing elements. Time-of-flight analysis is used to unveil quantitative single cell information contained in its magnetic fingerprint. Furthermore, we used erythrocytes as a biological model to validate our methodology with respect to precise analysis of the hydrodynamic cell diameter, quantification of binding capacity of immunomagnetic labels, and discrimination of cell morphology. The extracted time-of-flight information should enable point-of-care quantitative flow cytometry in whole blood for clinical applications, such as immunology and primary hemostasis.

Brain metastases of breast cancer.

PubMed

Palmieri, Diane; Smith, Quentin R; Lockman, Paul R; Bronder, Julie; Gril, Brunilde; Chambers, Ann F; Weil, Robert J; Steeg, Patricia S

Central nervous system or brain metastases traditionally occur in 10-16% of metastatic breast cancer patients and are associated with a dismal prognosis. The development of brain metastases has been associated with young age, and tumors that are estrogen receptor negative, Her-2+ or of the basal phenotype. Treatment typically includes whole brain irradiation, or either stereotactic radiosurgery or surgery with whole brain radiation, resulting in an approximately 20% one year survival. The blood-brain barrier is a formidable obstacle to the delivery of chemotherapeutics to the brain. Mouse experimental metastasis model systems have been developed for brain metastasis using selected sublines of human MDA-MB-231 breast carcinoma cells. Using micron sized iron particles and MRI imaging, the fate of MDA-MB-231BR cells has been mapped: Approximately 2% of injected cells form larger macroscopic metastases, while 5% of cells remain as dormant cells in the brain. New therapies with permeability for the blood-brain barrier are needed to counteract both types of tumor cells.

Epidermal growth factor receptor subunit locations determined in hydrated cells with environmental scanning electron microscopy.

PubMed

Peckys, Diana B; Baudoin, Jean-Pierre; Eder, Magdalena; Werner, Ulf; de Jonge, Niels

2013-01-01

Imaging single epidermal growth factor receptors (EGFR) in intact cells is presently limited by the available microscopy methods. Environmental scanning electron microscopy (ESEM) of whole cells in hydrated state in combination with specific labeling with gold nanoparticles was used to localize activated EGFRs in the plasma membranes of COS7 and A549 cells. The use of a scanning transmission electron microscopy (STEM) detector yielded a spatial resolution of 3 nm, sufficient to identify the locations of individual EGFR dimer subunits. The sizes and distribution of dimers and higher order clusters of EGFRs were determined. The distance between labels bound to dimers amounted to 19 nm, consistent with a molecular model. A fraction of the EGFRs was found in higher order clusters with sizes ranging from 32-56 nm. ESEM can be used for quantitative whole cell screening studies of membrane receptors, and for the study of nanoparticle-cell interactions in general.

Epidermal growth factor receptor subunit locations determined in hydrated cells with environmental scanning electron microscopy

PubMed Central

Peckys, Diana B.; Baudoin, Jean-Pierre; Eder, Magdalena; Werner, Ulf; de Jonge, Niels

2013-01-01

Imaging single epidermal growth factor receptors (EGFR) in intact cells is presently limited by the available microscopy methods. Environmental scanning electron microscopy (ESEM) of whole cells in hydrated state in combination with specific labeling with gold nanoparticles was used to localize activated EGFRs in the plasma membranes of COS7 and A549 cells. The use of a scanning transmission electron microscopy (STEM) detector yielded a spatial resolution of 3 nm, sufficient to identify the locations of individual EGFR dimer subunits. The sizes and distribution of dimers and higher order clusters of EGFRs were determined. The distance between labels bound to dimers amounted to 19 nm, consistent with a molecular model. A fraction of the EGFRs was found in higher order clusters with sizes ranging from 32–56 nm. ESEM can be used for quantitative whole cell screening studies of membrane receptors, and for the study of nanoparticle-cell interactions in general. PMID:24022088

Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

NASA Astrophysics Data System (ADS)

Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

2016-03-01

The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

Parameter uncertainty analysis of a biokinetic model of caesium

DOE PAGES

Li, W. B.; Klein, W.; Blanchardon, Eric; ...

2014-04-17

Parameter uncertainties for the biokinetic model of caesium (Cs) developed by Leggett et al. were inventoried and evaluated. The methods of parameter uncertainty analysis were used to assess the uncertainties of model predictions with the assumptions of model parameter uncertainties and distributions. Furthermore, the importance of individual model parameters was assessed by means of sensitivity analysis. The calculated uncertainties of model predictions were compared with human data of Cs measured in blood and in the whole body. It was found that propagating the derived uncertainties in model parameter values reproduced the range of bioassay data observed in human subjects atmore » different times after intake. The maximum ranges, expressed as uncertainty factors (UFs) (defined as a square root of ratio between 97.5th and 2.5th percentiles) of blood clearance, whole-body retention and urinary excretion of Cs predicted at earlier time after intake were, respectively: 1.5, 1.0 and 2.5 at the first day; 1.8, 1.1 and 2.4 at Day 10 and 1.8, 2.0 and 1.8 at Day 100; for the late times (1000 d) after intake, the UFs were increased to 43, 24 and 31, respectively. The model parameters of transfer rates between kidneys and blood, muscle and blood and the rate of transfer from kidneys to urinary bladder content are most influential to the blood clearance and to the whole-body retention of Cs. For the urinary excretion, the parameters of transfer rates from urinary bladder content to urine and from kidneys to urinary bladder content impact mostly. The implication and effect on the estimated equivalent and effective doses of the larger uncertainty of 43 in whole-body retention in the later time, say, after Day 500 will be explored in a successive work in the framework of EURADOS.« less

Single Folding Optical Potential for Elastic Scattering of Protons from 14N and 16O in a Wide Range of Energies

NASA Astrophysics Data System (ADS)

Hamada, Sh.

2018-03-01

Available experimental data for protons elastically scattered from 14N and 16O target nuclei are reanalyzed within the framework of single folding optical potential (SFOP) model. In this model, the real part of the potential is derived on the basis of single folding potential. The renormalization factor N r is extracted for the two aforementioned nuclear systems. Theoretical calculations fairly reproduce the experimental data in the whole angular range. Energy dependence of real and imaginary volume integrals as well as reaction cross sections are discussed.

Going beyond the X

ERIC Educational Resources Information Center

Robertson, Carol

2018-01-01

How much do students really know about chromosomes? This article describes a partner activity and then a whole-class activity that use modeling to teach DNA replication, connect it to the shape of chromosomes during mitosis, and help students understand how daughter cells have the same DNA. Modeling is integral to science, helping students…

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry.

PubMed

García, Míriam R; Vázquez, José A; Teixeira, Isabel G; Alonso, Antonio A

2017-01-01

A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

A mathematical framework for modelling cambial surface evolution using a level set method

PubMed Central

Sellier, Damien; Plank, Michael J.; Harrington, Jonathan J.

2011-01-01

Background and Aims During their lifetime, tree stems take a series of successive nested shapes. Individual tree growth models traditionally focus on apical growth and architecture. However, cambial growth, which is distributed over a surface layer wrapping the whole organism, equally contributes to plant form and function. This study aims at providing a framework to simulate how organism shape evolves as a result of a secondary growth process that occurs at the cellular scale. Methods The development of the vascular cambium is modelled as an expanding surface using the level set method. The surface consists of multiple compartments following distinct expansion rules. Growth behaviour can be formulated as a mathematical function of surface state variables and independent variables to describe biological processes. Key Results The model was coupled to an architectural model and to a forest stand model to simulate cambium dynamics and wood formation at the scale of the organism. The model is able to simulate competition between cambia, surface irregularities and local features. Predicting the shapes associated with arbitrarily complex growth functions does not add complexity to the numerical method itself. Conclusions Despite their slenderness, it is sometimes useful to conceive of trees as expanding surfaces. The proposed mathematical framework provides a way to integrate through time and space the biological and physical mechanisms underlying cambium activity. It can be used either to test growth hypotheses or to generate detailed maps of wood internal structure. PMID:21470972

An ovarian bioreactor for in vitro culture of the whole bovine ovary: a preliminary report.

PubMed

Zanotelli, Matthew R; Henningsen, Joseph D; Hopkins, Patrick M; Dederich, Aaron P; Herman, Tessa; Puccinelli, Tracy J; Salih, Sana M

2016-08-04

Improved cancer therapeutics and enhanced cancer survivorship have emphasized the severe long-term side effects of chemotherapy. Specifically, studies have linked many chemotherapy agents with primary ovarian insufficiency, although an exact insult model has not yet been determined. To investigate and ultimately solve this problem, a novel device for extended study of mammalian ovaries in vitro was developed. A bioreactor was fabricated for bovine ovarian culture that provides intravascular delivery of media to the ovary through isolation and cannulation of a main ovarian artery branch. Whole ovaries were cultured in vitro using three methods: (1) continuously supplied fresh culture media, (2) recirculated culture media, or (3) continuously supplied fresh culture media supplemented with 500 nM doxorubicin for 24 or 48 h. TUNEL assay was used to assess apoptotic cell percentages in the three groups as compared to uncultured baseline ovaries. The ovary culture method was shown to maintain cell viability by effectively delivering nutrient-enriched pH-balanced media at a constant flow rate. Lower apoptosis observed in ovaries cultured in continuously supplied fresh culture media illustrates that this culture device and method are the first to sustain whole bovine ovary viability for 48 h. Meanwhile, the increase in the percentage of cell apoptosis with doxorubicin treatment indicates that the device can provide an alternative model for testing chemotherapy and chemoprotection treatments to prevent primary ovarian insufficiency in cancer patients. An ovarian bioreactor with consistent culture media flow through an ovarian vasculature-assisted approach maintains short-term whole bovine ovary viability.

Separation of granulocytes from whole blood by leukoadhesion, phase 1

NASA Technical Reports Server (NTRS)

1976-01-01

Capillary glass tubes are investigated for the separation and retrieval of large quantities of viable granulocytes and monocytes from whole blood on a continuous basis from a single donor. This effort represented the feasibility demonstration of a three phase program for development of a capillary tube cell separation device. The activity included the analysis and parametric laboratory testing with subscale models required to design a prototype device. Capillary tubes 40 cm long with a nominal 0.030 cm internal diameter yielded the highest total process efficiency. Recovery efficiencies as high as 89% of the adhering cell population were obtained. Granulocyte phagocytosis of latex particles indicated approximately 90% viability. Monocytes recovered from the separation column retained their capability to stimulate human bone marrow colony growth, as demonstrated in an in vitro cell culture assay.

Crypt dynamics and colorectal cancer: advances in mathematical modelling.

PubMed

van Leeuwen, I M M; Byrne, H M; Jensen, O E; King, J R

2006-06-01

Mathematical modelling forms a key component of systems biology, offering insights that complement and stimulate experimental studies. In this review, we illustrate the role of theoretical models in elucidating the mechanisms involved in normal intestinal crypt dynamics and colorectal cancer. We discuss a range of modelling approaches, including models that describe cell proliferation, migration, differentiation, crypt fission, genetic instability, APC inactivation and tumour heterogeneity. We focus on the model assumptions, limitations and applications, rather than on the technical details. We also present a new stochastic model for stem-cell dynamics, which predicts that, on average, APC inactivation occurs more quickly in the stem-cell pool in the absence of symmetric cell division. This suggests that natural niche succession may protect stem cells against malignant transformation in the gut. Finally, we explain how we aim to gain further understanding of the crypt system and of colorectal carcinogenesis with the aid of multiscale models that cover all levels of organization from the molecular to the whole organ.

Construction of the yeast whole-cell Rhizopus oryzae lipase biocatalyst with high activity.

PubMed

Chen, Mei-ling; Guo, Qin; Wang, Rui-zhi; Xu, Juan; Zhou, Chen-wei; Ruan, Hui; He, Guo-qing

2011-07-01

Surface display is effectively utilized to construct a whole-cell biocatalyst. Codon optimization has been proven to be effective in maximizing production of heterologous proteins in yeast. Here, the cDNA sequence of Rhizopus oryzae lipase (ROL) was optimized and synthesized according to the codon bias of Saccharomyces cerevisiae, and based on the Saccharomyces cerevisiae cell surface display system with α-agglutinin as an anchor, recombinant yeast displaying fully codon-optimized ROL with high activity was successfully constructed. Compared with the wild-type ROL-displaying yeast, the activity of the codon-optimized ROL yeast whole-cell biocatalyst (25 U/g dried cells) was 12.8-fold higher in a hydrolysis reaction using p-nitrophenyl palmitate (pNPP) as the substrate. To our knowledge, this was the first attempt to combine the techniques of yeast surface display and codon optimization for whole-cell biocatalyst construction. Consequently, the yeast whole-cell ROL biocatalyst was constructed with high activity. The optimum pH and temperature for the yeast whole-cell ROL biocatalyst were pH 7.0 and 40 °C. Furthermore, this whole-cell biocatalyst was applied to the hydrolysis of tributyrin and the resulted conversion of butyric acid reached 96.91% after 144 h.

Animal cell hydraulics.

PubMed

Charras, Guillaume T; Mitchison, Timothy J; Mahadevan, L

2009-09-15

Water is the dominant ingredient of cells and its dynamics are crucial to life. We and others have suggested a physical picture of the cell as a soft, fluid-infiltrated sponge, surrounded by a water-permeable barrier. To understand water movements in an animal cell, we imposed an external, inhomogeneous osmotic stress on cultured cancer cells. This forced water through the membrane on one side, and out on the other. Inside the cell, it created a gradient in hydration, that we visualized by tracking cellular responses using natural organelles and artificially introduced quantum dots. The dynamics of these markers at short times were the same for normal and metabolically poisoned cells, indicating that the cellular responses are primarily physical rather than chemical. Our finding of an internal gradient in hydration is inconsistent with a continuum model for cytoplasm, but consistent with the sponge model, and implies that the effective pore size of the sponge is small enough to retard water flow significantly on time scales ( approximately 10-100 seconds) relevant to cell physiology. We interpret these data in terms of a theoretical framework that combines mechanics and hydraulics in a multiphase poroelastic description of the cytoplasm and explains the experimentally observed dynamics quantitatively in terms of a few coarse-grained parameters that are based on microscopically measurable structural, hydraulic and mechanical properties. Our fluid-filled sponge model could provide a unified framework to understand a number of disparate observations in cell morphology and motility.

Anaesthetic modulation of nicotinic ion channel kinetics in bovine chromaffin cells.

PubMed Central

Charlesworth, P; Richards, C D

1995-01-01

1. We have investigated the action of the anaesthetics methoxyflurane, methohexitone and etomidate on the nicotinic acetylcholine receptor channel of bovine adrenal chromaffin cells using the whole cell patch clamp technique. 2. Spectral analysis of macroscopic currents evoked by 25 microM carbachol revealed that each of the agents tested reduced the lifetime of the channel open state in a dose-dependent manner. The whole cell current was inhibited in a concentration-dependent fashion by each agent. 3. Channel gating parameters were calculated from single channel studies and the results used to test models explaining the modulation of nicotinic acetylcholine receptor channels by anaesthetics. 4. Each of the agents studied reduced the mean channel open time in a concentration-dependent manner. Anaesthetic concentrations reducing mean open time by 50% were: 370 microM methoxyflurane, 30 microM methohexitone or 23 microM etomidate. 5. Methohexitone and etomidate produced an increase in the number of brief closures within bursts, while no such increase was observed with methoxyflurane. Despite these inter-burst gaps, mean burst length was reduced by each of the agents tested. 6. It is concluded that a simple sequential blocking model fails to account for the action of these anaesthetics. An extended model, in which blocked channels can close, may be applicable. PMID:7773553

An Off-Lattice Hybrid Discrete-Continuum Model of Tumor Growth and Invasion

PubMed Central

Jeon, Junhwan; Quaranta, Vito; Cummings, Peter T.

2010-01-01

Abstract We have developed an off-lattice hybrid discrete-continuum (OLHDC) model of tumor growth and invasion. The continuum part of the OLHDC model describes microenvironmental components such as matrix-degrading enzymes, nutrients or oxygen, and extracellular matrix (ECM) concentrations, whereas the discrete portion represents individual cell behavior such as cell cycle, cell-cell, and cell-ECM interactions and cell motility by the often-used persistent random walk, which can be depicted by the Langevin equation. Using this framework of the OLHDC model, we develop a phenomenologically realistic and bio/physically relevant model that encompasses the experimentally observed superdiffusive behavior (at short times) of mammalian cells. When systemic simulations based on the OLHDC model are performed, tumor growth and its morphology are found to be strongly affected by cell-cell adhesion and haptotaxis. There is a combination of the strength of cell-cell adhesion and haptotaxis in which fingerlike shapes, characteristic of invasive tumor, are observed. PMID:20074513

A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression.

PubMed

Saha, Budhaditya; Nguyen, Thin; Phung, Dinh; Venkatesh, Svetha

2016-07-01

Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental disorders often occur in combinations, e.g., a patient with an anxiety disorder may also develop depression. This co-occurring mental health condition provides the focus for our work on classifying online communities with an interest in depression. For this, we have crawled a large body of 620 000 posts made by 80 000 users in 247 online communities. We have extracted the topics and psycholinguistic features expressed in the posts, using these as inputs to our model. Following a machine learning technique, we have formulated a joint modeling framework in order to classify mental health-related co-occurring online communities from these features. Finally, we performed empirical validation of the model on the crawled dataset where our model outperforms recent state-of-the-art baselines.

Overcoming food allergy through acquired tolerance conferred by transfer of Tregs in a murine model.

PubMed

Yamashita, H; Takahashi, K; Tanaka, H; Nagai, H; Inagaki, N

2012-02-01

The number of food allergy patients is increasing. Some children outgrow their food allergies through tolerance, whereas others remain susceptible throughout their lives. We aimed to contribute to food allergy therapeutics by understanding induction of oral tolerance in a murine food allergy model. We modified an existing murine food allergy model by using ovalbumin (OVA) to induce oral tolerance, either by pretreating mice with OVA or by transferring mesenteric lymph node (MLN) cells or T cells derived from mice treated with OVA. Pretreatment with OVA prevented food allergy, with complete suppression of OVA-specific immunoglobulin (Ig)E and IgA antibody production and interleukin (IL)-4, IL-10, and IL-9 mRNA expression. The proportion of regulatory T cells (Tregs) in MLN cells and expression of transforming growth factor-β mRNA increased. In the transfer model, anaphylaxis secondary to OVA intake was suppressed by transfer of whole MLN cells and Tregs from OVA-treated mice. However, OVA-specific IgE and IgA expressions were partially attenuated by transfer of antigen-specific and nonspecific Tregs, but not by whole MLN cells from OVA-treated mice. In the Treg transfer model, IL-4 and IL-10 mRNA expression decreased, but IL-9 mRNA expression increased. We concluded that oral tolerance for food antigens is induced in two ways: (i) by initial exposure to antigen, or inherent tolerance, and (ii) by transfer of Tregs, or acquired tolerance. Because food allergies occur when inherent tolerance is absent, understanding of acquired tolerance is important for the development of therapies for food allergy. © 2011 John Wiley & Sons A/S.

