How causal analysis can reveal autonomy in models of biological systems

Science.gov (United States)

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'.

MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

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Anass BAYAGA

2010-07-01

Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

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Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

2013-05-28

Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

A Simple Exercise Reveals the Way Students Think about Scientific Modeling

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Ruebush, Laura; Sulikowski, Michelle; North, Simon

2009-01-01

Scientific modeling is an integral part of contemporary science, yet many students have little understanding of how models are developed, validated, and used to predict and explain phenomena. A simple modeling exercise led to significant gains in understanding key attributes of scientific modeling while revealing some stubborn misconceptions.…

Assessing Reliability of Cellulose Hydrolysis Models to Support Biofuel Process Design – Identifiability and Uncertainty Analysis

DEFF Research Database (Denmark)

Sin, Gürkan; Meyer, Anne S.; Gernaey, Krist

2010-01-01

The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done in the ori......The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done...

A Reformulation of the Dual Career Conceptual Model for Analysis in an Organizational Scope: Revealing new Aspects

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Heliani Berlato

2017-01-01

Full Text Available Couples who live a dual career, in general, are characterized by their continuing professional engagement and their desire for personal growth together. It is a synergy between career aspirations and family sphere, so that they co-exist; reflecting nowadays, a challenge for people who seek to live this duality. Not exempt from it, it is possible to understand the need for management models of people who are in harmony with the desires of dual career couples who are part of organizations. If in the 1980s the existence of dual career couples was not so common in Brazil, nowadays organizations increasingly receive these couples, which impacts the need for people management models to keep up with these social changes. Therefore, the model recognizes that the personal dimension (impacts on the organizational context cannot be avoided, and also that other factors affect both spheres (personal and organizational when referring to the normative roles that permeate these areas. The main intention of this essay is to construct a theoretical model of dual career to consider the factor - organization, as vital to understand (and accept the need to consider other dimensions on the dual career analytical perspective. The first evidences of dual career studies in Brazil revealed that the look at this movement only from the individual's margin is limited. This way, to consider the existence of other dimensions and consequently the influences they may cause, favors an expansion of the perspective, and also brings a detailing about the external factors (organization, society and culture that influence the dual career couple. To consider that this couple, as well as having personal challenges in the relationship between work and family, is subject to the culture that regulates their roles (men and women and that directly influences how organizations will handle that topic reveals the merit of this study. This, in turn, draws attention to the organizational sphere

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

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Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

International Nuclear Information System (INIS)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D.

2011-01-01

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in 1 H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

Gaussian graphical modeling reveals specific lipid correlations in glioblastoma cells

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Mueller, Nikola S.; Krumsiek, Jan; Theis, Fabian J.; Böhm, Christian; Meyer-Bäse, Anke

2011-06-01

Advances in high-throughput measurements of biological specimens necessitate the development of biologically driven computational techniques. To understand the molecular level of many human diseases, such as cancer, lipid quantifications have been shown to offer an excellent opportunity to reveal disease-specific regulations. The data analysis of the cell lipidome, however, remains a challenging task and cannot be accomplished solely based on intuitive reasoning. We have developed a method to identify a lipid correlation network which is entirely disease-specific. A powerful method to correlate experimentally measured lipid levels across the various samples is a Gaussian Graphical Model (GGM), which is based on partial correlation coefficients. In contrast to regular Pearson correlations, partial correlations aim to identify only direct correlations while eliminating indirect associations. Conventional GGM calculations on the entire dataset can, however, not provide information on whether a correlation is truly disease-specific with respect to the disease samples and not a correlation of control samples. Thus, we implemented a novel differential GGM approach unraveling only the disease-specific correlations, and applied it to the lipidome of immortal Glioblastoma tumor cells. A large set of lipid species were measured by mass spectrometry in order to evaluate lipid remodeling as a result to a combination of perturbation of cells inducing programmed cell death, while the other perturbations served solely as biological controls. With the differential GGM, we were able to reveal Glioblastoma-specific lipid correlations to advance biomedical research on novel gene therapies.

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

Energy Technology Data Exchange (ETDEWEB)

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

2012-10-02

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

Conformational Dynamics of apo-GlnBP Revealed by Experimental and Computational Analysis

KAUST Repository

Feng, Yitao

2016-10-13

The glutamine binding protein (GlnBP) binds l-glutamine and cooperates with its cognate transporters during glutamine uptake. Crystal structure analysis has revealed an open and a closed conformation for apo- and holo-GlnBP, respectively. However, the detailed conformational dynamics have remained unclear. Herein, we combined NMR spectroscopy, MD simulations, and single-molecule FRET techniques to decipher the conformational dynamics of apo-GlnBP. The NMR residual dipolar couplings of apo-GlnBP were in good agreement with a MD-derived structure ensemble consisting of four metastable states. The open and closed conformations are the two major states. This four-state model was further validated by smFRET experiments and suggests the conformational selection mechanism in ligand recognition of GlnBP. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Conformational Dynamics of apo-GlnBP Revealed by Experimental and Computational Analysis

KAUST Repository

Feng, Yitao; Zhang, Lu; Wu, Shaowen; Liu, Zhijun; Gao, Xin; Zhang, Xu; Liu, Maili; Liu, Jianwei; Huang, Xuhui; Wang, Wenning

2016-01-01

The glutamine binding protein (GlnBP) binds l-glutamine and cooperates with its cognate transporters during glutamine uptake. Crystal structure analysis has revealed an open and a closed conformation for apo- and holo-GlnBP, respectively. However, the detailed conformational dynamics have remained unclear. Herein, we combined NMR spectroscopy, MD simulations, and single-molecule FRET techniques to decipher the conformational dynamics of apo-GlnBP. The NMR residual dipolar couplings of apo-GlnBP were in good agreement with a MD-derived structure ensemble consisting of four metastable states. The open and closed conformations are the two major states. This four-state model was further validated by smFRET experiments and suggests the conformational selection mechanism in ligand recognition of GlnBP. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

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Lingling Zhang

Full Text Available Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

Genome sequencing and analysis reveals possible determinants of Staphylococcus aureus nasal carriage

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Cole Alexander M

2008-09-01

Full Text Available Abstract Background Nasal carriage of Staphylococcus aureus is a major risk factor in clinical and community settings due to the range of etiologies caused by the organism. We have identified unique immunological and ultrastructural properties associated with nasal carriage isolates denoting a role for bacterial factors in nasal carriage. However, despite extensive molecular level characterizations by several groups suggesting factors necessary for colonization on nasal epithelium, genetic determinants of nasal carriage are unknown. Herein, we have set a genomic foundation for unraveling the bacterial determinants of nasal carriage in S. aureus. Results MLST analysis revealed no lineage specific differences between carrier and non-carrier strains suggesting a role for mobile genetic elements. We completely sequenced a model carrier isolate (D30 and a model non-carrier strain (930918-3 to identify differential gene content. Comparison revealed the presence of 84 genes unique to the carrier strain and strongly suggests a role for Type VII secretion systems in nasal carriage. These genes, along with a putative pathogenicity island (SaPIBov present uniquely in the carrier strains are likely important in affecting carriage. Further, PCR-based genotyping of other clinical isolates for a specific subset of these 84 genes raise the possibility of nasal carriage being caused by multiple gene sets. Conclusion Our data suggest that carriage is likely a heterogeneic phenotypic trait and implies a role for nucleotide level polymorphism in carriage. Complete genome level analyses of multiple carriage strains of S. aureus will be important in clarifying molecular determinants of S. aureus nasal carriage.

Modelling reveals kinetic advantages of co-transcriptional splicing.

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Stuart Aitken

2011-10-01

Full Text Available Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Modelling reveals kinetic advantages of co-transcriptional splicing.

Science.gov (United States)

Aitken, Stuart; Alexander, Ross D; Beggs, Jean D

2011-10-01

Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Formal Analysis of BPMN Models Using Event-B

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Bryans, Jeremy W.; Wei, Wei

The use of business process models has gone far beyond documentation purposes. In the development of business applications, they can play the role of an artifact on which high level properties can be verified and design errors can be revealed in an effort to reduce overhead at later software development and diagnosis stages. This paper demonstrates how formal verification may add value to the specification, design and development of business process models in an industrial setting. The analysis of these models is achieved via an algorithmic translation from the de-facto standard business process modeling language BPMN to Event-B, a widely used formal language supported by the Rodin platform which offers a range of simulation and verification technologies.

Sensitivity Analysis for Urban Drainage Modeling Using Mutual Information

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Chuanqi Li

2014-11-01

Full Text Available The intention of this paper is to evaluate the sensitivity of the Storm Water Management Model (SWMM output to its input parameters. A global parameter sensitivity analysis is conducted in order to determine which parameters mostly affect the model simulation results. Two different methods of sensitivity analysis are applied in this study. The first one is the partial rank correlation coefficient (PRCC which measures nonlinear but monotonic relationships between model inputs and outputs. The second one is based on the mutual information which provides a general measure of the strength of the non-monotonic association between two variables. Both methods are based on the Latin Hypercube Sampling (LHS of the parameter space, and thus the same datasets can be used to obtain both measures of sensitivity. The utility of the PRCC and the mutual information analysis methods are illustrated by analyzing a complex SWMM model. The sensitivity analysis revealed that only a few key input variables are contributing significantly to the model outputs; PRCCs and mutual information are calculated and used to determine and rank the importance of these key parameters. This study shows that the partial rank correlation coefficient and mutual information analysis can be considered effective methods for assessing the sensitivity of the SWMM model to the uncertainty in its input parameters.

Equation-free analysis of two-component system signalling model reveals the emergence of co-existing phenotypes in the absence of multistationarity.

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Rebecca B Hoyle

Full Text Available Phenotypic differences of genetically identical cells under the same environmental conditions have been attributed to the inherent stochasticity of biochemical processes. Various mechanisms have been suggested, including the existence of alternative steady states in regulatory networks that are reached by means of stochastic fluctuations, long transient excursions from a stable state to an unstable excited state, and the switching on and off of a reaction network according to the availability of a constituent chemical species. Here we analyse a detailed stochastic kinetic model of two-component system signalling in bacteria, and show that alternative phenotypes emerge in the absence of these features. We perform a bifurcation analysis of deterministic reaction rate equations derived from the model, and find that they cannot reproduce the whole range of qualitative responses to external signals demonstrated by direct stochastic simulations. In particular, the mixed mode, where stochastic switching and a graded response are seen simultaneously, is absent. However, probabilistic and equation-free analyses of the stochastic model that calculate stationary states for the mean of an ensemble of stochastic trajectories reveal that slow transcription of either response regulator or histidine kinase leads to the coexistence of an approximate basal solution and a graded response that combine to produce the mixed mode, thus establishing its essential stochastic nature. The same techniques also show that stochasticity results in the observation of an all-or-none bistable response over a much wider range of external signals than would be expected on deterministic grounds. Thus we demonstrate the application of numerical equation-free methods to a detailed biochemical reaction network model, and show that it can provide new insight into the role of stochasticity in the emergence of phenotypic diversity.

Comprehensive analysis of ultrasonic vocalizations in a mouse model of fragile X syndrome reveals limited, call type specific deficits.

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Snigdha Roy

Full Text Available Fragile X syndrome (FXS is a well-recognized form of inherited mental retardation, caused by a mutation in the fragile X mental retardation 1 (Fmr1 gene. The gene is located on the long arm of the X chromosome and encodes fragile X mental retardation protein (FMRP. Absence of FMRP in fragile X patients as well as in Fmr1 knockout (KO mice results, among other changes, in abnormal dendritic spine formation and altered synaptic plasticity in the neocortex and hippocampus. Clinical features of FXS include cognitive impairment, anxiety, abnormal social interaction, mental retardation, motor coordination and speech articulation deficits. Mouse pups generate ultrasonic vocalizations (USVs when isolated from their mothers. Whether those social ultrasonic vocalizations are deficient in mouse models of FXS is unknown. Here we compared isolation-induced USVs generated by pups of Fmr1-KO mice with those of their wild type (WT littermates. Though the total number of calls was not significantly different between genotypes, a detailed analysis of 10 different categories of calls revealed that loss of Fmr1 expression in mice causes limited and call-type specific deficits in ultrasonic vocalization: the carrier frequency of flat calls was higher, the percentage of downward calls was lower and that the frequency range of complex calls was wider in Fmr1-KO mice compared to their WT littermates.

Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

Science.gov (United States)

He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

2014-12-01

Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

Transcriptomic analysis reveals ethylene as stimulator and auxin as regulator of adventitious root formation in petunia cuttings

OpenAIRE

Druege, Uwe; Franken, Philipp; Lischewski, Sandra; Ahkami, Amir H.; Zerche, Siegfried; Hause, Bettina; Hajirezaei, Mohammad R.

2014-01-01

Adventitious root (AR) formation in the stem base of cuttings is the basis for propagation of many plant species and petunia is used as model to study this developmental process. Following AR formation from 2 to 192 hours after excision (hpe) of cuttings, transcriptome analysis by microarray revealed a change of the character of the rooting zone from stem base to root identity. The greatest shift in the number of differentially expressed genes was observed between 24 and 72 hpe, when the cate...

Multilocus analysis reveals three candidate genes for Chinese migraine susceptibility.

Science.gov (United States)

An, X-K; Fang, J; Yu, Z-Z; Lin, Q; Lu, C-X; Qu, H-L; Ma, Q-L

2017-08-01

Several genome-wide association studies (GWASs) in Caucasian populations have identified 12 loci that are significantly associated with migraine. More evidence suggests that serotonin receptors are also involved in migraine pathophysiology. In the present study, a case-control study was conducted in a cohort of 581 migraine cases and 533 ethnically matched controls among a Chinese population. Eighteen polymorphisms from serotonin receptors and GWASs were selected, and genotyping was performed using a Sequenom MALDI-TOF mass spectrometry iPLEX platform. The genotypic and allelic distributions of MEF2D rs2274316 and ASTN2 rs6478241 were significantly different between migraine patients and controls. Univariate and multivariate analysis revealed significant associations of polymorphisms in the MEF2D and ASTN2 genes with migraine susceptibility. MEF2D, PRDM16 and ASTN2 were also found to be associated with migraine without aura (MO) and migraine with family history. And, MEF2D and ASTN2 also served as genetic risk factors for the migraine without family history. The generalized multifactor dimensionality reduction analysis identified that MEF2D and HTR2E constituted the two-factor interaction model. Our study suggests that the MEF2D, PRDM16 and ASTN2 genes from GWAS are associated with migraine susceptibility, especially MO, among Chinese patients. It appears that there is no association with serotonin receptor related genes. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

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Du Toit W P Schabort

Full Text Available We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus.

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

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Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Stability Analysis of the Embankment Model

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G.S. Gopalakrishna

2009-01-01

Full Text Available In analysis of embankment model affected by dynamic force, employment of shaking table is a scientific way in assessment of earthquake behavior. This work focused on saturated loose sandy foundation and enbankment. The results generated through the pore pressure sensors indicated pore water pressure playing main role in creation of liquefaction and stability of the system, and also revealed deformation, settlement, liquefaction intensity and time stability of system in direct correlation with the strength and characteristics of soil. One of the economical methods in stabilization of soil foundation is improvement of some part soil foundation.

Peptidomic analysis reveals proteolytic activity of kefir microorganisms on bovine milk proteins.

Science.gov (United States)

Dallas, David C; Citerne, Florine; Tian, Tian; Silva, Vitor L M; Kalanetra, Karen M; Frese, Steven A; Robinson, Randall C; Mills, David A; Barile, Daniela

2016-04-15

The microorganisms that make up kefir grains are well known for lactose fermentation, but the extent to which they hydrolyze and consume milk proteins remains poorly understood. Peptidomics technologies were used to examine the proteolytic activity of kefir grains on bovine milk proteins. Gel electrophoresis revealed substantial digestion of milk proteins by kefir grains, with mass spectrometric analysis showing the release of 609 protein fragments and alteration of the abundance of >1500 peptides that derived from 27 milk proteins. Kefir contained 25 peptides identified from the literature as having biological activity, including those with antihypertensive, antimicrobial, immunomodulatory, opioid and anti-oxidative functions. 16S rRNA and shotgun metagenomic sequencing identified the principle taxa in the culture as Lactobacillus species. The model kefir sample contained thousands of protein fragments released in part by kefir microorganisms and in part by native milk proteases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Peptidomic analysis reveals proteolytic activity of kefir microorganisms on bovine milk proteins

Science.gov (United States)

Dallas, David C.; Citerne, Florine; Tian, Tian; Silva, Vitor L. M.; Kalanetra, Karen M.; Frese, Steven A.; Robinson, Randall C.; Mills, David A.; Barile, Daniela

2015-01-01

Scope The microorganisms that make up kefir grains are well known for lactose fermentation, but the extent to which they hydrolyze and consume milk proteins remains poorly understood. Peptidomics technologies were used to examine the proteolytic activity of kefir grains on bovine milk proteins. Methods and results Gel electrophoresis revealed substantial digestion of milk proteins by kefir grains, with mass spectrometric analysis showing the release of 609 protein fragments and alteration of the abundance of >1,500 peptides that derived from 27 milk proteins. Kefir contained 25 peptides identified from the literature as having biological activity, including those with antihypertensive, antimicrobial, immunomodulatory, opioid and anti-oxidative functions. 16S rRNA and shotgun metagenomic sequencing identified the principle taxa in the culture as Lactobacillus species. Conclusion The model kefir sample contained thousands of protein fragments released in part by kefir microorganisms and in part by native milk proteases. PMID:26616950

{sup 1}H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

Energy Technology Data Exchange (ETDEWEB)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D., E-mail: bernard.lemire@ualberta.ca [University of Alberta, Department of Biochemistry, School of Molecular and Systems Medicine (Canada)

2011-04-15

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in {sup 1}H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

ANALYSIS MODEL FOR RETURN ON CAPITAL EMPLOYED

Directory of Open Access Journals (Sweden)

BURJA CAMELIA

2013-02-01

Full Text Available At the microeconomic level, the appreciation of the capitals’ profitability is a very complex action which is ofinterest for stakeholders. This study has as main purpose to extend the traditional analysis model for the capitals’profitability, based on the ratio “Return on capital employed”. In line with it the objectives of this work aim theidentification of factors that exert an influence on the capital’s profitability utilized by a company and the measurementof their contribution in the manifestation of the phenomenon. The proposed analysis model is validated on the use caseof a representative company from the agricultural sector. The results obtained reveal that in a company there are somefactors which can act positively on the capitals’ profitability: capital turnover, sales efficiency, increase the share ofsales in the total revenues, improvement of the expenses’ efficiency. The findings are useful both for the decisionmakingfactors in substantiating the economic strategies and for the capital owners who are interested in efficiency oftheir investments.

Structural modeling and in silico analysis of human superoxide dismutase 2.

Directory of Open Access Journals (Sweden)

Mariana Dias Castela de Carvalho

Full Text Available Aging in the world population has increased every year. Superoxide dismutase 2 (Mn-SOD or SOD2 protects against oxidative stress, a main factor influencing cellular longevity. Polymorphisms in SOD2 have been associated with the development of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, as well as psychiatric disorders, such as schizophrenia, depression and bipolar disorder. In this study, all of the described natural variants (S10I, A16V, E66V, G76R, I82T and R156W of SOD2 were subjected to in silico analysis using eight different algorithms: SNPeffect, PolyPhen-2, PhD-SNP, PMUT, SIFT, SNAP, SNPs&GO and nsSNPAnalyzer. This analysis revealed disparate results for a few of the algorithms. The results showed that, from at least one algorithm, each amino acid substitution appears to harmfully affect the protein. Structural theoretical models were created for variants through comparative modelling performed using the MHOLline server (which includes MODELLER and PROCHECK and ab initio modelling, using the I-Tasser server. The predicted models were evaluated using TM-align, and the results show that the models were constructed with high accuracy. The RMSD values of the modelled mutants indicated likely pathogenicity for all missense mutations. Structural phylogenetic analysis using ConSurf revealed that human SOD2 is highly conserved. As a result, a human-curated database was generated that enables biologists and clinicians to explore SOD2 nsSNPs, including predictions of their effects and visualisation of the alignment of both the wild-type and mutant structures. The database is freely available at http://bioinfogroup.com/database and will be regularly updated.

Models and data requirements for human reliability analysis

International Nuclear Information System (INIS)

1989-03-01

It has been widely recognised for many years that the safety of the nuclear power generation depends heavily on the human factors related to plant operation. This has been confirmed by the accidents at Three Mile Island and Chernobyl. Both these cases revealed how human actions can defeat engineered safeguards and the need for special operator training to cover the possibility of unexpected plant conditions. The importance of the human factor also stands out in the analysis of abnormal events and insights from probabilistic safety assessments (PSA's), which reveal a large proportion of cases having their origin in faulty operator performance. A consultants' meeting, organized jointly by the International Atomic Energy Agency (IAEA) and the International Institute for Applied Systems Analysis (IIASA) was held at IIASA in Laxenburg, Austria, December 7-11, 1987, with the aim of reviewing existing models used in Probabilistic Safety Assessment (PSA) for Human Reliability Analysis (HRA) and of identifying the data required. The report collects both the contributions offered by the members of the Expert Task Force and the findings of the extensive discussions that took place during the meeting. Refs, figs and tabs

Proteomic analysis of three gonad types of swamp eel reveals genes differentially expressed during sex reversal.

Science.gov (United States)

Sheng, Yue; Zhao, Wei; Song, Ying; Li, Zhigang; Luo, Majing; Lei, Quan; Cheng, Hanhua; Zhou, Rongjia

2015-05-18

A variety of mechanisms are engaged in sex determination in vertebrates. The teleost fish swamp eel undergoes sex reversal naturally and is an ideal model for vertebrate sexual development. However, the importance of proteome-wide scanning for gonad reversal was not previously determined. We report a 2-D electrophoresis analysis of three gonad types of proteomes during sex reversal. MS/MS analysis revealed a group of differentially expressed proteins during ovary to ovotestis to testis transformation. Cbx3 is up-regulated during gonad reversal and is likely to have a role in spermatogenesis. Rab37 is down-regulated during the reversal and is mainly associated with oogenesis. Both Cbx3 and Rab37 are linked up in a protein network. These datasets in gonadal proteomes provide a new resource for further studies in gonadal development.

Sequence analysis of serum albumins reveals the molecular evolution of ligand recognition properties.

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Fanali, Gabriella; Ascenzi, Paolo; Bernardi, Giorgio; Fasano, Mauro

2012-01-01

Serum albumin (SA) is a circulating protein providing a depot and carrier for many endogenous and exogenous compounds. At least seven major binding sites have been identified by structural and functional investigations mainly in human SA. SA is conserved in vertebrates, with at least 49 entries in protein sequence databases. The multiple sequence analysis of this set of entries leads to the definition of a cladistic tree for the molecular evolution of SA orthologs in vertebrates, thus showing the clustering of the considered species, with lamprey SAs (Lethenteron japonicum and Petromyzon marinus) in a separate outgroup. Sequence analysis aimed at searching conserved domains revealed that most SA sequences are made up by three repeated domains (about 600 residues), as extensively characterized for human SA. On the contrary, lamprey SAs are giant proteins (about 1400 residues) comprising seven repeated domains. The phylogenetic analysis of the SA family reveals a stringent correlation with the taxonomic classification of the species available in sequence databases. A focused inspection of the sequences of ligand binding sites in SA revealed that in all sites most residues involved in ligand binding are conserved, although the versatility towards different ligands could be peculiar of higher organisms. Moreover, the analysis of molecular links between the different sites suggests that allosteric modulation mechanisms could be restricted to higher vertebrates.

Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

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Claire A Hales

Full Text Available Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142, and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

Science.gov (United States)

Hales, Claire A; Robinson, Emma S J; Houghton, Conor J

2016-01-01

Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

Bifurcation Analysis of an Existing Mathematical Model Reveals Novel Treatment Strategies and Suggests Potential Cure for Type 1 Diabetes

DEFF Research Database (Denmark)

Nielsen, Kenneth Hagde Mandrup; Ottesen, Johnny T.; Pociot, Flemming

2014-01-01

Type 1 diabetes is a disease with serious personal and socioeconomic consequences that has attracted the attention of modellers recently. But as models of this disease tend to be complicated, there has been only limited mathematical analysis to date. Here we address this problem by providing...... a bifurcation analysis of a previously published mathematical model for the early stages of type 1 diabetes in diabetes-prone NOD mice, which is based on the data available in the literature. We also show positivity and the existence of a family of attracting trapping regions in the positive 5D cone, converging...... or activated macrophages, increasing the phagocytic ability of resting and activated macrophages simultaneously and lastly, adding additional macrophages to the site of inflammation. The latter seems counter-intuitive at first glance, but nevertheless it appears to be the most promising, as evidenced by recent...

Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models

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Poleszczuk, Jan; Hahnfeldt, Philip; Enderling, Heiko

2015-01-01

Anti-angiogenic cancer treatments induce tumor starvation and regression by targeting the tumor vasculature that delivers oxygen and nutrients. Mathematical models prove valuable tools to study the proof-of-concept, efficacy and underlying mechanisms of such treatment approaches. The effects of parameter value uncertainties for two models of tumor development under angiogenic signaling and anti-angiogenic treatment are studied. Data fitting is performed to compare predictions of both models and to obtain nominal parameter values for sensitivity analysis. Sensitivity analysis reveals that the success of different cancer treatments depends on tumor size and tumor intrinsic parameters. In particular, we show that tumors with ample vascular support can be successfully targeted with conventional cytotoxic treatments. On the other hand, tumors with curtailed vascular support are not limited by their growth rate and therefore interruption of neovascularization emerges as the most promising treatment target. PMID:25785600

Analysis of the fibroblast growth factor system reveals alterations in a mouse model of spinal muscular atrophy.

Science.gov (United States)

Hensel, Niko; Ratzka, Andreas; Brinkmann, Hella; Klimaschewski, Lars; Grothe, Claudia; Claus, Peter

2012-01-01

The monogenetic disease Spinal Muscular Atrophy (SMA) is characterized by a progressive loss of motoneurons leading to muscle weakness and atrophy due to severe reduction of the Survival of Motoneuron (SMN) protein. Several models of SMA show deficits in neurite outgrowth and maintenance of neuromuscular junction (NMJ) structure. Survival of motoneurons, axonal outgrowth and formation of NMJ is controlled by neurotrophic factors such as the Fibroblast Growth Factor (FGF) system. Besides their classical role as extracellular ligands, some FGFs exert also intracellular functions controlling neuronal differentiation. We have previously shown that intracellular FGF-2 binds to SMN and regulates the number of a subtype of nuclear bodies which are reduced in SMA patients. In the light of these findings, we systematically analyzed the FGF-system comprising five canonical receptors and 22 ligands in a severe mouse model of SMA. In this study, we demonstrate widespread alterations of the FGF-system in both muscle and spinal cord. Importantly, FGF-receptor 1 is upregulated in spinal cord at a pre-symptomatic stage as well as in a mouse motoneuron-like cell-line NSC34 based model of SMA. Consistent with that, phosphorylations of FGFR-downstream targets Akt and ERK are increased. Moreover, ERK hyper-phosphorylation is functionally linked to FGFR-1 as revealed by receptor inhibition experiments. Our study shows that the FGF system is dysregulated at an early stage in SMA and may contribute to the SMA pathogenesis.

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

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Henry D Priest

Full Text Available Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

The ATLAS Analysis Model

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Amir Farbin

The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

Re-Analysis of Metagenomic Sequences from Acute Flaccidmyelitis Patients Reveals Alternatives to Enterovirus D68 Infection

Science.gov (United States)

2015-07-13

caused in some cases by infection with enterovirus D68. We found that among the patients whose symptoms were previously attributed to enterovirus D68...distribution is unlimited. Re-analysis of metagenomic sequences from acute flaccidmyelitis patients reveals alternatives to enterovirus D68...Street Baltimore, MD 21218 -2685 ABSTRACT Re-analysis of metagenomic sequences from acute flaccidmyelitis patients reveals alternatives to enterovirus

Energy-Water Modeling and Analysis | Energy Analysis | NREL

Science.gov (United States)

Generation (ReEDS Model Analysis) U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather Modeling and Analysis Energy-Water Modeling and Analysis NREL's energy-water modeling and analysis vulnerabilities from various factors, including water. Example Projects Renewable Electricity Futures Study

Revealing the underlying drivers of disaster risk: a global analysis

Science.gov (United States)

Peduzzi, Pascal

2017-04-01

Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL

Differential proteomic analysis reveals novel links between primary metabolism and antibiotic production in Amycolatopsis balhimycina

DEFF Research Database (Denmark)

Gallo, G.; Renzone, G.; Alduina, R.

2010-01-01

A differential proteomic analysis, based on 2-DE and MS procedures, was performed on Amycolatopsis balhimycina DSM5908, the actinomycete producing the vancomycin-like antibiotic balhimycin. A comparison of proteomic profiles before and during balhimycin production characterized differentially...... available over the World Wide Web as interactive web pages (http://www.unipa.it/ampuglia/Abal-proteome-maps). Functional clustering analysis revealed that differentially expressed proteins belong to functional groups involved in central carbon metabolism, amino acid metabolism and protein biosynthesis...... intermediates, were upregulated during antibiotic production. qRT-PCR analysis revealed that 8 out of 14 upregulated genes showed a positive correlation between changes at translational and transcriptional expression level. Furthermore, proteomic analysis of two nonproducing mutants, restricted to a sub...

Statistical performance and information content of time lag analysis and redundancy analysis in time series modeling.

Science.gov (United States)

Angeler, David G; Viedma, Olga; Moreno, José M

2009-11-01

Time lag analysis (TLA) is a distance-based approach used to study temporal dynamics of ecological communities by measuring community dissimilarity over increasing time lags. Despite its increased use in recent years, its performance in comparison with other more direct methods (i.e., canonical ordination) has not been evaluated. This study fills this gap using extensive simulations and real data sets from experimental temporary ponds (true zooplankton communities) and landscape studies (landscape categories as pseudo-communities) that differ in community structure and anthropogenic stress history. Modeling time with a principal coordinate of neighborhood matrices (PCNM) approach, the canonical ordination technique (redundancy analysis; RDA) consistently outperformed the other statistical tests (i.e., TLAs, Mantel test, and RDA based on linear time trends) using all real data. In addition, the RDA-PCNM revealed different patterns of temporal change, and the strength of each individual time pattern, in terms of adjusted variance explained, could be evaluated, It also identified species contributions to these patterns of temporal change. This additional information is not provided by distance-based methods. The simulation study revealed better Type I error properties of the canonical ordination techniques compared with the distance-based approaches when no deterministic component of change was imposed on the communities. The simulation also revealed that strong emphasis on uniform deterministic change and low variability at other temporal scales is needed to result in decreased statistical power of the RDA-PCNM approach relative to the other methods. Based on the statistical performance of and information content provided by RDA-PCNM models, this technique serves ecologists as a powerful tool for modeling temporal change of ecological (pseudo-) communities.

Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.

Science.gov (United States)

Schmitz, Alexander; Fischer, Sabine C; Mattheyer, Christian; Pampaloni, Francesco; Stelzer, Ernst H K

2017-03-03

Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid's size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 10 5 to 1 × 10 6  cells/mm 3 . Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.

Comparative analysis reveals that polyploidy does not decelerate diversification in fish.