Statistical characterization of spatial patterns of rainfall cells in extratropical cyclones

NASA Astrophysics Data System (ADS)

Bacchi, Baldassare; Ranzi, Roberto; Borga, Marco

1996-11-01

The assumption of a particular type of distribution of rainfall cells in space is needed for the formulation of several space-time rainfall models. In this study, weather radar-derived rain rate maps are employed to evaluate different types of spatial organization of rainfall cells in storms through the use of distance functions and second-moment measures. In particular the spatial point patterns of the local maxima of rainfall intensity are compared to a completely spatially random (CSR) point process by applying an objective distance measure. For all the analyzed radar maps the CSR assumption is rejected, indicating that at the resolution of the observation considered, rainfall cells are clustered. Therefore a theoretical framework for evaluating and fitting alternative models to the CSR is needed. This paper shows how the "reduced second-moment measure" of the point pattern can be employed to estimate the parameters of a Neyman-Scott model and to evaluate the degree of adequacy to the experimental data. Some limitations of this theoretical framework, and also its effectiveness, in comparison to the use of scaling functions, are discussed.

Fiber-optic multiphoton flow cytometry in whole blood and in vivo

NASA Astrophysics Data System (ADS)

Chang, Yu-Chung; Ye, Jing Yong; Thomas, Thommey P.; Cao, Zhengyi; Kotlyar, Alina; Tkaczyk, Eric R.; Baker, James R.; Norris, Theodore B.

2010-07-01

Circulating tumor cells in the bloodstream are sensitive indicators for metastasis and disease prognosis. Circulating cells have usually been monitored via extraction from blood, and more recently in vivo using free-space optics; however, long-term intravital monitoring of rare circulating cells remains a major challenge. We demonstrate the application of a two-photon-fluorescence optical fiber probe for the detection of cells in whole blood and in vivo. A double-clad fiber was used to enhance the detection sensitivity. Two-channel detection was employed to enable simultaneous measurement of multiple fluorescent markers. Because the fiber probe circumvents scattering and absorption from whole blood, the detected signal strength from fluorescent cells was found to be similar in phosphate-buffered saline (PBS) and in whole blood. The detection efficiency of cells labeled with the membrane-binding dye 1,1'-dioctadecyl-3,3,3',3'-tetramethylindoldicarbocyanine, 4-chlorobenzenesulfonate (DiD) was demonstrated to be the same in PBS and in whole blood. A high detection efficiency of green fluorescent protein (GFP)-expressing cells in whole blood was also demonstrated. To characterize in vivo detection, DiD-labeled untransfected and GFP-transfected cells were injected into live mice, and the cell circulation dynamics was monitored in real time. The detection efficiency of GFP-expressing cells in vivo was consistent with that observed ex vivo in whole blood.

Novel in vitro and mathematical models for the prediction of chemical toxicity.

PubMed

Williams, Dominic P; Shipley, Rebecca; Ellis, Marianne J; Webb, Steve; Ward, John; Gardner, Iain; Creton, Stuart

2013-01-01

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. The scientific basis of drug safety is very complex and currently remains poorly understood, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ∼21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of (1) the physiological gap between cells currently used and human hepatocytes existing in their native state, (2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, (3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, (4) lack of consideration of systemic effects. Reproduction of centrilobular and periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen and hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science.

Novel in vitro and mathematical models for the prediction of chemical toxicity

PubMed Central

Shipley, Rebecca; Ellis, Marianne J.; Webb, Steve; Ward, John; Gardner, Iain; Creton, Stuart

2013-01-01

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. The scientific basis of drug safety is very complex and currently remains poorly understood, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ∼21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of (1) the physiological gap between cells currently used and human hepatocytes existing in their native state, (2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, (3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, (4) lack of consideration of systemic effects. Reproduction of centrilobular and periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen and hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science. PMID:26966512

Multiscale Modeling of Antibody-Drug Conjugates: Connecting Tissue and Cellular Distribution to Whole Animal Pharmacokinetics and Potential Implications for Efficacy.

PubMed

Cilliers, Cornelius; Guo, Hans; Liao, Jianshan; Christodolu, Nikolas; Thurber, Greg M

2016-09-01

Antibody-drug conjugates exhibit complex pharmacokinetics due to their combination of macromolecular and small molecule properties. These issues range from systemic concerns, such as deconjugation of the small molecule drug during the long antibody circulation time or rapid clearance from nonspecific interactions, to local tumor tissue heterogeneity, cell bystander effects, and endosomal escape. Mathematical models can be used to study the impact of these processes on overall distribution in an efficient manner, and several types of models have been used to analyze varying aspects of antibody distribution including physiologically based pharmacokinetic (PBPK) models and tissue-level simulations. However, these processes are quantitative in nature and cannot be handled qualitatively in isolation. For example, free antibody from deconjugation of the small molecule will impact the distribution of conjugated antibodies within the tumor. To incorporate these effects into a unified framework, we have coupled the systemic and organ-level distribution of a PBPK model with the tissue-level detail of a distributed parameter tumor model. We used this mathematical model to analyze new experimental results on the distribution of the clinical antibody-drug conjugate Kadcyla in HER2-positive mouse xenografts. This model is able to capture the impact of the drug-antibody ratio (DAR) on tumor penetration, the net result of drug deconjugation, and the effect of using unconjugated antibody to drive ADC penetration deeper into the tumor tissue. This modeling approach will provide quantitative and mechanistic support to experimental studies trying to parse the impact of multiple mechanisms of action for these complex drugs.

Multiscale Modeling of Antibody Drug Conjugates: Connecting tissue and cellular distribution to whole animal pharmacokinetics and potential implications for efficacy

PubMed Central

Cilliers, Cornelius; Guo, Hans; Liao, Jianshan; Christodolu, Nikolas; Thurber, Greg M.

2016-01-01

Antibody drug conjugates exhibit complex pharmacokinetics due to their combination of macromolecular and small molecule properties. These issues range from systemic concerns, such as deconjugation of the small molecule drug during the long antibody circulation time or rapid clearance from non-specific interactions, to local tumor tissue heterogeneity, cell bystander effects, and endosomal escape. Mathematical models can be used to study the impact of these processes on overall distribution in an efficient manner, and several types of models have been used to analyze varying aspects of antibody distribution including physiologically based pharmacokinetic (PBPK) models and tissue-level simulations. However, these processes are quantitative in nature and cannot be handled qualitatively in isolation. For example, free antibody from deconjugation of the small molecule will impact the distribution of conjugated antibodies within the tumor. To incorporate these effects into a unified framework, we have coupled the systemic and organ-level distribution of a PBPK model with the tissue-level detail of a distributed parameter tumor model. We used this mathematical model to analyze new experimental results on the distribution of the clinical antibody drug conjugate Kadcyla in HER2 positive mouse xenografts. This model is able to capture the impact of the drug antibody ratio (DAR) on tumor penetration, the net result of drug deconjugation, and the effect of using unconjugated antibody to drive ADC penetration deeper into the tumor tissue. This modeling approach will provide quantitative and mechanistic support to experimental studies trying to parse the impact of multiple mechanisms of action for these complex drugs. PMID:27287046

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in Sorghum bicolor

PubMed Central

2013-01-01

Background A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency. Results A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R 2 ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R 2 of 0.94 and RMSEP of 0.64 μg.mgDW-1.h-1. Conclusions This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential. PMID:24365407

Lithium-ion Open Circuit Voltage (OCV) curve modelling and its ageing adjustment

NASA Astrophysics Data System (ADS)

Lavigne, L.; Sabatier, J.; Francisco, J. Mbala; Guillemard, F.; Noury, A.

2016-08-01

This paper is a contribution to lithium-ion batteries modelling taking into account aging effects. It first analyses the impact of aging on electrode stoichiometry and then on lithium-ion cell Open Circuit Voltage (OCV) curve. Through some hypotheses and an appropriate definition of the cell state of charge, it shows that each electrode equilibrium potential, but also the whole cell equilibrium potential can be modelled by a polynomial that requires only one adjustment parameter during aging. An adjustment algorithm, based on the idea that for two fixed OCVs, the state of charge between these two equilibrium states is unique for a given aging level, is then proposed. Its efficiency is evaluated on a battery pack constituted of four cells.

Blue intensity matters for cell cycle profiling in fluorescence DAPI-stained images.

PubMed

Ferro, Anabela; Mestre, Tânia; Carneiro, Patrícia; Sahumbaiev, Ivan; Seruca, Raquel; Sanches, João M

2017-05-01

In the past decades, there has been an amazing progress in the understanding of the molecular mechanisms of the cell cycle. This has been possible largely due to a better conceptualization of the cycle itself, but also as a consequence of technological advances. Herein, we propose a new fluorescence image-based framework targeted at the identification and segmentation of stained nuclei with the purpose to determine DNA content in distinct cell cycle stages. The method is based on discriminative features, such as total intensity and area, retrieved from in situ stained nuclei by fluorescence microscopy, allowing the determination of the cell cycle phase of both single and sub-population of cells. The analysis framework was built on a modified k-means clustering strategy and refined with a Gaussian mixture model classifier, which enabled the definition of highly accurate classification clusters corresponding to G1, S and G2 phases. Using the information retrieved from area and fluorescence total intensity, the modified k-means (k=3) cluster imaging framework classified 64.7% of the imaged nuclei, as being at G1 phase, 12.0% at G2 phase and 23.2% at S phase. Performance of the imaging framework was ascertained with normal murine mammary gland cells constitutively expressing the Fucci2 technology, exhibiting an overall sensitivity of 94.0%. Further, the results indicate that the imaging framework has a robust capacity to both identify a given DAPI-stained nucleus to its correct cell cycle phase, as well as to determine, with very high probability, true negatives. Importantly, this novel imaging approach is a non-disruptive method that allows an integrative and simultaneous quantitative analysis of molecular and morphological parameters, thus awarding the possibility of cell cycle profiling in cytological and histological samples.

[Sea urchin embryo, DNA-damaged cell cycle checkpoint and the mechanisms initiating cancer development].

PubMed

Bellé, Robert; Le Bouffant, Ronan; Morales, Julia; Cosson, Bertrand; Cormier, Patrick; Mulner-Lorillon, Odile

2007-01-01

Cell division is an essential process for heredity, maintenance and evolution of the whole living kingdom. Sea urchin early development represents an excellent experimental model for the analysis of cell cycle checkpoint mechanisms since embryonic cells contain a functional DNA-damage checkpoint and since the whole sea urchin genome is sequenced. The DNA-damaged checkpoint is responsible for an arrest in the cell cycle when DNA is damaged or incorrectly replicated, for activation of the DNA repair mechanism, and for commitment to cell death by apoptosis in the case of failure to repair. New insights in cancer biology lead to two fundamental concepts about the very first origin of cancerogenesis. Cancers result from dysfunction of DNA-damaged checkpoints and cancers appear as a result of normal stem cell (NCS) transformation into a cancer stem cell (CSC). The second aspect suggests a new definition of "cancer", since CSC can be detected well before any clinical evidence. Since early development starts from the zygote, which is a primary stem cell, sea urchin early development allows analysis of the early steps of the cancerization process. Although sea urchins do not develop cancers, the model is alternative and complementary to stem cells which are not easy to isolate, do not divide in a short time and do not divide synchronously. In the field of toxicology and incidence on human health, the sea urchin experimental model allows assessment of cancer risk from single or combined molecules long before any epidemiologic evidence is available. Sea urchin embryos were used to test the worldwide used pesticide Roundup that contains glyphosate as the active herbicide agent; it was shown to activate the DNA-damage checkpoint of the first cell cycle of development. The model therefore allows considerable increase in risk evaluation of new products in the field of cancer and offers a tool for the discovery of molecular markers for early diagnostic in cancer biology. Prevention and early diagnosis are two decisive elements of human cancer therapy.

Querying quantitative logic models (Q2LM) to study intracellular signaling networks and cell-cytokine interactions.

PubMed

Morris, Melody K; Shriver, Zachary; Sasisekharan, Ram; Lauffenburger, Douglas A

2012-03-01

Mathematical models have substantially improved our ability to predict the response of a complex biological system to perturbation, but their use is typically limited by difficulties in specifying model topology and parameter values. Additionally, incorporating entities across different biological scales ranging from molecular to organismal in the same model is not trivial. Here, we present a framework called "querying quantitative logic models" (Q2LM) for building and asking questions of constrained fuzzy logic (cFL) models. cFL is a recently developed modeling formalism that uses logic gates to describe influences among entities, with transfer functions to describe quantitative dependencies. Q2LM does not rely on dedicated data to train the parameters of the transfer functions, and it permits straight-forward incorporation of entities at multiple biological scales. The Q2LM framework can be employed to ask questions such as: Which therapeutic perturbations accomplish a designated goal, and under what environmental conditions will these perturbations be effective? We demonstrate the utility of this framework for generating testable hypotheses in two examples: (i) a intracellular signaling network model; and (ii) a model for pharmacokinetics and pharmacodynamics of cell-cytokine interactions; in the latter, we validate hypotheses concerning molecular design of granulocyte colony stimulating factor. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Performance characteristics of a visual-search human-model observer with sparse PET image data

NASA Astrophysics Data System (ADS)

Gifford, Howard C.

2012-02-01

As predictors of human performance in detection-localization tasks, statistical model observers can have problems with tasks that are primarily limited by target contrast or structural noise. Model observers with a visual-search (VS) framework may provide a more reliable alternative. This framework provides for an initial holistic search that identifies suspicious locations for analysis by a statistical observer. A basic VS observer for emission tomography focuses on hot "blobs" in an image and uses a channelized nonprewhitening (CNPW) observer for analysis. In [1], we investigated this model for a contrast-limited task with SPECT images; herein, a statisticalnoise limited task involving PET images is considered. An LROC study used 2D image slices with liver, lung and soft-tissue tumors. Human and model observers read the images in coronal, sagittal and transverse display formats. The study thus measured the detectability of tumors in a given organ as a function of display format. The model observers were applied under several task variants that tested their response to structural noise both at the organ boundaries alone and over the organs as a whole. As measured by correlation with the human data, the VS observer outperformed the CNPW scanning observer.

Computer model for electrochemical cell performance loss over time in terms of capacity, power, and conductance (CPC)

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

Gering, Kevin L.

2015-09-01

Available capacity, power, and cell conductance figure centrally into performance characterization of electrochemical cells (such as Li-ion cells) over their service life. For example, capacity loss in Li-ion cells is due to a combination of mechanisms, including loss of free available lithium, loss of active host sites, shifts in the potential-capacity curve, etc. Further distinctions can be made regarding irreversible and reversible capacity loss mechanisms. There are tandem needs for accurate interpretation of capacity at characterization conditions (cycling rate, temperature, etc.) and for robust self-consistent modeling techniques that can be used for diagnostic analysis of cell data as well asmore » forecasting of future performance. Analogous issues exist for aging effects on cell conductance and available power. To address these needs, a modeling capability was developed that provides a systematic analysis of the contributing factors to battery performance loss over aging and to act as a regression/prediction platform for cell performance. The modeling basis is a summation of self-consistent chemical kinetics rate expressions, which as individual expressions each covers a distinct mechanism (e.g., loss of active host sites, lithium loss), but collectively account for the net loss of premier metrics (e.g., capacity) over time for a particular characterization condition. Specifically, sigmoid-based rate expressions are utilized to describe each contribution to performance loss. Through additional mathematical development another tier of expressions is derived and used to perform differential analyses and segregate irreversible versus reversible contributions, as well as to determine concentration profiles over cell aging for affected Li+ ion inventory and fraction of active sites that remain at each time step. Reversible fade components are surmised by comparing fade rates at fast versus slow cycling conditions. The model is easily utilized for predictive calculations so that future capacity performance can be estimated. The invention covers mathematical and theoretical frameworks, and demonstrates application to various Li-ion cells covering test periods that vary in duration, and shows model predictions well past the end of test periods. Version 2.0 Enhancements: the code now covers path-dependent aging scenarios, wherein the framework allows for arbitrarily-chosen aging conditions over a timeline to accommodate prediction of battery aging over a multiplicity of changing conditions. The code framework also allows for cell conductance and power loss evaluations over cell aging, analysis of series strings that contain a thermal anomaly (hot spot), and evaluation of battery thermal management parameters that impact battery lifetimes. Lastly, a comprehensive GUI now resides in the Ver. 2.0 code.« less

Peptidoglycan and Teichoic Acid Levels and Alterations in Staphylococcus aureus by Cell-Wall and Whole-Cell Nuclear Magnetic Resonance.

PubMed

Romaniuk, Joseph A H; Cegelski, Lynette

2018-06-11

Gram-positive bacteria surround themselves with a multilayered macromolecular cell wall that is essential to cell survival and serves as a major target for antibiotics. The cell wall of Staphylococcus aureus is composed of two major structural components, peptidoglycan (PG) and wall teichoic acid (WTA), together creating a heterogeneous and insoluble matrix that poses a challenge to quantitative compositional analysis. Here, we present 13 C cross polarization magic angle spinning solid-state nuclear magnetic resonance (NMR) spectra of intact cell walls, purified PG, and purified WTA. The spectra reveal the clear molecular differences in the two polymers and enable quantification of PG and WTA in isolated cell walls, an attractive alternative to estimating teichoic acid content from a phosphate analysis of completely pyrolyzed cell walls. Furthermore, we discovered that unique PG and WTA spectral signatures could be identified in whole-cell NMR spectra and used to compare PG and WTA levels among intact bacterial cell samples. The distinguishing whole-cell 13 C NMR contributions associated with PG include the GlcNAc-MurNAc sugar carbons and glycyl α-carbons. WTA contributes carbons from the phosphoribitol backbone. Distinguishing 15 N spectral signatures include glycyl amide nitrogens in PG and the esterified d-alanyl amine nitrogens in WTA. 13 C NMR analysis was performed with samples at natural abundance and included 10 whole-cell sample comparisons. Changes consistent with altered PG and WTA content were detected in whole-cell spectra of bacteria harvested at different growth times and in cells treated with tunicamycin. This use of whole-cell NMR provides quantitative parameters of composition in the context of whole-cell activity.

Single-cell systems level analysis of human Toll-Like-Receptor activation defines a chemokine signature in Systemic Lupus Erythematosus

PubMed Central

O'Gorman, William E.; Hsieh, Elena W.Y.; Savig, Erica S.; Gherardini, Pier Federico; Hernandez, Joseph D.; Hansmann, Leo; Balboni, Imelda M.; Utz, Paul J.; Bendall, Sean C.; Fantl, Wendy J.; Lewis, David B.; Nolan, Garry P.; Davis, Mark M.

2015-01-01

Background Activation of Toll-Like Receptors (TLRs) induces inflammatory responses involved in immunity to pathogens and autoimmune pathogenesis, such as in Systemic Lupus Erythematosus (SLE). Although TLRs are differentially expressed across the immune system, a comprehensive analysis of how multiple immune cell subsets respond in a system-wide manner has previously not been described. Objective To characterize TLR activation across multiple immune cell subsets and individuals, with the goal of establishing a reference framework against which to compare pathological processes. Methods Peripheral whole blood samples were stimulated with TLR ligands, and analyzed by mass cytometry simultaneously for surface marker expression, activation states of intracellular signaling proteins, and cytokine production. We developed a novel data visualization tool to provide an integrated view of TLR signaling networks with single-cell resolution. We studied seventeen healthy volunteer donors and eight newly diagnosed untreated SLE patients. Results Our data revealed the diversity of TLR-induced responses within cell types, with TLR ligand specificity. Subsets of NK and T cells selectively induced NF-κB in response to TLR2 ligands. CD14hi monocytes exhibited the most polyfunctional cytokine expression patterns, with over 80 distinct cytokine combinations. Monocytic TLR-induced cytokine patterns were shared amongst a group of healthy donors, with minimal intra- and inter- individual variability. Furthermore, autoimmune disease altered baseline cytokine production, as newly diagnosed untreated SLE patients shared a distinct monocytic chemokine signature, despite clinical heterogeneity. Conclusion Mass cytometry analysis defined a systems-level reference framework for human TLR activation, which can be applied to study perturbations in inflammatory disease, such as SLE. PMID:26037552

Identification and characterization of the autophagy-related genes Atg12 and Atg5 in hydra.

PubMed

Dixit, Nishikant S; Shravage, Bhupendra V; Ghaskadbi, Surendra

2017-01-01

Autophagy is an evolutionarily conserved process in eukaryotic cells that is involved in the degradation of cytoplasmic contents including organelles via the lysosome. Hydra is an early metazoan which exhibits simple tissue grade organization, a primitive nervous system, and is one of the classical non-bilaterian models extensively used in evo-devo research. Here, we describe the characterization of two core autophagy genes, Atg12 and Atg5, from hydra. In silico analyses including sequence similarity, domain analysis, and phylogenetic analysis demonstrate the conservation of these genes across eukaryotes. The predicted 3D structure of hydra Atg12 showed very little variance when compared to human Atg12 and yeast Atg12, whereas the hydra Atg5 predicted 3D structure was found to be variable, when compared with its human and yeast homologs. Strikingly, whole mount in situ hybridization showed high expression of Atg12 transcripts specifically in nematoblasts, whereas Atg5 transcripts were found to be expressed strongly in budding region and growing buds. This study may provide a framework to understand the evolution of autophagy networks in higher eukaryotes.

An Interdisciplinary Approach for Designing Kinetic Models of the Ras/MAPK Signaling Pathway.

PubMed

Reis, Marcelo S; Noël, Vincent; Dias, Matheus H; Albuquerque, Layra L; Guimarães, Amanda S; Wu, Lulu; Barrera, Junior; Armelin, Hugo A

2017-01-01

We present in this article a methodology for designing kinetic models of molecular signaling networks, which was exemplarily applied for modeling one of the Ras/MAPK signaling pathways in the mouse Y1 adrenocortical cell line. The methodology is interdisciplinary, that is, it was developed in a way that both dry and wet lab teams worked together along the whole modeling process.

New approach to 'top-and-bottom' whole blood separation using the multiunit TACSI WB system: quality of blood components.

PubMed

Lotens, A; Najdovski, T; Cellier, N; Ernotte, B; Lambermont, M; Rapaille, A

2014-10-01

TACSI whole blood system is designed to combine primary and secondary processing of six whole blood bags into plasma units, buffy coat and red blood cell concentrates. The aim of this study was to investigate the specifications and in vitro storage parameters of blood components compared with standard centrifugation and separation processing. Whole blood bags, collected in CRC kits, were treated on a TACSI whole blood system. They were compared with whole blood bags collected in Composelect kits. In addition to routine quality control analyses, conservation studies were performed on red blood cell concentrates for 42 days and on plasma for 6 months. Platelets pools with five buffy coats were also created, and cellular contamination was evaluated. Red blood cell concentrates produced from TACSI whole blood met European quality requirements. For white blood cell count, one individual result exceeded 1 × 10(6) cells/unit. All plasma units fell within specifications for residual cellular contamination and storage parameters. The performances of the TACSI whole blood system allow for the preparation of low volume buffy coats with a recovery of 90% of whole blood platelets. Haemoglobin losses in TACSI BC are smaller, but this did not result in higher haemoglobin content of red cells. These BC are suitable for the production of platelet concentrates. From these in vitro data, red blood cell concentrates produced using TACSI whole blood are suitable for clinical use with a quality at least equivalent to the control group. © 2014 International Society of Blood Transfusion.

Comparison of Whole-Cell SELEX Methods for the Identification of Staphylococcus Aureus-Specific DNA Aptamers

PubMed Central

Moon, Jihea; Kim, Giyoung; Park, Saet Byeol; Lim, Jongguk; Mo, Changyeun

2015-01-01

Whole-cell Systemic Evolution of Ligands by Exponential enrichment (SELEX) is the process by which aptamers specific to target cells are developed. Aptamers selected by whole-cell SELEX have high affinity and specificity for bacterial surface molecules and live bacterial targets. To identify DNA aptamers specific to Staphylococcus aureus, we applied our rapid whole-cell SELEX method to a single-stranded ssDNA library. To improve the specificity and selectivity of the aptamers, we designed, selected, and developed two categories of aptamers that were selected by two kinds of whole-cell SELEX, by mixing and combining FACS analysis and a counter-SELEX process. Using this approach, we have developed a biosensor system that employs a high affinity aptamer for detection of target bacteria. FAM-labeled aptamer sequences with high binding to S. aureus, as determined by fluorescence spectroscopic analysis, were identified, and aptamer A14, selected by the basic whole-cell SELEX using a once-off FACS analysis, and which had a high binding affinity and specificity, was chosen. The binding assay was evaluated using FACS analysis. Our study demonstrated the development of a set of whole-cell SELEX derived aptamers specific to S. aureus; this approach can be used in the identification of other bacteria. PMID:25884791

Comparison of whole-cell SELEX methods for the identification of Staphylococcus aureus-specific DNA aptamers.

PubMed

Moon, Jihea; Kim, Giyoung; Park, Saet Byeol; Lim, Jongguk; Mo, Changyeun

2015-04-15

Whole-cell Systemic Evolution of Ligands by Exponential enrichment (SELEX) is the process by which aptamers specific to target cells are developed. Aptamers selected by whole-cell SELEX have high affinity and specificity for bacterial surface molecules and live bacterial targets. To identify DNA aptamers specific to Staphylococcus aureus, we applied our rapid whole-cell SELEX method to a single-stranded ssDNA library. To improve the specificity and selectivity of the aptamers, we designed, selected, and developed two categories of aptamers that were selected by two kinds of whole-cell SELEX, by mixing and combining FACS analysis and a counter-SELEX process. Using this approach, we have developed a biosensor system that employs a high affinity aptamer for detection of target bacteria. FAM-labeled aptamer sequences with high binding to S. aureus, as determined by fluorescence spectroscopic analysis, were identified, and aptamer A14, selected by the basic whole-cell SELEX using a once-off FACS analysis, and which had a high binding affinity and specificity, was chosen. The binding assay was evaluated using FACS analysis. Our study demonstrated the development of a set of whole-cell SELEX derived aptamers specific to S. aureus; this approach can be used in the identification of other bacteria.

The 3 H and BMSEST Models for Spirituality in Multicultural Whole-Person Medicine

PubMed Central

Anandarajah, Gowri

2008-01-01

PURPOSE The explosion of evidence in the last decade supporting the role of spirituality in whole-person patient care has prompted proposals for a move to a biopsychosocial-spiritual model for health. Making this paradigm shift in today’s multicultural societies poses many challenges, however. This article presents 2 theoretical models that provide common ground for further exploration of the role of spirituality in medicine. METHODS The 3 H model (head, heart, hands) and the BMSEST models (body, mind, spirit, environment, social, transcendent) evolved from the author’s 12-year experience with curricula development regarding spirituality and medicine, 16-year experience as an attending family physician and educator, lived experience with both Hinduism and Christianity since childhood, and a lifetime study of the world’s great spiritual traditions. The models were developed, tested with learners, and refined. RESULTS The 3 H model offers a multidimensional definition of spirituality, applicable across cultures and belief systems, that provides opportunities for a common vocabulary for spirituality. Therapeutic options, from general spiritual care (compassion, presence, and the healing relationship), to specialized spiritual care (eg, by clinical chaplains), to spiritual self-care are discussed. The BMSEST model provides a conceptual framework for the role of spirituality in the larger health care context, useful for patient care, education, and research. Interactions among the 6 BMSEST components, with references to ongoing research, are proposed. CONCLUSIONS Including spirituality in whole-person care is a way of furthering our understanding of the complexities of human health and well-being. The 3 H and BMSEST models suggest a multidimensional and multidisciplinary approach based on universal concepts and a foundation in both the art and science of medicine. PMID:18779550

A theoretical framework for jamming in confluent biological tissues

NASA Astrophysics Data System (ADS)

Manning, M. Lisa

2015-03-01

For important biological functions such as wound healing, embryonic development, and cancer tumorogenesis, cells must initially rearrange and move over relatively large distances, like a liquid. Subsequently, these same tissues must undergo buckling and support shear stresses, like a solid. Our work suggests that biological tissues can accommodate these disparate requirements because the tissues are close to glass or jamming transition. While recent self propelled particle models generically predict a glass/jamming transition that is driven by packing density φ and happens at some critical φc less than unity, many biological tissues that are confluent with no gaps between cells appear to undergo a jamming transition at a constant density (φ = 1). I will discuss a new theoretical framework for predicting energy barriers and rates of cell migration in 2D tissue monolayers, and show that this model predicts a novel type of rigidity transition, which takes place at constant φ = 1 and depends only on single cell properties such as cell-cell adhesion, cortical tension and cell elasticity. This model additionally predicts that an experimentally observable parameter, the ratio between a cell's perimeter and the square root of its cross-sectional area, attains a specific, critical value at the jamming transition. We show that this prediction is precisely realized in primary epithelial cultures from human patients, with implications for asthma pathology.

A Framework for Modeling Competitive and Cooperative Computation in Retinal Processing

NASA Astrophysics Data System (ADS)

Moreno-Díaz, Roberto; de Blasio, Gabriel; Moreno-Díaz, Arminda

2008-07-01

The structure of the retina suggests that it should be treated (at least from the computational point of view), as a layered computer. Different retinal cells contribute to the coding of the signals down to ganglion cells. Also, because of the nature of the specialization of some ganglion cells, the structure suggests that all these specialization processes should take place at the inner plexiform layer and they should be of a local character, prior to a global integration and frequency-spike coding by the ganglion cells. The framework we propose consists of a layered computational structure, where outer layers provide essentially with band-pass space-time filtered signals which are progressively delayed, at least for their formal treatment. Specialization is supposed to take place at the inner plexiform layer by the action of spatio-temporal microkernels (acting very locally), and having a centerperiphery space-time structure. The resulting signals are then integrated by the ganglion cells through macrokernels structures. Practically all types of specialization found in different vertebrate retinas, as well as the quasilinear behavior in some higher vertebrates, can be modeled and simulated within this framework. Finally, possible feedback from central structures is considered. Though their relevance to retinal processing is not definitive, it is included here for the sake of completeness, since it is a formal requisite for recursiveness.

Dynamical dark matter: A new framework for dark-matter physics

NASA Astrophysics Data System (ADS)

Dienes, Keith R.; Thomas, Brooks

2013-05-01

Although much remains unknown about the dark matter of the universe, one property is normally considered sacrosanct: dark matter must be stable well beyond cosmological time scales. However, a new framework for dark-matter physics has recently been proposed which challenges this assumption. In the "dynamical dark matter" (DDM) framework, the dark sector consists of a vast ensemble of individual dark-matter components with differing masses, lifetimes, and cosmological abundances. Moreover, the usual requirement of stability is replaced by a delicate balancing between lifetimes and cosmological abundances across the ensemble as a whole. As a result, it is possible for the DDM ensemble to remain consistent with all experimental and observational bounds on dark matter while nevertheless giving rise to collective behaviors which transcend those normally associated with traditional dark-matter candidates. These include a new, non-trivial darkmatter equation of state as well as potentially distinctive signatures in collider and direct-detection experiments. In this review article, we provide a self-contained introduction to the DDM framework and summarize some of the work which has recently been done in this area. We also present an explicit model within the DDM framework, and outline a number of ideas for future investigation.

A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

PubMed

Samarasinghe, S; Ling, H

In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced parameters and protein concentrations similar to the original RNN system. Results thus demonstrated the reliability of the proposed RNN method for modelling relatively large networks by modularisation for practical settings. Advantages of the method are its ability to represent accurate continuous system dynamics and ease of: parameter estimation through training with data from a practical setting, model analysis (40% faster than ODE), fine tuning parameters when more data are available, sub-model extension when new elements and/or interactions come to light and model expansion with addition of sub-models. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-core processing and scheduling performance in CMS

NASA Astrophysics Data System (ADS)

Hernández, J. M.; Evans, D.; Foulkes, S.

2012-12-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

Developing a Zebrafish Model of NF1 for Structure-Function Analysis and Identification of Modifier Genes

DTIC Science & Technology

2010-04-01

equipped with a spinning-disc confocal system ( Yokogawa ) was used. The statistical significance of changes to OPC cell numbers and migration upon nf1...that they are expressed in overlapping tissues. We examined the expression of both genes by whole mount in situ hybridization between the 4- cell stage...sorted cells confirmed expression, particularly in the vascular endothelium (Figure 4E-G), while RNA from 1- cell embryos indicate that both genes are

A causal framework for integrating contemporary and Vedic holism.

PubMed

Kineman, John J

2017-12-01

Whereas the last Century of science was characterized by epistemological uncertainty; the current Century will likely be characterized by ontological complexity (Gorban and Yablonsky, 2013). Advances in Systems Theory by mathematical biologist Robert Rosen suggest an elegant way forward (Rosen, 2013). "R-theory" (Kineman, 2012) is a synthesis of Rosen's theories explaining complexity and life in terms of a meta-model for 'whole' systems (and their fractions) in terms of "5 th -order holons". Such holons are Rosen "modeling relations" relating system-dependent processes with their formative contexts via closed cycles of four archetypal (Aristotelian) causes. This approach has post-predicted the three most basic taxa of life, plus a quasi-organismic form that may describe proto, component, and ecosystemic life. R-theory thus suggests a fundamentally complex ontology of existence inverting the current view that complexity arises from simple mechanisms. This model of cyclical causality corresponds to the ancient meta-model described in the Vedas and Upanishads of India. Part I of this discussion (Kineman, 2016a) presented a case for associating Vedic philosophy with Harappan civilization, allowing interpretation of ancient concepts of "cosmic order" (Rta) in the Rig Veda, nonduality (advaita), seven-fold beingness (saptanna) and other forms of holism appearing later in the Upanishads. By deciphering the model of wholeness that was applied and tested in ancient times, it is possible to compare, test, and confirm the holon model as a mathematical definition of life, systemic wholeness, and sustainability that may be applied today in modern terms, even as a foundation for holistic science. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Advances in in-situ product recovery (ISPR) in whole cell biotechnology during the last decade.

PubMed

Van Hecke, Wouter; Kaur, Guneet; De Wever, Heleen

2014-11-15

The review presents the state-of-the-art in the applications of in-situ product recovery (ISPR) in whole-cell biotechnology over the last 10years. It summarizes various ISPR-integrated fermentation processes for the production of a wide spectrum of bio-based products. A critical assessment of the performance of various ISPR concepts with respect to the degree of product enrichment, improved productivity, reduced process flows and increased yields is provided. Requirements to allow a successful industrial implementation of ISPR are also discussed. Finally, supporting technologies such as online monitoring, mathematical modeling and use of recombinant microorganisms with ISPR are presented. Copyright © 2014 Elsevier Inc. All rights reserved.

Simple Microfluidic Device For Studying Chemotaxis In Response To Dual Gradients

PubMed Central

Moussavi-Haramic, S. F.; Pezzi, H. M.; Huttenlocher, A.; Beebe, D. J.

2016-01-01

Chemotaxis is a fundamental biological process where complex chemotactic gradients are integrated and prioritized to guide cell migration toward specific locations. To understand the mechanisms of gradient dependent cell migration, it is important to develop in vitro models that recapitulate key attributes of the chemotactic cues present in vivo. Current in vitro tools for studying cell migration are not amenable to easily study the response of neutrophils to dual gradients. Many of these systems require external pumps and complex setups to establish and maintain the gradients. Here we report a simple yet innovative microfluidic device for studying cell migration in the presence of dual chemotactic gradients through a 3-dimensional substrate. The device is tested and validated by studying the migration of the neutrophil-like cell line PLB-985 to gradients of fMLP. Furthermore, the device is expanded and used with heparinised whole blood, whereupon neutrophils were observed to migrate from whole blood towards gradients of fMLP eliminating the need for any neutrophil purification or capture steps. PMID:25893484

Markov State Models of gene regulatory networks.

PubMed

Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

2017-02-06

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.

A Competency Framework for the Practice of Psychology: Procedures and Implications.