Science.gov (United States)

Zhan, S H; Glick, L; Tsigenopoulos, C S; Otto, S P; Mayrose, I

2014-02-01

While the proliferation of the species-rich teleost fish has been ascribed to an ancient genome duplication event at the base of this group, the broader impact of polyploidy on fish evolution and diversification remains poorly understood. Here, we investigate the association between polyploidy and diversification in several fish lineages: the sturgeons (Acipenseridae: Acipenseriformes), the botiid loaches (Botiidae: Cypriniformes), Cyprininae fishes (Cyprinidae: Cypriniformes) and the salmonids (Salmonidae: Salmoniformes). Using likelihood-based evolutionary methodologies, we co-estimate speciation and extinction rates associated with polyploid vs. diploid fish lineages. Family-level analysis of Acipenseridae and Botiidae revealed no significant difference in diversification rates between polyploid and diploid relatives, while analysis of the subfamily Cyprininae revealed higher polyploid diversification. Additionally, order-level analysis of the polyploid Salmoniformes and its diploid sister clade, the Esociformes, did not support a significantly different net diversification rate between the two groups. Taken together, our results suggest that polyploidy is generally not associated with decreased diversification in fish - a pattern that stands in contrast to that previously observed in plants. While there are notable differences in the time frame examined in the two studies, our results suggest that polyploidy is associated with different diversification patterns in these two major branches of the eukaryote tree of life. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

The selection pressures induced non-smooth infectious disease model and bifurcation analysis

International Nuclear Information System (INIS)

Qin, Wenjie; Tang, Sanyi

2014-01-01

Highlights: • A non-smooth infectious disease model to describe selection pressure is developed. • The effect of selection pressure on infectious disease transmission is addressed. • The key factors which are related to the threshold value are determined. • The stabilities and bifurcations of model have been revealed in more detail. • Strategies for the prevention of emerging infectious disease are proposed. - Abstract: Mathematical models can assist in the design strategies to control emerging infectious disease. This paper deduces a non-smooth infectious disease model induced by selection pressures. Analysis of this model reveals rich dynamics including local, global stability of equilibria and local sliding bifurcations. Model solutions ultimately stabilize at either one real equilibrium or the pseudo-equilibrium on the switching surface of the present model, depending on the threshold value determined by some related parameters. Our main results show that reducing the threshold value to a appropriate level could contribute to the efficacy on prevention and treatment of emerging infectious disease, which indicates that the selection pressures can be beneficial to prevent the emerging infectious disease under medical resource limitation

Quantitative flux analysis reveals folate-dependent NADPH production

Science.gov (United States)

Fan, Jing; Ye, Jiangbin; Kamphorst, Jurre J.; Shlomi, Tomer; Thompson, Craig B.; Rabinowitz, Joshua D.

2014-06-01

ATP is the dominant energy source in animals for mechanical and electrical work (for example, muscle contraction or neuronal firing). For chemical work, there is an equally important role for NADPH, which powers redox defence and reductive biosynthesis. The most direct route to produce NADPH from glucose is the oxidative pentose phosphate pathway, with malic enzyme sometimes also important. Although the relative contribution of glycolysis and oxidative phosphorylation to ATP production has been extensively analysed, similar analysis of NADPH metabolism has been lacking. Here we demonstrate the ability to directly track, by liquid chromatography-mass spectrometry, the passage of deuterium from labelled substrates into NADPH, and combine this approach with carbon labelling and mathematical modelling to measure NADPH fluxes. In proliferating cells, the largest contributor to cytosolic NADPH is the oxidative pentose phosphate pathway. Surprisingly, a nearly comparable contribution comes from serine-driven one-carbon metabolism, in which oxidation of methylene tetrahydrofolate to 10-formyl-tetrahydrofolate is coupled to reduction of NADP+ to NADPH. Moreover, tracing of mitochondrial one-carbon metabolism revealed complete oxidation of 10-formyl-tetrahydrofolate to make NADPH. As folate metabolism has not previously been considered an NADPH producer, confirmation of its functional significance was undertaken through knockdown of methylenetetrahydrofolate dehydrogenase (MTHFD) genes. Depletion of either the cytosolic or mitochondrial MTHFD isozyme resulted in decreased cellular NADPH/NADP+ and reduced/oxidized glutathione ratios (GSH/GSSG) and increased cell sensitivity to oxidative stress. Thus, although the importance of folate metabolism for proliferating cells has been long recognized and attributed to its function of producing one-carbon units for nucleic acid synthesis, another crucial function of this pathway is generating reducing power.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease*

Science.gov (United States)

Dewhurst, Henry; Sundararaman, Niveda

2016-01-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

Science.gov (United States)

Torres, Matthew P; Dewhurst, Henry; Sundararaman, Niveda

2016-11-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Fast and accurate focusing analysis of large photon sieve using pinhole ring diffraction model.

Science.gov (United States)

Liu, Tao; Zhang, Xin; Wang, Lingjie; Wu, Yanxiong; Zhang, Jizhen; Qu, Hemeng

2015-06-10

In this paper, we developed a pinhole ring diffraction model for the focusing analysis of a large photon sieve. Instead of analyzing individual pinholes, we discuss the focusing of all of the pinholes in a single ring. An explicit equation for the diffracted field of individual pinhole ring has been proposed. We investigated the validity range of this generalized model and analytically describe the sufficient conditions for the validity of this pinhole ring diffraction model. A practical example and investigation reveals the high accuracy of the pinhole ring diffraction model. This simulation method could be used for fast and accurate focusing analysis of a large photon sieve.

Modeling reveals bistability and low-pass filtering in the network module determining blood stem cell fate.

Directory of Open Access Journals (Sweden)

Jatin Narula

2010-05-01

Full Text Available Combinatorial regulation of gene expression is ubiquitous in eukaryotes with multiple inputs converging on regulatory control elements. The dynamic properties of these elements determine the functionality of genetic networks regulating differentiation and development. Here we propose a method to quantitatively characterize the regulatory output of distant enhancers with a biophysical approach that recursively determines free energies of protein-protein and protein-DNA interactions from experimental analysis of transcriptional reporter libraries. We apply this method to model the Scl-Gata2-Fli1 triad-a network module important for cell fate specification of hematopoietic stem cells. We show that this triad module is inherently bistable with irreversible transitions in response to physiologically relevant signals such as Notch, Bmp4 and Gata1 and we use the model to predict the sensitivity of the network to mutations. We also show that the triad acts as a low-pass filter by switching between steady states only in response to signals that persist for longer than a minimum duration threshold. We have found that the auto-regulation loops connecting the slow-degrading Scl to Gata2 and Fli1 are crucial for this low-pass filtering property. Taken together our analysis not only reveals new insights into hematopoietic stem cell regulatory network functionality but also provides a novel and widely applicable strategy to incorporate experimental measurements into dynamical network models.

Structure and sensitivity analysis of individual-based predator–prey models

International Nuclear Information System (INIS)

Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

2012-01-01

The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

A Systems-Level Analysis Reveals Circadian Regulation of Splicing in Colorectal Cancer.

Science.gov (United States)

El-Athman, Rukeia; Fuhr, Luise; Relógio, Angela

2018-06-20

Accumulating evidence points to a significant role of the circadian clock in the regulation of splicing in various organisms, including mammals. Both dysregulated circadian rhythms and aberrant pre-mRNA splicing are frequently implicated in human disease, in particular in cancer. To investigate the role of the circadian clock in the regulation of splicing in a cancer progression context at the systems-level, we conducted a genome-wide analysis and compared the rhythmic transcriptional profiles of colon carcinoma cell lines SW480 and SW620, derived from primary and metastatic sites of the same patient, respectively. We identified spliceosome components and splicing factors with cell-specific circadian expression patterns including SRSF1, HNRNPLL, ESRP1, and RBM 8A, as well as altered alternative splicing events and circadian alternative splicing patterns of output genes (e.g., VEGFA, NCAM1, FGFR2, CD44) in our cellular model. Our data reveals a remarkable interplay between the circadian clock and pre-mRNA splicing with putative consequences in tumor progression and metastasis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Systems biology integration of proteomic data in rodent models of depression reveals involvement of the immune response and glutamatergic signaling.

Science.gov (United States)

Carboni, Lucia; Nguyen, Thanh-Phuong; Caberlotto, Laura

2016-12-01

The pathophysiological basis of major depression is incompletely understood. Recently, numerous proteomic studies have been performed in rodent models of depression to investigate the molecular underpinnings of depressive-like behaviours with an unbiased approach. The objective of the study is to integrate the results of these proteomic studies in depression models to shed light on the most relevant molecular pathways involved in the disease. Network analysis is performed integrating preexisting proteomic data from rodent models of depression. The IntAct mouse and the HRPD are used as reference protein-protein interaction databases. The functionality analyses of the networks are then performed by testing overrepresented GO biological process terms and pathways. Functional enrichment analyses of the networks revealed an association with molecular processes related to depression in humans, such as those involved in the immune response. Pathways impacted by clinically effective antidepressants are modulated, including glutamatergic signaling and neurotrophic responses. Moreover, dysregulations of proteins regulating energy metabolism and circadian rhythms are implicated. The comparison with protein pathways modulated in depressive patients revealed significant overlapping. This systems biology study supports the notion that animal models can contribute to the research into the biology and therapeutics of depression. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correction: Comparative analysis of fungal genomes reveals different plant cell wall degrading capacity in fungi

Science.gov (United States)

2014-01-01

Abstract The version of this article published in BMC Genomics 2013, 14: 274, contains 9 unpublished genomes (Botryobasidium botryosum, Gymnopus luxurians, Hypholoma sublateritium, Jaapia argillacea, Hebeloma cylindrosporum, Conidiobolus coronatus, Laccaria amethystina, Paxillus involutus, and P. rubicundulus) downloaded from JGI website. In this correction, we removed these genomes after discussion with editors and data producers whom we should have contacted before downloading these genomes. Removing these data did not alter the principle results and conclusions of our original work. The relevant Figures 1, 2, 3, 4 and 6; and Table 1 have been revised. Additional files 1, 3, 4, and 5 were also revised. We would like to apologize for any confusion or inconvenience this may have caused. Background Fungi produce a variety of carbohydrate activity enzymes (CAZymes) for the degradation of plant polysaccharide materials to facilitate infection and/or gain nutrition. Identifying and comparing CAZymes from fungi with different nutritional modes or infection mechanisms may provide information for better understanding of their life styles and infection models. To date, over hundreds of fungal genomes are publicly available. However, a systematic comparative analysis of fungal CAZymes across the entire fungal kingdom has not been reported. Results In this study, we systemically identified glycoside hydrolases (GHs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and glycosyltransferases (GTs) as well as carbohydrate-binding modules (CBMs) in the predicted proteomes of 94 representative fungi from Ascomycota, Basidiomycota, Chytridiomycota, and Zygomycota. Comparative analysis of these CAZymes that play major roles in plant polysaccharide degradation revealed that fungi exhibit tremendous diversity in the number and variety of CAZymes. Among them, some families of GHs and CEs are the most prevalent CAZymes that are distributed in all of the fungi analyzed

Development of a CANDU Moderator Analysis Model; Based on Coupled Solver

International Nuclear Information System (INIS)

Yoon, Churl; Park, Joo Hwan

2006-01-01

A CFD model for predicting the CANDU-6 moderator temperature has been developed for several years in KAERI, which is based on CFX-4. This analytic model(CFX4-CAMO) has some strength in the modeling of hydraulic resistance in the core region and in the treatment of heat source term in the energy equations. But the convergence difficulties and slow computing speed reveal to be the limitations of this model, because the CFX-4 code adapts a segregated solver to solve the governing equations with strong coupled-effect. Compared to CFX-4 using segregated solver, CFX-10 adapts high efficient and robust coupled-solver. Before December 2005 when CFX-10 was distributed, the previous version of CFX-10(CFX-5. series) also adapted coupled solver but didn't have any capability to apply porous media approaches correctly. In this study, the developed moderator analysis model based on CFX- 4 (CFX4-CAMO) is transformed into a new moderator analysis model based on CFX-10. The new model is examined and the results are compared to the former

Semi-automated landmark-based 3D analysis reveals new morphometric characteristics in the trochlear dysplastic femur.

Science.gov (United States)

Van Haver, Annemieke; De Roo, Karel; De Beule, Matthieu; Van Cauter, Sofie; Audenaert, Emmanuel; Claessens, Tom; Verdonk, Peter

2014-11-01

The authors hypothesise that the trochlear dysplastic distal femur is not only characterised by morphological changes to the trochlea. The purpose of this study is to describe the morphological characteristics of the trochlear dysplastic femur in and outside the trochlear region with a landmark-based 3D analysis. Arthro-CT scans of 20 trochlear dysplastic and 20 normal knees were used to generate 3D models including the cartilage. To rule out size differences, a set of landmarks were defined on the distal femur to isotropically scale the 3D models to a standard size. A predefined series of landmark-based reference planes were applied on the distal femur. With these landmarks and reference planes, a series of previously described characteristics associated with trochlear dysplasia as well as a series of morphometric characteristics were measured. For the previously described characteristics, the analysis replicated highly significant differences between trochlear dysplastic and normal knees. Furthermore, the analysis showed that, when knee size is taken into account, the cut-off values of the trochlear bump and depth would be 1 mm larger in the largest knees compared to the smallest knees. For the morphometric characteristics, the analysis revealed that the trochlear dysplastic femur is also characterised by a 10% smaller intercondylar notch, 6-8% larger posterior condyles (lateral-medial) in the anteroposterior direction and a 6% larger medial condyle in the proximodistal direction compared to a normal femur. This study shows that knee size is important in the application of absolute metric cut-off values and that the posterior femur also shows a significantly different morphology.

Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

Science.gov (United States)

Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

2014-01-01

There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

Science.gov (United States)

Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven

2006-01-01

A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

Directory of Open Access Journals (Sweden)

Maryam Kheirollahpour

2014-01-01

Full Text Available The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA was applied to reveal the hidden (secondary effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.

Superposed ruptile deformational events revealed by field and VOM structural analysis

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Kumaira, Sissa; Guadagnin, Felipe; Keller Lautert, Maiara

2017-04-01

Virtual outcrop models (VOM) is becoming an important application in the analysis of geological structures due to the possibility of obtaining the geometry and in some cases kinematic aspects of analyzed structures in a tridimensional photorealistic space. These data are used to gain quantitative information on the deformational features which coupled with numeric models can assist in understands deformational processes. Old basement units commonly register superposed deformational events either ductile or ruptile along its evolution. The Porongos Belt, located at southern Brazil, have a complex deformational history registering at least five ductile and ruptile deformational events. In this study, we presents a structural analysis of a quarry in the Porongos Belt, coupling field and VOM structural information to understand process involved in the last two deformational events. Field information was acquired using traditional structural methods for analysis of ruptile structures, such as the descriptions, drawings, acquisition of orientation vectors and kinematic analysis. VOM was created from the image-based modeling method through photogrammetric data acquisition and orthorectification. Photogrammetric data acquisition was acquired using Sony a3500 camera and a total of 128 photographs were taken from ca. 10-20 m from the outcrop in different orientations. Thirty two control point coordinates were acquired using a combination of RTK dGPS surveying and total station work, providing a precision of few millimeters for x, y and z. Photographs were imported into the Photo Scan software to create a 3D dense point cloud from structure from-motion algorithm, which were triangulated and textured to generate the VOM. VOM was georreferenced (oriented and scaled) using the ground control points, and later analyzed in OpenPlot software to extract structural information. Data was imported in Wintensor software to obtain tensor orientations, and Move software to process and

Social phenotype extended to communities: expanded multilevel social selection analysis reveals fitness consequences of interspecific interactions.

Science.gov (United States)

Campobello, Daniela; Hare, James F; Sarà, Maurizio

2015-04-01

In social species, fitness consequences are associated with both individual and social phenotypes. Social selection analysis has quantified the contribution of conspecific social traits to individual fitness. There has been no attempt, however, to apply a social selection approach to quantify the fitness implications of heterospecific social phenotypes. Here, we propose a novel social selection based approach integrating the role of all social interactions at the community level. We extended multilevel selection analysis by including a term accounting for the group phenotype of heterospecifics. We analyzed nest activity as a model social trait common to two species, the lesser kestrel (Falco naumanni) and jackdaw (Corvus monedula), nesting in either single- or mixed-species colonies. By recording reproductive outcome as a measure of relative fitness, our results reveal an asymmetric system wherein only jackdaw breeding performance was affected by the activity phenotypes of both conspecific and heterospecific neighbors. Our model incorporating heterospecific social phenotypes is applicable to animal communities where interacting species share a common social trait, thus allowing an assessment of the selection pressure imposed by interspecific interactions in nature. Finally, we discuss the potential role of ecological limitations accounting for random or preferential assortments among interspecific social phenotypes, and the implications of such processes to community evolution. © 2015 The Author(s).

Harmonic Instability Assessment Using State-Space Modeling and Participation Analysis in Inverter-Fed Power Systems

DEFF Research Database (Denmark)

Wang, Yanbo; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

parameters on the harmonic instability of the power system. Moreover, the harmonic-frequency oscillation modes are identified, where participation analysis is presented to evaluate the contributions of different states to these modes and to further reveal how the system gives rise to harmonic instability......This paper presents a harmonic instability analysis method using state-space modeling and participation analysis in the inverter-fed ac power systems. A full-order state-space model for the droop-controlled Distributed Generation (DG) inverter is built first, including the time delay of the digital...... control system, inner current and voltage control loops, and outer droop-based power control loop. Based on the DG inverter model, an overall state-space model of a two-inverter-fed system is established. The eigenvalue-based stability analysis is then presented to assess the influence of controller...

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

Science.gov (United States)

Simões, Paula; Barata, Eduardo; Cruz, Luis

2013-11-01

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.

Bayesian analysis for uncertainty estimation of a canopy transpiration model

Science.gov (United States)

Samanta, S.; Mackay, D. S.; Clayton, M. K.; Kruger, E. L.; Ewers, B. E.

2007-04-01

A Bayesian approach was used to fit a conceptual transpiration model to half-hourly transpiration rates for a sugar maple (Acer saccharum) stand collected over a 5-month period and probabilistically estimate its parameter and prediction uncertainties. The model used the Penman-Monteith equation with the Jarvis model for canopy conductance. This deterministic model was extended by adding a normally distributed error term. This extension enabled using Markov chain Monte Carlo simulations to sample the posterior parameter distributions. The residuals revealed approximate conformance to the assumption of normally distributed errors. However, minor systematic structures in the residuals at fine timescales suggested model changes that would potentially improve the modeling of transpiration. Results also indicated considerable uncertainties in the parameter and transpiration estimates. This simple methodology of uncertainty analysis would facilitate the deductive step during the development cycle of deterministic conceptual models by accounting for these uncertainties while drawing inferences from data.

Changes in cod muscle proteins during frozen storage revealed by proteome analysis and multivariate data analysis

DEFF Research Database (Denmark)

Kjærsgård, Inger Vibeke Holst; Nørrelykke, M.R.; Jessen, Flemming

2006-01-01

Multivariate data analysis has been combined with proteomics to enhance the recovery of information from 2-DE of cod muscle proteins during different storage conditions. Proteins were extracted according to 11 different storage conditions and samples were resolved by 2-DE. Data generated by 2-DE...... was subjected to principal component analysis (PCA) and discriminant partial least squares regression (DPLSR). Applying PCA to 2-DE data revealed the samples to form groups according to frozen storage time, whereas differences due to different storage temperatures or chilled storage in modified atmosphere...... light chain 1, 2 and 3, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, aldolase A and two ?-actin fragments, and a nuclease diphosphate kinase B fragment to change in concentration, during frozen storage. Application of proteomics, multivariate data analysis and MS/MS to analyse...

Kinetic modeling and dynamic analysis of simultaneous saccharification and fermentation of cellulose to bioethanol

International Nuclear Information System (INIS)

Shadbahr, Jalil; Khan, Faisal; Zhang, Yan

2017-01-01

Highlights: • Deeper understanding of saccharification and fermentation process. • A new kinetic model for dynamic analysis of the simultaneous saccharification and fermentation. • Testing and validation of kinetic model. - Abstract: Kinetic modeling and dynamic analysis of the simultaneous saccharification and fermentation (SSF) of cellulose to ethanol was carried out in this study to determine the key reaction kinetics parameters and product inhibition features of the process. To obtain the more reliable kinetic parameters which can be applied for a wide range of operating conditions, batch SSF experiments were carried out at three enzyme loadings (10, 15 and 20 FPU/g cellulose) and two levels of initial concentrations of fermentable sugars (glucose and mannose). Results indicated that the maximum ethanol yield and concentration were achieved at high level of sugar concentrations with intermediate enzyme loading (15 FPU/g cellulose). Dynamic analysis of the acquired experimental results revealed that cellulase inhibition by cellobiose plays the most important role at high level of enzyme loading and low level of initial sugar concentrations. The inhibition of glucose becomes significant when high concentrations of sugars were present in the feedstock. Experimental results of SSF process also reveal that an efficient mixing between the phases helps to improve the ethanol yield significantly.

Comparative proteomics and codon substitution analysis reveal mechanisms of differential resistance to hypoxia in congeneric snails

KAUST Repository

Mu, Huawei; Sun, Jin; Cheung, Siu Gin; Fang, Ling; Zhou, Haiyun; Luan, Tiangang; Zhang, Huoming; Wong, Chris K.C.; Qiu, Jian-Wen

2017-01-01

Although high-throughput proteomics has been widely applied to study mechanisms of environmental adaptation, the conclusions from studies that are based on one species can be confounded by phylogeny. We compare the freshwater snail Pomacea canaliculata (a notorious invasive species) and its congener Pomacea diffusa (a non-invasive species) to understand the molecular mechanisms of their differential resistance to hypoxia. A 72-h acute exposure experiment showed that P. canaliculata is more tolerant to hypoxia than P. diffusa. The two species were then exposed to three levels of dissolved oxygen (6.7, 2.0 and 1.0mgL−1) for 8h, and their gill proteins were analyzed using iTRAQ-coupled LC-MS/MS. The two species showed striking differences in protein expression profiles, with the more hypoxia tolerant P. canaliculata having more up-regulated proteins in signal transduction and down-regulated proteins in glycolysis and the tricarboxylic acid cycle. Evolutionary analysis revealed five orthologous genes encoding differentially expressed proteins having clear signal of positive selection, indicating selection has acted on some of the hypoxia responsive genes. Our case study has highlighted the potential of integrated proteomics and comparative evolutionary analysis for understanding the genetic basis of adaptation to global environmental change in non-model species. SignificanceRapid globalization in recent decades has greatly facilitated species introduction around the world. Successfully established introduced species, so-called invasive species, have threatened the invaded ecosystems. There has been substantial interest in studying how invasive species respond to extreme environmental conditions because the results can help not only predict their range of expansion and manage their impact, but also may reveal the adaptive mechanisms underlying their invasiveness. Our study has adopted a comparative approach to study the differential physiological and proteomic

Comparative proteomics and codon substitution analysis reveal mechanisms of differential resistance to hypoxia in congeneric snails

KAUST Repository

Mu, Huawei

2017-11-06

Although high-throughput proteomics has been widely applied to study mechanisms of environmental adaptation, the conclusions from studies that are based on one species can be confounded by phylogeny. We compare the freshwater snail Pomacea canaliculata (a notorious invasive species) and its congener Pomacea diffusa (a non-invasive species) to understand the molecular mechanisms of their differential resistance to hypoxia. A 72-h acute exposure experiment showed that P. canaliculata is more tolerant to hypoxia than P. diffusa. The two species were then exposed to three levels of dissolved oxygen (6.7, 2.0 and 1.0mgL−1) for 8h, and their gill proteins were analyzed using iTRAQ-coupled LC-MS/MS. The two species showed striking differences in protein expression profiles, with the more hypoxia tolerant P. canaliculata having more up-regulated proteins in signal transduction and down-regulated proteins in glycolysis and the tricarboxylic acid cycle. Evolutionary analysis revealed five orthologous genes encoding differentially expressed proteins having clear signal of positive selection, indicating selection has acted on some of the hypoxia responsive genes. Our case study has highlighted the potential of integrated proteomics and comparative evolutionary analysis for understanding the genetic basis of adaptation to global environmental change in non-model species. SignificanceRapid globalization in recent decades has greatly facilitated species introduction around the world. Successfully established introduced species, so-called invasive species, have threatened the invaded ecosystems. There has been substantial interest in studying how invasive species respond to extreme environmental conditions because the results can help not only predict their range of expansion and manage their impact, but also may reveal the adaptive mechanisms underlying their invasiveness. Our study has adopted a comparative approach to study the differential physiological and proteomic

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

Science.gov (United States)

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Transmission risk assessment of invasive fluke Fascioloides magna using GIS-modelling and multicriteria analysis methods

Directory of Open Access Journals (Sweden)

Juhásová L.

2017-06-01

Full Text Available The combination of multicriteria analysis (MCA, particularly analytic hierarchy process (AHP and geographic information system (GIS were applied for transmission risk assessment of Fascioloides magna (Trematoda; Fasciolidae in south-western Slovakia. Based on the details on F. magna life cycle, the following risk factors (RF of parasite transmission were determined: intermediate (RFIH and final hosts (RFFH (biological factors, annual precipitation (RFAP, land use (RFLU, flooded area (RFFA, and annual mean air temperature (RFAT (environmental factors. Two types of risk analyses were modelled: (1 potential risk analysis was focused on the determination of the potential risk of parasite transmission into novel territories (data on F. magna occurrence were excluded; (2 actual risk analysis considered also the summary data on F. magna occurrence in the model region (risk factor parasite occurrence RFPO included in the analysis. The results of the potential risk analysis provided novel distribution pattern and revealed new geographical area as the potential risk zone of F. magna occurrence. Although the actual risk analysis revealed all four risk zones of F. magna transmission (acceptable, moderate, undesirable and unacceptable, its outputs were significantly affected by the data on parasite occurrence what reduced the informative value of the actual transmission risk assessment.

The elastic network model reveals a consistent picture on intrinsic functional dynamics of type II restriction endonucleases

International Nuclear Information System (INIS)

Uyar, A; Kurkcuoglu, O; Doruker, P; Nilsson, L

2011-01-01

The vibrational dynamics of various type II restriction endonucleases, in complex with cognate/non-cognate DNA and in the apo form, are investigated with the elastic network model in order to reveal common functional mechanisms in this enzyme family. Scissor-like and tong-like motions observed in the slowest modes of all enzymes and their complexes point to common DNA recognition and cleavage mechanisms. Normal mode analysis further points out that the scissor-like motion has an important role in differentiating between cognate and non-cognate sequences at the recognition site, thus implying its catalytic relevance. Flexible regions observed around the DNA-binding site of the enzyme usually concentrate on the highly conserved β-strands, especially after DNA binding. These β-strands may have a structurally stabilizing role in functional dynamics for target site recognition and cleavage. In addition, hot spot residues based on high-frequency modes reveal possible communication pathways between the two distant cleavage sites in the enzyme family. Some of these hot spots also exist on the shortest path between the catalytic sites and are highly conserved

Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer.

Science.gov (United States)

Song, Yimeng; Zhong, Lijun; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

2017-12-01

Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation. Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues. More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results. The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CAD-Based Modeling of Advanced Rotary Wing Structures for Integrated 3-D Aeromechanics Analysis

Science.gov (United States)

Staruk, William

This dissertation describes the first comprehensive use of integrated 3-D aeromechanics modeling, defined as the coupling of 3-D solid finite element method (FEM) structural dynamics with 3-D computational fluid dynamics (CFD), for the analysis of a real helicopter rotor. The development of this new methodology (a departure from how rotor aeroelastic analysis has been performed for 40 years), its execution on a real rotor, and the fundamental understanding of aeromechanics gained from it, are the key contributions of this dissertation. This work also presents the first CFD/CSD analysis of a tiltrotor in edgewise flight, revealing many of its unique loading mechanisms. The use of 3-D FEM, integrated with a trim solver and aerodynamics modeling, has the potential to enhance the design of advanced rotors by overcoming fundamental limitations of current generation beam-based analysis tools and offering integrated internal dynamic stress and strain predictions for design. Two primary goals drove this research effort: 1) developing a methodology to create 3-D CAD-based brick finite element models of rotors including multibody joints, controls, and aerodynamic interfaces, and 2) refining X3D, the US Army's next generation rotor structural dynamics solver featuring 3-D FEM within a multibody formulation with integrated aerodynamics, to model a tiltrotor in the edgewise conversion flight regime, which drives critical proprotor structural loads. Prior tiltrotor analysis has primarily focused on hover aerodynamics with rigid blades or forward flight whirl-flutter stability with simplified aerodynamics. The first goal was met with the development of a detailed methodology for generating multibody 3-D structural models, starting from CAD geometry, continuing to higher-order hexahedral finite element meshing, to final assembly of the multibody model by creating joints, assigning material properties, and defining the aerodynamic interface. Several levels of verification and

Novel cancer gene variants and gene fusions of triple-negative breast cancers (TNBCs) reveal their molecular diversity conserved in the patient-derived xenograft (PDX) model.

Science.gov (United States)

Jung, Jaeyun; Jang, Kiwon; Ju, Jung Min; Lee, Eunji; Lee, Jong Won; Kim, Hee Jung; Kim, Jisun; Lee, Sae Byul; Ko, Beom Seok; Son, Byung Ho; Lee, Hee Jin; Gong, Gyungyup; Ahn, Sei Yeon; Choi, Jung Kyoon; Singh, Shree Ram; Chang, Suhwan

2018-04-20

Despite the improved 5-year survival rate of breast cancer, triple-negative breast cancer (TNBC) remains a challenge due to lack of effective targeted therapy and higher recurrence and metastasis than other subtypes. To identify novel druggable targets and to understand its unique biology, we tried to implement 24 patient-derived xenografts (PDXs) of TNBC. The overall success rate of PDX implantation was 45%, much higher than estrogen receptor (ER)-positive cases. Immunohistochemical analysis revealed conserved ER/PR/Her2 negativity (with two exceptions) between the original and PDX tumors. Genomic analysis of 10 primary tumor-PDX pairs with Ion AmpliSeq CCP revealed high degree of variant conservation (85.0% to 96.9%) between primary and PDXs. Further analysis showed 44 rare variants with a predicted high impact in 36 genes including Trp53, Pten, Notch1, and Col1a1. Among them, we confirmed frequent Notch1 variant. Furthermore, RNA-seq analysis of 24 PDXs revealed 594 gene fusions, of which 163 were in-frame, including AZGP1-GJC3 and NF1-AARSD1. Finally, western blot analysis of oncogenic signaling proteins supporting molecular diversity of TNBC PDXs. Overall, our report provides a molecular basis for the usefulness of the TNBC PDX model in preclinical study. Copyright © 2018. Published by Elsevier B.V.

Next-generation sequence analysis of cancer xenograft models.

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Fernando J Rossello

Full Text Available Next-generation sequencing (NGS studies in cancer are limited by the amount, quality and purity of tissue samples. In this situation, primary xenografts have proven useful preclinical models. However, the presence of mouse-derived stromal cells represents a technical challenge to their use in NGS studies. We examined this problem in an established primary xenograft model of small cell lung cancer (SCLC, a malignancy often diagnosed from small biopsy or needle aspirate samples. Using an in silico strategy that assign reads according to species-of-origin, we prospectively compared NGS data from primary xenograft models with matched cell lines and with published datasets. We show here that low-coverage whole-genome analysis demonstrated remarkable concordance between published genome data and internal controls, despite the presence of mouse genomic DNA. Exome capture sequencing revealed that this enrichment procedure was highly species-specific, with less than 4% of reads aligning to the mouse genome. Human-specific expression profiling with RNA-Seq replicated array-based gene expression experiments, whereas mouse-specific transcript profiles correlated with published datasets from human cancer stroma. We conclude that primary xenografts represent a useful platform for complex NGS analysis in cancer research for tumours with limited sample resources, or those with prominent stromal cell populations.

A random effects meta-analysis model with Box-Cox transformation.

Science.gov (United States)

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

Data analysis and approximate models model choice, location-scale, analysis of variance, nonparametric regression and image analysis

CERN Document Server

Davies, Patrick Laurie

2014-01-01

Introduction IntroductionApproximate Models Notation Two Modes of Statistical AnalysisTowards One Mode of Analysis Approximation, Randomness, Chaos, Determinism ApproximationA Concept of Approximation Approximation Approximating a Data Set by a Model Approximation Regions Functionals and EquivarianceRegularization and Optimality Metrics and DiscrepanciesStrong and Weak Topologies On Being (almost) Honest Simulations and Tables Degree of Approximation and p-values ScalesStability of Analysis The Choice of En(α, P) Independence Procedures, Approximation and VaguenessDiscrete Models The Empirical Density Metrics and Discrepancies The Total Variation Metric The Kullback-Leibler and Chi-Squared Discrepancies The Po(λ) ModelThe b(k, p) and nb(k, p) Models The Flying Bomb Data The Student Study Times Data OutliersOutliers, Data Analysis and Models Breakdown Points and Equivariance Identifying Outliers and Breakdown Outliers in Multivariate Data Outliers in Linear Regression Outliers in Structured Data The Location...

High-speed image analysis reveals chaotic vibratory behaviors of pathological vocal folds

Energy Technology Data Exchange (ETDEWEB)

Zhang Yu, E-mail: yuzhang@xmu.edu.c [Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of Education, Xiamen University, Xiamen Fujian 361005 (China); Shao Jun [Shanghai EENT Hospital of Fudan University, Shanghai (China); Krausert, Christopher R. [Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792-7375 (United States); Zhang Sai [Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of Education, Xiamen University, Xiamen Fujian 361005 (China); Jiang, Jack J. [Shanghai EENT Hospital of Fudan University, Shanghai (China); Department of Surgery, Division of Otolaryngology - Head and Neck Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792-7375 (United States)

2011-01-15

Research highlights: Low-dimensional human glottal area data. Evidence of chaos in human laryngeal activity from high-speed digital imaging. Traditional perturbation analysis should be cautiously applied to aperiodic high speed image signals. Nonlinear dynamic analysis may be helpful for understanding disordered behaviors in pathological laryngeal systems. - Abstract: Laryngeal pathology is usually associated with irregular dynamics of laryngeal activity. High-speed imaging facilitates direct observation and measurement of vocal fold vibrations. However, chaotic dynamic characteristics of aperiodic high-speed image data have not yet been investigated in previous studies. In this paper, we will apply nonlinear dynamic analysis and traditional perturbation methods to quantify high-speed image data from normal subjects and patients with various laryngeal pathologies including vocal fold nodules, polyps, bleeding, and polypoid degeneration. The results reveal the low-dimensional dynamic characteristics of human glottal area data. In comparison to periodic glottal area series from a normal subject, aperiodic glottal area series from pathological subjects show complex reconstructed phase space, fractal dimension, and positive Lyapunov exponents. The estimated positive Lyapunov exponents provide the direct evidence of chaos in pathological human vocal folds from high-speed digital imaging. Furthermore, significant differences between the normal and pathological groups are investigated for nonlinear dynamic and perturbation analyses. Jitter in the pathological group is significantly higher than in the normal group, but shimmer does not show such a difference. This finding suggests that the traditional perturbation analysis should be cautiously applied to high speed image signals. However, the correlation dimension and the maximal Lyapunov exponent reveal a statistically significant difference between normal and pathological groups. Nonlinear dynamic analysis is capable of

High-speed image analysis reveals chaotic vibratory behaviors of pathological vocal folds

International Nuclear Information System (INIS)

Zhang Yu; Shao Jun; Krausert, Christopher R.; Zhang Sai; Jiang, Jack J.

2011-01-01

Research highlights: → Low-dimensional human glottal area data. → Evidence of chaos in human laryngeal activity from high-speed digital imaging. → Traditional perturbation analysis should be cautiously applied to aperiodic high speed image signals. → Nonlinear dynamic analysis may be helpful for understanding disordered behaviors in pathological laryngeal systems. - Abstract: Laryngeal pathology is usually associated with irregular dynamics of laryngeal activity. High-speed imaging facilitates direct observation and measurement of vocal fold vibrations. However, chaotic dynamic characteristics of aperiodic high-speed image data have not yet been investigated in previous studies. In this paper, we will apply nonlinear dynamic analysis and traditional perturbation methods to quantify high-speed image data from normal subjects and patients with various laryngeal pathologies including vocal fold nodules, polyps, bleeding, and polypoid degeneration. The results reveal the low-dimensional dynamic characteristics of human glottal area data. In comparison to periodic glottal area series from a normal subject, aperiodic glottal area series from pathological subjects show complex reconstructed phase space, fractal dimension, and positive Lyapunov exponents. The estimated positive Lyapunov exponents provide the direct evidence of chaos in pathological human vocal folds from high-speed digital imaging. Furthermore, significant differences between the normal and pathological groups are investigated for nonlinear dynamic and perturbation analyses. Jitter in the pathological group is significantly higher than in the normal group, but shimmer does not show such a difference. This finding suggests that the traditional perturbation analysis should be cautiously applied to high speed image signals. However, the correlation dimension and the maximal Lyapunov exponent reveal a statistically significant difference between normal and pathological groups. Nonlinear dynamic

Choice experiments versus revealed choice models : a before-after study of consumer spatial shopping behavior

NARCIS (Netherlands)

Timmermans, H.J.P.; Borgers, A.W.J.; Waerden, van der P.J.H.J.

1992-01-01

The purpose of this article is to compare a set of multinomial logit models derived from revealed choice data and a decompositional choice model derived from experimental data in terms of predictive success in the context of consumer spatial shopping behavior. Data on consumer shopping choice

A Project Team Analysis Using Tuckman's Model of Small-Group Development.

Science.gov (United States)

Natvig, Deborah; Stark, Nancy L

2016-12-01

Concerns about equitable workloads for nursing faculty have been well documented, yet a standardized system for workload management does not exist. A project team was challenged to establish an academic workload management system when two dissimilar universities were consolidated. Tuckman's model of small-group development was used as the framework for the analysis of processes and effectiveness of a workload project team. Agendas, notes, and meeting minutes were used as the primary sources of information. Analysis revealed the challenges the team encountered. Utilization of a team charter was an effective tool in guiding the team to become a highly productive group. Lessons learned from the analysis are discussed. Guiding a diverse group into a highly productive team is complex. The use of Tuckman's model of small-group development provided a systematic mechanism to review and understand group processes and tasks. [J Nurs Educ. 2016;55(12):675-681.]. Copyright 2016, SLACK Incorporated.

Analysis of a Heroin Epidemic Model with Saturated Treatment Function

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Isaac Mwangi Wangari

2017-01-01

Full Text Available A mathematical model is developed that examines how heroin addiction spreads in society. The model is formulated to take into account the treatment of heroin users by incorporating a realistic functional form that “saturates” representing the limited availability of treatment. Bifurcation analysis reveals that the model has an intrinsic backward bifurcation whenever the saturation parameter is larger than a fixed threshold. We are particularly interested in studying the model’s global stability. In the absence of backward bifurcations, Lyapunov functions can often be found and used to prove global stability. However, in the presence of backward bifurcations, such Lyapunov functions may not exist or may be difficult to construct. We make use of the geometric approach to global stability to derive a condition that ensures that the system is globally asymptotically stable. Numerical simulations are also presented to give a more complete representation of the model dynamics. Sensitivity analysis performed by Latin hypercube sampling (LHS suggests that the effective contact rate in the population, the relapse rate of heroin users undergoing treatment, and the extent of saturation of heroin users are mechanisms fuelling heroin epidemic proliferation.

Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

Proteome-wide analysis of arginine monomethylation reveals widespread occurrence in human cells

DEFF Research Database (Denmark)

Larsen, Sara C; Sylvestersen, Kathrine B; Mund, Andreas

2016-01-01

to the frequency of somatic mutations at arginine methylation sites throughout the proteome, we observed that somatic mutations were common at arginine methylation sites in proteins involved in mRNA splicing. Furthermore, in HeLa and U2OS cells, we found that distinct arginine methyltransferases differentially...... kidney 293 cells, indicating that the occurrence of this modification is comparable to phosphorylation and ubiquitylation. A site-level conservation analysis revealed that arginine methylation sites are less evolutionarily conserved compared to arginines that were not identified as modified...... as coactivator-associated arginine methyltransferase 1 (CARM1)] or PRMT1 increased the RNA binding function of HNRNPUL1. High-content single-cell imaging additionally revealed that knocking down CARM1 promoted the nuclear accumulation of SRSF2, independent of cell cycle phase. Collectively, the presented human...

Recent adaptive events in human brain revealed by meta-analysis of positively selected genes.

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Yue Huang

Full Text Available BACKGROUND AND OBJECTIVES: Analysis of positively-selected genes can help us understand how human evolved, especially the evolution of highly developed cognitive functions. However, previous works have reached conflicting conclusions regarding whether human neuronal genes are over-represented among genes under positive selection. METHODS AND RESULTS: We divided positively-selected genes into four groups according to the identification approaches, compiling a comprehensive list from 27 previous studies. We showed that genes that are highly expressed in the central nervous system are enriched in recent positive selection events in human history identified by intra-species genomic scan, especially in brain regions related to cognitive functions. This pattern holds when different datasets, parameters and analysis pipelines were used. Functional category enrichment analysis supported these findings, showing that synapse-related functions are enriched in genes under recent positive selection. In contrast, immune-related functions, for instance, are enriched in genes under ancient positive selection revealed by inter-species coding region comparison. We further demonstrated that most of these patterns still hold even after controlling for genomic characteristics that might bias genome-wide identification of positively-selected genes including gene length, gene density, GC composition, and intensity of negative selection. CONCLUSION: Our rigorous analysis resolved previous conflicting conclusions and revealed recent adaptation of human brain functions.

Parametric mapping using spectral analysis for 11C-PBR28 PET reveals neuroinflammation in mild cognitive impairment subjects.

Science.gov (United States)

Fan, Zhen; Dani, Melanie; Femminella, Grazia D; Wood, Melanie; Calsolaro, Valeria; Veronese, Mattia; Turkheimer, Federico; Gentleman, Steve; Brooks, David J; Hinz, Rainer; Edison, Paul

2018-07-01

Neuroinflammation and microglial activation play an important role in amnestic mild cognitive impairment (MCI) and Alzheimer's disease. In this study, we investigated the spatial distribution of neuroinflammation in MCI subjects, using spectral analysis (SA) to generate parametric maps and quantify 11 C-PBR28 PET, and compared these with compartmental and other kinetic models of quantification. Thirteen MCI and nine healthy controls were enrolled in this study. Subjects underwent 11 C-PBR28 PET scans with arterial cannulation. Spectral analysis with an arterial plasma input function was used to generate 11 C-PBR28 parametric maps. These maps were then compared with regional 11 C-PBR28 V T (volume of distribution) using a two-tissue compartment model and Logan graphic analysis. Amyloid load was also assessed with 18 F-Flutemetamol PET. With SA, three component peaks were identified in addition to blood volume. The 11 C-PBR28 impulse response function (IRF) at 90 min produced the lowest coefficient of variation. Single-subject analysis using this IRF demonstrated microglial activation in five out of seven amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake revealed a group-wise significant increase in neuroinflammation in amyloid-positive MCI subjects versus HC in multiple cortical association areas, and particularly in the temporal lobe. Interestingly, compartmental analysis detected group-wise increase in 11 C-PBR28 binding in the thalamus of amyloid-positive MCI subjects, while Logan parametric maps did not perform well. This study demonstrates for the first time that spectral analysis can be used to generate parametric maps of 11 C-PBR28 uptake, and is able to detect microglial activation in amyloid-positive MCI subjects. IRF parametric maps of 11 C-PBR28 uptake allow voxel-wise single-subject analysis and could be used to evaluate microglial activation in individual subjects.

Analysis reveals potential rangeland impacts if Williamson Act eliminated

Directory of Open Access Journals (Sweden)

William C. Wetzel

2012-10-01

Full Text Available California budget cuts have resulted in dramatic reductions in state funding for the Williamson Act, a land protection program that reduces property taxes for the owners of 15 million acres of California farms and rangeland. With state reimbursements to counties eliminated, the decision to continue Williamson Act contracts lies with individual counties. We investigated the consequences of eliminating the Williamson Act, using a geospatial analysis and a mail questionnaire asking ranchers for plans under a hypothetical elimination scenario. The geospatial analysis revealed that 72% of rangeland parcels enrolled in Williamson Act contracts contained habitat important for statewide conservation goals. Presented with the elimination scenario, survey respondents reported an intention to sell 20% of their total 496,889 acres. The tendency of survey participants to respond that they would sell land was highest among full-time ranchers with low household incomes and without off-ranch employment. A majority (76% of the ranchers who reported that they would sell land predicted that the buyers would develop it for nonagricultural uses, suggesting substantial changes to California's landscape in a future without the Williamson Act.

Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

Science.gov (United States)

Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

2016-06-01

We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

Genomic analysis of primordial dwarfism reveals novel disease genes.

Science.gov (United States)

Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S

2014-02-01

Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis.

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Directory of Open Access Journals (Sweden)

Hong Xue

2018-01-01

Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

Science.gov (United States)

Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states. PMID:25309414

DIGE proteome analysis reveals suitability of ischemic cardiac in vitro model for studying cellular response to acute ischemia and regeneration.

Directory of Open Access Journals (Sweden)

Sina Haas

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

ModelMate - A graphical user interface for model analysis

Science.gov (United States)

Banta, Edward R.

2011-01-01

ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

Landslide Kinematical Analysis through Inverse Numerical Modelling and Differential SAR Interferometry

Science.gov (United States)

Castaldo, R.; Tizzani, P.; Lollino, P.; Calò, F.; Ardizzone, F.; Lanari, R.; Guzzetti, F.; Manunta, M.

2015-11-01

The aim of this paper is to propose a methodology to perform inverse numerical modelling of slow landslides that combines the potentialities of both numerical approaches and well-known remote-sensing satellite techniques. In particular, through an optimization procedure based on a genetic algorithm, we minimize, with respect to a proper penalty function, the difference between the modelled displacement field and differential synthetic aperture radar interferometry (DInSAR) deformation time series. The proposed methodology allows us to automatically search for the physical parameters that characterize the landslide behaviour. To validate the presented approach, we focus our analysis on the slow Ivancich landslide (Assisi, central Italy). The kinematical evolution of the unstable slope is investigated via long-term DInSAR analysis, by exploiting about 20 years of ERS-1/2 and ENVISAT satellite acquisitions. The landslide is driven by the presence of a shear band, whose behaviour is simulated through a two-dimensional time-dependent finite element model, in two different physical scenarios, i.e. Newtonian viscous flow and a deviatoric creep model. Comparison between the model results and DInSAR measurements reveals that the deviatoric creep model is more suitable to describe the kinematical evolution of the landslide. This finding is also confirmed by comparing the model results with the available independent inclinometer measurements. Our analysis emphasizes that integration of different data, within inverse numerical models, allows deep investigation of the kinematical behaviour of slow active landslides and discrimination of the driving forces that govern their deformation processes.

Sediment transport processes in the Pearl River Estuary as revealed by grain-size end-member modeling and sediment trend analysis

Science.gov (United States)

Li, Tao; Li, Tuan-Jie

2018-04-01

The analysis of grain-size distribution enables us to decipher sediment transport processes and understand the causal relations between dynamic processes and grain-size distributions. In the present study, grain sizes were measured from surface sediments collected in the Pearl River Estuary and its adjacent coastal areas. End-member modeling analysis attempts to unmix the grain sizes into geologically meaningful populations. Six grain-size end-members were identified. Their dominant modes are 0 Φ, 1.5 Φ, 2.75 Φ, 4.5 Φ, 7 Φ, and 8 Φ, corresponding to coarse sand, medium sand, fine sand, very coarse silt, silt, and clay, respectively. The spatial distributions of the six end-members are influenced by sediment transport and depositional processes. The two coarsest end-members (coarse sand and medium sand) may reflect relict sediments deposited during the last glacial period. The fine sand end-member would be difficult to transport under fair weather conditions, and likely indicates storm deposits. The three remaining fine-grained end-members (very coarse silt, silt, and clay) are recognized as suspended particles transported by saltwater intrusion via the flood tidal current, the Guangdong Coastal Current, and riverine outflow. The grain-size trend analysis shows distinct transport patterns for the three fine-grained end-members. The landward transport of the very coarse silt end-member occurs in the eastern part of the estuary, the seaward transport of the silt end-member occurs in the western part, and the east-west transport of the clay end-member occurs in the coastal areas. The results show that grain-size end-member modeling analysis in combination with sediment trend analysis help to better understand sediment transport patterns and the associated transport mechanisms.

REVEAL - A tool for rule driven analysis of safety critical software

International Nuclear Information System (INIS)

Miedl, H.; Kersken, M.

1998-01-01

As the determination of ultrahigh reliability figures for safety critical software is hardly possible, national and international guidelines and standards give mainly requirements for the qualitative evaluation of software. An analysis whether all these requirements are fulfilled is time and effort consuming and prone to errors, if performed manually by analysts, and should instead be dedicated to tools as far as possible. There are many ''general-purpose'' software analysis tools, both static and dynamic, which help analyzing the source code. However, they are not designed to assess the adherence to specific requirements of guidelines and standards in the nuclear field. Against the background of the development of I and C systems in the nuclear field which are based on digital techniques and implemented in high level language, it is essential that the assessor or licenser has a tool with which he can automatically and uniformly qualify as many aspects as possible of the high level language software. For this purpose the software analysis tool REVEAL has been developed at ISTec and the Halden Reactor Project. (author)

Molecular basis of structural make-up of feeds in relation to nutrient absorption in ruminants, revealed with advanced molecular spectroscopy: A review on techniques and models

Energy Technology Data Exchange (ETDEWEB)

Rahman, Md. Mostafizar [Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada; Yu, Peiqiang [Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

2017-01-31

Progress in ruminant feed research is no more feasible only based on wet chemical analysis, which is merely able to provide information on chemical composition of feeds regardless of their digestive features and nutritive value in ruminants. Studying internal structural make-up of functional groups/feed nutrients is often vital for understanding the digestive behaviors and nutritive values of feeds in ruminant because the intrinsic structure of feed nutrients is more related to its overall absorption. In this article, the detail information on the recent developments in molecular spectroscopic techniques to reveal microstructural information of feed nutrients and the use of nutrition models in regards to ruminant feed research was reviewed. The emphasis of this review was on (1) the technological progress in the use of molecular spectroscopic techniques in ruminant feed research; (2) revealing spectral analysis of functional groups of biomolecules/feed nutrients; (3) the use of advanced nutrition models for better prediction of nutrient availability in ruminant systems; and (4) the application of these molecular techniques and combination of nutrient models in cereals, co-products and pulse crop research. The information described in this article will promote better insight in the progress of research on molecular structural make-up of feed nutrients in ruminants.

Multistationary and oscillatory modes of free radicals generation by the mitochondrial respiratory chain revealed by a bifurcation analysis.

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Vitaly A Selivanov

Full Text Available The mitochondrial electron transport chain transforms energy satisfying cellular demand and generates reactive oxygen species (ROS that act as metabolic signals or destructive factors. Therefore, knowledge of the possible modes and bifurcations of electron transport that affect ROS signaling provides insight into the interrelationship of mitochondrial respiration with cellular metabolism. Here, a bifurcation analysis of a sequence of the electron transport chain models of increasing complexity was used to analyze the contribution of individual components to the modes of respiratory chain behavior. Our algorithm constructed models as large systems of ordinary differential equations describing the time evolution of the distribution of redox states of the respiratory complexes. The most complete model of the respiratory chain and linked metabolic reactions predicted that condensed mitochondria produce more ROS at low succinate concentration and less ROS at high succinate levels than swelled mitochondria. This prediction was validated by measuring ROS production under various swelling conditions. A numerical bifurcation analysis revealed qualitatively different types of multistationary behavior and sustained oscillations in the parameter space near a region that was previously found to describe the behavior of isolated mitochondria. The oscillations in transmembrane potential and ROS generation, observed in living cells were reproduced in the model that includes interaction of respiratory complexes with the reactions of TCA cycle. Whereas multistationarity is an internal characteristic of the respiratory chain, the functional link of respiration with central metabolism creates oscillations, which can be understood as a means of auto-regulation of cell metabolism.

Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

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María P. Cortés

2017-12-01

Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

Models of Economic Analysis

OpenAIRE

Adrian Ioana; Tiberiu Socaciu

2013-01-01

The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

Comparison of LTI and LTP Models for Stability Analysis of Grid Converters

DEFF Research Database (Denmark)

Kwon, Jun Bum; Wang, Xiongfei; Blaabjerg, Frede

2016-01-01

The stability analysis of grid-connected converters have attracted increasing attentions, due to the oscillations arising in wind power plants, micro-grids, and other emerging power electronics based power systems. The modeling tool of converters thus becomes essential to faithfully reveal...... oscillations without any hidden regions. This paper presents a detailed comparison of two linearized modeling methods, which are, respectively, developed in the Linear Time-Invariant (LTI) and the Linear Time-Periodic (LTP) frameworks. The LTP model can consider the effect of frequency-coupling dynamics, which...... are occurred by the time-varying behavior, while the conventional LTI model can not capture this behavior. The advantages and limits of two models are then illustrated with examples. The compared results are verified in the frequency domain and time domain as well....

Meta-analysis reveals an association between signal transducer and activator of transcription-4 polymorphism and hepatocellular carcinoma risk.

Science.gov (United States)

Zhang, Li; Xu, Kuihua; Liu, Chuanmiao; Chen, Jiasheng

2017-03-01

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related mortality worldwide. Signal transducer and activator of transcription (STAT) proteins play a multitude of important functions in liver pathophysiology. Recent studies have indicated associations of rs7574865 single nucleotide polymorphism (SNP) in the STAT4 gene with various autoimmune diseases. The association between STAT4 polymorphism and the risk of HCC has been analyzed in several studies, but results remain inconsistent. This study used a meta-analysis approach to comprehensively investigate the correlation between STAT4 polymorphism and HCC risk based on previously published reports. Studies were searched from the databases of PubMed, EMBase, Web of Science, and the Chinese National Knowledge Infrastructure up to 31 December 2015. The meta-analysis was carried out based on the statement of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Eight published studies, consisting of 7503 HCC patients (cases) and 13 831 individuals without HCC (controls), were included in the present study. Meta-analysis of the included studies revealed that STAT4 rs7574865 polymorphism contributed to the risk of HCC under all four genetic models, consisting of the allelic model (G vs. T: odds ratio [OR], 1.25; 95% confidence interval [CI], 1.19-1.30), the dominant effect model (GG + GT vs. TT: OR, 1.52; 95% CI, 1.26-1.84), the recessive effect model (GG vs. GT + TT: OR, 1.35; 95% CI, 1.21-1.50), and the co-dominant effect model (GG vs.. TT: OR, 1.72; 95% CI, 1.42-2.10) comparisons. No publication bias was indicated from either visualization of the funnel plot or Egger's test. A significantly increased risk of HCC associated with the rs7574865 G was found. The rs7574865 polymorphism might be used as one risk factor for HCC. © 2016 The Japan Society of Hepatology.

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

AN ANALYSIS ON THE DECISION MODEL OF SMART PLUS INSURANCE PRODUCT PURCHASE

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Fitry Primadona

2016-09-01

Full Text Available The purposes of this study were 1 to analyze the decision model of Smart Plus insurance product purchase and 2 to determine the criteria, sub-criteria, and alternative priorities in Smart Plus purchase decision model. The methods utilized in the study included a survey and interview (in-depth interview by using an AHP analysis (Analytical Hierarchy Process and processing software of "Expert Choice". The result of the first analysis indicated the four marketing mixes that had been performed (Price, Product, Process, and Place; while the second one showed that the purchase of Smart Plus product is based on the factors with the level of interest as follow: benefit (36.3%, premium (35.7%, membership process (14.6%, and provider (13.4%. The result of the second analysis revealed the important sub-criteria including premium offer, additional benefits, membership card, and temporary certificate from the medical specialist.Keywords: AHP, life insurance, marketing mix, purchase decision

Meta-analysis reveals host-dependent nitrogen recycling as a mechanism of symbiont control in Aiptasia

KAUST Repository

Cui, Guoxin

2018-02-22

The metabolic symbiosis with photosynthetic algae of the genus Symbiodinium allows corals to thrive in the oligotrophic environments of tropical seas. Many aspects of this relationship have been investigated using transcriptomic analyses in the emerging model organism Aiptasia. However, previous studies identified thousands of putatively symbiosis-related genes, making it difficult to disentangle symbiosis-induced responses from undesired experimental parameters. Using a meta-analysis approach, we identified a core set of 731 high-confidence symbiosis-associated genes that reveal host-dependent recycling of waste ammonium and amino acid synthesis as central processes in this relationship. Combining transcriptomic and metabolomic analyses, we show that symbiont-derived carbon enables host recycling of ammonium into nonessential amino acids. We propose that this provides a regulatory mechanism to control symbiont growth through a carbon-dependent negative feedback of nitrogen availability to the symbiont. The dependence of this mechanism on symbiont-derived carbon highlights the susceptibility of this symbiosis to changes in carbon translocation, as imposed by environmental stress.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

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E. Damaraju

2014-01-01

Full Text Available Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length, and a dynamic sense, computed using sliding windows (44 s in length and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual, as well as reduced connectivity (hypoconnectivity between sensory networks from all modalities. Dynamic analysis suggests that (1, on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2, that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity

Allosteric effects in bacteriophage HK97 procapsids revealed directly from covariance analysis of cryo EM data.

Science.gov (United States)

Xu, Nan; Veesler, David; Doerschuk, Peter C; Johnson, John E

2018-05-01

The information content of cryo EM data sets exceeds that of the electron scattering potential (cryo EM) density initially derived for structure determination. Previously we demonstrated the power of data variance analysis for characterizing regions of cryo EM density that displayed functionally important variance anomalies associated with maturation cleavage events in Nudaurelia Omega Capensis Virus and the presence or absence of a maturation protease in bacteriophage HK97 procapsids. Here we extend the analysis in two ways. First, instead of imposing icosahedral symmetry on every particle in the data set during the variance analysis, we only assume that the data set as a whole has icosahedral symmetry. This change removes artifacts of high variance along icosahedral symmetry axes, but retains all of the features previously reported in the HK97 data set. Second we present a covariance analysis that reveals correlations in structural dynamics (variance) between the interior of the HK97 procapsid with the protease and regions of the exterior (not seen in the absence of the protease). The latter analysis corresponds well with hydrogen deuterium exchange studies previously published that reveal the same correlation. Copyright © 2018 Elsevier Inc. All rights reserved.

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

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Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

Growth conditions of 0-group plaice Pleuronectes platessa in the western Wadden Sea as revealed by otolith microstructure analysis

Science.gov (United States)

Cardoso, Joana F. M. F.; Freitas, Vânia; de Paoli, Hélène; Witte, Johannes IJ.; van der Veer, Henk W.

2016-05-01

Growth studies based on population-based growth estimates are limited by the fact that they do not take into account differences in age/size structure within the population. To overcome these problems, otolith microstructure analysis is often used to estimate individual growth. Here, we analyse growth of 0-group plaice in the western Wadden Sea in two years: a year preceded by a mild winter (1995) and a year preceded by a severe winter (1996). Growth was analysed by combining information on individual growth based on otolith analysis with predictions of maximum growth (= under optimal food conditions) based on a Dynamic Energy Budget model. Otolith analysis revealed that settlement occurred earlier in 1995 than in 1996. In both years, one main cohort was found, followed by a group of late settlers. No differences in mean length-at-age were found between these groups. DEB modelling suggested that growth was not maximal during the whole growing season: realized growth (the fraction of maximum growth realized by 0-group plaice) declined in the summer, although this decline was relatively small. In addition, late settling individuals exhibited lower realized growth than individuals from the main cohort. This study confirms that growth conditions for 0-group plaice are not optimal and that a growth reduction occurs in summer, as suggested in previous studies.

Scaling analysis and model estimation of solar corona index

Science.gov (United States)

Ray, Samujjwal; Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik

2018-04-01

A monthly average solar green coronal index time series for the period from January 1939 to December 2008 collected from NOAA (The National Oceanic and Atmospheric Administration) has been analysed in this paper in perspective of scaling analysis and modelling. Smoothed and de-noising have been done using suitable mother wavelet as a pre-requisite. The Finite Variance Scaling Method (FVSM), Higuchi method, rescaled range (R/S) and a generalized method have been applied to calculate the scaling exponents and fractal dimensions of the time series. Autocorrelation function (ACF) is used to find autoregressive (AR) process and Partial autocorrelation function (PACF) has been used to get the order of AR model. Finally a best fit model has been proposed using Yule-Walker Method with supporting results of goodness of fit and wavelet spectrum. The results reveal an anti-persistent, Short Range Dependent (SRD), self-similar property with signatures of non-causality, non-stationarity and nonlinearity in the data series. The model shows the best fit to the data under observation.

3D Product authenticity model for online retail: An invariance analysis

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Algharabat, R.

2010-01-01

Full Text Available This study investigates the effects of different levels of invariance analysis on three dimensional (3D product authenticity model (3DPAM constructs in the e- retailing context. A hypothetical retailer website presents a variety of laptops using 3D product visualisations. The proposed conceptual model achieves acceptable fit and the hypothesised paths are all valid. We empirically investigate the invariance across the subgroups to validate the results of our 3DPAM. We concluded that the 3D product authenticity model construct was invariant for our sample across different gender, level of education and study backgrounds. These findings suggested that all our subgroups conceptualised the 3DPAM similarly. Also the results show some non-invariance results for the structural and latent mean models. The gender group posits a non-invariance latent mean model. Study backgrounds group reveals a non-invariance result for the structural model. These findings allowed us to understand the 3DPAMs validity in the e-retail context. Managerial implications are explained.

Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Science.gov (United States)

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDRspeech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

Combination of Metabolomic and Proteomic Analysis Revealed Different Features among Lactobacillus delbrueckii Subspecies bulgaricus and lactis Strains While In Vivo Testing in the Model Organism Caenorhabditis elegans Highlighted Probiotic Properties

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Elena Zanni

2017-06-01

Full Text Available Lactobacillus delbrueckii represents a technologically relevant member of lactic acid bacteria, since the two subspecies bulgaricus and lactis are widely associated with fermented dairy products. In the present work, we report the characterization of two commercial strains belonging to L. delbrueckii subspecies bulgaricus, lactis and a novel strain previously isolated from a traditional fermented fresh cheese. A phenomic approach was performed by combining metabolomic and proteomic analysis of the three strains, which were subsequently supplemented as food source to the model organism Caenorhabditis elegans, with the final aim to evaluate their possible probiotic effects. Restriction analysis of 16S ribosomal DNA revealed that the novel foodborne strain belonged to L. delbrueckii subspecies lactis. Proteomic and metabolomic approaches showed differences in folate, aminoacid and sugar metabolic pathways among the three strains. Moreover, evaluation of C. elegans lifespan, larval development, brood size, and bacterial colonization capacity demonstrated that L. delbrueckii subsp. bulgaricus diet exerted beneficial effects on nematodes. On the other hand, both L. delbrueckii subsp. lactis strains affected lifespan and larval development. We have characterized three strains belonging to L. delbrueckii subspecies bulgaricus and lactis highlighting their divergent origin. In particular, the two closely related isolates L. delbrueckii subspecies lactis display different galactose metabolic capabilities. Moreover, the L. delbrueckii subspecies bulgaricus strain demonstrated potential probiotic features. Combination of omic platforms coupled with in vivo screening in the simple model organism C. elegans is a powerful tool to characterize industrially relevant bacterial isolates.