PubMed

Hunsley, John; Spivak, Howard; Schaffer, Jack; Cox, Darcy; Caro, Carla; Rodolfa, Emil; Greenberg, Sandra

2016-09-01

Several competency models for training and practice in professional psychology have been proposed in the United States and Canada. Typically, the procedures used in developing and finalizing these models have involved both expert working groups and opportunities for input from interested parties. What has been missing, however, are empirical data to determine the degree to which the model reflects the views of members of the profession as a whole. Using survey data from 466 licensed or registered psychologists (approximately half of whom completed one of two versions of the survey), we examined the degree to which psychologists, both those engaged primarily in practice and those involved in doctoral training, agreed with the competency framework developed by the Association of State and Provincial Psychology Boards' Practice Analysis Task Force (Rodolfa et al., 2013). When distinct time points in training and licensure or registration were considered (i.e., entry-level supervised practice in practicum settings, advanced-level supervised practice during internship, entry level independent practice, and advanced practice), there was limited agreement by survey respondents with the competency framework's proposal about when specific competencies should be attained. In contrast, greater agreement was evident by respondents with the competency framework when the reference point was focused on entry to independent practice (i.e., the competencies necessary for licensure or registration). We discuss the implications of these findings for the development of competency models, as well as for the implementation of competency requirements in both licensure or registration and training contexts. © 2016 Wiley Periodicals, Inc.

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU

PubMed Central

Xia, Yong; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations. PMID:26581957

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU.

PubMed

Xia, Yong; Wang, Kuanquan; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

CelOWS: an ontology based framework for the provision of semantic web services related to biological models.

PubMed

Matos, Ely Edison; Campos, Fernanda; Braga, Regina; Palazzi, Daniele

2010-02-01

The amount of information generated by biological research has lead to an intensive use of models. Mathematical and computational modeling needs accurate description to share, reuse and simulate models as formulated by original authors. In this paper, we introduce the Cell Component Ontology (CelO), expressed in OWL-DL. This ontology captures both the structure of a cell model and the properties of functional components. We use this ontology in a Web project (CelOWS) to describe, query and compose CellML models, using semantic web services. It aims to improve reuse and composition of existent components and allow semantic validation of new models.

Development of an analytical model for estimating global terrestrial carbon assimilation using a rate-limitation framework

NASA Astrophysics Data System (ADS)

Donohue, Randall; Yang, Yuting; McVicar, Tim; Roderick, Michael

2016-04-01

A fundamental question in climate and ecosystem science is "how does climate regulate the land surface carbon budget?" To better answer that question, here we develop an analytical model for estimating mean annual terrestrial gross primary productivity (GPP), which is the largest carbon flux over land, based on a rate-limitation framework. Actual GPP (climatological mean from 1982 to 2010) is calculated as a function of the balance between two GPP potentials defined by the climate (i.e., precipitation and solar radiation) and a third parameter that encodes other environmental variables and modifies the GPP-climate relationship. The developed model was tested at three spatial scales using different GPP sources, i.e., (1) observed GPP from 94 flux-sites, (2) modelled GPP (using the model-tree-ensemble approach) at 48654 (0.5 degree) grid-cells and (3) at 32 large catchments across the globe. Results show that the proposed model could account for the spatial GPP patterns, with a root-mean-square error of 0.70, 0.65 and 0.3 g C m-2 d-1 and R2 of 0.79, 0.92 and 0.97 for the flux-site, grid-cell and catchment scales, respectively. This analytical GPP model shares a similar form with the Budyko hydroclimatological model, which opens the possibility of a general analytical framework to analyze the linked carbon-water-energy cycles.

Addition of autologous mesenchymal stem cells to whole blood for bioenhanced ACL repair has no benefit in the porcine model.

PubMed

Proffen, Benedikt L; Vavken, Patrick; Haslauer, Carla M; Fleming, Braden C; Harris, Chad E; Machan, Jason T; Murray, Martha M

2015-02-01

Coculture of mesenchymal stem cells (MSCs) from the retropatellar fat pad and peripheral blood has been shown to stimulate anterior cruciate ligament (ACL) fibroblast proliferation and collagen production in vitro. Current techniques of bioenhanced ACL repair in animal studies involve adding a biologic scaffold, in this case an extracellular matrix-based scaffold saturated with autologous whole blood, to a simple suture repair of the ligament. Whether the enrichment of whole blood with MSCs would further improve the in vivo results of bioenhanced ACL repair was investigated. The addition of MSCs derived from adipose tissue or peripheral blood to the blood-extracellular matrix composite, which is used in bioenhanced ACL repair to stimulate healing, would improve the biomechanical properties of a bioenhanced ACL repair after 15 weeks of healing. Controlled laboratory study. Twenty-four adolescent Yucatan mini-pigs underwent ACL transection followed by (1) bioenhanced ACL repair, (2) bioenhanced ACL repair with the addition of autologous adipose-derived MSCs, and (3) bioenhanced ACL repair with the addition of autologous peripheral blood derived MSCs. After 15 weeks of healing, the structural properties of the ACL (yield load, failure load, and linear stiffness) were measured. Cell and vascular density were measured in the repaired ACL via histology, and its tissue structure was qualitatively evaluated using the advanced Ligament Maturity Index. After 15 weeks of healing, there were no significant improvements in the biomechanical or histological properties with the addition of adipose-derived MSCs. The only significant change with the addition of peripheral blood MSCs was an increase in knee anteroposterior laxity when measured at 30° of flexion. These findings suggest that the addition of adipose or peripheral blood MSCs to whole blood before saturation of an extracellular matrix carrier with the blood did not improve the functional results of bioenhanced ACL repair after 15 weeks of healing in the pig model. Whole blood represents a practical biologic additive to ligament repair, and any other additive (including stem cells) should be demonstrated to be superior to this baseline before clinical use is considered. © 2014 The Author(s).

A C-terminally truncated form of β-catenin acts as a novel regulator of Wnt/β-catenin signaling in planarians

PubMed Central

Rabaneda-Lombarte, Neus; Gelabert, Maria; Xie, Jianlei; Wu, Wei

2017-01-01

β-Catenin, the core element of the Wnt/β-catenin pathway, is a multifunctional and evolutionarily conserved protein which performs essential roles in a variety of developmental and homeostatic processes. Despite its crucial roles, the mechanisms that control its context-specific functions in time and space remain largely unknown. The Wnt/β-catenin pathway has been extensively studied in planarians, flatworms with the ability to regenerate and remodel the whole body, providing a ‘whole animal’ developmental framework to approach this question. Here we identify a C-terminally truncated β-catenin (β-catenin4), generated by gene duplication, that is required for planarian photoreceptor cell specification. Our results indicate that the role of β-catenin4 is to modulate the activity of β-catenin1, the planarian β-catenin involved in Wnt signal transduction in the nucleus, mediated by the transcription factor TCF-2. This inhibitory form of β-catenin, expressed in specific cell types, would provide a novel mechanism to modulate nuclear β-catenin signaling levels. Genomic searches and in vitro analysis suggest that the existence of a C-terminally truncated form of β-catenin could be an evolutionarily conserved mechanism to achieve a fine-tuned regulation of Wnt/β-catenin signaling in specific cellular contexts. PMID:28976975

A C-terminally truncated form of β-catenin acts as a novel regulator of Wnt/β-catenin signaling in planarians.

PubMed

Su, Hanxia; Sureda-Gomez, Miquel; Rabaneda-Lombarte, Neus; Gelabert, Maria; Xie, Jianlei; Wu, Wei; Adell, Teresa

2017-10-01

β-Catenin, the core element of the Wnt/β-catenin pathway, is a multifunctional and evolutionarily conserved protein which performs essential roles in a variety of developmental and homeostatic processes. Despite its crucial roles, the mechanisms that control its context-specific functions in time and space remain largely unknown. The Wnt/β-catenin pathway has been extensively studied in planarians, flatworms with the ability to regenerate and remodel the whole body, providing a 'whole animal' developmental framework to approach this question. Here we identify a C-terminally truncated β-catenin (β-catenin4), generated by gene duplication, that is required for planarian photoreceptor cell specification. Our results indicate that the role of β-catenin4 is to modulate the activity of β-catenin1, the planarian β-catenin involved in Wnt signal transduction in the nucleus, mediated by the transcription factor TCF-2. This inhibitory form of β-catenin, expressed in specific cell types, would provide a novel mechanism to modulate nuclear β-catenin signaling levels. Genomic searches and in vitro analysis suggest that the existence of a C-terminally truncated form of β-catenin could be an evolutionarily conserved mechanism to achieve a fine-tuned regulation of Wnt/β-catenin signaling in specific cellular contexts.

A Bayesian Framework to Account for Complex Non-Genetic Factors in Gene Expression Levels Greatly Increases Power in eQTL Studies

PubMed Central

Durbin, Richard; Winn, John

2010-01-01

Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/. PMID:20463871

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions.

PubMed

Saha, Tanumoy; Rathmann, Isabel; Galic, Milos

2017-07-11

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion.

PubMed

Anderson, Alexander R A

2005-06-01

In this paper we present a hybrid mathematical model of the invasion of healthy tissue by a solid tumour. In particular we consider early vascular growth, just after angiogenesis has occurred. We examine how the geometry of the growing tumour is affected by tumour cell heterogeneity caused by genetic mutations. As the tumour grows, mutations occur leading to a heterogeneous tumour cell population with some cells having a greater ability to migrate, proliferate or degrade the surrounding tissue. All of these cell properties are closely controlled by cell-cell and cell-matrix interactions and as such the physical geometry of the whole tumour will be dependent on these individual cell interactions. The hybrid model we develop focuses on four key variables implicated in the invasion process: tumour cells, host tissue (extracellular matrix), matrix-degradative enzymes and oxygen. The model is considered to be hybrid since the latter three variables are continuous (i.e. concentrations) and the tumour cells are discrete (i.e. individuals). With this hybrid model we examine how individual-based cell interactions (with one another and the matrix) can affect the tumour shape and discuss which of these interactions is perhaps most crucial in influencing the tumour's final structure.

Multi-scale and multi-physics model of the uterine smooth muscle with mechanotransduction.

PubMed

Yochum, Maxime; Laforêt, Jérémy; Marque, Catherine

2018-02-01

Preterm labor is an important public health problem. However, the efficiency of the uterine muscle during labor is complex and still poorly understood. This work is a first step towards a model of the uterine muscle, including its electrical and mechanical components, to reach a better understanding of the uterus synchronization. This model is proposed to investigate, by simulation, the possible role of mechanotransduction for the global synchronization of the uterus. The electrical diffusion indeed explains the local propagation of contractile activity, while the tissue stretching may play a role in the synchronization of distant parts of the uterine muscle. This work proposes a multi-physics (electrical, mechanical) and multi-scales (cell, tissue, whole uterus) model, which is applied to a realistic uterus 3D mesh. This model includes electrical components at different scales: generation of action potentials at the cell level, electrical diffusion at the tissue level. It then links these electrical events to the mechanical behavior, at the cellular level (via the intracellular calcium concentration), by simulating the force generated by each active cell. It thus computes an estimation of the intra uterine pressure (IUP) by integrating the forces generated by each active cell at the whole uterine level, as well as the stretching of the tissue (by using a viscoelastic law for the behavior of the tissue). It finally includes at the cellular level stretch activated channels (SACs) that permit to create a loop between the mechanical and the electrical behavior (mechanotransduction). The simulation of different activated regions of the uterus, which in this first "proof of concept" case are electrically isolated, permits the activation of inactive regions through the stretching (induced by the electrically active regions) computed at the whole organ scale. This permits us to evidence the role of the mechanotransduction in the global synchronization of the uterus. The results also permit us to evidence the effect on IUP of this enhanced synchronization induced by the presence of SACs. This proposed simplified model will be further improved in order to permit a better understanding of the global uterine synchronization occurring during efficient labor contractions. Copyright © 2017 Elsevier Ltd. All rights reserved.

T-Cell Artificial Focal Triggering Tools: Linking Surface Interactions with Cell Response

PubMed Central

Carpentier, Benoît; Pierobon, Paolo; Hivroz, Claire; Henry, Nelly

2009-01-01

T-cell activation is a key event in the immune system, involving the interaction of several receptor ligand pairs in a complex intercellular contact that forms between T-cell and antigen-presenting cells. Molecular components implicated in contact formation have been identified, but the mechanism of activation and the link between molecular interactions and cell response remain poorly understood due to the complexity and dynamics exhibited by whole cell-cell conjugates. Here we demonstrate that simplified model colloids grafted so as to target appropriate cell receptors can be efficiently used to explore the relationship of receptor engagement to the T-cell response. Using immortalized Jurkat T cells, we monitored both binding and activation events, as seen by changes in the intracellular calcium concentration. Our experimental strategy used flow cytometry analysis to follow the short time scale cell response in populations of thousands of cells. We targeted both T-cell receptor CD3 (TCR/CD3) and leukocyte-function-associated antigen (LFA-1) alone or in combination. We showed that specific engagement of TCR/CD3 with a single particle induced a transient calcium signal, confirming previous results and validating our approach. By decreasing anti-CD3 particle density, we showed that contact nucleation was the most crucial and determining step in the cell-particle interaction under dynamic conditions, due to shear stress produced by hydrodynamic flow. Introduction of LFA-1 adhesion molecule ligands at the surface of the particle overcame this limitation and elucidated the low TCR/CD3 ligand density regime. Despite their simplicity, model colloids induced relevant biological responses which consistently echoed whole cell behavior. We thus concluded that this biophysical approach provides useful tools for investigating initial events in T-cell activation, and should enable the design of intelligent artificial systems for adoptive immunotherapy. PMID:19274104

Development of a Method to Implement Whole-Genome Bisulfite Sequencing of cfDNA from Cancer Patients and a Mouse Tumor Model.

PubMed

Maggi, Elaine C; Gravina, Silvia; Cheng, Haiying; Piperdi, Bilal; Yuan, Ziqiang; Dong, Xiao; Libutti, Steven K; Vijg, Jan; Montagna, Cristina

2018-01-01

The goal of this study was to develop a method for whole genome cell-free DNA (cfDNA) methylation analysis in humans and mice with the ultimate goal to facilitate the identification of tumor derived DNA methylation changes in the blood. Plasma or serum from patients with pancreatic neuroendocrine tumors or lung cancer, and plasma from a murine model of pancreatic adenocarcinoma was used to develop a protocol for cfDNA isolation, library preparation and whole-genome bisulfite sequencing of ultra low quantities of cfDNA, including tumor-specific DNA. The protocol developed produced high quality libraries consistently generating a conversion rate >98% that will be applicable for the analysis of human and mouse plasma or serum to detect tumor-derived changes in DNA methylation.

A cell-free framework for rapid biosynthetic pathway prototyping and enzyme discovery.

PubMed

Karim, Ashty S; Jewett, Michael C

2016-07-01

Speeding up design-build-test (DBT) cycles is a fundamental challenge facing biochemical engineering. To address this challenge, we report a new cell-free protein synthesis driven metabolic engineering (CFPS-ME) framework for rapid biosynthetic pathway prototyping. In our framework, cell-free cocktails for synthesizing target small molecules are assembled in a mix-and-match fashion from crude cell lysates either containing selectively enriched pathway enzymes from heterologous overexpression or directly producing pathway enzymes in lysates by CFPS. As a model, we apply our approach to n-butanol biosynthesis showing that Escherichia coli lysates support a highly active 17-step CoA-dependent n-butanol pathway in vitro. The elevated degree of flexibility in the cell-free environment allows us to manipulate physiochemical conditions, access enzymatic nodes, discover new enzymes, and prototype enzyme sets with linear DNA templates to study pathway performance. We anticipate that CFPS-ME will facilitate efforts to define, manipulate, and understand metabolic pathways for accelerated DBT cycles without the need to reengineer organisms. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

A cost-effectiveness analysis of typhoid fever vaccines in US military personnel.

PubMed

Warren, T A; Finder, S F; Brier, K L; Ries, A J; Weber, M P; Miller, M R; Potyk, R P; Reeves, C S; Moran, E L; Tornow, J J

1996-11-01

Typhoid fever has been a problem for military personnel throughout history. A cost-effectiveness analysis of typhoid fever vaccines from the perspective of the US military was performed. Currently 3 vaccine preparations are available in the US: an oral live Type 21A whole cell vaccine; a single-dose parenteral, cell subunit vaccine; and a 2-dose parenteral heat-phenol killed, whole cell vaccine. This analysis assumed all vaccinees were US military personnel. Two pharmacoeconomic models were developed, one for personnel who have not yet been deployed, and the other for personnel who are deployed to an area endemic for typhoid fever. Drug acquisition, administration, adverse effect and lost work costs, as well as the costs associated with typhoid fever, were included in this analysis. Unique military issues, typhoid fever attack rates, vaccine efficacy, and compliance with each vaccine's dosage regimen were included in this analysis. A sensitivity analysis was performed to test the robustness of the models. Typhoid fever immunisation is not cost-effective for US military personnel unless they are considered imminently deployable or are deployed. The most cost-effective vaccine for US military personnel is the single-dose, cell subunit parenteral vaccine.

JTSA: an open source framework for time series abstractions.

PubMed

Sacchi, Lucia; Capozzi, Davide; Bellazzi, Riccardo; Larizza, Cristiana

2015-10-01

The evaluation of the clinical status of a patient is frequently based on the temporal evolution of some parameters, making the detection of temporal patterns a priority in data analysis. Temporal abstraction (TA) is a methodology widely used in medical reasoning for summarizing and abstracting longitudinal data. This paper describes JTSA (Java Time Series Abstractor), a framework including a library of algorithms for time series preprocessing and abstraction and an engine to execute a workflow for temporal data processing. The JTSA framework is grounded on a comprehensive ontology that models temporal data processing both from the data storage and the abstraction computation perspective. The JTSA framework is designed to allow users to build their own analysis workflows by combining different algorithms. Thanks to the modular structure of a workflow, simple to highly complex patterns can be detected. The JTSA framework has been developed in Java 1.7 and is distributed under GPL as a jar file. JTSA provides: a collection of algorithms to perform temporal abstraction and preprocessing of time series, a framework for defining and executing data analysis workflows based on these algorithms, and a GUI for workflow prototyping and testing. The whole JTSA project relies on a formal model of the data types and of the algorithms included in the library. This model is the basis for the design and implementation of the software application. Taking into account this formalized structure, the user can easily extend the JTSA framework by adding new algorithms. Results are shown in the context of the EU project MOSAIC to extract relevant patterns from data coming related to the long term monitoring of diabetic patients. The proof that JTSA is a versatile tool to be adapted to different needs is given by its possible uses, both as a standalone tool for data summarization and as a module to be embedded into other architectures to select specific phenotypes based on TAs in a large dataset. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Simultaneous recording of the action potential and its whole-cell associated ion current on NG108-15 cells cultured over a MWCNT electrode

NASA Astrophysics Data System (ADS)

Morales-Reyes, I.; Seseña-Rubfiaro, A.; Acosta-García, M. C.; Batina, N.; Godínez-Fernández, R.

2016-08-01

It is well known that, in excitable cells, the dynamics of the ion currents (I i) is extremely important to determine both the magnitude and time course of an action potential (A p). To observe these two processes simultaneously, we cultured NG108-15 cells over a multi-walled carbon nanotubes electrode (MWCNTe) surface and arranged a two independent Patch Clamp system configuration (Bi-Patch Clamp). The first system was used in the voltage or current clamp mode, using a glass micropipette as an electrode. The second system was modified to connect the MWCNTe to virtual ground. While the A p was recorded through the micropipette electrode, the MWCNTe was used to measure the underlying whole-cell current. This configuration allowed us to record both the membrane voltage (V m) and the current changes simultaneously. Images acquired by atomic force microscopy (AFM) and scanning electron microscopy (SEM) indicate that cultured cells developed a complex network of neurites, which served to establish the necessary close contact and strong adhesion to the MWCNTe surface. These features were a key factor to obtain the recording of the whole-cell I i with a high signal to noise ratio (SNR). The experimental results were satisfactorily reproduced by a theoretical model developed to simulate the proposed system. Besides the contribution to a better understanding of the fundamental mechanisms involved in cell communication, the developed method could be useful in cell physiology studies, pharmacology and diseases diagnosis.

A magnetic micropore chip for rapid (<1 hour) unbiased circulating tumor cell isolation and in situ RNA analysis.

PubMed

Ko, Jina; Bhagwat, Neha; Yee, Stephanie S; Black, Taylor; Redlinger, Colleen; Romeo, Janae; O'Hara, Mark; Raj, Arjun; Carpenter, Erica L; Stanger, Ben Z; Issadore, David

2017-09-12

The use of microtechnology for the highly selective isolation and sensitive detection of circulating tumor cells has shown enormous promise. One challenge for this technology is that the small feature sizes - which are the key to this technology's performance - can result in low sample throughput and susceptibility to clogging. Additionally, conventional molecular analysis of CTCs often requires cells to be taken off-chip for sample preparation and purification before analysis, leading to the loss of rare cells. To address these challenges, we have developed a microchip platform that combines fast, magnetic micropore based negative immunomagnetic selection (>10 mL h -1 ) with rapid on-chip in situ RNA profiling (>100× faster than conventional RNA labeling). This integrated chip can isolate both rare circulating cells and cell clusters directly from whole blood and allow individual cells to be profiled for multiple RNA cancer biomarkers, achieving sample-to-answer in less than 1 hour for 10 mL of whole blood. To demonstrate the power of this approach, we applied our device to the circulating tumor cell based diagnosis of pancreatic cancer. We used a genetically engineered lineage-labeled mouse model of pancreatic cancer (KPCY) to validate the performance of our chip. We show that in a cohort of patient samples (N = 25) that this device can detect and perform in situ RNA analysis on circulating tumor cells in patients with pancreatic cancer, even in those with extremely sparse CTCs (<1 CTC mL -1 of whole blood).

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

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

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

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Convenience experimentation.

PubMed

Krohs, Ulrich

2012-03-01

Systems biology aims at explaining life processes by means of detailed models of molecular networks, mainly on the whole-cell scale. The whole cell perspective distinguishes the new field of systems biology from earlier approaches within molecular cell biology. The shift was made possible by the high throughput methods that were developed for gathering 'omic' (genomic, proteomic, etc.) data. These new techniques are made commercially available as semi-automatic analytic equipment, ready-made analytic kits and probe arrays. There is a whole industry of supplies for what may be called convenience experimentation. My paper inquires some epistemic consequences of strong reliance on convenience experimentation in systems biology. In times when experimentation was automated to a lesser degree, modeling and in part even experimentation could be understood fairly well as either being driven by hypotheses, and thus proceed by the testing of hypothesis, or as being performed in an exploratory mode, intended to sharpen concepts or initially vague phenomena. In systems biology, the situation is dramatically different. Data collection became so easy (though not cheap) that experimentation is, to a high degree, driven by convenience equipment, and model building is driven by the vast amount of data that is produced by convenience experimentation. This results in a shift in the mode of science. The paper shows that convenience driven science is not primarily hypothesis-testing, nor is it in an exploratory mode. It rather proceeds in a gathering mode. This shift demands another shift in the mode of evaluation, which now becomes an exploratory endeavor, in response to the superabundance of gathered data. Copyright © 2011 Elsevier Ltd. All rights reserved.

Whole Genome Amplification of Labeled Viable Single Cells Suited for Array-Comparative Genomic Hybridization.

PubMed

Kroneis, Thomas; El-Heliebi, Amin

2015-01-01

Understanding details of a complex biological system makes it necessary to dismantle it down to its components. Immunostaining techniques allow identification of several distinct cell types thereby giving an inside view of intercellular heterogeneity. Often staining reveals that the most remarkable cells are the rarest. To further characterize the target cells on a molecular level, single cell techniques are necessary. Here, we describe the immunostaining, micromanipulation, and whole genome amplification of single cells for the purpose of genomic characterization. First, we exemplify the preparation of cell suspensions from cultured cells as well as the isolation of peripheral mononucleated cells from blood. The target cell population is then subjected to immunostaining. After cytocentrifugation target cells are isolated by micromanipulation and forwarded to whole genome amplification. For whole genome amplification, we use GenomePlex(®) technology allowing downstream genomic analysis such as array-comparative genomic hybridization.

The Development of a Conceptual Framework and Tools to Assess Undergraduates' Principled Use of Models in Cellular Biology

PubMed Central

Merritt, Brett; Urban-Lurain, Mark; Parker, Joyce

2010-01-01

Recent science education reform has been marked by a shift away from a focus on facts toward deep, rich, conceptual understanding. This requires assessment that also focuses on conceptual understanding rather than recall of facts. This study outlines our development of a new assessment framework and tool—a taxonomy— which, unlike existing frameworks and tools, is grounded firmly in a framework that considers the critical role that models play in science. It also provides instructors a resource for assessing students' ability to reason about models that are central to the organization of key scientific concepts. We describe preliminary data arising from the application of our tool to exam questions used by instructors of a large-enrollment cell and molecular biology course over a 5-yr period during which time our framework and the assessment tool were increasingly used. Students were increasingly able to describe and manipulate models of the processes and systems being studied in this course as measured by assessment items. However, their ability to apply these models in new contexts did not improve. Finally, we discuss the implications of our results and the future directions for our research. PMID:21123691

The growth threshold conjecture: a theoretical framework for understanding T-cell tolerance.

PubMed

Arias, Clemente F; Herrero, Miguel A; Cuesta, José A; Acosta, Francisco J; Fernández-Arias, Cristina

2015-07-01

Adaptive immune responses depend on the capacity of T cells to target specific antigens. As similar antigens can be expressed by pathogens and host cells, the question naturally arises of how can T cells discriminate friends from foes. In this work, we suggest that T cells tolerate cells whose proliferation rates remain below a permitted threshold. Our proposal relies on well-established facts about T-cell dynamics during acute infections: T-cell populations are elastic (they expand and contract) and they display inertia (contraction is delayed relative to antigen removal). By modelling inertia and elasticity, we show that tolerance to slow-growing populations can emerge as a population-scale feature of T cells. This result suggests a theoretical framework to understand immune tolerance that goes beyond the self versus non-self dichotomy. It also accounts for currently unexplained observations, such as the paradoxical tolerance to slow-growing pathogens or the presence of self-reactive T cells in the organism.

Multi-Scale Characean Experimental System: From Electrophysiology of Membrane Transporters to Cell-to-Cell Connectivity, Cytoplasmic Streaming and Auxin Metabolism

PubMed Central

Beilby, Mary J.

2016-01-01

The morphology of characean algae could be mistaken for a higher plant: stem-like axes with leaf-like branchlets anchored in the soil by root-like rhizoids. However, all of these structures are made up of giant multinucleate cells separated by multicellular nodal complexes. The excised internodal cells survive long enough for the nodes to give rise to new thallus. The size of the internodes and their thick cytoplasmic layer minimize impalement injury and allow specific micro-electrode placement. The cell structure can be manipulated by centrifugation, perfusion of cell contents or creation of cytoplasmic droplets, allowing access to both vacuolar and cytoplasmic compartments and both sides of the cell membranes. Thousands of electrical measurements on intact or altered cells and cytoplasmic droplets laid down basis to modern plant electrophysiology. Furthermore, the giant internodal cells and whole thalli facilitate research into many other plant properties. As nutrients have to be transported from rhizoids to growing parts of the thallus and hormonal signals need to pass from cell to cell, Characeae possess very fast cytoplasmic streaming. The mechanism was resolved in the characean model. Plasmodesmata between the internodal cells and nodal complexes facilitate transport of ions, nutrients and photosynthates across the nodes. The internal structure was found to be similar to those of higher plants. Recent experiments suggest a strong circadian influence on metabolic pathways producing indole-3-acetic acid (IAA) and serotonin/melatonin. The review will discuss the impact of the characean models arising from fragments of cells, single cells, cell-to-cell transport or whole thalli on understanding of plant evolution and physiology. PMID:27504112

Multi-Scale Characean Experimental System: From Electrophysiology of Membrane Transporters to Cell-to-Cell Connectivity, Cytoplasmic Streaming and Auxin Metabolism.

PubMed

Beilby, Mary J

2016-01-01

The morphology of characean algae could be mistaken for a higher plant: stem-like axes with leaf-like branchlets anchored in the soil by root-like rhizoids. However, all of these structures are made up of giant multinucleate cells separated by multicellular nodal complexes. The excised internodal cells survive long enough for the nodes to give rise to new thallus. The size of the internodes and their thick cytoplasmic layer minimize impalement injury and allow specific micro-electrode placement. The cell structure can be manipulated by centrifugation, perfusion of cell contents or creation of cytoplasmic droplets, allowing access to both vacuolar and cytoplasmic compartments and both sides of the cell membranes. Thousands of electrical measurements on intact or altered cells and cytoplasmic droplets laid down basis to modern plant electrophysiology. Furthermore, the giant internodal cells and whole thalli facilitate research into many other plant properties. As nutrients have to be transported from rhizoids to growing parts of the thallus and hormonal signals need to pass from cell to cell, Characeae possess very fast cytoplasmic streaming. The mechanism was resolved in the characean model. Plasmodesmata between the internodal cells and nodal complexes facilitate transport of ions, nutrients and photosynthates across the nodes. The internal structure was found to be similar to those of higher plants. Recent experiments suggest a strong circadian influence on metabolic pathways producing indole-3-acetic acid (IAA) and serotonin/melatonin. The review will discuss the impact of the characean models arising from fragments of cells, single cells, cell-to-cell transport or whole thalli on understanding of plant evolution and physiology.

The effects of RPM and recycle on separation efficiency in a clinical blood cell centrifuge.

PubMed

Drumheller, P D; Van Wie, B J; Petersen, J N; Oxford, R J; Schneider, G W

1987-11-01

A COBE blood cell centrifuge, model 2997 with a single stage channel, was modified to allow computer controlled sampling, and to allow recycle of red blood cells (RBCs) and plasma streams using bovine whole blood. The effects of recycle of the packed RBC and plasma product streams, and of the centrifuge RPM on platelet and white blood cell (WBC) separation efficiencies were quantified using a central composite factorial experimental design. These data were then fit using second order models. Both the model for the WBC separation efficiency and the model for the platelet separation efficiency predict that RPM has the greatest effect on separation efficiency and that RBC and plasma recycle have detrimental effects at moderate to low RPM, but have negligible impact on separation efficiency at high RPM.

On the mechanochemical theory of biological pattern formation with application to vasculogenesis.

PubMed

Murray, James D

2003-02-01

We first describe the Murray-Oster mechanical theory of pattern formation, the biological basis of which is experimentally well documented. The model quantifies the interaction of cells and the extracellular matrix via the cell-generated forces. The model framework is described in quantitative detail. Vascular endothelial cells, when cultured on gelled basement membrane matrix, rapidly aggregate into clusters while deforming the matrix into a network of cord-like structures tessellating the planar culture. We apply the mechanical theory of pattern formation to this culture system and show that neither strain-biased anisotropic cell traction nor cell migration are necessary for pattern formation: isotropic, strain-stimulated cell traction is sufficient to form the observed patterns. Predictions from the model were confirmed experimentally.

Architecture and inherent robustness of a bacterial cell-cycle control system.

PubMed

Shen, Xiling; Collier, Justine; Dill, David; Shapiro, Lucy; Horowitz, Mark; McAdams, Harley H

2008-08-12

A closed-loop control system drives progression of the coupled stalked and swarmer cell cycles of the bacterium Caulobacter crescentus in a near-mechanical step-like fashion. The cell-cycle control has a cyclical genetic circuit composed of four regulatory proteins with tight coupling to processive chromosome replication and cell division subsystems. We report a hybrid simulation of the coupled cell-cycle control system, including asymmetric cell division and responses to external starvation signals, that replicates mRNA and protein concentration patterns and is consistent with observed mutant phenotypes. An asynchronous sequential digital circuit model equivalent to the validated simulation model was created. Formal model-checking analysis of the digital circuit showed that the cell-cycle control is robust to intrinsic stochastic variations in reaction rates and nutrient supply, and that it reliably stops and restarts to accommodate nutrient starvation. Model checking also showed that mechanisms involving methylation-state changes in regulatory promoter regions during DNA replication increase the robustness of the cell-cycle control. The hybrid cell-cycle simulation implementation is inherently extensible and provides a promising approach for development of whole-cell behavioral models that can replicate the observed functionality of the cell and its responses to changing environmental conditions.

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

NASA Astrophysics Data System (ADS)

Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

2016-03-01

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Robust Dehaze Algorithm for Degraded Image of CMOS Image Sensors.

PubMed

Qu, Chen; Bi, Du-Yan; Sui, Ping; Chao, Ai-Nong; Wang, Yun-Fei

2017-09-22

The CMOS (Complementary Metal-Oxide-Semiconductor) is a new type of solid image sensor device widely used in object tracking, object recognition, intelligent navigation fields, and so on. However, images captured by outdoor CMOS sensor devices are usually affected by suspended atmospheric particles (such as haze), causing a reduction in image contrast, color distortion problems, and so on. In view of this, we propose a novel dehazing approach based on a local consistent Markov random field (MRF) framework. The neighboring clique in traditional MRF is extended to the non-neighboring clique, which is defined on local consistent blocks based on two clues, where both the atmospheric light and transmission map satisfy the character of local consistency. In this framework, our model can strengthen the restriction of the whole image while incorporating more sophisticated statistical priors, resulting in more expressive power of modeling, thus, solving inadequate detail recovery effectively and alleviating color distortion. Moreover, the local consistent MRF framework can obtain details while maintaining better results for dehazing, which effectively improves the image quality captured by the CMOS image sensor. Experimental results verified that the method proposed has the combined advantages of detail recovery and color preservation.

Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks

NASA Astrophysics Data System (ADS)

St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.

2018-02-01

We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

PubMed Central

2014-01-01

Background Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. Methods Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). Results Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. Conclusions The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols. PMID:25984272

Implementation of a Smeared Crack Band Model in a Micromechanics Framework

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Whole Blood Activation Results in Altered T Cell and Monocyte Cytokine Production Profiles by Flow Cytometry

NASA Technical Reports Server (NTRS)

Crucian, Brian E.; Sams, Clarence F.

2001-01-01

An excellent monitor of the immune balance of peripheral circulating cells is to determine their cytokine production patterns in response to stimuli. Using flow cytometry, a positive identification of cytokine producing cells in a mixed culture may be achieved. Recently, the ability to assess cytokine production following a whole-blood activation culture has been described. In this study, whole blood activation was compared to traditional PBMC activation and the individual cytokine secretion patterns for both T cells, T cell subsets and monocytes was determined by flow cytometry. RESULTS: For T cell cytokine assessment (IFNg/IL-10 and IL-21/L-4) following PMA +ionomycin activation: (1) a Significantly greater percentages of T cells producing IFNgamma and IL-2 were observed following whole-blood culture and (2) altered T cell cytokine production kinetics were observed by varying whole blood culture times. Four-color analysiS was used to allow assessment of cytokine production by specific T cell subsets. It was found that IFNgamma production was significantly elevated in the CD3+/CD8+ T cell population as compared to the CD3+/CD8- population following five hours of whole blood activation. Conversely, IL-2 and IL-10 production were Significantly elevated in the CD3+/CD8- T cell population as compared to the CD3+/CD8+ population. Monocyte cytokine production was assessed in both culture systems following LPS activation for 24 hours. A three-color flow cytometric was used to assess two cytokines (IL-1a/IL-12 and TNFa/IL-10) in conjunction with CD14. Nearly all monocytes were stimulated to produce IL-1a, IL-12 and TNFa. equally well in both culture systems, however monocyte production of IL-10 was significantly elevated in whole blood culture as compared to PBMC culture. IL-12 producing monocytes appeared to be a distinct subpopulation of the IL-1a producing set, whereas IL-10 and TNFa producing monocytes were largely mutually exclusive. IL-10 and TNFa producing monocytes may represent distinct monocyte subsets with unique functions. CONCLUSIONS: Whole blood culture eliminates the need to purify cell populations prior to culture and may have Significant utility for the routine monitoring of the cytokine balances of the peripheral blood T cell and monocyte populations. In addition, there are distinct advantages to performing whole-blood (WB) activation as compared to PBMC activation. These advantages would include retaining all various cell-cell interactions as well as any soluble factors present in serum that influence cell activation. In this study, alterations in cytokine production are demonstrated between whole blood and PBMC activation. It is likely that whole blood activation more accurately represents the in-vivo immune balance than PBMC activation.