Combination of Metabolomic and Proteomic Analysis Revealed Different Features among Lactobacillus delbrueckii Subspecies bulgaricus and lactis Strains While In Vivo Testing in the Model Organism Caenorhabditis elegans Highlighted Probiotic Properties.

Science.gov (United States)

Zanni, Elena; Schifano, Emily; Motta, Sara; Sciubba, Fabio; Palleschi, Claudio; Mauri, Pierluigi; Perozzi, Giuditta; Uccelletti, Daniela; Devirgiliis, Chiara; Miccheli, Alfredo

2017-01-01

Lactobacillus delbrueckii represents a technologically relevant member of lactic acid bacteria, since the two subspecies bulgaricus and lactis are widely associated with fermented dairy products. In the present work, we report the characterization of two commercial strains belonging to L. delbrueckii subspecies bulgaricus , lactis and a novel strain previously isolated from a traditional fermented fresh cheese. A phenomic approach was performed by combining metabolomic and proteomic analysis of the three strains, which were subsequently supplemented as food source to the model organism Caenorhabditis elegans , with the final aim to evaluate their possible probiotic effects. Restriction analysis of 16S ribosomal DNA revealed that the novel foodborne strain belonged to L. delbrueckii subspecies lactis . Proteomic and metabolomic approaches showed differences in folate, aminoacid and sugar metabolic pathways among the three strains. Moreover, evaluation of C. elegans lifespan, larval development, brood size, and bacterial colonization capacity demonstrated that L. delbrueckii subsp. bulgaricus diet exerted beneficial effects on nematodes. On the other hand, both L. delbrueckii subsp. lactis strains affected lifespan and larval development. We have characterized three strains belonging to L. delbrueckii subspecies bulgaricus and lactis highlighting their divergent origin. In particular, the two closely related isolates L. delbrueckii subspecies lactis display different galactose metabolic capabilities. Moreover, the L. delbrueckii subspecies bulgaricus strain demonstrated potential probiotic features. Combination of omic platforms coupled with in vivo screening in the simple model organism C. elegans is a powerful tool to characterize industrially relevant bacterial isolates.

Surplus thermal energy model of greenhouses and coefficient analysis for effective utilization

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Seung-Hwan Yang

2016-03-01

Full Text Available If a greenhouse in the temperate and subtropical regions is maintained in a closed condition, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This study considered this excess energy as surplus thermal energy (STE, which can be recovered, stored and used when heating is necessary. To use the STE economically and effectively, the amount of STE must be estimated before designing a utilization system. Therefore, this study proposed an STE model using energy balance equations for the three steps of the STE generation process. The coefficients in the model were determined by the results of previous research and experiments using the test greenhouse. The proposed STE model produced monthly errors of 17.9%, 10.4% and 7.4% for December, January and February, respectively. Furthermore, the effects of the coefficients on the model accuracy were revealed by the estimation error assessment and linear regression analysis through fixing dynamic coefficients. A sensitivity analysis of the model coefficients indicated that the coefficients have to be determined carefully. This study also provides effective ways to increase the amount of STE.

Surplus thermal energy model of greenhouses and coefficient analysis for effective utilization

Energy Technology Data Exchange (ETDEWEB)

Yang, S.H.; Son, J.E.; Lee, S.D.; Cho, S.I.; Ashtiani-Araghi, A.; Rhee, J.Y.

2016-11-01

If a greenhouse in the temperate and subtropical regions is maintained in a closed condition, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This study considered this excess energy as surplus thermal energy (STE), which can be recovered, stored and used when heating is necessary. To use the STE economically and effectively, the amount of STE must be estimated before designing a utilization system. Therefore, this study proposed an STE model using energy balance equations for the three steps of the STE generation process. The coefficients in the model were determined by the results of previous research and experiments using the test greenhouse. The proposed STE model produced monthly errors of 17.9%, 10.4% and 7.4% for December, January and February, respectively. Furthermore, the effects of the coefficients on the model accuracy were revealed by the estimation error assessment and linear regression analysis through fixing dynamic coefficients. A sensitivity analysis of the model coefficients indicated that the coefficients have to be determined carefully. This study also provides effective ways to increase the amount of STE. (Author)

Sensitive analysis and modifications to reflood-related constitutive models of RELAP5

International Nuclear Information System (INIS)

Li Dong; Liu Xiaojing; Yang Yanhua

2014-01-01

Previous system code calculation reveals that the cladding temperature is underestimated and quench front appears too early during reflood process. To find out the parameters shows important effect on the results, sensitive analysis is performed on parameters of constitutive physical models. Based on the phenomenological and theoretical analysis, four parameters are selected: wall to vapor film boiling heat transfer coefficient, wall to liquid film boiling heat transfer coefficient, dry wall interfacial friction coefficient and minimum droplet diameter. In order to improve the reflood simulation ability of RELAP5 code, the film boiling heat transfer model and dry wall interfacial friction model which are corresponding models of those influential parameters are studied. Modifications have been made and installed into RELAP5 code. Six tests of FEBA are simulated by RELAP5 to study the predictability of reflood-related physical models. A dispersed flow film boiling heat transfer (DFFB) model is applied when void fraction is above 0.9. And a factor is multiplied to the post-CHF drag coefficient to fit the experiment better. Finally, the six FEBA tests are calculated again so as to assess the modifications. Better results are obtained which prove the advantage of the modified models. (author)

Integrative analysis and expression profiling of secondary cell wall genes in C4 biofuel model Setaria italica reveals targets for lignocellulose bioengineering

Directory of Open Access Journals (Sweden)

Mehanathan eMuthamilarasan

2015-11-01

Full Text Available Several underutilized grasses have excellent potential for use as bioenergy feedstock due to their lignocellulosic biomass. Genomic tools have enabled identification of lignocellulose biosynthesis genes in several sequenced plants. However, the non-availability of whole genome sequence of bioenergy grasses hinders the study on bioenergy genomics and their genomics-assisted crop improvement. Foxtail millet (Setaria italica L.; Si is a model crop for studying systems biology of bioenergy grasses. In the present study, a systematic approach has been used for identification of gene families involved in cellulose (CesA/Csl, callose (Gsl and monolignol biosynthesis (PAL, C4H, 4CL, HCT, C3H, CCoAOMT, F5H, COMT, CCR, CAD and construction of physical map of foxtail millet. Sequence alignment and phylogenetic analysis of identified proteins showed that monolignol biosynthesis proteins were highly diverse, whereas CesA/Csl and Gsl proteins were homologous to rice and Arabidopsis. Comparative mapping of foxtail millet lignocellulose biosynthesis genes with other C4 panicoid genomes revealed maximum homology with switchgrass, followed by sorghum and maize. Expression profiling of candidate lignocellulose genes in response to different abiotic stresses and hormone treatments showed their differential expression pattern, with significant higher expression of SiGsl12, SiPAL2, SiHCT1, SiF5H2 and SiCAD6 genes. Further, due to the evolutionary conservation of grass genomes, the insights gained from the present study could be extrapolated for identifying genes involved in lignocellulose biosynthesis in other biofuel species for further characterization.

Integrative analysis and expression profiling of secondary cell wall genes in C4 biofuel model Setaria italica reveals targets for lignocellulose bioengineering.

Science.gov (United States)

Muthamilarasan, Mehanathan; Khan, Yusuf; Jaishankar, Jananee; Shweta, Shweta; Lata, Charu; Prasad, Manoj

2015-01-01

Several underutilized grasses have excellent potential for use as bioenergy feedstock due to their lignocellulosic biomass. Genomic tools have enabled identification of lignocellulose biosynthesis genes in several sequenced plants. However, the non-availability of whole genome sequence of bioenergy grasses hinders the study on bioenergy genomics and their genomics-assisted crop improvement. Foxtail millet (Setaria italica L.; Si) is a model crop for studying systems biology of bioenergy grasses. In the present study, a systematic approach has been used for identification of gene families involved in cellulose (CesA/Csl), callose (Gsl) and monolignol biosynthesis (PAL, C4H, 4CL, HCT, C3H, CCoAOMT, F5H, COMT, CCR, CAD) and construction of physical map of foxtail millet. Sequence alignment and phylogenetic analysis of identified proteins showed that monolignol biosynthesis proteins were highly diverse, whereas CesA/Csl and Gsl proteins were homologous to rice and Arabidopsis. Comparative mapping of foxtail millet lignocellulose biosynthesis genes with other C4 panicoid genomes revealed maximum homology with switchgrass, followed by sorghum and maize. Expression profiling of candidate lignocellulose genes in response to different abiotic stresses and hormone treatments showed their differential expression pattern, with significant higher expression of SiGsl12, SiPAL2, SiHCT1, SiF5H2, and SiCAD6 genes. Further, due to the evolutionary conservation of grass genomes, the insights gained from the present study could be extrapolated for identifying genes involved in lignocellulose biosynthesis in other biofuel species for further characterization.

An Improved Rigid Multibody Model for the Dynamic Analysis of the Planetary Gearbox in a Wind Turbine

Directory of Open Access Journals (Sweden)

Wenguang Yang

2016-01-01

Full Text Available This paper proposes an improved rigid multibody model for the dynamic analysis of the planetary gearbox in a wind turbine. The improvements mainly include choosing the inertia frame as the reference frame of the carrier, the ring, and the sun and adding a new degree of freedom for each planet. An element assembly method is introduced to build the model, and a time-varying mesh stiffness model is presented. A planetary gear study case is employed to verify the validity of the improved model. Comparisons between the improvement model and the traditional model show that the natural characteristics are very close; the improved model can obtain the right equivalent moment of inertia of the planetary gear in the transient simulation, and all the rotation speeds satisfy the transmission relationships well; harmonic resonance and resonance modulation phenomena can be found in their vibration signals. The improved model is applied in a multistage gearbox dynamics analysis to reveal the prospects of the model. Modal analysis and transient analysis with and without time-varying mesh stiffness considered are conducted. The rotation speeds from the transient analysis are consistent with the theory, and resonance modulation can be found in the vibration signals.

Supercomputer and cluster performance modeling and analysis efforts:2004-2006.

Energy Technology Data Exchange (ETDEWEB)

Sturtevant, Judith E.; Ganti, Anand; Meyer, Harold (Hal) Edward; Stevenson, Joel O.; Benner, Robert E., Jr. (.,; .); Goudy, Susan Phelps; Doerfler, Douglas W.; Domino, Stefan Paul; Taylor, Mark A.; Malins, Robert Joseph; Scott, Ryan T.; Barnette, Daniel Wayne; Rajan, Mahesh; Ang, James Alfred; Black, Amalia Rebecca; Laub, Thomas William; Vaughan, Courtenay Thomas; Franke, Brian Claude

2007-02-01

This report describes efforts by the Performance Modeling and Analysis Team to investigate performance characteristics of Sandia's engineering and scientific applications on the ASC capability and advanced architecture supercomputers, and Sandia's capacity Linux clusters. Efforts to model various aspects of these computers are also discussed. The goals of these efforts are to quantify and compare Sandia's supercomputer and cluster performance characteristics; to reveal strengths and weaknesses in such systems; and to predict performance characteristics of, and provide guidelines for, future acquisitions and follow-on systems. Described herein are the results obtained from running benchmarks and applications to extract performance characteristics and comparisons, as well as modeling efforts, obtained during the time period 2004-2006. The format of the report, with hypertext links to numerous additional documents, purposefully minimizes the document size needed to disseminate the extensive results from our research.

Application of REVEAL-W to risk-based configuration control

International Nuclear Information System (INIS)

Dezfuli, H.; Meyer, J.; Modarres, M.

1994-01-01

Over the past two years, the concept of risk-based configuration control has been introduced to the US Nuclear Regulatory Commission and the nuclear industry. Converting much of the current, deterministically based regulation of nuclear power plants to risk-based regulation can result in lower levels of risk while relieving unnecessary burdens on power plant operators and regulatory staff. To achieve the potential benefits of risk-based configuration control, the risk models developed for nuclear power plants should be (1) flexible enough to effectively support necessary risk calculations, and (2) transparent enough to encourage their use by all parties. To address these needs, SCIENTECH, Inc., has developed the PC-based REVEAL W (formerly known as SMART). This graphic-oriented and user-friendly application software allows the user to develop transparent complex logic models based on the concept of the master plant logic diagram. The logic model is success-oriented and compact. The analytical capability built into REVEAL W is generic, so the software can support different types of risk-based evaluations, such as probabilistic safety assessment, accident sequence precursor analysis, design evaluation and configuration management. In this paper, we focus on the application of REVEAL W to support risk-based configuration control of nuclear power plants. (author)

Analysis of lithium deinsertion/insertion in Li{sub y}FePO{sub 4} with a simple mathematical model

Energy Technology Data Exchange (ETDEWEB)

Delacourt, C., E-mail: charles.delacourt@u-picardie.fr [Laboratoire de Reactivite et de Chimie des Solides, CNRS UMR 6007, Universite de Picardie Jules Verne (France); Safari, M. [Laboratoire de Reactivite et de Chimie des Solides, CNRS UMR 6007, Universite de Picardie Jules Verne (France)

2011-05-30

Highlights: > An analysis of the onsets of charge/discharge curves of Li{sub y}FePO{sub 4} is performed by means of a mathematical model. > It reveals a dependence of the apparent 'particle radius' on the current density. > The mosaic model, introduced some years ago for lithium insertion/deinsertion in Li{sub y}FePO{sub 4}, is invoked to account for this unusual dependence. - Abstract: The onset of experimental galvanostatic charge/discharge data of Li{sub y}FePO{sub 4} at low current density and at room temperature is analyzed using a single-particle mathematical model. The model contains only two adjustable parameters, namely one related to solid-state diffusion in the active particle and another one related to the surface resistance of the particle. The analysis reveals that these two parameters depend on the current density in a similar manner, meaning that there exists a correlation between them. An immediate consequence is that the onset of the experimental charge/discharge curves is properly modeled with the particle radius as a unique parameter depending on the current density. Hypotheses are made to shed light on this unusual dependence.

Causal Models for Mediation Analysis: An Introduction to Structural Mean Models.

Science.gov (United States)

Zheng, Cheng; Atkins, David C; Zhou, Xiao-Hua; Rhew, Isaac C

2015-01-01

Mediation analyses are critical to understanding why behavioral interventions work. To yield a causal interpretation, common mediation approaches must make an assumption of "sequential ignorability." The current article describes an alternative approach to causal mediation called structural mean models (SMMs). A specific SMM called a rank-preserving model (RPM) is introduced in the context of an applied example. Particular attention is given to the assumptions of both approaches to mediation. Applying both mediation approaches to the college student drinking data yield notable differences in the magnitude of effects. Simulated examples reveal instances in which the traditional approach can yield strongly biased results, whereas the RPM approach remains unbiased in these cases. At the same time, the RPM approach has its own assumptions that must be met for correct inference, such as the existence of a covariate that strongly moderates the effect of the intervention on the mediator and no unmeasured confounders that also serve as a moderator of the effect of the intervention or the mediator on the outcome. The RPM approach to mediation offers an alternative way to perform mediation analysis when there may be unmeasured confounders.

Mitochondrial dysfunction, oxidative stress and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson’s disease

Energy Technology Data Exchange (ETDEWEB)

Chin, Mark H.; Qian, Weijun; Wang, Haixing; Petyuk, Vladislav A.; Bloom, Joshua S.; Sforza, Daniel M.; Lacan, Goran; Liu, Dahai; Khan, Arshad H.; Cantor, Rita M.; Bigelow, Diana J.; Melega, William P.; Camp, David G.; Smith, Richard D.; Smith, Desmond J.

2008-02-10

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson disease (PD) are not completely understood. Here we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 85 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response and apoptosis. Additionally, codon usage and miRNAs may play an important role in translational control in the striatum. These results constitute one of the largest datasets integrating protein and transcript changes for these neurotoxin models with many similar endpoint phenotypes but distinct mechanisms.

Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

International Nuclear Information System (INIS)

Jacobs, William R; Dodd, Tony J; Anderson, Sean R; Wilson, Emma D; Porrill, John; Assaf, Tareq; Rossiter, Jonathan

2015-01-01

Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input–output data (voltage-displacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input structure. Frequency response analysis of the DEA dynamics was performed using generalized frequency response functions, providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics. (paper)

Reliability analysis and prediction of mixed mode load using Markov Chain Model

International Nuclear Information System (INIS)

Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

2014-01-01

The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle.

Science.gov (United States)

Mateescu, Raluca G; Garrick, Dorian J; Reecy, James M

2017-01-01

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms

Empirical study of travel mode forecasting improvement for the combined revealed preference/stated preference data–based discrete choice model

Directory of Open Access Journals (Sweden)

Yanfu Qiao

2016-01-01

Full Text Available The combined revealed preference/stated preference data–based discrete choice model has provided the actual choice-making restraints as well as reduced the prediction errors. But the random error variance of alternatives belonging to different data would impact its universality. In this article, we studied the traffic corridor between Chengdu and Longquan with the revealed preference/stated preference joint model, and the single stated preference data model separately predicted the choice probability of each mode. We found the revealed preference/stated preference joint model is universal only when there is a significant difference between the random error terms in different data. The single stated preference data would amplify the travelers’ preference and cause prediction error. We proposed a universal way that uses revealed preference data to modify the single stated preference data parameter estimation results to achieve the composite utility and reduce the prediction error. And the result suggests that prediction results are more reasonable based on the composite utility than the results based on the single stated preference data, especially forecasting the mode share of bus. The future metro line will be the main travel mode in this corridor, and 45% of passenger flow will transfer to the metro.

Survival analysis models and applications

CERN Document Server

Liu, Xian

2012-01-01

Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

Financial analysis and forecasting of the results of small businesses performance based on regression model

Directory of Open Access Journals (Sweden)

Svetlana O. Musienko

2017-03-01

Full Text Available Objective to develop the economicmathematical model of the dependence of revenue on other balance sheet items taking into account the sectoral affiliation of the companies. Methods using comparative analysis the article studies the existing approaches to the construction of the company management models. Applying the regression analysis and the least squares method which is widely used for financial management of enterprises in Russia and abroad the author builds a model of the dependence of revenue on other balance sheet items taking into account the sectoral affiliation of the companies which can be used in the financial analysis and prediction of small enterprisesrsquo performance. Results the article states the need to identify factors affecting the financial management efficiency. The author analyzed scientific research and revealed the lack of comprehensive studies on the methodology for assessing the small enterprisesrsquo management while the methods used for large companies are not always suitable for the task. The systematized approaches of various authors to the formation of regression models describe the influence of certain factors on the company activity. It is revealed that the resulting indicators in the studies were revenue profit or the company relative profitability. The main drawback of most models is the mathematical not economic approach to the definition of the dependent and independent variables. Basing on the analysis it was determined that the most correct is the model of dependence between revenues and total assets of the company using the decimal logarithm. The model was built using data on the activities of the 507 small businesses operating in three spheres of economic activity. Using the presented model it was proved that there is direct dependence between the sales proceeds and the main items of the asset balance as well as differences in the degree of this effect depending on the economic activity of small

iTRAQ-based proteomic analysis reveals alterations in the liver induced by restricted meal frequency in a pig model.

Science.gov (United States)

Liu, Jingbo; Liu, Zhengqun; Chen, Liang; Zhang, Hongfu

2016-01-01

The present study was conducted to investigate the effects of meal frequency on metabolite levels in pig plasma and hepatic proteome by isobaric tags for relative and absolute quantitation (iTRAQ) analysis. Twenty-four pigs (60.7 ± 1.0 kg) consumed the same amount of feed either in 2 (M2, n = 12) or 12 (M12, n = 12) meals per day. After an 8-wk feeding period, plasma concentrations of metabolites and hormones, hepatic biochemical traits, and proteome (n = 4 per group) were measured. Pigs on the M12 regimen had lower average daily gain and gain-to-feed ratio than pigs fed the M2 regimen. The M2 regimen resulted in lower total lipid, glycogen, and triacylglycerol content in the liver and circulating triacylglycerol concentration than that in the M12 pigs. The metabolic hormone concentrations were not affected by meal frequency, with the exception of elevated fibroblast growth factor 21 concentrations in the M2 regimen compared with the M12 regimen. The iTRAQ-based proteomic analysis revealed 35 differentially expressed proteins in the liver between pigs fed two and 12 meals per day, and these differentially expressed proteins were involved in the regulation of general biological process such as glucose and energy metabolism, lipid metabolism, protein and amino acid metabolism, stress response, and cell redox homeostasis. Altogether, the proteomic results provide insights into the mechanism mediating the beneficial effects of restricted meal frequency on the metabolic fitness. Copyright © 2016 Elsevier Inc. All rights reserved.

Multilocus Sequence Analysis of Nectar Pseudomonads Reveals High Genetic Diversity and Contrasting Recombination Patterns

Science.gov (United States)

Álvarez-Pérez, Sergio; de Vega, Clara; Herrera, Carlos M.

2013-01-01

The genetic and evolutionary relationships among floral nectar-dwelling Pseudomonas ‘sensu stricto’ isolates associated to South African and Mediterranean plants were investigated by multilocus sequence analysis (MLSA) of four core housekeeping genes (rrs, gyrB, rpoB and rpoD). A total of 35 different sequence types were found for the 38 nectar bacterial isolates characterised. Phylogenetic analyses resulted in the identification of three main clades [nectar groups (NGs) 1, 2 and 3] of nectar pseudomonads, which were closely related to five intrageneric groups: Pseudomonas oryzihabitans (NG 1); P. fluorescens, P. lutea and P. syringae (NG 2); and P. rhizosphaerae (NG 3). Linkage disequilibrium analysis pointed to a mostly clonal population structure, even when the analysis was restricted to isolates from the same floristic region or belonging to the same NG. Nevertheless, signatures of recombination were observed for NG 3, which exclusively included isolates retrieved from the floral nectar of insect-pollinated Mediterranean plants. In contrast, the other two NGs comprised both South African and Mediterranean isolates. Analyses relating diversification to floristic region and pollinator type revealed that there has been more unique evolution of the nectar pseudomonads within the Mediterranean region than would be expected by chance. This is the first work analysing the sequence of multiple loci to reveal geno- and ecotypes of nectar bacteria. PMID:24116076

Multilocus sequence analysis of nectar pseudomonads reveals high genetic diversity and contrasting recombination patterns.

Science.gov (United States)

Alvarez-Pérez, Sergio; de Vega, Clara; Herrera, Carlos M

2013-01-01

The genetic and evolutionary relationships among floral nectar-dwelling Pseudomonas 'sensu stricto' isolates associated to South African and Mediterranean plants were investigated by multilocus sequence analysis (MLSA) of four core housekeeping genes (rrs, gyrB, rpoB and rpoD). A total of 35 different sequence types were found for the 38 nectar bacterial isolates characterised. Phylogenetic analyses resulted in the identification of three main clades [nectar groups (NGs) 1, 2 and 3] of nectar pseudomonads, which were closely related to five intrageneric groups: Pseudomonas oryzihabitans (NG 1); P. fluorescens, P. lutea and P. syringae (NG 2); and P. rhizosphaerae (NG 3). Linkage disequilibrium analysis pointed to a mostly clonal population structure, even when the analysis was restricted to isolates from the same floristic region or belonging to the same NG. Nevertheless, signatures of recombination were observed for NG 3, which exclusively included isolates retrieved from the floral nectar of insect-pollinated Mediterranean plants. In contrast, the other two NGs comprised both South African and Mediterranean isolates. Analyses relating diversification to floristic region and pollinator type revealed that there has been more unique evolution of the nectar pseudomonads within the Mediterranean region than would be expected by chance. This is the first work analysing the sequence of multiple loci to reveal geno- and ecotypes of nectar bacteria.

Stability Analysis of a Reaction-Diffusion System Modeling Atherogenesis

KAUST Repository

Ibragimov, Akif

2010-01-01

This paper presents a linear, asymptotic stability analysis for a reaction-diffusionconvection system modeling atherogenesis, the initiation of atherosclerosis, as an inflammatory instability. Motivated by the disease paradigm articulated by Ross, atherogenesis is viewed as an inflammatory spiral with a positive feedback loop involving key cellular and chemical species interacting and reacting within the intimal layer of muscular arteries. The inflammatory spiral is initiated as an instability from a healthy state which is defined to be an equilibrium state devoid of certain key inflammatory markers. Disease initiation is studied through a linear, asymptotic stability analysis of a healthy equilibrium state. Various theorems are proved, giving conditions on system parameters guaranteeing stability of the health state, and a general framework is developed for constructing perturbations from a healthy state that exhibit blow-up, which are interpreted as corresponding to disease initiation. The analysis reveals key features that arterial geometry, antioxidant levels, and the source of inflammatory components (through coupled third-kind boundary conditions or through body sources) play in disease initiation. © 2010 Society for Industrial and Applied Mathematics.

Dynamic gene expression analysis in a H1N1 influenza virus mouse pneumonia model.

Science.gov (United States)

Bao, Yanyan; Gao, Yingjie; Shi, Yujing; Cui, Xiaolan

2017-06-01

H1N1, a major pathogenic subtype of influenza A virus, causes a respiratory infection in humans and livestock that can range from a mild infection to more severe pneumonia associated with acute respiratory distress syndrome. Understanding the dynamic changes in the genome and the related functional changes induced by H1N1 influenza virus infection is essential to elucidating the pathogenesis of this virus and thereby determining strategies to prevent future outbreaks. In this study, we filtered the significantly expressed genes in mouse pneumonia using mRNA microarray analysis. Using STC analysis, seven significant gene clusters were revealed, and using STC-GO analysis, we explored the significant functions of these seven gene clusters. The results revealed GOs related to H1N1 virus-induced inflammatory and immune functions, including innate immune response, inflammatory response, specific immune response, and cellular response to interferon-beta. Furthermore, the dynamic regulation relationships of the key genes in mouse pneumonia were revealed by dynamic gene network analysis, and the most important genes were filtered, including Dhx58, Cxcl10, Cxcl11, Zbp1, Ifit1, Ifih1, Trim25, Mx2, Oas2, Cd274, Irgm1, and Irf7. These results suggested that during mouse pneumonia, changes in the expression of gene clusters and the complex interactions among genes lead to significant changes in function. Dynamic gene expression analysis revealed key genes that performed important functions. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology, as well as the use of mice as a model organism for human H1N1 influenza virus infection studies.

Modelling wedding marketing strategies: An fsQCA Analysis

Directory of Open Access Journals (Sweden)

Anestis Fotiadis

2018-05-01

Full Text Available Aim of the study is to develop a model delineating customer perceptions on wedding marketing strategies in Kaohsiung, Taiwan. Main objective of this paper is to analyse a category of special events: the wedding market sector in Kaohsiung, Taiwan by examining how they attract consumers regarding their marketing strategies using the method of fuzzy-set Qualitative Comparative Analysis (fsQCA. Based on a survey to married, in relationship and singles local citizens of Taiwan the relationships between impressions, importance, push factors with decision making was explored. To test the hypotheses of the proposed model a primary research study was conducted employing a mall intercept technique via distribution of a self-administered questionnaire within a cross sectional on-site field research context. A fsQCA modelling approach technique was employed in order to measure, estimate and confirm the different casual paths constructs, as well as to test the significance of the paths between different segments of the wedding industry. Our findings reveal that the presence of importance, push factors and decision making determines the level of consumer perception performance. However, impressions do not show significant impact on consumer perceptions.

Multiscale Signal Analysis and Modeling

CERN Document Server

Zayed, Ahmed

2013-01-01

Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

Stability and Bifurcation Analysis of a Three-Species Food Chain Model with Fear

Science.gov (United States)

Panday, Pijush; Pal, Nikhil; Samanta, Sudip; Chattopadhyay, Joydev

In the present paper, we investigate the impact of fear in a tri-trophic food chain model. We propose a three-species food chain model, where the growth rate of middle predator is reduced due to the cost of fear of top predator, and the growth rate of prey is suppressed due to the cost of fear of middle predator. Mathematical properties such as equilibrium analysis, stability analysis, bifurcation analysis and persistence have been investigated. We also describe the global stability analysis of the equilibrium points. Our numerical simulations reveal that cost of fear in basal prey may exhibit bistability by producing unstable limit cycles, however, fear in middle predator can replace unstable limit cycles by a stable limit cycle or a stable interior equilibrium. We observe that fear can stabilize the system from chaos to stable focus through the period-halving phenomenon. We conclude that chaotic dynamics can be controlled by the fear factors. We apply basic tools of nonlinear dynamics such as Poincaré section and maximum Lyapunov exponent to identify the chaotic behavior of the system.

Comparative genome and transcriptome analysis reveals distinctive surface characteristics and unique physiological potentials of Pseudomonas aeruginosa ATCC 27853

KAUST Repository

Cao, Huiluo

2017-06-12

Pseudomonas aeruginosa ATCC 27853 was isolated from a hospital blood specimen in 1971 and has been widely used as a model strain to survey antibiotics susceptibilities, biofilm development, and metabolic activities of Pseudomonas spp.. Although four draft genomes of P. aeruginosa ATCC 27853 have been sequenced, the complete genome of this strain is still lacking, hindering a comprehensive understanding of its physiology and functional genome.Here we sequenced and assembled the complete genome of P. aeruginosa ATCC 27853 using the Pacific Biosciences SMRT (PacBio) technology and Illumina sequencing platform. We found that accessory genes of ATCC 27853 including prophages and genomic islands (GIs) mainly contribute to the difference between P. aeruginosa ATCC 27853 and other P. aeruginosa strains. Seven prophages were identified within the genome of P. aeruginosa ATCC 27853. Of the predicted 25 GIs, three contain genes that encode monoxoygenases, dioxygenases and hydrolases that could be involved in the metabolism of aromatic compounds. Surveying virulence-related genes revealed that a series of genes that encode the B-band O-antigen of LPS are lacking in ATCC 27853. Distinctive SNPs in genes of cellular adhesion proteins such as type IV pili and flagella biosynthesis were also observed in this strain. Colony morphology analysis confirmed an enhanced biofilm formation capability of ATCC 27853 on solid agar surface compared to Pseudomonas aeruginosa PAO1. We then performed transcriptome analysis of ATCC 27853 and PAO1 using RNA-seq and compared the expression of orthologous genes to understand the functional genome and the genomic details underlying the distinctive colony morphogenesis. These analyses revealed an increased expression of genes involved in cellular adhesion and biofilm maturation such as type IV pili, exopolysaccharide and electron transport chain components in ATCC 27853 compared with PAO1. In addition, distinctive expression profiles of the

Biophysical analysis of HTLV-1 particles reveals novel insights into particle morphology and Gag stochiometry

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Fogarty Keir H

2010-09-01

Full Text Available Abstract Background Human T-lymphotropic virus type 1 (HTLV-1 is an important human retrovirus that is a cause of adult T-cell leukemia/lymphoma. While an important human pathogen, the details regarding virus replication cycle, including the nature of HTLV-1 particles, remain largely unknown due to the difficulties in propagating the virus in tissue culture. In this study, we created a codon-optimized HTLV-1 Gag fused to an EYFP reporter as a model system to quantitatively analyze HTLV-1 particles released from producer cells. Results The codon-optimized Gag led to a dramatic and highly robust level of Gag expression as well as virus-like particle (VLP production. The robust level of particle production overcomes previous technical difficulties with authentic particles and allowed for detailed analysis of particle architecture using two novel methodologies. We quantitatively measured the diameter and morphology of HTLV-1 VLPs in their native, hydrated state using cryo-transmission electron microscopy (cryo-TEM. Furthermore, we were able to determine HTLV-1 Gag stoichiometry as well as particle size with the novel biophysical technique of fluorescence fluctuation spectroscopy (FFS. The average HTLV-1 particle diameter determined by cryo-TEM and FFS was 71 ± 20 nm and 75 ± 4 nm, respectively. These values are significantly smaller than previous estimates made of HTLV-1 particles by negative staining TEM. Furthermore, cryo-TEM reveals that the majority of HTLV-1 VLPs lacks an ordered structure of the Gag lattice, suggesting that the HTLV-1 Gag shell is very likely to be organized differently compared to that observed with HIV-1 Gag in immature particles. This conclusion is supported by our observation that the average copy number of HTLV-1 Gag per particle is estimated to be 510 based on FFS, which is significantly lower than that found for HIV-1 immature virions. Conclusions In summary, our studies represent the first quantitative biophysical

COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS

Directory of Open Access Journals (Sweden)

Marijana Zekić-Sušac

2013-02-01

Full Text Available Despite increased interest in the entrepreneurial intentions and career choices of young adults, reliable prediction models are yet to be developed. Two nonparametric methods were used in this paper to model entrepreneurial intentions: principal component analysis (PCA and artificial neural networks (ANNs. PCA was used to perform feature extraction in the first stage of modelling, while artificial neural networks were used to classify students according to their entrepreneurial intentions in the second stage. Four modelling strategies were tested in order to find the most efficient model. Dataset was collected in an international survey on entrepreneurship self-efficacy and identity. Variables describe students’ demographics, education, attitudes, social and cultural norms, self-efficacy and other characteristics. The research reveals benefits from the combination of the PCA and ANNs in modeling entrepreneurial intentions, and provides some ideas for further research.