Treatment of whole blood with riboflavin plus ultraviolet light, an alternative to gamma irradiation in the prevention of transfusion-associated graft-versus-host disease?

PubMed

Fast, Loren D; Nevola, Martha; Tavares, Jennifer; Reddy, Heather L; Goodrich, Ray P; Marschner, Susanne

2013-02-01

Exposure of blood products to gamma irradiation is currently the standard of care in the prevention of transfusion-associated graft-versus-host disease (TA-GVHD). Regulatory, technical, and clinical challenges associated with the use of gamma irradiators are driving efforts to develop alternatives. Pathogen reduction methods were initially developed to reduce the risk of microbial transmission by blood components. Through modifications of nucleic acids, these technologies interfere with the replication of both pathogens and white blood cells (WBCs). To date, systems for pathogen and WBC inactivation of products containing red blood cells are less well established than those for platelets and plasma. In this study, the in vitro and in vivo function of WBCs present in whole blood after exposure to riboflavin plus ultraviolet light (Rb-UV) was examined and compared to responses of WBCs obtained from untreated or gamma-irradiated blood by measuring proliferation, cytokine production, activation, and antigen presentation and xenogeneic (X-)GVHD responses in an in vivo mouse model. In vitro studies demonstrated that treatment of whole blood with Rb-UV was as effective as gamma irradiation in preventing WBC proliferation, but was more effective in preventing antigen presentation, cytokine production, and T-cell activation. Consistent with in vitro findings, treatment with Rb-UV was as effective as gamma irradiation in preventing X-GVHD, a mouse model for TA-GVHD. The ability to effectively inactivate WBCs in fresh whole blood using Rb-UV, prior to separation into components, provides the transfusion medicine community with a potential alternative to gamma irradiation. © 2012 American Association of Blood Banks.

Three-dimensional locations of gold-labeled proteins in a whole mount eukaryotic cell obtained with 3nm precision using aberration-corrected scanning transmission electron microscopy.

PubMed

Dukes, Madeline J; Ramachandra, Ranjan; Baudoin, Jean-Pierre; Gray Jerome, W; de Jonge, Niels

2011-06-01

Three-dimensional (3D) maps of proteins within the context of whole cells are important for investigating cellular function. However, 3D reconstructions of whole cells are challenging to obtain using conventional transmission electron microscopy (TEM). We describe a methodology to determine the 3D locations of proteins labeled with gold nanoparticles on whole eukaryotic cells. The epidermal growth factor receptors on COS7 cells were labeled with gold nanoparticles, and critical-point dried whole-mount cell samples were prepared. 3D focal series were obtained with aberration-corrected scanning transmission electron microscopy (STEM), without tilting the specimen. The axial resolution was improved with deconvolution. The vertical locations of the nanoparticles in a whole-mount cell were determined with a precision of 3nm. From the analysis of the variation of the axial positions of the labels we concluded that the cellular surface was ruffled. To achieve sufficient stability of the sample under electron beam irradiation during the recording of the focal series, the sample was carbon coated. A quantitative method was developed to analyze the stability of the ultrastructure after electron beam irradiation using TEM. The results of this study demonstrate the feasibility of using aberration-corrected STEM to study the 3D nanoparticle distribution in whole cells. Copyright © 2011 Elsevier Inc. All rights reserved.

Three-dimensional locations of gold-labeled proteins in a whole mount eukaryotic cell obtained with 3 nm precision using aberration-corrected scanning transmission electron microscopy

PubMed Central

Dukes, Madeline J.; Ramachandra, Ranjan; Baudoin, Jean-Pierre; Jerome, W. Gray; de Jonge, Niels

2011-01-01

Three-dimensional (3D) maps of proteins within the context of whole cells are important for investigating cellular function. However, 3D reconstructions of whole cells are challenging to obtain using conventional transmission electron microscopy (TEM). We describe a methodology to determine the 3D locations of proteins labeled with gold nanoparticles on whole eukaryotic cells. The epidermal growth factor receptors on COS7 cells were labeled with gold nanoparticles, and critical-point dried whole-mount cell samples were prepared. 3D focal series were obtained with aberration-corrected scanning transmission electron microscopy (STEM), without tilting the specimen. The axial resolution was improved with deconvolution. The vertical locations of the nanoparticles in a whole-mount cell were determined with a precision of 3 nm. From the analysis of the variation of the axial positions of the labels we concluded that the cellular surface was ruffled. To achieve sufficient stability of the sample under the electron beam irradiation during the recording of the focal series, the sample was carbon coated. A quantitative method was developed to analyze the stability of the ultrastructure after electron beam irradiation using TEM. The results of this study demonstrate the feasibility of using aberration-corrected STEM to study the 3D nanoparticle distribution in whole cells. PMID:21440635

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in Flash

NASA Technical Reports Server (NTRS)

Dubey, A.; Daley, C.; ZuHone, J.; Ricker, P. M.; Weide, K.; Graziani, C.

2012-01-01

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in FLASH

NASA Astrophysics Data System (ADS)

Dubey, A.; Daley, C.; ZuHone, J.; Ricker, P. M.; Weide, K.; Graziani, C.

2012-08-01

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid-structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

PubMed

Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain

2017-07-01

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data.

PubMed

Fan, Yu; Xi, Liu; Hughes, Daniel S T; Zhang, Jianjun; Zhang, Jianhua; Futreal, P Andrew; Wheeler, David A; Wang, Wenyi

2016-08-24

Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.

Two-photon in vivo flow cytometry using a fiber probe

NASA Astrophysics Data System (ADS)

Chang, Yu-Chung; Ye, Jing Yong; Thomas, Thommey P.; Cao, Zhengyi; Kotlyar, Alina; Tkaczyk, Eric R.; Baker, James R., Jr.; Norris, Theodore B.

2009-02-01

We have demonstrated the use of a double-clad fiber probe to conduct two-photon excited flow cytometry in vitro and in vivo. We conducted two-channel detection to measure fluorescence at two distinct wavelengths simultaneously. Because the scattering and absorption problems from whole blood were circumvented by the fiber probe, the detected signal strength from the cells were found to be similar in PBS and in whole blood. We achieved the same detection efficiency of the membrane-binding lipophilic dye DiD labeled cells in PBS and in whole blood. High detection efficiency of green fluorescent protein (GFP)-expressing cells in whole blood was demonstrated. DiD-labeled untransfected and GFP-transfected cells were injected into live mice and the circulation dynamics of the externally injected cells were monitored. The detection efficiency of GFP-expressing cells in vivo was consistent with that observed in whole blood.

Unexpected effects of different genetic backgrounds on identification of genomic rearrangements via whole-genome next generation sequencing.

PubMed

Chen, Zhangguo; Gowan, Katherine; Leach, Sonia M; Viboolsittiseri, Sawanee S; Mishra, Ameet K; Kadoishi, Tanya; Diener, Katrina; Gao, Bifeng; Jones, Kenneth; Wang, Jing H

2016-10-21

Whole genome next generation sequencing (NGS) is increasingly employed to detect genomic rearrangements in cancer genomes, especially in lymphoid malignancies. We recently established a unique mouse model by specifically deleting a key non-homologous end-joining DNA repair gene, Xrcc4, and a cell cycle checkpoint gene, Trp53, in germinal center B cells. This mouse model spontaneously develops mature B cell lymphomas (termed G1XP lymphomas). Here, we attempt to employ whole genome NGS to identify novel structural rearrangements, in particular inter-chromosomal translocations (CTXs), in these G1XP lymphomas. We sequenced six lymphoma samples, aligned our NGS data with mouse reference genome (in C57BL/6J (B6) background) and identified CTXs using CREST algorithm. Surprisingly, we detected widespread CTXs in both lymphomas and wildtype control samples, majority of which were false positive and attributable to different genetic backgrounds. In addition, we validated our NGS pipeline by sequencing multiple control samples from distinct tissues of different genetic backgrounds of mouse (B6 vs non-B6). Lastly, our studies showed that widespread false positive CTXs can be generated by simply aligning sequences from different genetic backgrounds of mouse. We conclude that mapping and alignment with reference genome might not be a preferred method for analyzing whole-genome NGS data obtained from a genetic background different from reference genome. Given the complex genetic background of different mouse strains or the heterogeneity of cancer genomes in human patients, in order to minimize such systematic artifacts and uncover novel CTXs, a preferred method might be de novo assembly of personalized normal control genome and cancer cell genome, instead of mapping and aligning NGS data to mouse or human reference genome. Thus, our studies have critical impact on the manner of data analysis for cancer genomics.

A Petascale Non-Hydrostatic Atmospheric Dynamical Core in the HOMME Framework

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

Tufo, Henry

The High-Order Method Modeling Environment (HOMME) is a framework for building scalable, conserva- tive atmospheric models for climate simulation and general atmospheric-modeling applications. Its spatial discretizations are based on Spectral-Element (SE) and Discontinuous Galerkin (DG) methods. These are local methods employing high-order accurate spectral basis-functions that have been shown to perform well on massively parallel supercomputers at any resolution and scale particularly well at high resolutions. HOMME provides the framework upon which the CAM-SE community atmosphere model dynamical-core is constructed. In its current incarnation, CAM-SE employs the hydrostatic primitive-equations (PE) of motion, which limits its resolution to simulations coarser thanmore » 0.1 per grid cell. The primary objective of this project is to remove this resolution limitation by providing HOMME with the capabilities needed to build nonhydrostatic models that solve the compressible Euler/Navier-Stokes equations.« less

A physics-based crystallographic modeling framework for describing the thermal creep behavior of Fe-Cr alloys

DOE PAGES

Wen, Wei; Capolungo, Laurent; Patra, Anirban; ...

2017-02-23

In this work, a physics-based thermal creep model is developed based on the understanding of the microstructure in Fe-Cr alloys. This model is associated with a transition state theory based framework that considers the distribution of internal stresses at sub-material point level. The thermally activated dislocation glide and climb mechanisms are coupled in the obstacle-bypass processes for both dislocation and precipitate-type barriers. A kinetic law is proposed to track the dislocation densities evolution in the subgrain interior and in the cell wall. The predicted results show that this model, embedded in the visco-plastic self-consistent (VPSC) framework, captures well the creepmore » behaviors for primary and steady-state stages under various loading conditions. We also discuss the roles of the mechanisms involved.« less

Micromechanical model of lung parenchyma hyperelasticity

NASA Astrophysics Data System (ADS)

Concha, Felipe; Sarabia-Vallejos, Mauricio; Hurtado, Daniel E.

2018-03-01

Mechanics plays a key role in respiratory physiology, as lung tissue cyclically deforms to bring air in and out the lung, a life-long process necessary for respiration. The study of regional mechanisms of deformation in lung parenchyma has received great attention to date due to its clinical relevance, as local overstretching and stress concentration in lung tissue is currently associated to pathological conditions such as lung injury during mechanical ventilation therapy. This mechanical approach to lung physiology has motivated the development of constitutive models to better understand the relation between stress and deformation in the lung. While material models proposed to date have been key in the development of whole-lung simulations, either they do not directly relate microstructural properties of alveolar tissue with coarse-scale behavior, or they require a high computational effort when based on real alveolar geometries. Furthermore, most models proposed to date have not been thoroughly validated for anisotropic deformation states, which are commonly found in normal lungs in-vivo. In this work, we develop a novel micromechanical model of lung parenchyma hyperelasticity using the framework of finite-deformation homogenization. To this end, we consider a tetrakaidecahedron unit cell with incompressible Neo-Hookean structural elements that account for the alveolar wall tissue responsible for the elastic response, and derive expressions for its effective coarse-scale behavior that directly depend on the alveolar wall elasticity, reference porosity, and two other geometrical coefficients. To validate the proposed model, we simulate the non-linear elastic response of twelve representative volume elements (RVEs) of lung parenchyma with micrometric dimensions, whose geometry is obtained from micrometric computed-tomography reconstructions of murine lungs. We show that the proposed micromechanical model accurately captures the RVEs response not only for isotropic volumetric expansion, but also for three other anisotropic loading conditions for different levels of tissue porosity, while displaying superior computational efficiency and stability in estimating coarse-scale response when compared to direct numerical simulations of RVEs. Further, we find that the most influential microstructural parameters on the response of the micromechanical model are the reference porosity and the alveolar wall elasticity. We also show that the model can reproduce uniaxial experimental tests on lung tissue samples, and estimate the Poisson ratio to be 0.22. We envision that our model will enable predictive and efficient whole-organ simulations useful to study the normal and diseased lung.

Building an Open Source Framework for Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Jagers, B.; Meijers, E.; Villars, M.

2015-12-01

In order to develop effective strategies and associated policies for environmental management, we need to understand the dynamics of the natural system as a whole and the human role therein. This understanding is gained by comparing our mental model of the world with observations from the field. However, to properly understand the system we should look at dynamics of water, sediments, water quality, and ecology throughout the whole system from catchment to coast both at the surface and in the subsurface. Numerical models are indispensable in helping us understand the interactions of the overall system, but we need to be able to update and adjust them to improve our understanding and test our hypotheses. To support researchers around the world with this challenging task we started a few years ago with the development of a new open source modeling environment DeltaShell that integrates distributed hydrological models with 1D, 2D, and 3D hydraulic models including generic components for the tracking of sediment, water quality, and ecological quantities throughout the hydrological cycle composed of the aforementioned components. The open source approach combined with a modular approach based on open standards, which allow for easy adjustment and expansion as demands and knowledge grow, provides an ideal starting point for addressing challenging integrated environmental questions.

A multi-level simulation platform of natural gas internal reforming solid oxide fuel cell-gas turbine hybrid generation system - Part II. Balancing units model library and system simulation

NASA Astrophysics Data System (ADS)

Bao, Cheng; Cai, Ningsheng; Croiset, Eric

2011-10-01

Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.

Integration of Multidisciplinary Sensory Data:

PubMed Central

Miller, Perry L.; Nadkarni, Prakash; Singer, Michael; Marenco, Luis; Hines, Michael; Shepherd, Gordon

2001-01-01

The paper provides an overview of neuroinformatics research at Yale University being performed as part of the national Human Brain Project. This research is exploring the integration of multidisciplinary sensory data, using the olfactory system as a model domain. The neuroinformatics activities fall into three main areas: 1) building databases and related tools that support experimental olfactory research at Yale and can also serve as resources for the field as a whole, 2) using computer models (molecular models and neuronal models) to help understand data being collected experimentally and to help guide further laboratory experiments, 3) performing basic neuroinformatics research to develop new informatics technologies, including a flexible data model (EAV/CR, entity-attribute-value with classes and relationships) designed to facilitate the integration of diverse heterogeneous data within a single unifying framework. PMID:11141511

["Health 2020" - the New European Framework Strategy of WHO].

PubMed

Michelsen, K; Brand, H

2012-12-01

The WHO Regional Committee for Europe agreed in September 2012 on the new framework strategy "Health 2020". The framework has the strategic objectives of improving health for all and reducing health inequalities as well as improving leadership and participatory governance for health. The present article introduces the basic points of "Health 2020". Central elements (European Action Plan for Strengthening Public Health and Public Health Services, health and well-being, reducing health inequalities, whole-of-governance and whole-of-society approaches) are described in more detail, taking background materials into account. Critical remarks address the implementation, reporting and governance issues. They are discussed by taking into account the context of the development of "Health 2020". Even if some critical aspects exist, it can be stated that "Health 2020" delivers a framework and orientation for health policies - as well as for the heterogeneous situation in WHO Europe as well as for Germany. © Georg Thieme Verlag KG Stuttgart · New York.

Marijuana smoke induces severe pulmonary hyperresponsiveness, inflammation, and emphysema in a predictive mouse model not via CB1 receptor activation.

PubMed

Helyes, Z; Kemény, Á; Csekő, K; Szőke, É; Elekes, K; Mester, M; Sándor, K; Perkecz, A; Kereskai, L; Márk, L; Bona, Á; Benkő, A; Pintér, E; Szolcsányi, J; Ledent, C; Sperlágh, B; Molnár, T F

2017-08-01

Sporadic clinical reports suggested that marijuana smoking induces spontaneous pneumothorax, but no animal models were available to validate these observations and to study the underlying mechanisms. Therefore, we performed a systematic study in CD1 mice as a predictive animal model and assessed the pathophysiological alterations in response to 4-mo-long whole body marijuana smoke with integrative methodologies in comparison with tobacco smoke. Bronchial responsiveness was measured with unrestrained whole body plethysmography, cell profile in the bronchoalveolar lavage fluid with flow cytometry, myeloperoxidase activity with spectrophotometry, inflammatory cytokines with ELISA, and histopathological alterations with light microscopy. Daily marijuana inhalation evoked severe bronchial hyperreactivity after a week. Characteristic perivascular/peribronchial edema, atelectasis, apical emphysema, and neutrophil and macrophage infiltration developed after 1 mo of marijuana smoking; lymphocyte accumulation after 2 mo; macrophage-like giant cells, irregular or destroyed bronchial mucosa, goblet cell hyperplasia after 3 mo; and severe atelectasis, emphysema, obstructed or damaged bronchioles, and endothelial proliferation at 4 mo. Myeloperoxidase activity, inflammatory cell, and cytokine profile correlated with these changes. Airway hyperresponsiveness and inflammation were not altered in mice lacking the CB1 cannabinoid receptor. In comparison, tobacco smoke induced hyperresponsiveness after 2 mo and significantly later caused inflammatory cell infiltration/activation with only mild emphysema. We provide the first systematic and comparative experimental evidence that marijuana causes severe airway hyperresponsiveness, inflammation, tissue destruction, and emphysema, which are not mediated by the CB1 receptor. Copyright © 2017 the American Physiological Society.

Promoting School Connectedness through Whole School Approaches

ERIC Educational Resources Information Center

Rowe, Fiona; Stewart, Donald; Patterson, Carla

2007-01-01

Purpose: The purpose of this paper is to develop a framework to demonstrate the contribution of whole school approaches embodied by the health-promoting school approach, to the promotion of school connectedness, defined as the cohesiveness between diverse groups in the school community, including students, families, school staff and the wider…

Nutrition Education: Towards a Whole-School Approach

ERIC Educational Resources Information Center

Rowe, Fiona; Stewart, Donald; Somerset, Shawn

2010-01-01

Purpose: Schools are widely accepted as having the potential to make substantial contributions to promoting healthy eating habits in children and adolescents. This paper aims to present a case study from an Australian school of how a whole-school approach, planned and implemented through a health promoting school framework, can foster improved…

Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

PubMed

Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

2009-08-31

Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.

[Progress in stem cells and regenerative medicine].

PubMed

Wang, Libin; Zhu, He; Hao, Jie; Zhou, Qi

2015-06-01

Stem cells have the ability to differentiate into all types of cells in the body and therefore have great application potential in regenerative medicine, in vitro disease modelling and drug screening. In recent years, stem cell technology has made great progress, and induced pluripotent stem cell technology revolutionizes the whole stem cell field. At the same time, stem cell research in our country has also achieved great progress and becomes an indispensable power in the worldwide stem cell research field. This review mainly focuses on the research progress in stem cells and regenerative medicine in our country since the advent of induced pluripotent stem cell technology, including induced pluripotent stem cells, transdifferentiation, haploid stem cells, and new gene editing tools.

A flexible and qualitatively stable model for cell cycle dynamics including DNA damage effects.

PubMed

Jeffries, Clark D; Johnson, Charles R; Zhou, Tong; Simpson, Dennis A; Kaufmann, William K

2012-01-01

This paper includes a conceptual framework for cell cycle modeling into which the experimenter can map observed data and evaluate mechanisms of cell cycle control. The basic model exhibits qualitative stability, meaning that regardless of magnitudes of system parameters its instances are guaranteed to be stable in the sense that all feasible trajectories converge to a certain trajectory. Qualitative stability can also be described by the signs of real parts of eigenvalues of the system matrix. On the biological side, the resulting model can be tuned to approximate experimental data pertaining to human fibroblast cell lines treated with ionizing radiation, with or without disabled DNA damage checkpoints. Together these properties validate a fundamental, first order systems view of cell dynamics. Classification Codes: 15A68.

Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.

PubMed

Getto, Philipp; Marciniak-Czochra, Anna

2015-01-01

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.

Simulation study of pO2 distribution in induced tumour masses and normal tissues within a microcirculation environment.

PubMed

Li, Mao; Li, Yan; Wen, Peng Paul

2014-01-01

The biological microenvironment is interrupted when tumour masses are introduced because of the strong competition for oxygen. During the period of avascular growth of tumours, capillaries that existed play a crucial role in supplying oxygen to both tumourous and healthy cells. Due to limitations of oxygen supply from capillaries, healthy cells have to compete for oxygen with tumourous cells. In this study, an improved Krogh's cylinder model which is more realistic than the previously reported assumption that oxygen is homogeneously distributed in a microenvironment, is proposed to describe the process of the oxygen diffusion from a capillary to its surrounding environment. The capillary wall permeability is also taken into account. The simulation study is conducted and the results show that when tumour masses are implanted at the upstream part of a capillary and followed by normal tissues, the whole normal tissues suffer from hypoxia. In contrast, when normal tissues are ahead of tumour masses, their pO2 is sufficient. In both situations, the pO2 in the whole normal tissues drops significantly due to the axial diffusion at the interface of normal tissues and tumourous cells. As the existence of the axial oxygen diffusion cannot supply the whole tumour masses, only these tumourous cells that are near the interface can be partially supplied, and have a small chance to survive.

Quantifying Selective Pressures Driving Bacterial Evolution Using Lineage Analysis

NASA Astrophysics Data System (ADS)

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population's rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages—i.e., the life histories of individuals and their ancestors—to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to Escherichia coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems.

Quantifying selective pressures driving bacterial evolution using lineage analysis

PubMed Central

Lambert, Guillaume; Kussell, Edo

2015-01-01

Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population’s rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages –i.e. the life-histories of individuals and their ancestors– to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to E. coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life-history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection, and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems. PMID:26213639

Modelling Molecular Mechanisms: A Framework of Scientific Reasoning to Construct Molecular-Level Explanations for Cellular Behaviour

ERIC Educational Resources Information Center

van Mil, Marc H. W.; Boerwinkel, Dirk Jan; Waarlo, Arend Jan

2013-01-01

Although molecular-level details are part of the upper-secondary biology curriculum in most countries, many studies report that students fail to connect molecular knowledge to phenomena at the level of cells, organs and organisms. Recent studies suggest that students lack a framework to reason about complex systems to make this connection. In this…

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

PubMed

Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T; Tyson, John J

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks

PubMed Central

Laomettachit, Teeraphan; Chen, Katherine C.; Baumann, William T.

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast. PMID:27187804

Giga-seal formation alters properties of sodium channels of human myoballs.

PubMed

Fahlke, C; Rüdel, R

1992-03-01

The influence of giga-seal formation on the properties of the Na+ channels within the covered membrane patch was investigated with a whole-cell pipette and a patch pipette applied to the same cell. Current kinetics, current/voltage relation and channel densities were determined in three combinations: (i) voltage-clamping and current recording with the whole-cell pipette, (ii) voltage-clamping with the whole-cell pipette and current recording with the patch pipette and, (iii) voltage-clamping and current recording with the patch pipette. The Hodgkin-Huxley (1952) parameters tau m and tau h were smaller for the patch currents than for the whole cell, and the h infinity curve was shifted in the negative direction. The channel density was of the order of 10 times smaller. All effects were independent of the extracellular Ca2+ concentration. The capacitive current generated in the patch by the whole-cell Na+ current and its effect on the transmembrane voltage of the patch were evaluated. The kinetic parameters of the Na+ channels in the patch did not depend on whether the voltage was clamped with the whole-cell pipette or the patch pipette. Thus, the results are not due to spurious voltage.

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

PubMed

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Cross-Species Extrapolation of Uptake and Disposition of Neutral Organic Chemicals in Fish Using a Multispecies Physiologically-Based Toxicokinetic Model Framework.

PubMed

Brinkmann, Markus; Schlechtriem, Christian; Reininghaus, Mathias; Eichbaum, Kathrin; Buchinger, Sebastian; Reifferscheid, Georg; Hollert, Henner; Preuss, Thomas G

2016-02-16

The potential to bioconcentrate is generally considered to be an unwanted property of a substance. Consequently, chemical legislation, including the European REACH regulations, requires the chemical industry to provide bioconcentration data for chemicals that are produced or imported at volumes exceeding 100 tons per annum or if there is a concern that a substance is persistent, bioaccumulative, and toxic. For the filling of the existing data gap for chemicals produced or imported at levels that are below this stipulated volume, without the need for additional animal experiments, physiologically-based toxicokinetic (PBTK) models can be used to predict whole-body and tissue concentrations of neutral organic chemicals in fish. PBTK models have been developed for many different fish species with promising results. In this study, we developed PBTK models for zebrafish (Danio rerio) and roach (Rutilus rutilus) and combined them with existing models for rainbow trout (Onchorhynchus mykiss), lake trout (Salvelinus namaycush), and fathead minnow (Pimephales promelas). The resulting multispecies model framework allows for cross-species extrapolation of the bioaccumulative potential of neutral organic compounds. Predictions were compared with experimental data and were accurate for most substances. Our model can be used for probabilistic risk assessment of chemical bioaccumulation, with particular emphasis on cross-species evaluations.

Data assimilation and prognostic whole ice sheet modelling with the variationally derived, higher order, open source, and fully parallel ice sheet model VarGlaS

NASA Astrophysics Data System (ADS)

Brinkerhoff, D. J.; Johnson, J. V.

2013-07-01

We introduce a novel, higher order, finite element ice sheet model called VarGlaS (Variational Glacier Simulator), which is built on the finite element framework FEniCS. Contrary to standard procedure in ice sheet modelling, VarGlaS formulates ice sheet motion as the minimization of an energy functional, conferring advantages such as a consistent platform for making numerical approximations, a coherent relationship between motion and heat generation, and implicit boundary treatment. VarGlaS also solves the equations of enthalpy rather than temperature, avoiding the solution of a contact problem. Rather than include a lengthy model spin-up procedure, VarGlaS possesses an automated framework for model inversion. These capabilities are brought to bear on several benchmark problems in ice sheet modelling, as well as a 500 yr simulation of the Greenland ice sheet at high resolution. VarGlaS performs well in benchmarking experiments and, given a constant climate and a 100 yr relaxation period, predicts a mass evolution of the Greenland ice sheet that matches present-day observations of mass loss. VarGlaS predicts a thinning in the interior and thickening of the margins of the ice sheet.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

The Cell Collective: Toward an open and collaborative approach to systems biology

PubMed Central

2012-01-01

Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction. PMID:22871178

Revisiting the body-schema concept in the context of whole-body postural-focal dynamics.

PubMed

Morasso, Pietro; Casadio, Maura; Mohan, Vishwanathan; Rea, Francesco; Zenzeri, Jacopo

2015-01-01

The body-schema concept is revisited in the context of embodied cognition, further developing the theory formulated by Marc Jeannerod that the motor system is part of a simulation network related to action, whose function is not only to shape the motor system for preparing an action (either overt or covert) but also to provide the self with information on the feasibility and the meaning of potential actions. The proposed computational formulation is based on a dynamical system approach, which is linked to an extension of the equilibrium-point hypothesis, called Passive Motor Paradigm: this dynamical system generates goal-oriented, spatio-temporal, sensorimotor patterns, integrating a direct and inverse internal model in a multi-referential framework. The purpose of such computational model is to operate at the same time as a general synergy formation machinery for planning whole-body actions in humanoid robots and/or for predicting coordinated sensory-motor patterns in human movements. In order to illustrate the computational approach, the integration of simultaneous, even partially conflicting tasks will be analyzed in some detail with regard to postural-focal dynamics, which can be defined as the fusion of a focal task, namely reaching a target with the whole-body, and a postural task, namely maintaining overall stability.

Revisiting the Body-Schema Concept in the Context of Whole-Body Postural-Focal Dynamics

PubMed Central

Morasso, Pietro; Casadio, Maura; Mohan, Vishwanathan; Rea, Francesco; Zenzeri, Jacopo

2015-01-01

The body-schema concept is revisited in the context of embodied cognition, further developing the theory formulated by Marc Jeannerod that the motor system is part of a simulation network related to action, whose function is not only to shape the motor system for preparing an action (either overt or covert) but also to provide the self with information on the feasibility and the meaning of potential actions. The proposed computational formulation is based on a dynamical system approach, which is linked to an extension of the equilibrium-point hypothesis, called Passive Motor Paradigm: this dynamical system generates goal-oriented, spatio-temporal, sensorimotor patterns, integrating a direct and inverse internal model in a multi-referential framework. The purpose of such computational model is to operate at the same time as a general synergy formation machinery for planning whole-body actions in humanoid robots and/or for predicting coordinated sensory–motor patterns in human movements. In order to illustrate the computational approach, the integration of simultaneous, even partially conflicting tasks will be analyzed in some detail with regard to postural-focal dynamics, which can be defined as the fusion of a focal task, namely reaching a target with the whole-body, and a postural task, namely maintaining overall stability. PMID:25741274

Modeling whole-tree carbon assimilation rate using observed transpiration rates and needle sugar carbon isotope ratios.

PubMed

Hu, Jia; Moore, David J P; Riveros-Iregui, Diego A; Burns, Sean P; Monson, Russell K

2010-03-01

*Understanding controls over plant-atmosphere CO(2) exchange is important for quantifying carbon budgets across a range of spatial and temporal scales. In this study, we used a simple approach to estimate whole-tree CO(2) assimilation rate (A(Tree)) in a subalpine forest ecosystem. *We analysed the carbon isotope ratio (delta(13)C) of extracted needle sugars and combined it with the daytime leaf-to-air vapor pressure deficit to estimate tree water-use efficiency (WUE). The estimated WUE was then combined with observations of tree transpiration rate (E) using sap flow techniques to estimate A(Tree). Estimates of A(Tree) for the three dominant tree species in the forest were combined with species distribution and tree size to estimate and gross primary productivity (GPP) using an ecosystem process model. *A sensitivity analysis showed that estimates of A(Tree) were more sensitive to dynamics in E than delta(13)C. At the ecosystem scale, the abundance of lodgepole pine trees influenced seasonal dynamics in GPP considerably more than Engelmann spruce and subalpine fir because of its greater sensitivity of E to seasonal climate variation. *The results provide the framework for a nondestructive method for estimating whole-tree carbon assimilation rate and ecosystem GPP over daily-to weekly time scales.

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application.

PubMed

Karakatsanis, Nicolas A; Lodge, Martin A; Tahari, Abdel K; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ~15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ~45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ~35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.

Dynamic whole body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

PubMed Central

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

Static whole body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single bed-coverage limiting the axial field-of-view to ~15–20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole body PET acquisition protocol of ~45min total length is presented, composed of (i) an initial 6-min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (6 passes x 7 bed positions, each scanned for 45sec). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares (OLS) Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of 10 different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole-body. In addition, the total acquisition length can be reduced from 45min to ~35min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error (MSE) and the CNR metrics, resulting in enhanced task-based imaging. PMID:24080962

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-10-01

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ˜15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ˜45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ˜35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.

A theoretical and computational framework for mechanics of the cortex

NASA Astrophysics Data System (ADS)

Torres-SáNchez, Alejandro; Arroyo, Marino

The cell cortex is a thin network of actin filaments lying beneath the cell surface of animal cells. Myosin motors exert contractile forces in this network leading to active stresses, which play a key role in processes such as cytokinesis or cell migration. Thus, understanding the mechanics of the cortex is fundamental to understand the mechanics of animal cells. Due to the dynamic remodeling of the actin network, the cortex behaves as a viscoelastic fluid. Furthermore, due to the difference between its thickness (tens of nanometers) and its dimensions (tens of microns), the cortex can be regarded a surface. Thus, we can model the cortex as a viscoelastic fluid, confined to a surface, that generates active stresses. Interestingly, geometric confinement results in the coupling between shape generation and material flows. In this work we present a theoretical framework to model the mechanics of the cortex that couples elasticity, hydrodynamics and force generation. We complement our theoretical description with a computational setting to simulate the resulting non-linear equations. We use this methodology to understand different processes such as asymmetric cell division or experimental probing of the rheology of the cortex We acknowledge the support of the Europen Research Council through Grant ERC CoG-681434.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

PubMed

Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Collective decision dynamics in the presence of external drivers

NASA Astrophysics Data System (ADS)

Bassett, Danielle S.; Alderson, David L.; Carlson, Jean M.

2012-09-01

We develop a sequence of models describing information transmission and decision dynamics for a network of individual agents subject to multiple sources of influence. Our general framework is set in the context of an impending natural disaster, where individuals, represented by nodes on the network, must decide whether or not to evacuate. Sources of influence include a one-to-many externally driven global broadcast as well as pairwise interactions, across links in the network, in which agents transmit either continuous opinions or binary actions. We consider both uniform and variable threshold rules on the individual opinion as baseline models for decision making. Our results indicate that (1) social networks lead to clustering and cohesive action among individuals, (2) binary information introduces high temporal variability and stagnation, and (3) information transmission over the network can either facilitate or hinder action adoption, depending on the influence of the global broadcast relative to the social network. Our framework highlights the essential role of local interactions between agents in predicting collective behavior of the population as a whole.

Tissue Engineering Whole Bones Through Endochondral Ossification: Regenerating the Distal Phalanx.

PubMed

Sheehy, Eamon J; Mesallati, Tariq; Kelly, Lara; Vinardell, Tatiana; Buckley, Conor T; Kelly, Daniel J

2015-01-01

Novel strategies are urgently required to facilitate regeneration of entire bones lost due to trauma or disease. In this study, we present a novel framework for the regeneration of whole bones by tissue engineering anatomically shaped hypertrophic cartilaginous grafts in vitro that subsequently drive endochondral bone formation in vivo. To realize this, we first fabricated molds from digitized images to generate mesenchymal stem cell-laden alginate hydrogels in the shape of different bones (the temporomandibular joint [TMJ] condyle and the distal phalanx). These constructs could be stimulated in vitro to generate anatomically shaped hypertrophic cartilaginous tissues that had begun to calcify around their periphery. Constructs were then formed into the shape of the distal phalanx to create the hypertrophic precursor of the osseous component of an engineered long bone. A layer of cartilage engineered through self-assembly of chondrocytes served as the articular surface of these constructs. Following chondrogenic priming and subcutaneous implantation, the hypertrophic phase of the engineered phalanx underwent endochondral ossification, leading to the generation of a vascularized bone integrated with a covering layer of stable articular cartilage. Furthermore, spatial bone deposition within the construct could be modulated by altering the architecture of the osseous component before implantation. These findings open up new horizons to whole limb regeneration by recapitulating key aspects of normal bone development.

The Impact of Cell Density and Mutations in a Model of Multidrug Resistance in Solid Tumors

PubMed Central

Greene, James; Lavi, Orit; Gottesman, Michael M.; Levy, Doron

2016-01-01

In this paper we develop a mathematical framework for describing multidrug resistance in cancer. To reflect the complexity of the underlying interplay between cancer cells and the therapeutic agent, we assume that the resistance level is a continuous parameter. Our model is written as a system of integro-differential equations that are parametrized by the resistance level. This model incorporates the cell-density and mutation dependence. Analysis and simulations of the model demonstrate how the dynamics evolves to a selection of one or more traits corresponding to different levels of resistance. The emerging limit distribution with nonzero variance is the desirable modeling outcome as it represents tumor heterogeneity. PMID:24553772

Developing a good practice model to evaluate the effectiveness of comprehensive primary health care in local communities

PubMed Central

2014-01-01

Background This paper describes the development of a model of Comprehensive Primary Health Care (CPHC) applicable to the Australian context. CPHC holds promise as an effective model of health system organization able to improve population health and increase health equity. However, there is little literature that describes and evaluates CPHC as a whole, with most evaluation focusing on specific programs. The lack of a consensus on what constitutes CPHC, and the complex and context-sensitive nature of CPHC are all barriers to evaluation. Methods The research was undertaken in partnership with six Australian primary health care services: four state government funded and managed services, one sexual health non-government organization, and one Aboriginal community controlled health service. A draft model was crafted combining program logic and theory-based approaches, drawing on relevant literature, 68 interviews with primary health care service staff, and researcher experience. The model was then refined through an iterative process involving two to three workshops at each of the six participating primary health care services, engaging health service staff, regional health executives and central health department staff. Results The resultant Southgate Model of CPHC in Australia model articulates the theory of change of how and why CPHC service components and activities, based on the theory, evidence and values which underpin a CPHC approach, are likely to lead to individual and population health outcomes and increased health equity. The model captures the importance of context, the mechanisms of CPHC, and the space for action services have to work within. The process of development engendered and supported collaborative relationships between researchers and stakeholders and the product provided a description of CPHC as a whole and a framework for evaluation. The model was endorsed at a research symposium involving investigators, service staff, and key stakeholders. Conclusions The development of a theory-based program logic model provided a framework for evaluation that allows the tracking of progress towards desired outcomes and exploration of the particular aspects of context and mechanisms that produce outcomes. This is important because there are no existing models which enable the evaluation of CPHC services in their entirety. PMID:24885812

Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory.