An integrated factor analysis model for product eco-design based on full life cycle assessment

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z.; Xiao, T.; Li, D.

2016-07-01

Among the methods of comprehensive analysis for a product or an enterprise, there exist defects and deficiencies in traditional standard cost analyses and life cycle assessment methods. For example, some methods only emphasize one dimension (such as economic or environmental factors) while neglecting other relevant dimensions. This paper builds a factor analysis model of resource value flow, based on full life cycle assessment and eco-design theory, in order to expose the relevant internal logic between these two factors. The model considers the efficient multiplication of resources, economic efficiency, and environmental efficiency as its core objectives. The model studies the status of resource value flow during the entire life cycle of a product, and gives an in-depth analysis on the mutual logical relationship of product performance, value, resource consumption, and environmental load to reveal the symptoms and potentials in different dimensions. This provides comprehensive, accurate and timely decision-making information for enterprise managers regarding product eco-design, as well as production and management activities. To conclude, it verifies the availability of this evaluation and analysis model using a Chinese SUV manufacturer as an example. (Author)

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

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Alberto Muñoz

2016-10-01

Full Text Available Ecological Niche Models (ENMs are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models. Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species and taxonomy (amphibians and reptiles. Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

Science.gov (United States)

Santos, Xavier; Felicísimo, Ángel M.

2016-01-01

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks. PMID

A whole-body model for glycogen regulation reveals a critical role for substrate cycling in maintaining blood glucose homeostasis.

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Ke Xu

2011-12-01

Full Text Available Timely, and sometimes rapid, metabolic adaptation to changes in food supply is critical for survival as an organism moves from the fasted to the fed state, and vice versa. These transitions necessitate major metabolic changes to maintain energy homeostasis as the source of blood glucose moves away from ingested carbohydrates, through hepatic glycogen stores, towards gluconeogenesis. The integration of hepatic glycogen regulation with extra-hepatic energetics is a key aspect of these adaptive mechanisms. Here we use computational modeling to explore hepatic glycogen regulation under fed and fasting conditions in the context of a whole-body model. The model was validated against previous experimental results concerning glycogen phosphorylase a (active and glycogen synthase a dynamics. The model qualitatively reproduced physiological changes that occur during transition from the fed to the fasted state. Analysis of the model reveals a critical role for the inhibition of glycogen synthase phosphatase by glycogen phosphorylase a. This negative regulation leads to high levels of glycogen synthase activity during fasting conditions, which in turn increases substrate (futile cycling, priming the system for a rapid response once an external source of glucose is restored. This work demonstrates that a mechanistic understanding of the design principles used by metabolic control circuits to maintain homeostasis can benefit from the incorporation of mathematical descriptions of these networks into "whole-body" contextual models that mimic in vivo conditions.

Diverse binding site structures revealed in homology models of polyreactive immunoglobulins

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Ramsland, Paul A.; Guddat, Luke W.; Edmundson, Allen B.; Raison, Robert L.

1997-09-01

We describe here computer-assisted homology models of the combiningsite structure of three polyreactive immunoglobulins. Template-based modelsof Fv (VL-VH) fragments were derived forthe surface IgM expressed by the malignant CD5 positive B cells from threepatients with chronic lymphocytic leukaemia (CLL). The conserved frameworkregions were constructed using crystal coordinates taken from highlyhomologous human variable domain structures (Pot and Hil). Complementaritydetermining regions (CDRs) were predicted by grafting loops, taken fromknown immunoglobulin structures, onto the Fv framework models. The CDRtemplates were chosen, where possible, to be of the same length and of highresidue identity or similarity. LCDR1, 2 and 3 as well as HCDR1 and 2 forthe Fv were constructed using this strategy. For HCDR3 prediction, adatabase containing the Cartesian coordinates of 30 of these loops wascompiled from unliganded antibody X-ray crystallographic structures and anHCDR3 of the same length as that of the B CLL Fv was selected as a template.In one case (Yar), the resulting HCDR3 model gave unfavourable interactionswhen incorporated into the Fv model. This HCDR3 was therefore modelled usingan alternative strategy of construction of the loop stems, using apreviously described HCDR3 conformation (Pot), followed by chain closurewith a β-turn. The template models were subjected to positionalrefinement using energy minimisation and molecular dynamics simulations(X-PLOR). An electrostatic surface description (GRASP) did not reveal acommon structural feature within the binding sites of the three polyreactiveFv. Thus, polyreactive immunoglobulins may recognise similar and multipleantigens through a diverse array of binding site structures.

Active nuclear transcriptome analysis reveals inflammasome-dependent mechanism for early neutrophil response to Mycobacterium marinum.

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Kenyon, Amy; Gavriouchkina, Daria; Zorman, Jernej; Napolitani, Giorgio; Cerundolo, Vincenzo; Sauka-Spengler, Tatjana

2017-07-26

The mechanisms governing neutrophil response to Mycobacterium tuberculosis remain poorly understood. In this study we utilise biotagging, a novel genome-wide profiling approach based on cell type-specific in vivo biotinylation in zebrafish to analyse the initial response of neutrophils to Mycobacterium marinum, a close genetic relative of M. tuberculosis used to model tuberculosis. Differential expression analysis following nuclear RNA-seq of neutrophil active transcriptomes reveals a significant upregulation in both damage-sensing and effector components of the inflammasome, including caspase b, NLRC3 ortholog (wu: fb15h11) and il1β. Crispr/Cas9-mediated knockout of caspase b, which acts by proteolytic processing of il1β, results in increased bacterial burden and less infiltration of macrophages to sites of mycobacterial infection, thus impairing granuloma development. We also show that a number of immediate early response genes (IEGs) are responsible for orchestrating the initial neutrophil response to mycobacterial infection. Further perturbation of the IEGs exposes egr3 as a key transcriptional regulator controlling il1β transcription.

Theoretical Models of Deliberative Democracy: A Critical Analysis

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Tutui Viorel

2015-07-01

Full Text Available Abstract: My paper focuses on presenting and analyzing some of the most important theoretical models of deliberative democracy and to emphasize their limits. Firstly, I will mention James Fishkin‟s account of deliberative democracy and its relations with other democratic models. He differentiates between four democratic theories: competitive democracy, elite deliberation, participatory democracy and deliberative democracy. Each of these theories makes an explicit commitment to two of the following four “principles”: political equality, participation, deliberation, nontyranny. Deliberative democracy is committed to political equality and deliberation. Secondly, I will present Philip Pettit‟s view concerning the main constraints of deliberative democracy: the inclusion constraint, the judgmental constraint and the dialogical constraint. Thirdly, I will refer to Amy Gutmann and Dennis Thompson‟s conception regarding the “requirements” or characteristics of deliberative democracy: the reason-giving requirement, the accessibility of reasons, the binding character of the decisions and the dynamic nature of the deliberative process. Finally, I will discuss Joshua Cohen‟s “ideal deliberative procedure” which has the following features: it is free, reasoned, the parties are substantively equal and the procedure aims to arrive at rationally motivated consensus. After presenting these models I will provide a critical analysis of each one of them with the purpose of revealing their virtues and limits. I will make some suggestions in order to combine the virtues of these models, to transcend their limitations and to offer a more systematical account of deliberative democracy. In the next four sections I will take into consideration four main strategies for combining political and epistemic values (“optimistic”, “deliberative”, “democratic” and “pragmatic” and the main objections they have to face. In the concluding section

fMRI Analysis-by-Synthesis Reveals a Dorsal Hierarchy That Extracts Surface Slant.

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Ban, Hiroshi; Welchman, Andrew E

2015-07-08

The brain's skill in estimating the 3-D orientation of viewed surfaces supports a range of behaviors, from placing an object on a nearby table, to planning the best route when hill walking. This ability relies on integrating depth signals across extensive regions of space that exceed the receptive fields of early sensory neurons. Although hierarchical selection and pooling is central to understanding of the ventral visual pathway, the successive operations in the dorsal stream are poorly understood. Here we use computational modeling of human fMRI signals to probe the computations that extract 3-D surface orientation from binocular disparity. To understand how representations evolve across the hierarchy, we developed an inference approach using a series of generative models to explain the empirical fMRI data in different cortical areas. Specifically, we simulated the responses of candidate visual processing algorithms and tested how well they explained fMRI responses. Thereby we demonstrate a hierarchical refinement of visual representations moving from the representation of edges and figure-ground segmentation (V1, V2) to spatially extensive disparity gradients in V3A. We show that responses in V3A are little affected by low-level image covariates, and have a partial tolerance to the overall depth position. Finally, we show that responses in V3A parallel perceptual judgments of slant. This reveals a relatively short computational hierarchy that captures key information about the 3-D structure of nearby surfaces, and more generally demonstrates an analysis approach that may be of merit in a diverse range of brain imaging domains. Copyright © 2015 Ban and Welchman.

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

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Christensen, Julie A E; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R; Jennum, Poul; Sorensen, Helge B D

2014-09-30

Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model. The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients. The topics showed visual accordance with the manually scored sleep stages, and the features revealed sleep characteristics containing information indicative of neurodegeneration. This study suggests that the amount of N3 and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

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Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

2018-06-01

Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

Grainyhead-like 2 (GRHL2) distribution reveals novel pathophysiological differences between human idiopathic pulmonary fibrosis and mouse models of pulmonary fibrosis

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Mahavadi, Poornima; Sasikumar, Satish; Cushing, Leah; Hyland, Tessa; Rosser, Ann E.; Riccardi, Daniela; Lu, Jining; Kalin, Tanya V.; Kalinichenko, Vladimir V.; Guenther, Andreas; Ramirez, Maria I.; Pardo, Annie; Selman, Moisés; Warburton, David

2013-01-01

Chronic injury of alveolar lung epithelium leads to epithelial disintegrity in idiopathic pulmonary fibrosis (IPF). We had reported earlier that Grhl2, a transcriptional factor, maintains alveolar epithelial cell integrity by directly regulating components of adherens and tight junctions and thus hypothesized an important role of GRHL2 in pathogenesis of IPF. Comparison of GRHL2 distribution at different stages of human lung development showed its abundance in developing lung epithelium and in adult lung epithelium. However, GRHL2 is detected in normal human lung mesenchyme only at early fetal stage (week 9). Similar mesenchymal reexpression of GRHL2 was also observed in IPF. Immunofluorescence analysis in serial sections from three IPF patients revealed at least two subsets of alveolar epithelial cells (AEC), based on differential GRHL2 expression and the converse fluorescence intensities for epithelial vs. mesenchymal markers. Grhl2 was not detected in mesenchyme in intraperitoneal bleomycin-induced injury as well as in spontaneously occurring fibrosis in double-mutant HPS1 and HPS2 mice, whereas in contrast in a radiation-induced fibrosis model, with forced Forkhead box M1 (Foxm1) expression, an overlap of Grhl2 with a mesenchymal marker was observed in fibrotic regions. Grhl2's role in alveolar epithelial cell plasticity was confirmed by altered Grhl2 gene expression analysis in IPF and further validated by in vitro manipulation of its expression in alveolar epithelial cell lines. Our findings reveal important pathophysiological differences between human IPF and specific mouse models of fibrosis and support a crucial role of GRHL2 in epithelial activation in lung fibrosis and perhaps also in epithelial plasticity. PMID:24375798

Concept analysis of moral courage in nursing: A hybrid model.

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Sadooghiasl, Afsaneh; Parvizy, Soroor; Ebadi, Abbas

2018-02-01

Moral courage is one of the most fundamental virtues in the nursing profession, however, little attention has been paid to it. As a result, no exact and clear definition of moral courage has ever been accessible. This study is carried out for the purposes of defining and clarifying its concept in the nursing profession. This study used a hybrid model of concept analysis comprising three phases, namely, a theoretical phase, field work phase, and a final analysis phase. To find relevant literature, electronic search of valid databases was utilized using keywords related to the concept of courage. Field work data were collected over an 11 months' time period from 2013 to 2014. In the field work phase, in-depth interviews were performed with 10 nurses. The conventional content analysis was used in two theoretical and field work phases using Graneheim and Lundman stages, and the results were combined in the final analysis phase. Ethical consideration: Permission for this study was obtained from the ethics committee of Tehran University of Medical Sciences. Oral and written informed consent was received from the participants. From the sum of 750 gained titles in theoretical phase, 26 texts were analyzed. The analysis resulted in 494 codes in text analysis and 226 codes in interview analysis. The literature review in the theoretical phase revealed two features of inherent-transcendental characteristics, two of which possessed a difficult nature. Working in the field phase added moral self-actualization characteristic, rationalism, spiritual beliefs, and scientific-professional qualifications to the feature of the concept. Moral courage is a pure and prominent characteristic of human beings. The antecedents of moral courage include model orientation, model acceptance, rationalism, individual excellence, acquiring academic and professional qualification, spiritual beliefs, organizational support, organizational repression, and internal and external personal barriers

Rasch model based analysis of the Force Concept Inventory

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Maja Planinic

2010-03-01

Full Text Available The Force Concept Inventory (FCI is an important diagnostic instrument which is widely used in the field of physics education research. It is therefore very important to evaluate and monitor its functioning using different tools for statistical analysis. One of such tools is the stochastic Rasch model, which enables construction of linear measures for persons and items from raw test scores and which can provide important insight in the structure and functioning of the test (how item difficulties are distributed within the test, how well the items fit the model, and how well the items work together to define the underlying construct. The data for the Rasch analysis come from the large-scale research conducted in 2006-07, which investigated Croatian high school students’ conceptual understanding of mechanics on a representative sample of 1676 students (age 17–18 years. The instrument used in research was the FCI. The average FCI score for the whole sample was found to be (27.7±0.4%, indicating that most of the students were still non-Newtonians at the end of high school, despite the fact that physics is a compulsory subject in Croatian schools. The large set of obtained data was analyzed with the Rasch measurement computer software WINSTEPS 3.66. Since the FCI is routinely used as pretest and post-test on two very different types of population (non-Newtonian and predominantly Newtonian, an additional predominantly Newtonian sample (N=141, average FCI score of 64.5% of first year students enrolled in introductory physics course at University of Zagreb was also analyzed. The Rasch model based analysis suggests that the FCI has succeeded in defining a sufficiently unidimensional construct for each population. The analysis of fit of data to the model found no grossly misfitting items which would degrade measurement. Some items with larger misfit and items with significantly different difficulties in the two samples of students do require further

Hydraulic head interpolation using ANFIS—model selection and sensitivity analysis

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Kurtulus, Bedri; Flipo, Nicolas

2012-01-01

The aim of this study is to investigate the efficiency of ANFIS (adaptive neuro fuzzy inference system) for interpolating hydraulic head in a 40-km 2 agricultural watershed of the Seine basin (France). Inputs of ANFIS are Cartesian coordinates and the elevation of the ground. Hydraulic head was measured at 73 locations during a snapshot campaign on September 2009, which characterizes low-water-flow regime in the aquifer unit. The dataset was then split into three subsets using a square-based selection method: a calibration one (55%), a training one (27%), and a test one (18%). First, a method is proposed to select the best ANFIS model, which corresponds to a sensitivity analysis of ANFIS to the type and number of membership functions (MF). Triangular, Gaussian, general bell, and spline-based MF are used with 2, 3, 4, and 5 MF per input node. Performance criteria on the test subset are used to select the 5 best ANFIS models among 16. Then each is used to interpolate the hydraulic head distribution on a (50×50)-m grid, which is compared to the soil elevation. The cells where the hydraulic head is higher than the soil elevation are counted as "error cells." The ANFIS model that exhibits the less "error cells" is selected as the best ANFIS model. The best model selection reveals that ANFIS models are very sensitive to the type and number of MF. Finally, a sensibility analysis of the best ANFIS model with four triangular MF is performed on the interpolation grid, which shows that ANFIS remains stable to error propagation with a higher sensitivity to soil elevation.

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

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Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

2015-01-01

Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

Evolutionary Meta-Analysis of Association Studies Reveals Ancient Constraints Affecting Disease Marker Discovery

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Dudley, Joel T.; Chen, Rong; Sanderford, Maxwell; Butte, Atul J.; Kumar, Sudhir

2012-01-01

Genome-wide disease association studies contrast genetic variation between disease cohorts and healthy populations to discover single nucleotide polymorphisms (SNPs) and other genetic markers revealing underlying genetic architectures of human diseases. Despite scores of efforts over the past decade, many reproducible genetic variants that explain substantial proportions of the heritable risk of common human diseases remain undiscovered. We have conducted a multispecies genomic analysis of 5,831 putative human risk variants for more than 230 disease phenotypes reported in 2,021 studies. We find that the current approaches show a propensity for discovering disease-associated SNPs (dSNPs) at conserved genomic positions because the effect size (odds ratio) and allelic P value of genetic association of an SNP relates strongly to the evolutionary conservation of their genomic position. We propose a new measure for ranking SNPs that integrates evolutionary conservation scores and the P value (E-rank). Using published data from a large case-control study, we demonstrate that E-rank method prioritizes SNPs with a greater likelihood of bona fide and reproducible genetic disease associations, many of which may explain greater proportions of genetic variance. Therefore, long-term evolutionary histories of genomic positions offer key practical utility in reassessing data from existing disease association studies, and in the design and analysis of future studies aimed at revealing the genetic basis of common human diseases. PMID:22389448

Comparative analysis reveals the underlying mechanism of vertebrate seasonal reproduction.

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Ikegami, Keisuke; Yoshimura, Takashi

2016-02-01

Animals utilize photoperiodic changes as a calendar to regulate seasonal reproduction. Birds have highly sophisticated photoperiodic mechanisms and functional genomics analysis in quail uncovered the signal transduction pathway regulating avian seasonal reproduction. Birds detect light with deep brain photoreceptors. Long day (LD) stimulus induces secretion of thyroid-stimulating hormone (TSH) from the pars tuberalis (PT) of the pituitary gland. PT-derived TSH locally activates thyroid hormone (TH) in the hypothalamus, which induces gonadotropin-releasing hormone (GnRH) and hence gonadotropin secretion. However, during winter, low temperatures increase serum TH for adaptive thermogenesis, which accelerates germ cell apoptosis by activating the genes involved in metamorphosis. Therefore, TH has a dual role in the regulation of seasonal reproduction. Studies using TSH receptor knockout mice confirmed the involvement of PT-derived TSH in mammalian seasonal reproduction. In addition, studies in mice revealed that the tissue-specific glycosylation of TSH diversifies its function in the circulation to avoid crosstalk. In contrast to birds and mammals, one of the molecular machineries necessary for the seasonal reproduction of fish are localized in the saccus vasculosus from the photoreceptor to the neuroendocrine output. Thus, comparative analysis is a powerful tool to uncover the universality and diversity of fundamental properties in various organisms. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis and modelling of engineering structures in frequency domain

International Nuclear Information System (INIS)

Ishtev, K.; Bonev, Z.; Petrov, P.; Philipov, P.

1987-01-01

This paper deals with some possible applications for modelling and analysis of engineering structures, basing on technique, mentioned above. The governing system of equations is written by using frequency domain approach since elemination technique has computational significance in this field. Modelling is made basing on the well known relationship Y(jw) = W(jw) * X(jw). Here X(jw) is a complex Fourier spectra associated with the imput signals being defined as earthquake, wind, hydrodynamic, control or other type of action. W(jw) is a matrix complex transfer function which reveals the correlation between input X und output Y spectra. Y (ja) represents a complex Fourier spectra of output signals. Input and output signals are both associated with master degrees of freedom, thus matrix transfer function is composed of elements in such a manner that solve unknown parameters are implemented implicitly. It is available an integration algorithm of 'condensed' system of equations. (orig./GL)

Decision makers use norms, not cost-benefit analysis, when choosing to conceal or reveal unfair rewards.

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Marco Heimann

Full Text Available We introduce the Conceal or Reveal Dilemma, in which individuals receive unfair benefits, and must decide whether to conceal or to reveal this unfair advantage. This dilemma has two important characteristics: it does not lend itself easily to cost-benefit analysis, neither to the application of any strong universal norm. As a consequence, it is ideally suited to the study of interindividual and intercultural variations in moral-economic norms. In this paper we focus on interindividual variations, and we report four studies showing that individuals cannot be swayed by financial incentives to conceal or to reveal, and follow instead fixed, idiosyncratic strategies. We discuss how this result can be extended to individual and cultural variations in the tendency to display or to hide unfair rewards.

Differential proteomic analysis reveals sequential heat stress-responsive regulatory network in radish (Raphanus sativus L.) taproot.

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Wang, Ronghua; Mei, Yi; Xu, Liang; Zhu, Xianwen; Wang, Yan; Guo, Jun; Liu, Liwang

2018-05-01

Differential abundance protein species (DAPS) involved in reducing damage and enhancing thermotolerance in radish were firstly identified. Proteomic analysis and omics association analysis revealed a HS-responsive regulatory network in radish. Heat stress (HS) is a major destructive factor influencing radish production and supply in summer, for radish is a cool season vegetable crop being susceptible to high temperature. In this study, the proteome changes of radish taproots under 40 °C treatment at 0 h (Control), 12 h (Heat12) and 24 h (Heat24) were analyzed using iTRAQ (Isobaric Tag for Relative and Absolute Quantification) approach. In total, 2258 DAPS representing 1542 differentially accumulated uniprotein species which respond to HS were identified. A total of 604, 910 and 744 DAPS was detected in comparison of Control vs. Heat12, Control vs. Heat24, and Heat12 vs. Heat24, respectively. Gene ontology and pathway analysis showed that annexin, ubiquitin-conjugating enzyme, ATP synthase, heat shock protein (HSP) and other stress-related proteins were predominately enriched in signal transduction, stress and defense pathways, photosynthesis and energy metabolic pathways, working cooperatively to reduce stress-induced damage in radish. Based on iTRAQ combined with the transcriptomics analysis, a schematic model of a sequential HS-responsive regulatory network was proposed. The initial sensing of HS occurred at the plasma membrane, and then key components of stress signal transduction triggered heat-responsive genes in the plant protective metabolism to re-establish homeostasis and enhance thermotolerance. These results provide new insights into characteristics of HS-responsive DAPS and facilitate dissecting the molecular mechanisms underlying heat tolerance in radish and other root crops.

Three-dimensional Crustal Structure beneath the Tibetan Plateau Revealed by Multi-scale Gravity Analysis

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Xu, C.; Luo, Z.; Sun, R.; Li, Q.

2017-12-01

The Tibetan Plateau, the largest and highest plateau on Earth, was uplifted, shorten and thicken by the collision and continuous convergence of the Indian and Eurasian plates since 50 million years ago, the Eocene epoch. Fine three-dimensional crustal structure of the Tibetan Plateau is helpful in understanding the tectonic development. At present, the ordinary method used for revealing crustal structure is seismic method, which is inhibited by poor seismic station coverage, especially in the central and western plateau primarily due to the rugged terrain. Fortunately, with the implementation of satellite gravity missions, gravity field models have demonstrated unprecedented global-scale accuracy and spatial resolution, which can subsequently be employed to study the crustal structure of the entire Tibetan Plateau. This study inverts three-dimensional crustal density and Moho topography of the Tibetan Plateau from gravity data using multi-scale gravity analysis. The inverted results are in agreement with those provided by the previous works. Besides, they can reveal rich tectonic development of the Tibetan Plateau: (1) The low-density channel flow can be observed from the inverted crustal density; (2) The Moho depth in the west is deeper than that in the east, and the deepest Moho, which is approximately 77 km, is located beneath the western Qiangtang Block; (3) The Moho fold, the directions of which are in agreement with the results of surface movement velocities estimated from Global Positioning System, exists clearly on the Moho topography.This study is supported by the National Natural Science Foundation of China (Grant No. 41504015), the China Postdoctoral Science Foundation (Grant No. 2015M572146), and the Surveying and Mapping Basic Research Programme of the National Administration of Surveying, Mapping and Geoinformation (Grant No. 15-01-08).

Unified fluid flow model for pressure transient analysis in naturally fractured media

International Nuclear Information System (INIS)

Babak, Petro; Azaiez, Jalel

2015-01-01

Naturally fractured reservoirs present special challenges for flow modeling with regards to their internal geometrical structure. The shape and distribution of matrix porous blocks and the geometry of fractures play key roles in the formulation of transient interporosity flow models. Although these models have been formulated for several typical geometries of the fracture networks, they appeared to be very dissimilar for different shapes of matrix blocks, and their analysis presents many technical challenges. The aim of this paper is to derive and analyze a unified approach to transient interporosity flow models for slightly compressible fluids that can be used for any matrix geometry and fracture network. A unified fractional differential transient interporosity flow model is derived using asymptotic analysis for singularly perturbed problems with small parameters arising from the assumption of a much smaller permeability of the matrix blocks compared to that of the fractures. This methodology allowed us to unify existing transient interporosity flow models formulated for different shapes of matrix blocks including bounded matrix blocks, unbounded matrix cylinders with any orthogonal crossection, and matrix slabs. The model is formulated using a fractional order diffusion equation for fluid pressure that involves Caputo derivative of order 1/2 with respect to time. Analysis of the unified fractional derivative model revealed that the surface area-to-volume ratio is the key parameter in the description of the flow through naturally fractured media. Expressions of this parameter are presented for matrix blocks of the same geometrical shape as well as combinations of different shapes with constant and random sizes. Numerical comparisons between the predictions of the unified model and those obtained from existing transient interporosity ones for matrix blocks in the form of slabs, spheres and cylinders are presented for linear, radial and spherical flow types for

Molecular analysis of sourdough reveals Lactobacillus mindensis sp. nov.

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Ehrmann, Matthias A; Müller, Martin R A; Vogel, Rudi F

2003-01-01

Genotypic fingerprinting to analyse the bacterial flora of an industrial sourdough revealed a coherent group of strains which could not be associated with a valid species. Comparative 16S rDNA sequence analysis showed that these strains formed a homogeneous cluster distinct from their closest relatives, Lactobacillus farciminis, Lactobacillus alimentarius and Lactobacillus kimchii. To characterize them further, physiological (sugar fermentation, formation of DL-lactate, hydrolysis of arginine, growth temperature, CO2 production) and chemotaxonomic properties have been determined. The DNA G +C content was 37.5 0.2 mol%. The peptidoglycan was of the lysine-D-iso-asparagine (L-Lys-D-Asp) type. The strains were homofermentative, Gram-positive, catalase-negative, non-spore-forming, non-motile rods. They were found as a major stable component of a rye flour sourdough fermentation. Physiological, biochemical as well as genotypic data suggested them to be a new species of the genus Lactobacillus. This was confirmed by DNA-DNA hybridization of genomic DNA, and the name Lactobacillus mindensis is proposed. The type strain of this species is DSM 14500T (=LMG 21508T).

Global analysis of general SU(2)xSU(2)xU(1) models with precision data

International Nuclear Information System (INIS)

Hsieh, Ken; Yu, Jiang-Hao; Yuan, C.-P.; Schmitz, Kai

2010-01-01

We present the results of a global analysis of a class of models with an extended electroweak gauge group of the form SU(2)xSU(2)xU(1), often denoted as G(221) models, which include as examples the left-right, the leptophobic, the hadrophobic, the fermiophobic, the un-unified, and the nonuniversal models. Using an effective Lagrangian approach, we compute the shifts to the coefficients in the electroweak Lagrangian due to the new heavy gauge bosons, and obtain the lower bounds on the masses of the Z ' and W ' bosons. The analysis of the electroweak parameter bounds reveals a consistent pattern of several key observables that are especially sensitive to the effects of new physics and thus dominate the overall shape of the respective parameter contours.

Global analysis of general SU(2) x SU(2) x U(1) models with precision data

International Nuclear Information System (INIS)

Hsieh, Ken; Yu, Jiang-Hao; Yuan, C.P.; Schmitz, Kai; Michigan State Univ., East Lansing, MI

2010-05-01

We present the results of a global analysis of a class of models with an extended electroweak gauge group of the form SU(2) x SU(2) x U(1), often denoted as G(221) models, which include as examples the left-right, the lepto-phobic, the hadro-phobic, the fermio-phobic, the un-unified, and the non-universal models. Using an effective Lagrangian approach, we compute the shifts to the coeffcients in the electroweak Lagrangian due to the new heavy gauge bosons, and obtain the lower bounds on the masses of the Z' and W' bosons. The analysis of the electroweak parameter bounds reveals a consistent pattern of several key observables that are especially sensitive to the effects of new physics and thus dominate the overall shape of the respective parameter contours. (orig.)

Hypersonic - Model Analysis as a Service

DEFF Research Database (Denmark)

Acretoaie, Vlad; Störrle, Harald

2014-01-01

Hypersonic is a Cloud-based tool that proposes a new approach to the deployment of model analysis facilities. It is implemented as a RESTful Web service API o_ering analysis features such as model clone detection. This approach allows the migration of resource intensive analysis algorithms from...

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Point correlation dimension can reveal functional changes caused by gap junction blockers in the 4-aminopyridine in vivo rat epilepsy model

Energy Technology Data Exchange (ETDEWEB)

Jardanhazy, Anett [Department of Neurology, University of Szeged, Semmelweis u. 6, Szeged H-6725 (Hungary); Molnar, Mark [Department of Psychophysiology, Institute for Psychology of the Hungarian Academy of Sciences, P.O. Box 398, Budapest H-1394 (Hungary)], E-mail: molnar@cogpsyphy.hu; Jardanhazy, Tamas [Department of Neurology, University of Szeged, Semmelweis u. 6, Szeged H-6725 (Hungary)], E-mail: jt@nepsy.szote.u-szeged.hu

2009-04-15

The contribution of gap junction (GJ) blockers to seizure initiation was reexamined by means of an analysis on nonlinear dynamics with point correlation dimension (PD2i) at as well as around the primary focus, and mirror focus in an already active 4-aminopyridine-induced in vivo epilepsy model. From the data base of the ECoGs of anesthetized adult rats treated with quinine, a selective blocker of Cx36, and in combination with an additional broad-spectrum GJ blocker, carbenoxolone, 14 cases of each condition were reexamined with a stationarity insensitive nonlinear PD2i method. The blockade of the Cx36 channels decreased the usual drop of the point correlation dimension at the beginning of the seizures, and this was enhanced by the additional use of the global blocker carbenoxolone. The so-called characteristic DC shift just prior to seizure onset denotes a low dimensional seizure event and the recognizable seizures display very variable, rapidly changing dynamics, as revealed by the PD2i analysis. This nonlinear PD2i analysis demonstrated that the different GJ blockers in the already active epileptic model helped seizure initiation, but exerted inhibitory effects on the seizure onset itself, acting differently on the local components of the network organization generating seizure discharges, possibly changing the coupling strengths and time delays in the GJ-s.

Point correlation dimension can reveal functional changes caused by gap junction blockers in the 4-aminopyridine in vivo rat epilepsy model

International Nuclear Information System (INIS)

Jardanhazy, Anett; Molnar, Mark; Jardanhazy, Tamas

2009-01-01

The contribution of gap junction (GJ) blockers to seizure initiation was reexamined by means of an analysis on nonlinear dynamics with point correlation dimension (PD2i) at as well as around the primary focus, and mirror focus in an already active 4-aminopyridine-induced in vivo epilepsy model. From the data base of the ECoGs of anesthetized adult rats treated with quinine, a selective blocker of Cx36, and in combination with an additional broad-spectrum GJ blocker, carbenoxolone, 14 cases of each condition were reexamined with a stationarity insensitive nonlinear PD2i method. The blockade of the Cx36 channels decreased the usual drop of the point correlation dimension at the beginning of the seizures, and this was enhanced by the additional use of the global blocker carbenoxolone. The so-called characteristic DC shift just prior to seizure onset denotes a low dimensional seizure event and the recognizable seizures display very variable, rapidly changing dynamics, as revealed by the PD2i analysis. This nonlinear PD2i analysis demonstrated that the different GJ blockers in the already active epileptic model helped seizure initiation, but exerted inhibitory effects on the seizure onset itself, acting differently on the local components of the network organization generating seizure discharges, possibly changing the coupling strengths and time delays in the GJ-s.

Secretome analysis of Aspergillus fumigatus reveals Asp-hemolysin as a major secreted protein.

Science.gov (United States)

Wartenberg, Dirk; Lapp, Katrin; Jacobsen, Ilse D; Dahse, Hans-Martin; Kniemeyer, Olaf; Heinekamp, Thorsten; Brakhage, Axel A

2011-11-01

Surface-associated and secreted proteins represent primarily exposed components of Aspergillus fumigatus during host infection. Several secreted proteins are known to be involved in defense mechanisms or immune evasion, thus, probably contributing to pathogenicity. Furthermore, several secreted antigens were identified as possible biomarkers for the verification of diseases caused by Aspergillus species. Nevertheless, there is only limited knowledge about the composition of the secretome and about molecular functions of particular proteins. To identify secreted proteins potentially essential for virulence, the core secretome of A. fumigatus grown in minimal medium was determined. Two-dimensional gel electrophoretic separation and subsequent MALDI-TOF-MS/MS analyses resulted in the identification of 64 different proteins. Additionally, secretome analyses of A. fumigatus utilizing elastin, collagen or keratin as main carbon and nitrogen source were performed. Thereby, the alkaline serine protease Alp1 was identified as the most abundant protein and hence presumably represents an important protease during host infection. Interestingly, the Asp-hemolysin (Asp-HS), which belongs to the protein family of aegerolysins and which was often suggested to be involved in fungal virulence, was present in the secretome under all growth conditions tested. In addition, a second, non-secreted protein with an aegerolysin domain annotated as Asp-hemolysin-like (HS-like) protein can be found to be encoded in the genome of A. fumigatus. Generation and analysis of Asp-HS and HS-like deletion strains revealed no differences in phenotype compared to the corresponding wild-type strain. Furthermore, hemolysis and cytotoxicity was not altered in both single-deletion and double-deletion mutants lacking both aegerolysin genes. All mutant strains showed no attenuation in virulence in a mouse infection model for invasive pulmonary aspergillosis. Overall, this study provides a comprehensive

Statistical Modelling of Wind Proles - Data Analysis and Modelling

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre

The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

An analysis of single amino acid repeats as use case for application specific background models

Directory of Open Access Journals (Sweden)

Sykacek Peter

2011-05-01

Full Text Available Abstract Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and

Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish

Directory of Open Access Journals (Sweden)

Xiang Li-xin

2010-08-01

Full Text Available Abstract Background Systematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish. Results RNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution. Conclusion This study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host

Stochastic modeling analysis and simulation

CERN Document Server

Nelson, Barry L

1995-01-01

A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, se

Combined Analysis of the Fruit Metabolome and Transcriptome Reveals Candidate Genes Involved in Flavonoid Biosynthesis in Actinidia arguta.

Science.gov (United States)

Li, Yukuo; Fang, Jinbao; Qi, Xiujuan; Lin, Miaomiao; Zhong, Yunpeng; Sun, Leiming; Cui, Wen

2018-05-15

To assess the interrelation between the change of metabolites and the change of fruit color, we performed a combined metabolome and transcriptome analysis of the flesh in two different Actinidia arguta cultivars: "HB" ("Hongbaoshixing") and "YF" ("Yongfengyihao") at two different fruit developmental stages: 70d (days after full bloom) and 100d (days after full bloom). Metabolite and transcript profiling was obtained by ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer and high-throughput RNA sequencing, respectively. The identification and quantification results of metabolites showed that a total of 28,837 metabolites had been obtained, of which 13,715 were annotated. In comparison of HB100 vs. HB70, 41 metabolites were identified as being flavonoids, 7 of which, with significant difference, were identified as bracteatin, luteolin, dihydromyricetin, cyanidin, pelargonidin, delphinidin and (-)-epigallocatechin. Association analysis between metabolome and transcriptome revealed that there were two metabolic pathways presenting significant differences during fruit development, one of which was flavonoid biosynthesis, in which 14 structural genes were selected to conduct expression analysis, as well as 5 transcription factor genes obtained by transcriptome analysis. RT-qPCR results and cluster analysis revealed that AaF3H , AaLDOX , AaUFGT , AaMYB , AabHLH , and AaHB2 showed the best possibility of being candidate genes. A regulatory network of flavonoid biosynthesis was established to illustrate differentially expressed candidate genes involved in accumulation of metabolites with significant differences, inducing red coloring during fruit development. Such a regulatory network linking genes and flavonoids revealed a system involved in the pigmentation of all-red-fleshed and all-green-fleshed A. arguta , suggesting this conjunct analysis approach is not only useful in understanding the relationship between genotype and phenotype

Supercritical kinetic analysis in simplified system of fuel debris using integral kinetic model

International Nuclear Information System (INIS)

Tuya, Delgersaikhan; Obara, Toru

2016-01-01

Highlights: • Kinetic analysis in simplified weakly coupled fuel debris system was performed. • The integral kinetic model was used to simulate criticality accidents. • The fission power and released energy during simulated accident were obtained. • Coupling between debris regions and its effect on the fission power was obtained. - Abstract: Preliminary prompt supercritical kinetic analyses in a simplified coupled system of fuel debris designed to roughly resemble a melted core of a nuclear reactor were performed using an integral kinetic model. The integral kinetic model, which can describe region- and time-dependent fission rate in a coupled system of arbitrary geometry, was used because the fuel debris system is weakly coupled in terms of neutronics. The results revealed some important characteristics of coupled systems, such as the coupling between debris regions and the effect of the coupling on the fission rate and released energy in each debris region during the simulated criticality accident. In brief, this study showed that the integral kinetic model can be applied to supercritical kinetic analysis in fuel debris systems and also that it can be a useful tool for investigating the effect of the coupling on consequences of a supercritical accident.

Phenotypic analysis of prostate-infiltrating lymphocytes reveals TH17 and Treg skewing.

Science.gov (United States)

Sfanos, Karen Sandell; Bruno, Tullia C; Maris, Charles H; Xu, Lauren; Thoburn, Christopher J; DeMarzo, Angelo M; Meeker, Alan K; Isaacs, William B; Drake, Charles G

2008-06-01

Pathologic examination of prostate glands removed from patients with prostate cancer commonly reveals infiltrating CD4+ and CD8+ T cells. Little is known about the phenotype of these cells, despite accumulating evidence suggesting a potential role for chronic inflammation in the etiology of prostate cancer. We developed a technique that samples the majority of the peripheral prostate through serial needle aspirates. CD4+ prostate-infiltrating lymphocytes (PIL) were isolated using magnetic beads and analyzed for subset skewing using both flow cytometry and quantitative reverse transcription-PCR. The transcriptional profile of fluorescence-activated cell sorted prostate-infiltrating regulatory T cells (CD4+, CD25+, GITR+) was compared with naïve, peripheral blood T cells using microarray analysis. CD4+ PIL showed a paucity of TH2 (interleukin-4-secreting) cells, a surprising finding given the generally accepted association of these cells with chronic, smoldering inflammation. Instead, CD4+ PIL seemed to be skewed towards a regulatory Treg phenotype (FoxP3+) as well as towards the TH17 phenotype (interleukin-17+). We also found that a preponderance of TH17-mediated inflammation was associated with a lower pathologic Gleason score. These protein level data were reflected at the message level, as analyzed by quantitative reverse transcription-PCR. Microarray analysis of pooled prostate-infiltrating T(reg) revealed expected Treg-associated transcripts (FoxP3, CTLA-4, GITR, LAG-3) as well as a number of unique cell surface markers that may serve as additional Treg markers. Taken together, these data suggest that TH17 and/or Treg CD4+ T cells (rather than TH2 T cells) may be involved in the development or progression of prostate cancer.

Analysis and logical modeling of biological signaling transduction networks

Science.gov (United States)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

Sensitivity analysis of infectious disease models: methods, advances and their application

Science.gov (United States)

Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

2013-01-01

Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

Metagenomic Analysis of the Sponge Discodermia Reveals the Production of the Cyanobacterial Natural Product Kasumigamide by 'Entotheonella'.

Science.gov (United States)

Nakashima, Yu; Egami, Yoko; Kimura, Miki; Wakimoto, Toshiyuki; Abe, Ikuro

2016-01-01

Sponge metagenomes are a useful platform to mine cryptic biosynthetic gene clusters responsible for production of natural products involved in the sponge-microbe association. Since numerous sponge-derived bioactive metabolites are biosynthesized by the symbiotic bacteria, this strategy may concurrently reveal sponge-symbiont produced compounds. Accordingly, a metagenomic analysis of the Japanese marine sponge Discodermia calyx has resulted in the identification of a hybrid type I polyketide synthase-nonribosomal peptide synthetase gene (kas). Bioinformatic analysis of the gene product suggested its involvement in the biosynthesis of kasumigamide, a tetrapeptide originally isolated from freshwater free-living cyanobacterium Microcystis aeruginosa NIES-87. Subsequent investigation of the sponge metabolic profile revealed the presence of kasumigamide in the sponge extract. The kasumigamide producing bacterium was identified as an 'Entotheonella' sp. Moreover, an in silico analysis of kas gene homologs uncovered the presence of kas family genes in two additional bacteria from different phyla. The production of kasumigamide by distantly related multiple bacterial strains implicates horizontal gene transfer and raises the potential for a wider distribution across other bacterial groups.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

NARCIS (Netherlands)

Macé, Aurélien; Tuke, Marcus A; Deelen, Patrick; Kristiansson, Kati; Mattsson, Hannele; Nõukas, Margit; Sapkota, Yadav; Schick, Ursula; Porcu, Eleonora; Rüeger, Sina; McDaid, Aaron F; Porteous, David; Winkler, Thomas W; Salvi, Erika; Shrine, Nick; Liu, Xueping; Ang, Wei Q; Zhang, Weihua; Feitosa, Mary F; Venturini, Cristina; van der Most, Peter J; Rosengren, Anders; Wood, Andrew R; Beaumont, Robin N; Jones, Samuel E; Ruth, Katherine S; Yaghootkar, Hanieh; Tyrrell, Jessica; Havulinna, Aki S; Boers, Harmen; Mägi, Reedik; Kriebel, Jennifer; Müller-Nurasyid, Martina; Perola, Markus; Nieminen, Markku; Lokki, Marja-Liisa; Kähönen, Mika; Viikari, Jorma S; Geller, Frank; Lahti, Jari; Palotie, Aarno; Koponen, Päivikki; Lundqvist, Annamari; Rissanen, Harri; Bottinger, Erwin P; Afaq, Saima; Wojczynski, Mary K; Lenzini, Petra; Nolte, Ilja M; Sparsø, Thomas; Schupf, Nicole; Christensen, Kaare; Perls, Thomas T; Newman, Anne B; Werge, Thomas; Snieder, Harold; Spector, Timothy D; Chambers, John C; Koskinen, Seppo; Melbye, Mads; Raitakari, Olli T; Lehtimäki, Terho; Tobin, Martin D; Wain, Louise V; Sinisalo, Juha; Peters, Annette; Meitinger, Thomas; Martin, Nicholas G; Wray, Naomi R; Montgomery, Grant W; Medland, Sarah E; Swertz, Morris A; Vartiainen, Erkki; Borodulin, Katja; Männistö, Satu; Murray, Anna; Bochud, Murielle; Jacquemont, Sébastien; Rivadeneira, Fernando; Hansen, Thomas F; Oldehinkel, Albertine J; Mangino, Massimo; Province, Michael A; Deloukas, Panos; Kooner, Jaspal S; Freathy, Rachel M; Pennell, Craig; Feenstra, Bjarke; Strachan, David P; Lettre, Guillaume; Hirschhorn, Joel; Cusi, Daniele; Heid, Iris M; Hayward, Caroline; Männik, Katrin; Beckmann, Jacques S; Loos, Ruth J F; Nyholt, Dale R; Metspalu, Andres; Eriksson, Johan G; Weedon, Michael N; Salomaa, Veikko; Franke, Lude; Reymond, Alexandre; Frayling, Timothy M; Kutalik, Zoltán

2017-01-01

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at

Ferricyanide-based analysis of aqueous lignin suspension revealed sequestration of water-soluble lignin moieties

OpenAIRE

Joshua, CJ; Simmons, BA; Singer, SW

2016-01-01

© 2016 The Royal Society of Chemistry. This study describes the application of a ferricyanide-based assay as a simple and inexpensive assay for rapid analysis of aqueous lignin samples. The assay measures the formation of Prussian blue from the redox reaction between a mixture of potassium ferricyanide and ferric chloride, and phenolic hydroxyl groups of lignin or lignin-derived phenolic moieties. This study revealed that soluble lignin moieties exhibited stronger ferricyanide reactivity than...

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

DEFF Research Database (Denmark)

Huang, Sijia; Chong, Nicole; Lewis, Nathan

2016-01-01

diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

Development of a Unified Rock Bolt Model in Discontinuous Deformation Analysis

Science.gov (United States)

He, L.; An, X. M.; Zhao, X. B.; Zhao, Z. Y.; Zhao, J.

2018-03-01

In this paper, a unified rock bolt model is proposed and incorporated into the two-dimensional discontinuous deformation analysis. In the model, the bolt shank is discretized into a finite number of (modified) Euler-Bernoulli beam elements with the degrees of freedom represented at the end nodes, while the face plate is treated as solid blocks. The rock mass and the bolt shank deform independently, but interact with each other through a few anchored points. The interactions between the rock mass and the face plate are handled via general contact algorithm. Different types of rock bolts (e.g., Expansion Shell, fully grouted rebar, Split Set, cone bolt, Roofex, Garford and D-bolt) can be realized by specifying the corresponding constitutive model for the tangential behavior of the anchored points. Four failure modes, namely tensile failure and shear failure of the bolt shank, debonding along the bolt/rock interface and loss of the face plate, are available in the analysis procedure. The performance of a typical conventional rock bolt (fully grouted rebar) and a typical energy-absorbing rock bolt (D-bolt) under the scenarios of suspending loosened blocks and rock dilation is investigated using the proposed model. The reliability of the proposed model is verified by comparing the simulation results with theoretical predictions and experimental observations. The proposed model could be used to reveal the mechanism of each type of rock bolt in realistic scenarios and to provide a numerical way for presenting the detailed profile about the behavior of bolts, in particular at intermediate loading stages.

Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

Directory of Open Access Journals (Sweden)

Suttida Rakkapao

2016-10-01

Full Text Available This study investigated the multiple-choice test of understanding of vectors (TUV, by applying item response theory (IRT. The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test’s distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

Science.gov (United States)

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-12-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

Hidden Markov model analysis reveals the advantage of analytic eye movement patterns in face recognition across cultures.

Science.gov (United States)

Chuk, Tim; Crookes, Kate; Hayward, William G; Chan, Antoni B; Hsiao, Janet H

2017-12-01

It remains controversial whether culture modulates eye movement behavior in face recognition. Inconsistent results have been reported regarding whether cultural differences in eye movement patterns exist, whether these differences affect recognition performance, and whether participants use similar eye movement patterns when viewing faces from different ethnicities. These inconsistencies may be due to substantial individual differences in eye movement patterns within a cultural group. Here we addressed this issue by conducting individual-level eye movement data analysis using hidden Markov models (HMMs). Each individual's eye movements were modeled with an HMM. We clustered the individual HMMs according to their similarities and discovered three common patterns in both Asian and Caucasian participants: holistic (looking mostly at the face center), left-eye-biased analytic (looking mostly at the two individual eyes in addition to the face center with a slight bias to the left eye), and right-eye-based analytic (looking mostly at the right eye in addition to the face center). The frequency of participants adopting the three patterns did not differ significantly between Asians and Caucasians, suggesting little modulation from culture. Significantly more participants (75%) showed similar eye movement patterns when viewing own- and other-race faces than different patterns. Most importantly, participants with left-eye-biased analytic patterns performed significantly better than those using either holistic or right-eye-biased analytic patterns. These results suggest that active retrieval of facial feature information through an analytic eye movement pattern may be optimal for face recognition regardless of culture. Copyright © 2017 Elsevier B.V. All rights reserved.

Axial displacement of external and internal implant-abutment connection evaluated by linear mixed model analysis.

Science.gov (United States)

Seol, Hyon-Woo; Heo, Seong-Joo; Koak, Jai-Young; Kim, Seong-Kyun; Kim, Shin-Koo

2015-01-01

To analyze the axial displacement of external and internal implant-abutment connection after cyclic loading. Three groups of external abutments (Ext group), an internal tapered one-piece-type abutment (Int-1 group), and an internal tapered two-piece-type abutment (Int-2 group) were prepared. Cyclic loading was applied to implant-abutment assemblies at 150 N with a frequency of 3 Hz. The amount of axial displacement, the Periotest values (PTVs), and the removal torque values(RTVs) were measured. Both a repeated measures analysis of variance and pattern analysis based on the linear mixed model were used for statistical analysis. Scanning electron microscopy (SEM) was used to evaluate the surface of the implant-abutment connection. The mean axial displacements after 1,000,000 cycles were 0.6 μm in the Ext group, 3.7 μm in the Int-1 group, and 9.0 μm in the Int-2 group. Pattern analysis revealed a breakpoint at 171 cycles. The Ext group showed no declining pattern, and the Int-1 group showed no declining pattern after the breakpoint (171 cycles). However, the Int-2 group experienced continuous axial displacement. After cyclic loading, the PTV decreased in the Int-2 group, and the RTV decreased in all groups. SEM imaging revealed surface wear in all groups. Axial displacement and surface wear occurred in all groups. The PTVs remained stable, but the RTVs decreased after cyclic loading. Based on linear mixed model analysis, the Ext and Int-1 groups' axial displacements plateaued after little cyclic loading. The Int-2 group's rate of axial displacement slowed after 100,000 cycles.

Global analysis of general SU(2) x SU(2) x U(1) models with precision data

Energy Technology Data Exchange (ETDEWEB)

Hsieh, Ken; Yu, Jiang-Hao; Yuan, C.P. [Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy; Schmitz, Kai [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy

2010-05-15

We present the results of a global analysis of a class of models with an extended electroweak gauge group of the form SU(2) x SU(2) x U(1), often denoted as G(221) models, which include as examples the left-right, the lepto-phobic, the hadro-phobic, the fermio-phobic, the un-unified, and the non-universal models. Using an effective Lagrangian approach, we compute the shifts to the coeffcients in the electroweak Lagrangian due to the new heavy gauge bosons, and obtain the lower bounds on the masses of the Z' and W' bosons. The analysis of the electroweak parameter bounds reveals a consistent pattern of several key observables that are especially sensitive to the effects of new physics and thus dominate the overall shape of the respective parameter contours. (orig.)

Experimental measurement and modeling analysis on mechanical properties of incudostapedial joint.

Science.gov (United States)

Zhang, Xiangming; Gan, Rong Z

2011-10-01

The incudostapedial (IS) joint between the incus and stapes is a synovial joint consisting of joint capsule, cartilage, and synovial fluid. The mechanical properties of the IS joint directly affect the middle ear transfer function for sound transmission. However, due to the complexity and small size of the joint, the mechanical properties of the IS joint have not been reported in the literature. In this paper, we report our current study on mechanical properties of human IS joint using both experimental measurement and finite element (FE) modeling analysis. Eight IS joint samples with the incus and stapes attached were harvested from human cadaver temporal bones. Tension, compression, stress relaxation and failure tests were performed on those samples in a micro-material testing system. An analytical approach with the hyperelastic Ogden model and a 3D FE model of the IS joint including the cartilage, joint capsule, and synovial fluid were employed to derive mechanical parameters of the IS joint. The comparison of measurements and modeling results reveals the relationship between the mechanical properties and structure of the IS joint.

Combined Use of Systematic Conservation Planning, Species Distribution Modelling, and Connectivity Analysis Reveals Severe Conservation Gaps in a Megadiverse Country (Peru)

Science.gov (United States)

Fajardo, Javier; Lessmann, Janeth; Bonaccorso, Elisa; Devenish, Christian; Muñoz, Jesús

2014-01-01

Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species' geographic ranges to reduce the effect of biased sampling and partial knowledge about species' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network. PMID:25479411

[Model-based biofuels system analysis: a review].

Science.gov (United States)

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

Gene array analysis of PD-1H overexpressing monocytes reveals a pro-inflammatory profile

Directory of Open Access Journals (Sweden)

Preeti Bharaj

2018-02-01

Full Text Available We have previously reported that overexpression of Programmed Death -1 Homolog (PD-1H in human monocytes leads to activation and spontaneous secretion of multiple pro inflammatory cytokines. Here we evaluate changes in monocytes gene expression after enforced PD-1H expression by gene array. The results show that there are significant alterations in 51 potential candidate genes that relate to immune response, cell adhesion and metabolism. Genes corresponding to pro-inflammatory cytokines showed the highest upregulation, 7, 3.2, 3.0, 5.8, 4.4 and 3.1 fold upregulation of TNF-α, IL-1 β, IFN-α, γ, λ and IL-27 relative to vector control. The data are in agreement with cytometric bead array analysis showing induction of proinflammatory cytokines, IL-6, IL-1β and TNF-α by PD-1H. Other genes related to inflammation, include transglutaminase 2 (TG2, NF-κB (p65 and p50 and toll like receptors (TLR 3 and 4 were upregulated 5, 4.5 and 2.5 fold, respectively. Gene set enrichment analysis (GSEA also revealed that signaling pathways related to inflammatory response, such as NFκB, AT1R, PYK2, MAPK, RELA, TNFR1, MTOR and proteasomal degradation, were significantly upregulated in response to PD-1H overexpression. We validated the results utilizing a standard inflammatory sepsis model in humanized BLT mice, finding that PD-1H expression was highly correlated with proinflammatory cytokine production. We therefore conclude that PD-1H functions to enhance monocyte activation and the induction of a pro-inflammatory gene expression profile.

ROCK PROPERTIES MODEL ANALYSIS MODEL REPORT

International Nuclear Information System (INIS)

Clinton Lum

2002-01-01

The purpose of this Analysis and Model Report (AMR) is to document Rock Properties Model (RPM) 3.1 with regard to input data, model methods, assumptions, uncertainties and limitations of model results, and qualification status of the model. The report also documents the differences between the current and previous versions and validation of the model. The rock properties models are intended principally for use as input to numerical physical-process modeling, such as of ground-water flow and/or radionuclide transport. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. This work was conducted in accordance with the following planning documents: WA-0344, ''3-D Rock Properties Modeling for FY 1998'' (SNL 1997, WA-0358), ''3-D Rock Properties Modeling for FY 1999'' (SNL 1999), and the technical development plan, Rock Properties Model Version 3.1, (CRWMS MandO 1999c). The Interim Change Notice (ICNs), ICN 02 and ICN 03, of this AMR were prepared as part of activities being conducted under the Technical Work Plan, TWP-NBS-GS-000003, ''Technical Work Plan for the Integrated Site Model, Process Model Report, Revision 01'' (CRWMS MandO 2000b). The purpose of ICN 03 is to record changes in data input status due to data qualification and verification activities. These work plans describe the scope, objectives, tasks, methodology, and implementing procedures for model construction. The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The work scope for this activity consists of the following: (1) Conversion of the input data (laboratory measured porosity data, x-ray diffraction mineralogy, petrophysical calculations of bound water, and petrophysical calculations of porosity) for each borehole into stratigraphic coordinates; (2) Re-sampling and merging of data sets; (3) Development of geostatistical simulations of porosity; (4

Automatic sleep classification using a data-driven topic model reveals latent sleep states

DEFF Research Database (Denmark)

Koch, Henriette; Christensen, Julie Anja Engelhard; Frandsen, Rune

2014-01-01

Latent Dirichlet Allocation. Model application was tested on control subjects and patients with periodic leg movements (PLM) representing a non-neurodegenerative group, and patients with idiopathic REM sleep behavior disorder (iRBD) and Parkinson's Disease (PD) representing a neurodegenerative group......Background: The golden standard for sleep classification uses manual scoring of polysomnography despite points of criticism such as oversimplification, low inter-rater reliability and the standard being designed on young and healthy subjects. New method: To meet the criticism and reveal the latent...... sleep states, this study developed a general and automatic sleep classifier using a data-driven approach. Spectral EEG and EOG measures and eye correlation in 1 s windows were calculated and each sleep epoch was expressed as a mixture of probabilities of latent sleep states by using the topic model...

SENSITIVITY ANALYSIS OF BIOME-BGC MODEL FOR DRY TROPICAL FORESTS OF VINDHYAN HIGHLANDS, INDIA

OpenAIRE

M. Kumar; A. S. Raghubanshi

2012-01-01

A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to...

Intercity Travel Demand Analysis Model

Directory of Open Access Journals (Sweden)

Ming Lu

2014-01-01

Full Text Available It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.

Analysis of NIF experiments with the minimal energy implosion model

Energy Technology Data Exchange (ETDEWEB)

Cheng, B., E-mail: bcheng@lanl.gov; Kwan, T. J. T.; Wang, Y. M.; Merrill, F. E.; Batha, S. H. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Cerjan, C. J. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)

2015-08-15

We apply a recently developed analytical model of implosion and thermonuclear burn to fusion capsule experiments performed at the National Ignition Facility that used low-foot and high-foot laser pulse formats. Our theoretical predictions are consistent with the experimental data. Our studies, together with neutron image analysis, reveal that the adiabats of the cold fuel in both low-foot and high-foot experiments are similar. That is, the cold deuterium-tritium shells in those experiments are all in a high adiabat state at the time of peak implosion velocity. The major difference between low-foot and high-foot capsule experiments is the growth of the shock-induced instabilities developed at the material interfaces which lead to fuel mixing with ablator material. Furthermore, we have compared the NIF capsules performance with the ignition criteria and analyzed the alpha particle heating in the NIF experiments. Our analysis shows that alpha heating was appreciable only in the high-foot experiments.

Analysis of NIF experiments with the minimal energy implosion model

International Nuclear Information System (INIS)

Cheng, B.; Kwan, T. J. T.; Wang, Y. M.; Merrill, F. E.; Batha, S. H.; Cerjan, C. J.

2015-01-01

We apply a recently developed analytical model of implosion and thermonuclear burn to fusion capsule experiments performed at the National Ignition Facility that used low-foot and high-foot laser pulse formats. Our theoretical predictions are consistent with the experimental data. Our studies, together with neutron image analysis, reveal that the adiabats of the cold fuel in both low-foot and high-foot experiments are similar. That is, the cold deuterium-tritium shells in those experiments are all in a high adiabat state at the time of peak implosion velocity. The major difference between low-foot and high-foot capsule experiments is the growth of the shock-induced instabilities developed at the material interfaces which lead to fuel mixing with ablator material. Furthermore, we have compared the NIF capsules performance with the ignition criteria and analyzed the alpha particle heating in the NIF experiments. Our analysis shows that alpha heating was appreciable only in the high-foot experiments

Complete genome sequence analysis of novel human bocavirus reveals genetic recombination between human bocavirus 2 and human bocavirus 4.

Science.gov (United States)

Khamrin, Pattara; Okitsu, Shoko; Ushijima, Hiroshi; Maneekarn, Niwat

2013-07-01

Epidemiological surveillance of human bocavirus (HBoV) was conducted on fecal specimens collected from hospitalized children with diarrhea in Chiang Mai, Thailand in 2011. By partial sequence analysis of VP1 gene, an unusual strain of HBoV (CMH-S011-11), was initially identified as HBoV4. The complete genome sequence of CMH-S011-11 was performed and analyzed further to clarify whether it was a recombinant strain or a new HBoV variant. Analysis of complete genome sequence revealed that the coding sequence starting from NS1, NP1 to VP1/VP2 was 4795 nucleotides long. Interestingly, the nucleotide sequence of NS1 gene of CMH-S011-11 was most closely related to the HBoV2 reference strains detected in Pakistan, which contradicted to the initial genotyping result of the partial VP1 region in the previous study. In addition, comparison of NP1 nucleotide sequence of CMH-S011-11 with those of other HBoV1-4 reference strains also revealed a high level of sequence identity with HBoV2. On the other hand, nucleotide sequence of VP1/VP2 gene of CMH-S011-11 was most closely related to those of HBoV4 reference strains detected in Nigeria. The overall full-length sequence analysis revealed that this CMH-S011-11 was grouped within HBoV4 species, but located in a separate branch from other HBoV4 prototype strains. Recombination analysis revealed that CMH-S011-11 was the result of recombination between HBoV2 and HBoV4 strains with the break point located near the start codon of VP2. Copyright © 2013 Elsevier B.V. All rights reserved.

Sexually dimorphic distribution of Prokr2 neurons revealed by the Prokr2-Cre mouse model.

Science.gov (United States)

Mohsen, Zaid; Sim, Hosung; Garcia-Galiano, David; Han, Xingfa; Bellefontaine, Nicole; Saunders, Thomas L; Elias, Carol F

2017-12-01

Prokineticin receptor 2 (PROKR2) is predominantly expressed in the mammalian central nervous system. Loss-of-function mutations of PROKR2 in humans are associated with Kallmann syndrome due to the disruption of gonadotropin releasing hormone neuronal migration and deficient olfactory bulb morphogenesis. PROKR2 has been also implicated in the neuroendocrine control of GnRH neurons post-migration and other physiological systems. However, the brain circuitry and mechanisms associated with these actions have been difficult to investigate mainly due to the widespread distribution of Prokr2-expressing cells, and the lack of animal models and molecular tools. Here, we describe the generation, validation and characterization of a new mouse model that expresses Cre recombinase driven by the Prokr2 promoter, using CRISPR-Cas9 technology. Cre expression was visualized using reporter genes, tdTomato and GFP, in males and females. Expression of Cre-induced reporter genes was found in brain sites previously described to express Prokr2, e.g., the paraventricular and the suprachiasmatic nuclei, and the area postrema. The Prokr2-Cre mouse model was further validated by colocalization of Cre-induced GFP and Prokr2 mRNA. No disruption of Prokr2 expression, GnRH neuronal migration or fertility was observed. Comparative analysis of Prokr2-Cre expression in male and female brains revealed a sexually dimorphic distribution confirmed by in situ hybridization. In females, higher Cre activity was found in the medial preoptic area, ventromedial nucleus of the hypothalamus, arcuate nucleus, medial amygdala and lateral parabrachial nucleus. In males, Cre was higher in the amygdalo-hippocampal area. The sexually dimorphic pattern of Prokr2 expression indicates differential roles in reproductive function and, potentially, in other physiological systems.