PubMed

Anelone, Anet J N; Spurgeon, Sarah K

2016-01-01

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.

Energy-based culture medium design for biomanufacturing optimization: A case study in monoclonal antibody production by GS-NS0 cells.

PubMed

Quiroga-Campano, Ana L; Panoskaltsis, Nicki; Mantalaris, Athanasios

2018-03-02

Demand for high-value biologics, a rapidly growing pipeline, and pressure from competition, time-to-market and regulators, necessitate novel biomanufacturing approaches, including Quality by Design (QbD) principles and Process Analytical Technologies (PAT), to facilitate accelerated, efficient and effective process development platforms that ensure consistent product quality and reduced lot-to-lot variability. Herein, QbD and PAT principles were incorporated within an innovative in vitro-in silico integrated framework for upstream process development (UPD). The central component of the UPD framework is a mathematical model that predicts dynamic nutrient uptake and average intracellular ATP content, based on biochemical reaction networks, to quantify and characterize energy metabolism and its adaptive response, metabolic shifts, to maintain ATP homeostasis. The accuracy and flexibility of the model depends on critical cell type/product/clone-specific parameters, which are experimentally estimated. The integrated in vitro-in silico platform and the model's predictive capacity reduced burden, time and expense of experimentation resulting in optimal medium design compared to commercially available culture media (80% amino acid reduction) and a fed-batch feeding strategy that increased productivity by 129%. The framework represents a flexible and efficient tool that transforms, improves and accelerates conventional process development in biomanufacturing with wide applications, including stem cell-based therapies. Copyright © 2018. Published by Elsevier Inc.

An ice sheet model validation framework for the Greenland ice sheet

NASA Astrophysics Data System (ADS)

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P.; Evans, Katherine J.; Kennedy, Joseph H.; Lenaerts, Jan; Lipscomb, William H.; Perego, Mauro; Salinger, Andrew G.; Tuminaro, Raymond S.; van den Broeke, Michiel R.; Nowicki, Sophie M. J.

2017-01-01

We propose a new ice sheet model validation framework - the Cryospheric Model Comparison Tool (CmCt) - that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013, using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin-scale and whole-ice-sheet-scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of < 1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate a predictive skill with respect to observed dynamic changes that have occurred on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

An ice sheet model validation framework for the Greenland ice sheet

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

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.

We propose a new ice sheet model validation framework the Cryospheric Model Comparison Tool (CMCT) that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quanti- tative metricsmore » for use in evaluating the different model simulations against the observations. We find 10 that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, the model initial condition as well as output from idealized and dynamic models all provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CMCT, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CMCT as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.« less

An ice sheet model validation framework for the Greenland ice sheet

DOE PAGES

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; ...

2017-01-17

We propose a new ice sheet model validation framework the Cryospheric Model Comparison Tool (CMCT) that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quanti- tative metricsmore » for use in evaluating the different model simulations against the observations. We find 10 that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, the model initial condition as well as output from idealized and dynamic models all provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CMCT, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CMCT as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.« less

An ice sheet model validation framework for the Greenland ice sheet

PubMed Central

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey; Chambers, Don P.; Evans, Katherine J.; Kennedy, Joseph H.; Lenaerts, Jan; Lipscomb, William H.; Perego, Mauro; Salinger, Andrew G.; Tuminaro, Raymond S.; van den Broeke, Michiel R.; Nowicki, Sophie M. J.

2018-01-01

We propose a new ice sheet model validation framework – the Cryospheric Model Comparison Tool (CmCt) – that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013 using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin- and whole-ice-sheet scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of <1 m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate predictive skill with respect to observed dynamic changes occurring on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation. PMID:29697704

An Ice Sheet Model Validation Framework for the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Price, Stephen F.; Hoffman, Matthew J.; Bonin, Jennifer A.; Howat, Ian M.; Neumann, Thomas A.; Saba, Jack; Tezaur, Irina; Guerber, Jeffrey R.; Chambers, Don P.; Evans, Katherine J.;

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

Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under differentmore » levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.« less

Exploring Wholeness in Music Teachers' Lives

ERIC Educational Resources Information Center

Fordice, Billy Donald

2013-01-01

This qualitative research explored how the retelling of a life story influenced teachers' self-understanding. Informed by the disciplines of psychology, anthropology, and philosophy I constructed a conceptual framework of life as a continuous narrative, reflected and focused by past and anticipated experiences. This framework was informed by…

Limited Variation in BK Virus T-Cell Epitopes Revealed by Next-Generation Sequencing

PubMed Central

Sahoo, Malaya K.; Tan, Susanna K.; Chen, Sharon F.; Kapusinszky, Beatrix; Concepcion, Katherine R.; Kjelson, Lynn; Mallempati, Kalyan; Farina, Heidi M.; Fernández-Viña, Marcelo; Tyan, Dolly; Grimm, Paul C.; Anderson, Matthew W.; Concepcion, Waldo

2015-01-01

BK virus (BKV) infection causing end-organ disease remains a formidable challenge to the hematopoietic cell transplant (HCT) and kidney transplant fields. As BKV-specific treatments are limited, immunologic-based therapies may be a promising and novel therapeutic option for transplant recipients with persistent BKV infection. Here, we describe a whole-genome, deep-sequencing methodology and bioinformatics pipeline that identify BKV variants across the genome and at BKV-specific HLA-A2-, HLA-B0702-, and HLA-B08-restricted CD8 T-cell epitopes. BKV whole genomes were amplified using long-range PCR with four inverse primer sets, and fragmentation libraries were sequenced on the Ion Torrent Personal Genome Machine (PGM). An error model and variant-calling algorithm were developed to accurately identify rare variants. A total of 65 samples from 18 pediatric HCT and kidney recipients with quantifiable BKV DNAemia underwent whole-genome sequencing. Limited genetic variation was observed. The median number of amino acid variants identified per sample was 8 (range, 2 to 37; interquartile range, 10), with the majority of variants (77%) detected at a frequency of <5%. When normalized for length, there was no statistical difference in the median number of variants across all genes. Similarly, the predominant virus population within samples harbored T-cell epitopes similar to the reference BKV strain that was matched for the BKV genotype. Despite the conservation of epitopes, low-level variants in T-cell epitopes were detected in 77.7% (14/18) of patients. Understanding epitope variation across the whole genome provides insight into the virus-immune interface and may help guide the development of protocols for novel immunologic-based therapies. PMID:26202116

A general observatory control software framework design for existing small and mid-size telescopes

NASA Astrophysics Data System (ADS)

Ge, Liang; Lu, Xiao-Meng; Jiang, Xiao-Jun

2015-07-01

A general framework for observatory control software would help to improve the efficiency of observation and operation of telescopes, and would also be advantageous for remote and joint observations. We describe a general framework for observatory control software, which considers principles of flexibility and inheritance to meet the expectations from observers and technical personnel. This framework includes observation scheduling, device control and data storage. The design is based on a finite state machine that controls the whole process.

Multiscale Modeling of Virus Entry via Receptor-Mediated Endocytosis

NASA Astrophysics Data System (ADS)

Liu, Jin

2012-11-01

Virus infections are ubiquitous and remain major threats to human health worldwide. Viruses are intracellular parasites and must enter host cells to initiate infection. Receptor-mediated endocytosis is the most common entry pathway taken by viruses, the whole process is highly complex and dictated by various events, such as virus motions, membrane deformations, receptor diffusion and ligand-receptor reactions, occurring at multiple length and time scales. We develop a multiscale model for virus entry through receptor-mediated endocytosis. The binding of virus to cell surface is based on a mesoscale three dimensional stochastic adhesion model, the internalization (endocytosis) of virus and cellular membrane deformation is based on the discretization of Helfrich Hamiltonian in a curvilinear space using Monte Carlo method. The multiscale model is based on the combination of these two models. We will implement this model to study the herpes simplex virus entry into B78 cells and compare the model predictions with experimental measurements.

Distinguishing between whole cells and cell debris using surface plasmon coupled emission (Conference Presentation)

NASA Astrophysics Data System (ADS)

Talukder, Muhammad A.; Menyuk, Curtis R.; Kostov, Yordan

2017-02-01

Distinguishing between intact cells, dead but still whole cells, and cell debris is an important but difficult task in life sciences. The most common way to identify dead cells is using a cell-impermeant DNA binding dye, such as propidium iodide. A healthy living cell has an intact cell membrane and will act as a barrier to the dye so that it cannot enter the cell. A dead cell has a compromised cell membrane, and it will allow the dye into the cell to bind to the DNA and become fluorescent. The dead cells therefore will be positive and the live cells will be negative. The dead cells later deteriorate quickly into debris. Different pieces of debris from a single cell can be incorrectly identified as separate dead cells. Although a flow cytometer can quickly perform numerous quantitative, sensitive measurements on each individual cell to determine the viability of cells within a large, heterogeneous population, it is bulky, expensive, and only large hospitals and laboratories can afford them. In this work, we show that the distance-dependent coupling of fluorophore light to surface plasmon coupled emission (SPCE) from fluorescently-labeled cells can be used to distinguish whole cells from cell debris. Once the fluorescent labels are excited by a laser, the fluorescently-labeled whole cells create two distinct intensity rings in the far-field, in contrast to fluorescently-labeled cell debris, which only creates one ring. The distinct far-field patterns can be captured by camera and used to distinguish between whole cells and cell debris.

Radiation Quality Effects on Transcriptome Profiles in 3-D Cultures After Charged Particle Irradiation

NASA Technical Reports Server (NTRS)

Patel, Zarana S.; Kidane, Yared H.; Huff, Janice L.

2014-01-01

In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.

Design of a flexible component gathering algorithm for converting cell-based models to graph representations for use in evolutionary search

PubMed Central

2014-01-01

Background The ability of science to produce experimental data has outpaced the ability to effectively visualize and integrate the data into a conceptual framework that can further higher order understanding. Multidimensional and shape-based observational data of regenerative biology presents a particularly daunting challenge in this regard. Large amounts of data are available in regenerative biology, but little progress has been made in understanding how organisms such as planaria robustly achieve and maintain body form. An example of this kind of data can be found in a new repository (PlanformDB) that encodes descriptions of planaria experiments and morphological outcomes using a graph formalism. Results We are developing a model discovery framework that uses a cell-based modeling platform combined with evolutionary search to automatically search for and identify plausible mechanisms for the biological behavior described in PlanformDB. To automate the evolutionary search we developed a way to compare the output of the modeling platform to the morphological descriptions stored in PlanformDB. We used a flexible connected component algorithm to create a graph representation of the virtual worm from the robust, cell-based simulation data. These graphs can then be validated and compared with target data from PlanformDB using the well-known graph-edit distance calculation, which provides a quantitative metric of similarity between graphs. The graph edit distance calculation was integrated into a fitness function that was able to guide automated searches for unbiased models of planarian regeneration. We present a cell-based model of planarian that can regenerate anatomical regions following bisection of the organism, and show that the automated model discovery framework is capable of searching for and finding models of planarian regeneration that match experimental data stored in PlanformDB. Conclusion The work presented here, including our algorithm for converting cell-based models into graphs for comparison with data stored in an external data repository, has made feasible the automated development, training, and validation of computational models using morphology-based data. This work is part of an ongoing project to automate the search process, which will greatly expand our ability to identify, consider, and test biological mechanisms in the field of regenerative biology. PMID:24917489

Cardiac cell: a biological laser?

PubMed

Chorvat, D; Chorvatova, A

2008-04-01

We present a new concept of cardiac cells based on an analogy with lasers, practical implementations of quantum resonators. In this concept, each cardiac cell comprises a network of independent nodes, characterised by a set of discrete energy levels and certain transition probabilities between them. Interaction between the nodes is given by threshold-limited energy transfer, leading to quantum-like behaviour of the whole network. We propose that in cardiomyocytes, during each excitation-contraction coupling cycle, stochastic calcium release and the unitary properties of ionic channels constitute an analogue to laser active medium prone to "population inversion" and "spontaneous emission" phenomena. This medium, when powered by an incoming threshold-reaching voltage discharge in the form of an action potential, responds to the calcium influx through L-type calcium channels by stimulated emission of Ca2+ ions in a coherent, synchronised and amplified release process known as calcium-induced calcium release. In parallel, phosphorylation-stimulated molecular amplification in protein cascades adds tuneable features to the cells. In this framework, the heart can be viewed as a coherent network of synchronously firing cardiomyocytes behaving as pulsed laser-like amplifiers, coupled to pulse-generating pacemaker master-oscillators. The concept brings a new viewpoint on cardiac diseases as possible alterations of "cell lasing" properties.

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.

Coordination of cell death and the cell cycle: linking proliferation to death through private and communal couplers.

PubMed

Abrams, John M; White, Michael A

2004-12-01

In development and in the adult, complex signaling pathways operate within and between cells to coordinate proliferation and cell death. These networks can be viewed as coupling devices that link engines driving the cell cycle and the initiation of apoptosis. We propose three simple frameworks for modeling the effects of proliferative drive on apoptotic propensity. This perspective offers a potentially useful foundation for predicting group behaviors of cells in normal and pathological settings.

Light Competition and Carbon Partitioning-Allocation in an improved Forest Ecosystem Model

NASA Astrophysics Data System (ADS)

Collalti, Alessio; Santini, Monia; Valentini Valentini, Riccardo

2010-05-01

In Italy about 100.000 km2 are covered by forests. This surface is the 30% of the whole national land and this shows how the forests are important both for socio-economic and for environmental aspects. Forests changes affect a delicate balance that involve not only vegetation components but also bio-geochemical cycles and global climate. The knowledge of the amount of Carbon sequestered by forests represents a precious information for their sustainable management in the framework of climate changes. Primary studies in terms of model about this important issue, has been done through Forest Ecosystem Model (FEM), well known and validated as 3PG (Landsberg et Waring, 1997; Sands 2004). It is based on light use efficiency approach at the canopy level. The present study started from the original model 3PG, producing an improved version that uses many of explicit formulations of all relevant ecophysiological processes but makes it able to be applied for natural forests. The mutual interaction of forest growth and light conditions causes vertical and horizontal differentiation in the natural forest mosaic. Only ecophysiological parameters which can be either directly measured or estimates with reasonable certainty are used. The model has been written in C language and has been created considering a tri-dimensional cell structure with different vertical layers depending on the forest type that has to be simulated. This 3PG 'improved' version enable to work on multi-layer and multi-species forests type with cell resolution of one hectare for the typical Italian forest species. The multi-layer version is the result of the implementation and development of Lambert-Beer law for the estimation of intercepted, absorbed and transmitted light through different storeys of the forest. It is possible estimates, for each storey, a Par value (Photosynthetic Active Radiation) through Leaf Area Index (LAI), Light Extinction Coefficient and cell Canopy Cover using a "Big Leaf" approach. Hence, the presence of a cohort in a storey determines the amount of light received for the photosynthetic processes. The population density (numbers of trees per cell) represents a good competition index for determining the tree crown structure and tree crown dimension within a forest population. The tree crown tend to branch out horizontally to intercept as much light as possible. The model assess the structure of the tree crown both vertically and horizontally on the base of the population density and it up-scales the result to the whole stand. The canopy depth and the percentage of horizontal coverage determines moreover a crowding competition index that lead to a specific biomass partitioning-allocation ratio among the different tree components (foliage, roots and stem) and especially for the stem affecting Height-Diameter (at breast height) ratio. In this model, Height-Diameter ratio is used as an alternative competition index in determining the vigour and the strength of competition on free growth status of trees. The forest dominant vegetative cover affects moreover the presence of a dominated layer, it influences its yield and its Carbon stocking capacity and hence it influences the forest ecosystem CO2 carbon balance. From this model it is possible to simulate the impact of Climate Change on forests, the feedback of one or more dominated layers in terms of CO2 uptake in a forest stand and the effects of forest management activities for the next years.

Development and validation of a whole-cell inhibition assay for bacterial methionine aminopeptidase by surface-enhanced laser desorption ionization-time of flight mass spectrometry.

PubMed

Greis, Kenneth D; Zhou, Songtao; Siehnel, Richard; Klanke, Chuck; Curnow, Alan; Howard, Jeremy; Layh-Schmitt, Gerlinde

2005-08-01

Bacterial methionine aminopeptidase (MAP) is a protease that removes methionine from the N termini of newly synthesized bacterial proteins after the peptide deformylase enzyme cleaves the formyl group from the initiator formylmethionine. MAP is an essential bacterial gene product and thus represents a potential target for therapeutic intervention. A fundamental challenge in the antibacterial drug discovery field is demonstrating conclusively that compounds with in vitro enzyme inhibition activity produce the desired antibacterial effect by interfering with the same target in whole bacterial cells. One way to address the activity of inhibitor compounds is by profiling cellular biomarkers in whole bacterial cells using compounds that are known inhibitors of a particular target. However, in the case of MAP, no specific inhibitors were available for such studies. Instead, a genetically attenuated MAP strain was generated in which MAP expression was placed under the control of an inducible arabinose promoter. Thus, MAP inhibition in whole cells could be mimicked by growth in the absence of arabinose. This genetically attenuated strain was used as a benchmark for MAP inhibition by profiling whole-cell lysates for unprocessed proteins using surface-enhanced laser desorption ionization-time of flight mass spectrometry (MS). Eight proteins between 4 and 14 kDa were confirmed as being unprocessed and containing the initiator methionine by adding back purified MAP to the preparations prior to MS analysis. Upon establishing these unprocessed proteins as biomarkers for MAP inhibition, the assay was used to screen small-molecule chemical inhibitors of purified MAP for whole-cell activity. Fifteen compound classes yielded three classes of compound with whole-cell activity for further optimization by chemical expansion. This report presents the development, validation, and implementation of a whole-cell inhibition assay for MAP.

Multi-core processing and scheduling performance in CMS

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

Hernandez, J. M.; Evans, D.; Foulkes, S.

2012-01-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resultingmore » in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.« less