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

Science.gov (United States)

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Distribution patterns of firearm discharge residues as revealed by neutron activation analysis

International Nuclear Information System (INIS)

Pillay, K.K.S.; Driscoll, D.C.; Jester, W.A.

1975-01-01

A systematic investigation using a variety of handguns has revealed the existence of distinguisable distribution patterns of firearm discharge residues on surfaces below the flight path of a bullet. The residues are identificable even at distances of 12 meters from the gun using nondestructive neutron activation analysis. The results of these investigations show that the distribution pattern for a gun is reproducible using similar ammunition and that there exist two distinct regions to the patterns developed between the firearm and the target-one with respect to the position of the gun and the other in the vicinity of the target. The judicious applications of these findings could be of significant value in criminal investigations. (T.G.)

Construction and analysis of a modular model of caspase activation in apoptosis

Directory of Open Access Journals (Sweden)

Ho Kenneth L

2008-12-01

Full Text Available Abstract Background A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic and intracellular (intrinsic signals. The extrinsic and intrinsic pathways are characterized by the formation of the death-inducing signaling complex (DISC and the apoptosome, respectively; both the DISC and the apoptosome are oligomers with complex formation dynamics. Additionally, the extrinsic and intrinsic pathways are coupled through the mitochondrial apoptosis-induced channel via the Bcl-2 family of proteins. Results A model of caspase activation is constructed and analyzed. The apoptosis signaling network is simplified through modularization methodologies and equilibrium abstractions for three functional modules. The mathematical model is composed of a system of ordinary differential equations which is numerically solved. Multiple linear regression analysis investigates the role of each module and reduced models are constructed to identify key contributions of the extrinsic and intrinsic pathways in triggering apoptosis for different cell lines. Conclusion Through linear regression techniques, we identified the feedbacks, dissociation of complexes, and negative regulators as the key components in apoptosis. The analysis and reduced models for our model formulation reveal that the chosen cell lines predominately exhibit strong extrinsic caspase, typical of type I cell, behavior. Furthermore, under the simplified model framework, the selected cells lines exhibit different modes by which caspase activation may occur. Finally the proposed modularized model of apoptosis may generalize behavior for additional cells and tissues, specifically identifying and predicting components responsible for the transition from type I to type II cell behavior.

Functional genome analysis of Bifidobacterium breve UCC2003 reveals type IVb tight adherence (Tad) pili as an essential and conserved host-colonization factor

Science.gov (United States)

O'Connell Motherway, Mary; Zomer, Aldert; Leahy, Sinead C.; Reunanen, Justus; Bottacini, Francesca; Claesson, Marcus J.; O'Brien, Frances; Flynn, Kiera; Casey, Patrick G.; Moreno Munoz, Jose Antonio; Kearney, Breda; Houston, Aileen M.; O'Mahony, Caitlin; Higgins, Des G.; Shanahan, Fergus; Palva, Airi; de Vos, Willem M.; Fitzgerald, Gerald F.; Ventura, Marco; O'Toole, Paul W.; van Sinderen, Douwe

2011-01-01

Development of the human gut microbiota commences at birth, with bifidobacteria being among the first colonizers of the sterile newborn gastrointestinal tract. To date, the genetic basis of Bifidobacterium colonization and persistence remains poorly understood. Transcriptome analysis of the Bifidobacterium breve UCC2003 2.42-Mb genome in a murine colonization model revealed differential expression of a type IVb tight adherence (Tad) pilus-encoding gene cluster designated “tad2003.” Mutational analysis demonstrated that the tad2003 gene cluster is essential for efficient in vivo murine gut colonization, and immunogold transmission electron microscopy confirmed the presence of Tad pili at the poles of B. breve UCC2003 cells. Conservation of the Tad pilus-encoding locus among other B. breve strains and among sequenced Bifidobacterium genomes supports the notion of a ubiquitous pili-mediated host colonization and persistence mechanism for bifidobacteria. PMID:21690406

Functional genome analysis of Bifidobacterium breve UCC2003 reveals type IVb tight adherence (Tad) pili as an essential and conserved host-colonization factor.

Science.gov (United States)

O'Connell Motherway, Mary; Zomer, Aldert; Leahy, Sinead C; Reunanen, Justus; Bottacini, Francesca; Claesson, Marcus J; O'Brien, Frances; Flynn, Kiera; Casey, Patrick G; Munoz, Jose Antonio Moreno; Kearney, Breda; Houston, Aileen M; O'Mahony, Caitlin; Higgins, Des G; Shanahan, Fergus; Palva, Airi; de Vos, Willem M; Fitzgerald, Gerald F; Ventura, Marco; O'Toole, Paul W; van Sinderen, Douwe

2011-07-05

Development of the human gut microbiota commences at birth, with bifidobacteria being among the first colonizers of the sterile newborn gastrointestinal tract. To date, the genetic basis of Bifidobacterium colonization and persistence remains poorly understood. Transcriptome analysis of the Bifidobacterium breve UCC2003 2.42-Mb genome in a murine colonization model revealed differential expression of a type IVb tight adherence (Tad) pilus-encoding gene cluster designated "tad(2003)." Mutational analysis demonstrated that the tad(2003) gene cluster is essential for efficient in vivo murine gut colonization, and immunogold transmission electron microscopy confirmed the presence of Tad pili at the poles of B. breve UCC2003 cells. Conservation of the Tad pilus-encoding locus among other B. breve strains and among sequenced Bifidobacterium genomes supports the notion of a ubiquitous pili-mediated host colonization and persistence mechanism for bifidobacteria.

Gene expression analysis of skin grafts and cultured keratinocytes using synthetic RNA normalization reveals insights into differentiation and growth control.

Science.gov (United States)

Katayama, Shintaro; Skoog, Tiina; Jouhilahti, Eeva-Mari; Siitonen, H Annika; Nuutila, Kristo; Tervaniemi, Mari H; Vuola, Jyrki; Johnsson, Anna; Lönnerberg, Peter; Linnarsson, Sten; Elomaa, Outi; Kankuri, Esko; Kere, Juha

2015-06-25

Keratinocytes (KCs) are the most frequent cells in the epidermis, and they are often isolated and cultured in vitro to study the molecular biology of the skin. Cultured primary cells and various immortalized cells have been frequently used as skin models but their comparability to intact skin has been questioned. Moreover, when analyzing KC transcriptomes, fluctuation of polyA+ RNA content during the KCs' lifecycle has been omitted. We performed STRT RNA sequencing on 10 ng samples of total RNA from three different sample types: i) epidermal tissue (split-thickness skin grafts), ii) cultured primary KCs, and iii) HaCaT cell line. We observed significant variation in cellular polyA+ RNA content between tissue and cell culture samples of KCs. The use of synthetic RNAs and SAMstrt in normalization enabled comparison of gene expression levels in the highly heterogenous samples and facilitated discovery of differences between the tissue samples and cultured cells. The transcriptome analysis sensitively revealed genes involved in KC differentiation in skin grafts and cell cycle regulation related genes in cultured KCs and emphasized the fluctuation of transcription factors and non-coding RNAs associated to sample types. The epidermal keratinocytes derived from tissue and cell culture samples showed highly different polyA+ RNA contents. The use of SAMstrt and synthetic RNA based normalization allowed the comparison between tissue and cell culture samples and thus proved to be valuable tools for RNA-seq analysis with translational approach. Transciptomics revealed clear difference both between tissue and cell culture samples and between primary KCs and immortalized HaCaT cells.

Meta-analysis a structural equation modeling approach

CERN Document Server

Cheung, Mike W-L

2015-01-01

Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

Biological variability in biomechanical engineering research: Significance and meta-analysis of current modeling practices.

Science.gov (United States)

Cook, Douglas; Julias, Margaret; Nauman, Eric

2014-04-11

Biological systems are characterized by high levels of variability, which can affect the results of biomechanical analyses. As a review of this topic, we first surveyed levels of variation in materials relevant to biomechanics, and compared these values to standard engineered materials. As expected, we found significantly higher levels of variation in biological materials. A meta-analysis was then performed based on thorough reviews of 60 research studies from the field of biomechanics to assess the methods and manner in which biological variation is currently handled in our field. The results of our meta-analysis revealed interesting trends in modeling practices, and suggest a need for more biomechanical studies that fully incorporate biological variation in biomechanical models and analyses. Finally, we provide some case study example of how biological variability may provide valuable insights or lead to surprising results. The purpose of this study is to promote the advancement of biomechanics research by encouraging broader treatment of biological variability in biomechanical modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Separating foliar physiology from morphology reveals the relative roles of vertically structured transpiration factors within red maple crowns and limitations of larger scale models

Science.gov (United States)

Bauerle, William L.; Bowden, Joseph D.

2011-01-01

A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions. PMID:21617246

Integrating model checking with HiP-HOPS in model-based safety analysis

International Nuclear Information System (INIS)

Sharvia, Septavera; Papadopoulos, Yiannis

2015-01-01

The ability to perform an effective and robust safety analysis on the design of modern safety–critical systems is crucial. Model-based safety analysis (MBSA) has been introduced in recent years to support the assessment of complex system design by focusing on the system model as the central artefact, and by automating the synthesis and analysis of failure-extended models. Model checking and failure logic synthesis and analysis (FLSA) are two prominent MBSA paradigms. Extensive research has placed emphasis on the development of these techniques, but discussion on their integration remains limited. In this paper, we propose a technique in which model checking and Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) – an advanced FLSA technique – can be applied synergistically with benefit for the MBSA process. The application of the technique is illustrated through an example of a brake-by-wire system. - Highlights: • We propose technique to integrate HiP-HOPS and model checking. • State machines can be systematically constructed from HiP-HOPS. • The strengths of different MBSA techniques are combined. • Demonstrated through modeling and analysis of brake-by-wire system. • Root cause analysis is automated and system dynamic behaviors analyzed and verified

Comparative Transcriptome Analysis Reveals Different Silk Yields of Two Silkworm Strains.

Directory of Open Access Journals (Sweden)

Juan Li

Full Text Available Cocoon and silk yields are the most important characteristics of sericulture. However, few studies have examined the genes that modulate these features. Further studies of these genes will be useful for improving the products of sericulture. JingSong (JS and Lan10 (L10 are two strains having significantly different cocoon and silk yields. In the current study, RNA-Seq and quantitative polymerase chain reaction (qPCR were performed on both strains in order to determine divergence of the silk gland, which controls silk biosynthesis in silkworms. Compared with L10, JS had 1375 differentially expressed genes (DEGs; 738 up-regulated genes and 673 down-regulated genes. Nine enriched gene ontology (GO terms were identified by GO enrichment analysis based on these DEGs. KEGG enrichment analysis results showed that the DEGs were enriched in three pathways, which were mainly associated with the processing and biosynthesis of proteins. The representative genes in the enrichment pathways and ten significant DEGs were further verified by qPCR, the results of which were consistent with the RNA-Seq data. Our study has revealed differences in silk glands between the two silkworm strains and provides a perspective for understanding the molecular mechanisms determining silk yield.

Metagenomic analysis reveals symbiotic relationship among bacteria in Microcystis-dominated community

Directory of Open Access Journals (Sweden)

Meili eXie

2016-02-01

Full Text Available Microcystis bloom, a cyanobacterial mass occurrence often found in eutrophicated water bodies, is one of the most serious threats to freshwater ecosystems worldwide. In nature, Microcystis forms aggregates or colonies that contain heterotrophic bacteria. The Microcystis-bacteria colonies were persistent even when they were maintained in lab culture for a long period. The relationship between Microcystis and the associated bacteria was investigated by a metagenomic approach in this study. We developed a visualization-guided method of binning for genome assembly after total colony DNA sequencing. We found that the method was effective in grouping sequences and it did not require reference genome sequence. Individual genomes of the colony bacteria were obtained and they provided valuable insights into microbial community structures. Analysis of metabolic pathways based on these genomes revealed that while all heterotrophic bacteria were dependent upon Microcystis for carbon and energy, Vitamin B12 biosynthesis, which is required for growth by Microcystis, was accomplished in a cooperative fashion among the bacteria. Our analysis also suggests that individual bacteria in the colony community contributed a complete pathway for degradation of benzoate, which is inhibitory to the cyanobacterial growth, and its ecological implication for Microcystis bloom is discussed.

Revealed preferences towards the appraisal of orphan drugs in Poland - multi criteria decision analysis.

Science.gov (United States)

Kolasa, Katarzyna; Zwolinski, Krzysztof Miroslaw; Zah, Vladimir; Kaló, Zoltán; Lewandowski, Tadeusz

2018-04-27

A Multi Criteria Decision Analysis (MCDA) technique was adopted to reveal the preferences of the Appraisal Body of the Polish HTA agency towards orphan drugs (OMPs). There were 34 positive and 23 negative HTA recommendations out of 54 distinctive drug-indication pairs. The MCDA matrix consisted of 13 criteria, seven of which made the most impact on the HTA process. Appraisal of clinical evidence, cost of therapy, and safety considerations were the main contributors to the HTA guidance, whilst advancement of technology and manufacturing costs made the least impact. MCDA can be regarded as a valuable tool for revealing decision makers' preferences in the healthcare sector. Given that only roughly half of all criteria included in the MCDA matrix were deemed to make an impact on the HTA process, there is certainly some room for improvement with respect to the adaptation of a new approach towards the value assessment of OMPs in Poland.

[Model of Analysis and Prevention of Accidents - MAPA: tool for operational health surveillance].

Science.gov (United States)

de Almeida, Ildeberto Muniz; Vilela, Rodolfo Andrade de Gouveia; da Silva, Alessandro José Nunes; Beltran, Sandra Lorena

2014-12-01

The analysis of work-related accidents is important for accident surveillance and prevention. Current methods of analysis seek to overcome reductionist views that see these occurrences as simple events explained by operator error. The objective of this paper is to analyze the Model of Analysis and Prevention of Accidents (MAPA) and its use in monitoring interventions, duly highlighting aspects experienced in the use of the tool. The descriptive analytical method was used, introducing the steps of the model. To illustrate contributions and or difficulties, cases where the tool was used in the context of service were selected. MAPA integrates theoretical approaches that have already been tried in studies of accidents by providing useful conceptual support from the data collection stage until conclusion and intervention stages. Besides revealing weaknesses of the traditional approach, it helps identify organizational determinants, such as management failings, system design and safety management involved in the accident. The main challenges lie in the grasp of concepts by users, in exploring organizational aspects upstream in the chain of decisions or at higher levels of the hierarchy, as well as the intervention to change the determinants of these events.

Eliciting mixed emotions: A meta-analysis comparing models, types and measures.

Directory of Open Access Journals (Sweden)

Raul eBerrios

2015-04-01

Full Text Available The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model – dimensional or discrete – as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative. The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = .77, which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought.

Use of principal components analysis and three-dimensional atmospheric-transport models for reactor-consequence evaluation

International Nuclear Information System (INIS)

Gudiksen, P.H.; Walton, J.J.; Alpert, D.J.; Johnson, J.D.

1982-01-01

This work explores the use of principal components analysis coupled to three-dimensional atmospheric transport and dispersion models for evaluating the environmental consequences of reactor accidents. This permits the inclusion of meteorological data from multiple sites and the effects of topography in the consequence evaluation; features not normally included in such analyses. The technique identifies prevailing regional wind patterns and their frequencies for use in the transport and dispersion calculations. Analysis of a hypothetical accident scenario involving a release of radioactivity from a reactor situated in a river valley indicated the technique is quite useful whenever recurring wind patterns exist, as is often the case in complex terrain situations. Considerable differences were revealed in a comparison with results obtained from a more conventional Gaussian plume model using only the reactor site meteorology and no topographic effects

VALUING BENEFITS FROM WATER QUALITY IMPROVEMENTS USING KUHN TUCKER MODEL - A COMPARATIVE ANALYSIS ON UTILITY FUNCTIONAL FORMS-

Science.gov (United States)

Okuyama, Tadahiro

Kuhn-Tucker model, which has studied in recent years, is a benefit valuation technique using the revealed-preference data, and the feature is to treatvarious patterns of corner solutions flexibly. It is widely known for the benefit calculation using the revealed-preference data that a value of a benefit changes depending on a functional form. However, there are little studies which examine relationship between utility functions and values of benefits in Kuhn-Tucker model. The purpose of this study is to analysis an influence of the functional form to the value of a benefit. Six types of utility functions are employed for benefit calculations. The data of the recreational activity of 26 beaches of Miyagi Prefecture were employed. Calculation results indicated that Phaneuf and Siderelis (2003) and Whitehead et al.(2010)'s functional forms are useful for benefit calculations.

Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancer

Directory of Open Access Journals (Sweden)

Chung Jae

2009-06-01

Full Text Available Abstract Background Cisplatin and carboplatin are the primary first-line therapies for the treatment of ovarian cancer. However, resistance to these platinum-based drugs occurs in the large majority of initially responsive tumors, resulting in fully chemoresistant, fatal disease. Although the precise mechanism(s underlying the development of platinum resistance in late-stage ovarian cancer patients currently remains unknown, CpG-island (CGI methylation, a phenomenon strongly associated with aberrant gene silencing and ovarian tumorigenesis, may contribute to this devastating condition. Methods To model the onset of drug resistance, and investigate DNA methylation and gene expression alterations associated with platinum resistance, we treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation and mRNA expression microarray analyses. To identify chemoresistance-associated, biological pathways likely impacted by DNA methylation, promoter CGI methylation and mRNA expression profiles were integrated and subjected to pathway enrichment analysis. Results Promoter CGI methylation revealed a positive association (Spearman correlation of 0.99 between the total number of hypermethylated CGIs and GI50 values (i.e., increased drug resistance following successive cisplatin treatment cycles. In accord with that result, chemoresistance was reversible by DNA methylation inhibitors. Pathway enrichment analysis revealed hypermethylation-mediated repression of cell adhesion and tight junction pathways and hypomethylation-mediated activation of the cell growth-promoting pathways PI3K/Akt, TGF-beta, and cell cycle progression, which may contribute to the onset of chemoresistance in ovarian cancer cells. Conclusion Selective epigenetic disruption of distinct biological

Crash rates analysis in China using a spatial panel model

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Wonmongo Lacina Soro

2017-10-01

Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.

Modeling of the Dorsal Gradient across Species Reveals Interaction between Embryo Morphology and Toll Signaling Pathway during Evolution

Science.gov (United States)

Koslen, Hannah R.; Chiel, Hillel J.; Mizutani, Claudia Mieko

2014-01-01

Morphogenetic gradients are essential to allocate cell fates in embryos of varying sizes within and across closely related species. We previously showed that the maternal NF-κB/Dorsal (Dl) gradient has acquired different shapes in Drosophila species, which result in unequally scaled germ layers along the dorso-ventral axis and the repositioning of the neuroectodermal borders. Here we combined experimentation and mathematical modeling to investigate which factors might have contributed to the fast evolutionary changes of this gradient. To this end, we modified a previously developed model that employs differential equations of the main biochemical interactions of the Toll (Tl) signaling pathway, which regulates Dl nuclear transport. The original model simulations fit well the D. melanogaster wild type, but not mutant conditions. To broaden the applicability of this model and probe evolutionary changes in gradient distributions, we adjusted a set of 19 independent parameters to reproduce three quantified experimental conditions (i.e. Dl levels lowered, nuclear size and density increased or decreased). We next searched for the most relevant parameters that reproduce the species-specific Dl gradients. We show that adjusting parameters relative to morphological traits (i.e. embryo diameter, nuclear size and density) alone is not sufficient to reproduce the species Dl gradients. Since components of the Tl pathway simulated by the model are fast-evolving, we next asked which parameters related to Tl would most effectively reproduce these gradients and identified a particular subset. A sensitivity analysis reveals the existence of nonlinear interactions between the two fast-evolving traits tested above, namely the embryonic morphological changes and Tl pathway components. Our modeling further suggests that distinct Dl gradient shapes observed in closely related melanogaster sub-group lineages may be caused by similar sequence modifications in Tl pathway components, which

A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis.

Directory of Open Access Journals (Sweden)

Guillem Casanovas

2014-01-01

Full Text Available Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease.

A catalog of automated analysis methods for enterprise models.

Science.gov (United States)

Florez, Hector; Sánchez, Mario; Villalobos, Jorge

2016-01-01

Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

Equation-free analysis of agent-based models and systematic parameter determination

Science.gov (United States)

Thomas, Spencer A.; Lloyd, David J. B.; Skeldon, Anne C.

2016-12-01

Agent based models (ABM)s are increasingly used in social science, economics, mathematics, biology and computer science to describe time dependent systems in circumstances where a description in terms of equations is difficult. Yet few tools are currently available for the systematic analysis of ABM behaviour. Numerical continuation and bifurcation analysis is a well-established tool for the study of deterministic systems. Recently, equation-free (EF) methods have been developed to extend numerical continuation techniques to systems where the dynamics are described at a microscopic scale and continuation of a macroscopic property of the system is considered. To date, the practical use of EF methods has been limited by; (1) the over-head of application-specific implementation; (2) the laborious configuration of problem-specific parameters; and (3) large ensemble sizes (potentially) leading to computationally restrictive run-times. In this paper we address these issues with our tool for the EF continuation of stochastic systems, which includes algorithms to systematically configuration problem specific parameters and enhance robustness to noise. Our tool is generic and can be applied to any 'black-box' simulator and determines the essential EF parameters prior to EF analysis. Robustness is significantly improved using our convergence-constraint with a corrector-repeat (C3R) method. This algorithm automatically detects outliers based on the dynamics of the underlying system enabling both an order of magnitude reduction in ensemble size and continuation of systems at much higher levels of noise than classical approaches. We demonstrate our method with application to several ABM models, revealing parameter dependence, bifurcation and stability analysis of these complex systems giving a deep understanding of the dynamical behaviour of the models in a way that is not otherwise easily obtainable. In each case we demonstrate our systematic parameter determination stage for

Intercity Travel Demand Analysis Model

OpenAIRE

Ming Lu; Hai Zhu; Xia Luo; Lei Lei

2014-01-01

It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model...

Uncertainty analysis of environmental models

International Nuclear Information System (INIS)

Monte, L.

1990-01-01

In the present paper an evaluation of the output uncertainty of an environmental model for assessing the transfer of 137 Cs and 131 I in the human food chain are carried out on the basis of a statistical analysis of data reported by the literature. The uncertainty analysis offers the oppotunity of obtaining some remarkable information about the uncertainty of models predicting the migration of non radioactive substances in the environment mainly in relation to the dry and wet deposition

Potential microRNA-mediated oncogenic intercellular communication revealed by pan-cancer analysis

Science.gov (United States)

Li, Yue; Zhang, Zhaolei

2014-11-01

Carcinogenesis consists of oncogenesis and metastasis, and intriguingly microRNAs (miRNAs) are involved in both processes. Although aberrant miRNA activities are prevalent in diverse tumor types, the exact mechanisms for how they regulate cancerous processes are not always clear. To this end, we performed a large-scale pan-cancer analysis via a novel probabilistic approach to infer recurrent miRNA-target interactions implicated in 12 cancer types using data from The Cancer Genome Atlas. We discovered ~20,000 recurrent miRNA regulations, which are enriched for cancer-related miRNAs/genes. Notably, miRNA 200 family (miR-200/141/429) is among the most prominent miRNA regulators, which is known to be involved in metastasis. Importantly, the recurrent miRNA regulatory network is not only enriched for cancer pathways but also for extracellular matrix (ECM) organization and ECM-receptor interactions. The results suggest an intriguing cancer mechanism involving miRNA-mediated cell-to-cell communication, which possibly involves delivery of tumorigenic miRNA messengers to adjacent cells via exosomes. Finally, survival analysis revealed 414 recurrent-prognostic associations, where both gene and miRNA involved in each interaction conferred significant prognostic power in one or more cancer types. Together, our comprehensive pan-cancer analysis provided not only biological insights into metastasis but also brought to bear the clinical relevance of the proposed recurrent miRNA-gene associations.

Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

Science.gov (United States)

Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

2016-05-01

Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights

Parametric uncertainty and global sensitivity analysis in a model of the carotid bifurcation: Identification and ranking of most sensitive model parameters.

Science.gov (United States)

Gul, R; Bernhard, S

2015-11-01

In computational cardiovascular models, parameters are one of major sources of uncertainty, which make the models unreliable and less predictive. In order to achieve predictive models that allow the investigation of the cardiovascular diseases, sensitivity analysis (SA) can be used to quantify and reduce the uncertainty in outputs (pressure and flow) caused by input (electrical and structural) model parameters. In the current study, three variance based global sensitivity analysis (GSA) methods; Sobol, FAST and a sparse grid stochastic collocation technique based on the Smolyak algorithm were applied on a lumped parameter model of carotid bifurcation. Sensitivity analysis was carried out to identify and rank most sensitive parameters as well as to fix less sensitive parameters at their nominal values (factor fixing). In this context, network location and temporal dependent sensitivities were also discussed to identify optimal measurement locations in carotid bifurcation and optimal temporal regions for each parameter in the pressure and flow waves, respectively. Results show that, for both pressure and flow, flow resistance (R), diameter (d) and length of the vessel (l) are sensitive within right common carotid (RCC), right internal carotid (RIC) and right external carotid (REC) arteries, while compliance of the vessels (C) and blood inertia (L) are sensitive only at RCC. Moreover, Young's modulus (E) and wall thickness (h) exhibit less sensitivities on pressure and flow at all locations of carotid bifurcation. Results of network location and temporal variabilities revealed that most of sensitivity was found in common time regions i.e. early systole, peak systole and end systole. Copyright © 2015 Elsevier Inc. All rights reserved.

Simulation modeling and analysis with Arena

CERN Document Server

Altiok, Tayfur

2007-01-01

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment.” It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeli...

Puerto Rico Revealed Preference Survey Data 2004

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Revealed preference models provide insights into recreational angler behavior and the economic value of recreational fishing trips. Revealed preference data is...

On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model

International Nuclear Information System (INIS)

Unkel, Steffen; Belka, Claus; Lauber, Kirsten

2016-01-01

The most frequently used method to quantitatively describe the response to ionizing irradiation in terms of clonogenic survival is the linear-quadratic (LQ) model. In the LQ model, the logarithm of the surviving fraction is regressed linearly on the radiation dose by means of a second-degree polynomial. The ratio of the estimated parameters for the linear and quadratic term, respectively, represents the dose at which both terms have the same weight in the abrogation of clonogenic survival. This ratio is known as the α/β ratio. However, there are plausible scenarios in which the α/β ratio fails to sufficiently reflect differences between dose-response curves, for example when curves with similar α/β ratio but different overall steepness are being compared. In such situations, the interpretation of the LQ model is severely limited. Colony formation assays were performed in order to measure the clonogenic survival of nine human pancreatic cancer cell lines and immortalized human pancreatic ductal epithelial cells upon irradiation at 0-10 Gy. The resulting dataset was subjected to LQ regression and non-linear log-logistic regression. Dimensionality reduction of the data was performed by cluster analysis and principal component analysis. Both the LQ model and the non-linear log-logistic regression model resulted in accurate approximations of the observed dose-response relationships in the dataset of clonogenic survival. However, in contrast to the LQ model the non-linear regression model allowed the discrimination of curves with different overall steepness but similar α/β ratio and revealed an improved goodness-of-fit. Additionally, the estimated parameters in the non-linear model exhibit a more direct interpretation than the α/β ratio. Dimensionality reduction of clonogenic survival data by means of cluster analysis was shown to be a useful tool for classifying radioresistant and sensitive cell lines. More quantitatively, principal component analysis allowed

Analysis of automotive rolling lobe air spring under alternative factors with finite element model

International Nuclear Information System (INIS)

Wong, Pak Kin; Xie, Zhengchao; Zhao, Jing; Xu, Tao; He, Feng

2014-01-01

Air springs are widely used in automotive suspensions for their superior performance in terms of low friction motion, adjustable load carrying capacity and user-friendly ride height control. However, it has posed great difficulties in constructing an accurate model as well as the analysis of the influence of alternative factors, such as cord angle, cord diameter and initial pressure. In this paper, a numerical model of the rolling lobe air spring (RLAS) is built by using finite element method and compared with an existing analytical model. An experiment with respect to the vertical stiffness of the RLAS is carried out to validate the accuracy of the proposed model. Evaluation result reveals that the existing analytical model cannot represent the performance of the RLAS very well, whereas the accuracy of the numerical model is very good. With the verified numerical model, the impacts of many alternative factors on the characteristics of the RLAS are analyzed. Numerical results show that the newly proposed model is reliable to determine the vertical characteristic and physical dimensions of the RLAS under the alternative factors.

Using principal component analysis to capture individual differences within a unified neuropsychological model of chronic post-stroke aphasia: Revealing the unique neural correlates of speech fluency, phonology and semantics.

Science.gov (United States)

Halai, Ajay D; Woollams, Anna M; Lambon Ralph, Matthew A

2017-01-01

Individual differences in the performance profiles of neuropsychologically-impaired patients are pervasive yet there is still no resolution on the best way to model and account for the variation in their behavioural impairments and the associated neural correlates. To date, researchers have generally taken one of three different approaches: a single-case study methodology in which each case is considered separately; a case-series design in which all individual patients from a small coherent group are examined and directly compared; or, group studies, in which a sample of cases are investigated as one group with the assumption that they are drawn from a homogenous category and that performance differences are of no interest. In recent research, we have developed a complementary alternative through the use of principal component analysis (PCA) of individual data from large patient cohorts. This data-driven approach not only generates a single unified model for the group as a whole (expressed in terms of the emergent principal components) but is also able to capture the individual differences between patients (in terms of their relative positions along the principal behavioural axes). We demonstrate the use of this approach by considering speech fluency, phonology and semantics in aphasia diagnosis and classification, as well as their unique neural correlates. PCA of the behavioural data from 31 patients with chronic post-stroke aphasia resulted in four statistically-independent behavioural components reflecting phonological, semantic, executive-cognitive and fluency abilities. Even after accounting for lesion volume, entering the four behavioural components simultaneously into a voxel-based correlational methodology (VBCM) analysis revealed that speech fluency (speech quanta) was uniquely correlated with left motor cortex and underlying white matter (including the anterior section of the arcuate fasciculus and the frontal aslant tract), phonological skills with

Compartmentation of glycogen metabolism revealed from 13C isotopologue distributions

Directory of Open Access Journals (Sweden)

Marin de Mas Igor

2011-10-01

Full Text Available Abstract Background Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution. Results The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated 13C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate. The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells. Conclusions The analysis of compartmentation of metabolic networks based on the measured 13C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured 13C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose

Sensitivity Analysis of Simulation Models

NARCIS (Netherlands)

Kleijnen, J.P.C.

2009-01-01

This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

Codimension-two bifurcation analysis on firing activities in Chay neuron model

International Nuclear Information System (INIS)

Duan Lixia; Lu Qishao

2006-01-01

Using codimension-two bifurcation analysis in the Chay neuron model, the relationship between the electric activities and the parameters of neurons is revealed. The whole parameter space is divided into two parts, that is, the firing and silence regions of neurons. It is found that the transition sets between firing and silence regions are composed of the Hopf bifurcation curves of equilibrium states and the saddle-node bifurcation curves of limit cycles, with some codimension-two bifurcation points. The transitions from silence to firing in neurons are due to the Hopf bifurcation or the fold limit cycle bifurcation, but the codimension-two singularities lead to complexity in dynamical behaviour of neuronal firing

Codimension-two bifurcation analysis on firing activities in Chay neuron model

Energy Technology Data Exchange (ETDEWEB)

Duan Lixia [School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083 (China); Lu Qishao [School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083 (China)]. E-mail: qishaolu@hotmail.com

2006-12-15

Using codimension-two bifurcation analysis in the Chay neuron model, the relationship between the electric activities and the parameters of neurons is revealed. The whole parameter space is divided into two parts, that is, the firing and silence regions of neurons. It is found that the transition sets between firing and silence regions are composed of the Hopf bifurcation curves of equilibrium states and the saddle-node bifurcation curves of limit cycles, with some codimension-two bifurcation points. The transitions from silence to firing in neurons are due to the Hopf bifurcation or the fold limit cycle bifurcation, but the codimension-two singularities lead to complexity in dynamical behaviour of neuronal firing.

Mechanical influences on morphogenesis of the knee joint revealed through morphological, molecular and computational analysis of immobilised embryos.

Directory of Open Access Journals (Sweden)

Karen A Roddy

2011-02-01

Full Text Available Very little is known about the regulation of morphogenesis in synovial joints. Mechanical forces generated from muscle contractions are required for normal development of several aspects of normal skeletogenesis. Here we show that biophysical stimuli generated by muscle contractions impact multiple events during chick knee joint morphogenesis influencing differential growth of the skeletal rudiment epiphyses and patterning of the emerging tissues in the joint interzone. Immobilisation of chick embryos was achieved through treatment with the neuromuscular blocking agent Decamethonium Bromide. The effects on development of the knee joint were examined using a combination of computational modelling to predict alterations in biophysical stimuli, detailed morphometric analysis of 3D digital representations, cell proliferation assays and in situ hybridisation to examine the expression of a selected panel of genes known to regulate joint development. This work revealed the precise changes to shape, particularly in the distal femur, that occur in an altered mechanical environment, corresponding to predicted changes in the spatial and dynamic patterns of mechanical stimuli and region specific changes in cell proliferation rates. In addition, we show altered patterning of the emerging tissues of the joint interzone with the loss of clearly defined and organised cell territories revealed by loss of characteristic interzone gene expression and abnormal expression of cartilage markers. This work shows that local dynamic patterns of biophysical stimuli generated from muscle contractions in the embryo act as a source of positional information guiding patterning and morphogenesis of the developing knee joint.

Mechanical Influences on Morphogenesis of the Knee Joint Revealed through Morphological, Molecular and Computational Analysis of Immobilised Embryos

Science.gov (United States)

Roddy, Karen A.; Prendergast, Patrick J.; Murphy, Paula

2011-01-01

Very little is known about the regulation of morphogenesis in synovial joints. Mechanical forces generated from muscle contractions are required for normal development of several aspects of normal skeletogenesis. Here we show that biophysical stimuli generated by muscle contractions impact multiple events during chick knee joint morphogenesis influencing differential growth of the skeletal rudiment epiphyses and patterning of the emerging tissues in the joint interzone. Immobilisation of chick embryos was achieved through treatment with the neuromuscular blocking agent Decamethonium Bromide. The effects on development of the knee joint were examined using a combination of computational modelling to predict alterations in biophysical stimuli, detailed morphometric analysis of 3D digital representations, cell proliferation assays and in situ hybridisation to examine the expression of a selected panel of genes known to regulate joint development. This work revealed the precise changes to shape, particularly in the distal femur, that occur in an altered mechanical environment, corresponding to predicted changes in the spatial and dynamic patterns of mechanical stimuli and region specific changes in cell proliferation rates. In addition, we show altered patterning of the emerging tissues of the joint interzone with the loss of clearly defined and organised cell territories revealed by loss of characteristic interzone gene expression and abnormal expression of cartilage markers. This work shows that local dynamic patterns of biophysical stimuli generated from muscle contractions in the embryo act as a source of positional information guiding patterning and morphogenesis of the developing knee joint. PMID:21386908

Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

Directory of Open Access Journals (Sweden)

Hiekata Takashi

2006-01-01

Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

Stochastic modelling of shifts in allele frequencies reveals a strongly polygynous mating system in the re-introduced Asiatic wild ass.

Science.gov (United States)

Renan, Sharon; Greenbaum, Gili; Shahar, Naama; Templeton, Alan R; Bouskila, Amos; Bar-David, Shirli

2015-04-01

Small populations are prone to loss of genetic variation and hence to a reduction in their evolutionary potential. Therefore, studying the mating system of small populations and its potential effects on genetic drift and genetic diversity is of high importance for their viability assessments. The traditional method for studying genetic mating systems is paternity analysis. Yet, as small populations are often rare and elusive, the genetic data required for paternity analysis are frequently unavailable. The endangered Asiatic wild ass (Equus hemionus), like all equids, displays a behaviourally polygynous mating system; however, the level of polygyny has never been measured genetically in wild equids. Combining noninvasive genetic data with stochastic modelling of shifts in allele frequencies, we developed an alternative approach to paternity analysis for studying the genetic mating system of the re-introduced Asiatic wild ass in the Negev Desert, Israel. We compared the shifts in allele frequencies (as a measure of genetic drift) that have occurred in the wild ass population since re-introduction onset to simulated scenarios under different proportions of mating males. We revealed a strongly polygynous mating system in which less than 25% of all males participate in the mating process each generation. This strongly polygynous mating system and its potential effect on the re-introduced population's genetic diversity could have significant consequences for the long-term persistence of the population in the Negev. The stochastic modelling approach and the use of allele-frequency shifts can be further applied to systems that are affected by genetic drift and for which genetic data are limited. © 2015 John Wiley & Sons Ltd.

Model parameterization as method for data analysis in dendroecology

Science.gov (United States)

Tychkov, Ivan; Shishov, Vladimir; Popkova, Margarita

2017-04-01

There is no argue in usefulness of process-based models in ecological studies. Only limitations is how developed algorithm of model and how it will be applied for research. Simulation of tree-ring growth based on climate provides valuable information of tree-ring growth response on different environmental conditions, but also shares light on species-specifics of tree-ring growth process. Visual parameterization of the Vaganov-Shashkin model, allows to estimate non-linear response of tree-ring growth based on daily climate data: daily temperature, estimated day light and soil moisture. Previous using of the VS-Oscilloscope (a software tool of the visual parameterization) shows a good ability to recreate unique patterns of tree-ring growth for coniferous species in Siberian Russia, USA, China, Mediterranean Spain and Tunisia. But using of the models mostly is one-sided to better understand different tree growth processes, opposite to statistical methods of analysis (e.g. Generalized Linear Models, Mixed Models, Structural Equations.) which can be used for reconstruction and forecast. Usually the models are used either for checking of new hypothesis or quantitative assessment of physiological tree growth data to reveal a growth process mechanisms, while statistical methods used for data mining assessment and as a study tool itself. The high sensitivity of the model's VS-parameters reflects the ability of the model to simulate tree-ring growth and evaluates value of limiting growth climate factors. Precise parameterization of VS-Oscilloscope provides valuable information about growth processes of trees and under what conditions these processes occur (e.g. day of growth season onset, length of season, value of minimal/maximum temperature for tree-ring growth, formation of wide or narrow rings etc.). The work was supported by the Russian Science Foundation (RSF # 14-14-00219)

Site effect classification based on microtremor data analysis using concentration-area fractal model

Science.gov (United States)

Adib, A.; Afzal, P.; Heydarzadeh, K.

2014-07-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, Central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modeling reveal that proper soil types are located around the central city. The results derived via the fractal modeling were utilized to improve the Nogoshi's classification results in the Meybod city. The resulted categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.

Modeling and analysis of Off-beam lidar returns from thick clouds, snow, and sea ice

International Nuclear Information System (INIS)

Varnai, T.; Cahalan, R. F.

2009-01-01

A group of recently developed lidar (laser ranging and detection) systems can detect signals returning from several wide field-of-views, allowing them to observe the way laser pulses spread in thick media. The new capability enabled accurate measurements of cloud geometrical thickness and promises improved measurements of internal cloud structure as well as snow and sea ice thickness. This paper presents a brief overview of radiation transport simulation techniques and data analysis methods that were developed for multi-view lidar applications and for and considering multiple scattering effects in single-view lidar data. In discussing methods for simulating the three-dimensional spread of lidar pulses, we present initial results from Phase 3 of the Intercomparison of 3-D Radiation Codes (I3RC) project. The results reveal some differences in the capabilities of participating models, while good agreement among several models provides consensus results suitable for testing future models. Detailed numerical results are available at the I3RC web site at http://i3rc.gsfc.nasa. gov. In considering data analysis methods, we focus on the Thickness from Off-beam Returns (THOR) lidar. THOR proved successful in measuring the geometrical thickness of optically thick clouds; here we focus on its potential for retrieving the vertical profile of scattering coefficient in clouds and for measuring snow thickness. Initial observations suggest considerable promise but also reveal some limitations, for example that the maximum retrievable snow thickness drops from about 0.5 m in pristine areas to about 0.15 m in polluted regions. (authors)

Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

Science.gov (United States)

Filo, Maurice G.

This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

Intestinal transcriptome analysis revealed differential salinity adaptation between two tilapiine species.

Science.gov (United States)

Ronkin, Dana; Seroussi, Eyal; Nitzan, Tali; Doron-Faigenboim, Adi; Cnaani, Avner

2015-03-01

Tilapias are a group of freshwater species, which vary in their ability to adapt to high salinity water. Osmotic regulation in fish is conducted mainly in the gills, kidney, and gastrointestinal tract (GIT). The mechanisms involved in ion and water transport through the GIT is not well-characterized, with only a few described complexes. Comparing the transcriptome of the anterior and posterior intestinal sections of a freshwater and saltwater adapted fish by deep-sequencing, we examined the salinity adaptation of two tilapia species: the high salinity-tolerant Oreochromis mossambicus (Mozambique tilapia), and the less salinity-tolerant Oreochromis niloticus (Nile tilapia). This comparative analysis revealed high similarity in gene expression response to salinity change between species in the posterior intestine and large differences in the anterior intestine. Furthermore, in the anterior intestine 68 genes were saltwater up-regulated in one species and down-regulated in the other species (47 genes up-regulated in O. niloticus and down-regulated in O. mossambicus, with 21 genes showing the reverse pattern). Gene ontology (GO) analysis showed a high proportion of transporter and ion channel function among these genes. The results of this study point to a group of genes that differed in their salinity-dependent regulation pattern in the anterior intestine as potentially having a role in the differential salinity tolerance of these two closely related species. Copyright © 2015 Elsevier Inc. All rights reserved.

Reliability analysis and operator modelling

International Nuclear Information System (INIS)

Hollnagel, Erik

1996-01-01

The paper considers the state of operator modelling in reliability analysis. Operator models are needed in reliability analysis because operators are needed in process control systems. HRA methods must therefore be able to account both for human performance variability and for the dynamics of the interaction. A selected set of first generation HRA approaches is briefly described in terms of the operator model they use, their classification principle, and the actual method they propose. In addition, two examples of second generation methods are also considered. It is concluded that first generation HRA methods generally have very simplistic operator models, either referring to the time-reliability relationship or to elementary information processing concepts. It is argued that second generation HRA methods must recognise that cognition is embedded in a context, and be able to account for that in the way human reliability is analysed and assessed

Modeling and Analysis of Wrinkled Membranes: An Overview

Science.gov (United States)

Yang, B.; Ding, H.; Lou, M.; Fang, H.; Broduer, Steve (Technical Monitor)

2001-01-01

Thin-film membranes are basic elements of a variety of space inflatable/deployable structures. Wrinkling degrades the performance and reliability of these membrane structures, and hence has been a topic of continued interest. Wrinkling analysis of membranes for general geometry and arbitrary boundary conditions is quite challenging. The objective of this presentation is two-fold. Firstly, the existing models of wrinkled membranes and related numerical solution methods are reviewed. The important issues to be discussed are the capability of a membrane model to characterize taut, wrinkled and slack states of membranes in a consistent and physically reasonable manner; the ability of a wrinkling analysis method to predict the formation and growth of wrinkled regions, and to determine out-of-plane deformation and wrinkled waves; the convergence of a numerical solution method for wrinkling analysis; and the compatibility of a wrinkling analysis with general-purpose finite element codes. According to this review, several opening issues in modeling and analysis of wrinkled membranes that are to be addressed in future research are summarized, The second objective of this presentation is to discuss a newly developed membrane model of two viable parameters (2-VP model) and associated parametric finite element method (PFEM) for wrinkling analysis are introduced. The innovations and advantages of the proposed membrane model and PFEM-based wrinkling analysis are: (1) Via a unified stress-strain relation; the 2-VP model treat the taut, wrinkled, and slack states of membranes consistently; (2) The PFEM-based wrinkling analysis has guaranteed convergence; (3) The 2-VP model along with PFEM is capable of predicting membrane out-of-plane deformations; and (4) The PFEM can be integrated into any existing finite element code. Preliminary numerical examples are also included in this presentation to demonstrate the 2-VP model and PFEM-based wrinkling analysis approach.

Computer modelling reveals new conformers of the ATP binding loop of Na+/K+-ATPase involved in the transphosphorylation process of the sodium pump.

Science.gov (United States)

Tejral, Gracian; Sopko, Bruno; Necas, Alois; Schoner, Wilhelm; Amler, Evzen

2017-01-01

Hydrolysis of ATP by Na + /K + -ATPase, a P-Type ATPase, catalyzing active Na + and K + transport through cellular membranes leads transiently to a phosphorylation of its catalytical α -subunit. Surprisingly, three-dimensional molecular structure analysis of P-type ATPases reveals that binding of ATP to the N-domain connected by a hinge to the P-domain is much too far away from the Asp 369 to allow the transfer of ATP's terminal phosphate to its aspartyl-phosphorylation site. In order to get information for how the transfer of the γ -phosphate group of ATP to the Asp 369 is achieved, analogous molecular modeling of the M 4 -M 5 loop of ATPase was performed using the crystal data of Na + /K + -ATPase of different species. Analogous molecular modeling of the cytoplasmic loop between Thr 338 and Ile 760 of the α 2 -subunit of Na + /K + -ATPase and the analysis of distances between the ATP binding site and phosphorylation site revealed the existence of two ATP binding sites in the open conformation; the first one close to Phe 475 in the N-domain, the other one close to Asp 369 in the P-domain. However, binding of Mg 2+ •ATP to any of these sites in the "open conformation" may not lead to phosphorylation of Asp 369 . Additional conformations of the cytoplasmic loop were found wobbling between "open conformation"  "semi-open conformation  "closed conformation" in the absence of 2Mg 2+ •ATP. The cytoplasmic loop's conformational change to the "semi-open conformation"-characterized by a hydrogen bond between Arg 543 and Asp 611 -triggers by binding of 2Mg 2+ •ATP to a single ATP site and conversion to the "closed conformation" the phosphorylation of Asp 369 in the P-domain, and hence the start of Na + /K + -activated ATP hydrolysis.

Molecular evolution and diversification of snake toxin genes, revealed by analysis of intron sequences.

Science.gov (United States)

Fujimi, T J; Nakajyo, T; Nishimura, E; Ogura, E; Tsuchiya, T; Tamiya, T

2003-08-14

The genes encoding erabutoxin (short chain neurotoxin) isoforms (Ea, Eb, and Ec), LsIII (long chain neurotoxin) and a novel long chain neurotoxin pseudogene were cloned from a Laticauda semifasciata genomic library. Short and long chain neurotoxin genes were also cloned from the genome of Laticauda laticaudata, a closely related species of L. semifasciata, by PCR. A putative matrix attached region (MAR) sequence was found in the intron I of the LsIII gene. Comparative analysis of 11 structurally relevant snake toxin genes (three-finger-structure toxins) revealed the molecular evolution of these toxins. Three-finger-structure toxin genes diverged from a common ancestor through two types of evolutionary pathways (long and short types), early in the course of evolution. At a later stage of evolution in each gene, the accumulation of mutations in the exons, especially exon II, by accelerated evolution may have caused the increased diversification in their functions. It was also revealed that the putative MAR sequence found in the LsIII gene was integrated into the gene after the species-level divergence.

Hierarchical modeling and analysis for spatial data

CERN Document Server

Banerjee, Sudipto; Gelfand, Alan E

2003-01-01

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

Tree analysis modeling of the associations between PHQ-9 depressive symptoms and doctor diagnosis of depression in primary care.

Science.gov (United States)

Chin, Weng-Yee; Wan, Eric Yuk Fai; Dowrick, Christopher; Arroll, Bruce; Lam, Cindy Lo Kuen

2018-04-26

The aim of this study was to explore the relationship between patient self-reported Patient Health Questionnaire-9 (PHQ-9) symptoms and doctor diagnosis of depression using a tree analysis approach. This was a secondary analysis on a dataset obtained from 10 179 adult primary care patients and 59 primary care physicians (PCPs) across Hong Kong. Patients completed a waiting room survey collecting data on socio-demographics and the PHQ-9. Blinded doctors documented whether they thought the patient had depression. Data were analyzed using multiple logistic regression and conditional inference decision tree modeling. PCPs diagnosed 594 patients with depression. Logistic regression identified gender, age, employment status, past history of depression, family history of mental illness and recent doctor visit as factors associated with a depression diagnosis. Tree analyses revealed different pathways of association between PHQ-9 symptoms and depression diagnosis for patients with and without past depression. The PHQ-9 symptom model revealed low mood, sense of worthlessness, fatigue, sleep disturbance and functional impairment as early classifiers. The PHQ-9 total score model revealed cut-off scores of >12 and >15 were most frequently associated with depression diagnoses in patients with and without past depression. A past history of depression is the most significant factor associated with the diagnosis of depression. PCPs appear to utilize a hypothetical-deductive problem-solving approach incorporating pre-test probability, with different associated factors for patients with and without past depression. Diagnostic thresholds may be too low for patients with past depression and too high for those without, potentially leading to over and under diagnosis of depression.

The Revealed Competitiveness of Major Ports in the East Asian Region: An Additive Market Share Analysis

Directory of Open Access Journals (Sweden)

Tae Seung Kim

2015-12-01

Full Text Available In the single cargo market, the ordinary market share analysis method has been the representative tool for revealed competitiveness analysis. This paper develops and employs an applied market share index called the additive market share (AMS. Data are collected from 15 major container ports for the 1998-2013 period. In comparison to the results of an ordinary market share analysis, the highest AMS is observed for the Bohai Rim port cluster from 2008, not for the Yangtze River cluster or the Pearl River cluster. There are substitutable relationships between Yangtze River and non-Chinese ports and between Pearl River and Bohai Rim ports from 2001. Finally, there is an internal competition at Pearl River and Yangtze River ports, whereas Bohai Rim and non-Chinese ports show internally complementary relationships.

Assessing Asset Pricing Models Using Revealed Preference

OpenAIRE

Jonathan B. Berk; Jules H. van Binsbergen

2014-01-01

We propose a new method of testing asset pricing models that relies on using quantities rather than prices or returns. We use the capital flows into and out of mutual funds to infer which risk model investors use. We derive a simple test statistic that allows us to infer, from a set of candidate models, the model that is closest to the model that investors use in making their capital allocation decisions. Using this methodology, we find that of the models most commonly used in the literature,...

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

Science.gov (United States)

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Evaluation of Thermal Margin Analysis Models for SMART

International Nuclear Information System (INIS)

Seo, Kyong Won; Kwon, Hyuk; Hwang, Dae Hyun

2011-01-01

Thermal margin of SMART would be analyzed by three different methods. The first method is subchannel analysis by MATRA-S code and it would be a reference data for the other two methods. The second method is an on-line few channel analysis by FAST code that would be integrated into SCOPS/SCOMS. The last one is a single channel module analysis by safety analysis. Several thermal margin analysis models for SMART reactor core by subchannel analysis were setup and tested. We adopted a strategy of single stage analysis for thermal analysis of SMART reactor core. The model should represent characteristics of the SMART reactor core including hot channel. The model should be simple as possible to be evaluated within reasonable time and cost

Analysis of third-party certification approaches using an occupational health and safety conformity-assessment model.

Science.gov (United States)

Redinger, C F; Levine, S P

1998-11-01

The occupational health and safety conformity-assessment model presented in this article was developed (1) to analyze 22 public and private programs to determine the extent to which these programs use third parties in conformity-assessment determinations, and (2) to establish a framework to guide future policy developments related to the use of third parties in occupational health and safety conformity-assessment activities. The units of analysis for this study included select Occupational Safety and Health Administration programs and standards, International Organization for Standardization-based standards and guidelines, and standards and guidelines developed by nongovernmental bodies. The model is based on a 15-cell matrix that categorizes first-, second-, and third-party activities in terms of assessment, accreditation, and accreditation-recognition activities. The third-party component of the model has three categories: industrial hygiene/safety testing and sampling; product, equipment, and laboratory certification; and, occupational health and safety management system registration/certification. Using the model, 16 of the 22 programs were found to have a third-party component in their conformity-assessment structure. The analysis revealed that (1) the model provides a useful means to describe and analyze various third-party approaches, (2) the model needs modification to capture aspects of traditional governmental conformity-assessment/enforcement activities, and (3) several existing third-party conformity-assessment systems offer robust models that can guide future third-party policy formulation and implementation activities.

Phylogenetic analysis reveals two genotypes of the emerging fungus Mucor indicus, an opportunistic human pathogen in immunocompromised patients

NARCIS (Netherlands)

Taj-Aldeen, Saad J.; Almaslamani, Muna; Theelen, B.J.F.; Boekhout, Teun

2017-01-01

Mucormycosis is a rare fungal infection caused by Mucor indicus. Phylogenetic analysis of many M. indicus isolates, mainly sampled from different clinical and environmental specimens collected worldwide, revealed two genotypes, I and II, based on ITS and D1/D2 LSU rDNA sequences. A retrospective

Molecular dynamics analysis reveals structural insights into mechanism of nicotine N-demethylation catalyzed by tobacco cytochrome P450 mono-oxygenase.

Directory of Open Access Journals (Sweden)

Shan Wang

Full Text Available CYP82E4, a cytochrome P450 monooxygenase, has nicotine N-demethylase (NND activity, which mediates the bioconversion of nicotine into nornicotine in senescing tobacco leaves. Nornicotine is a precursor of the carcinogen, tobacco-specific nitrosamine. CYP82E3 is an ortholog of CYP82E4 with 95% sequence identity, but it lacks NND activity. A recent site-directed mutagenesis study revealed that a single amino acid substitution, i.e., cysteine to tryptophan at the 330 position in the middle of protein, restores the NND activity of CYP82E3 entirely. However, the same amino acid change caused the loss of the NND activity of CYP82E4. To determine the mechanism of the functional turnover of the two molecules, four 3D structures, i.e., the two molecules and their corresponding cys-trp mutants were modeled. The resulting structures exhibited that the mutation site is far from the active site, which suggests that no direct interaction occurs between the two sites. Simulation studies in different biological scenarios revealed that the mutation introduces a conformation drift with the largest change at the F-G loop. The dynamics trajectories analysis using principal component analysis and covariance analysis suggests that the single amino acid change causes the opening and closing of the transfer channels of the substrates, products, and water by altering the motion of the F-G and B-C loops. The motion of helix I is also correlated with the motion of both the F-G loop and the B-C loop and; the single amino acid mutation resulted in the curvature of helix I. These results suggest that the single amino acid mutation outside the active site region may have indirectly mediated the flexibility of the F-G and B-C loops through helix I, causing a functional turnover of the P450 monooxygenase.

Construction of finite element model and stress analysis of anterior cruciate ligament tibial insertion.

Science.gov (United States)

Dai, Can; Yang, Liu; Guo, Lin; Wang, Fuyou; Gou, Jingyue; Deng, Zhilong

2015-01-01

The aim of the present study was to develop a more realistic finite element (FE) model of the human anterior cruciate ligament (ACL) tibial insertion and to analyze the stress distribution in the ACL internal fibers under load. The ACL tibial insertions were processed histologically. With Photoshop software, digital images taken from the histological slides were collaged, contour lines were drawn, and different gray values were filled based on the structure. The data were exported to Amira software and saved as ".hmascii" file. This document was imported into HyperMesh software. The solid mesh model generated using HyperMesh software was imported into Abaqus software. The material properties were introduced, boundary conditions were set, and load was added to carry out the FE analysis. The stress distribution of the ACL internal fibers was uneven. The lowest stress could be observed in the ACL lateral fibers under tensile and shear load. The establishment of ACL tibial insertion FE model and mechanical analysis could reveal the stress distribution in the ACL internal fibers under load. There was greater load carrying capacity in the ACL lateral fibers which could sustain greater tensile and shear forces.

Domain specific modeling and analysis

NARCIS (Netherlands)

Jacob, Joost Ferdinand

2008-01-01

It is desirable to model software systems in such a way that analysis of the systems, and tool development for such analysis, is readily possible and feasible in the context of large scientific research projects. This thesis emphasizes the methodology that serves as a basis for such developments.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration.

Science.gov (United States)

Nacher, Jose C; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Using structural equation modeling for network meta-analysis.

Science.gov (United States)

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

Mutational analysis of Sep-tRNA:Cys-tRNA synthase reveals critical residues for tRNA-dependent cysteine formation.

Science.gov (United States)

Helgadóttir, Sunna; Sinapah, Sylvie; Söll, Dieter; Ling, Jiqiang

2012-01-02

In methanogenic archaea, Sep-tRNA:Cys-tRNA synthase (SepCysS) converts Sep-tRNA(Cys) to Cys-tRNA(Cys). The mechanism of tRNA-dependent cysteine formation remains unclear due to the lack of functional studies. In this work, we mutated 19 conserved residues in Methanocaldococcus jannaschii SepCysS, and employed an in vivo system to determine the activity of the resulting variants. Our results show that three active-site cysteines (Cys39, Cys42 and Cys247) are essential for SepCysS activity. In addition, combined with structural modeling, our mutational and functional analyses also reveal multiple residues that are important for the binding of PLP, Sep and tRNA. Our work thus represents the first systematic functional analysis of conserved residues in archaeal SepCysSs, providing insights into the catalytic and substrate binding mechanisms of this poorly characterized enzyme. Copyright © 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

RNA-Seq Analysis Reveals MAPKKK Family Members Related to Drought Tolerance in Maize

Science.gov (United States)

Ren, Wen; Yang, Fengling; He, Hang; Zhao, Jiuran

2015-01-01

The mitogen-activated protein kinase (MAPK) cascade is an evolutionarily conserved signal transduction pathway that is involved in plant development and stress responses. As the first component of this phosphorelay cascade, mitogen-activated protein kinase kinase kinases (MAPKKKs) act as adaptors linking upstream signaling steps to the core MAPK cascade to promote the appropriate cellular responses; however, the functions of MAPKKKs in maize are unclear. Here, we identified 71 MAPKKK genes, of which 14 were novel, based on a computational analysis of the maize (Zea mays L.) genome. Using an RNA-seq analysis in the leaf, stem and root of maize under well-watered and drought-stress conditions, we identified 5,866 differentially expressed genes (DEGs), including 8 MAPKKK genes responsive to drought stress. Many of the DEGs were enriched in processes such as drought stress, abiotic stimulus, oxidation-reduction, and metabolic processes. The other way round, DEGs involved in processes such as oxidation, photosynthesis, and starch, proline, ethylene, and salicylic acid metabolism were clearly co-expressed with the MAPKKK genes. Furthermore, a quantitative real-time PCR (qRT-PCR) analysis was performed to assess the relative expression levels of MAPKKKs. Correlation analysis revealed that there was a significant correlation between expression levels of two MAPKKKs and relative biomass responsive to drought in 8 inbred lines. Our results indicate that MAPKKKs may have important regulatory functions in drought tolerance in maize. PMID:26599013

Comparative analysis of CDPK family in maize, Arabidopsis, rice and sorghum revealed potential targets for drought tolerance improvement

Science.gov (United States)

Mittal, Shikha; Mallikarjuna, Mallana Gowdra; Rao, Atmakuri R.; Jain, Prashant A.; Dash, Prasanta K.; Thirunavukkarasu, Nepolean

2017-12-01

Calcium dependent protein kinases (CDPKs) play major role in regulation of plant growth and development in response to various stresses including drought. A set of 32 CDPK genes identified in maize were further used for searching of orthologs in the model plant Arabidopsis (72) and major food crops such as rice (78) and sorghum (91). We comprehensively investigated the phylogenetic relationship, annotations, gene duplications, gene structure, divergence time, 3-D protein structures and tissue-specific drought induced expression of CDPK genes in all four species. Variation in intron frequency among these species likely contributed to the functional diversity of CDPK genes to various stress responses. Protein kinase and protein kinase C phosphorylation site domains were the most conserved motifs identified in all species. Four groups were identified from the sequence-based phylogenetic analysis, in which maize CDPKs were clustered in group III. The time of divergence (Ka/Ks) analysis revealed that the CDPKs were evolved through stabilizing selection. Expression data showed that the CDPK genes were highly expressed in leaf of maize, rice, and sorghum whereas in Arabidopsis the maximum expression was observed in root. 3-D protein structure were predicted for the nine genes (Arabidopsis: 2, maize: 2, rice: 3 and sorghum: 2) showing differential expression in at least three species. The predicted 3-D structures were further evaluated and validated by Ramachandran plot, ANOLEA, ProSA and Verify-3D. The superimposed 3-D structure of drought-related orthologous proteins retained similar folding pattern owing to their conserved nature. Functional annotation revealed the involvement of CDPK genes in various pathways such as osmotic homeostasis, cell protection and root growth. The interactions of CDPK genes in various pathways play crucial role in imparting drought tolerance through different ABA and MAPK signalling cascades. Our studies suggest that these selected candidate

Imaging mass spectrometry reveals elevated nigral levels of dynorphin neuropeptides in L-DOPA-induced dyskinesia in rat model of Parkinson's disease.

Directory of Open Access Journals (Sweden)

Anna Ljungdahl

Full Text Available L-DOPA-induced dyskinesia is a troublesome complication of L-DOPA pharmacotherapy of Parkinson's disease and has been associated with disturbed brain opioid transmission. However, so far the results of clinical and preclinical studies on the effects of opioids agonists and antagonists have been contradictory at best. Prodynorphin mRNA levels correlate well with the severity of dyskinesia in animal models of Parkinson's disease; however the identities of the actual neuroactive opioid effectors in their target basal ganglia output structures have not yet been determined. For the first time MALDI-TOF imaging mass spectrometry (IMS was used for unbiased assessment and topographical elucidation of prodynorphin-derived peptides in the substantia nigra of a unilateral rat model of Parkinson's disease and L-DOPA induced dyskinesia. Nigral levels of dynorphin B and alpha-neoendorphin strongly correlated with the severity of dyskinesia. Even if dynorphin peptide levels were elevated in both the medial and lateral part of the substantia nigra, MALDI IMS analysis revealed that the most prominent changes were localized to the lateral part of the substantia nigra. MALDI IMS is advantageous compared with traditional molecular methods, such as radioimmunoassay, in that neither the molecular identity analyzed, nor the specific localization needs to be predetermined. Indeed, MALDI IMS revealed that the bioconverted metabolite leu-enkephalin-arg also correlated positively with severity of dyskinesia. Multiplexing DynB and leu-enkephalin-arg ion images revealed small (0.25 by 0.5 mm nigral subregions with complementing ion intensities, indicating localized peptide release followed by bioconversion. The nigral dynorphins associated with L-DOPA-induced dyskinesia were not those with high affinity to kappa opioid receptors, but consisted of shorter peptides, mainly dynorphin B and alpha-neoendorphin that are known to bind and activate mu and delta opioid receptors

Optimization of rootkit revealing system resources – A game theoretic approach

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K. Muthumanickam

2015-10-01

Full Text Available Malicious rootkit is a collection of programs designed with the intent of infecting and monitoring the victim computer without the user’s permission. After the victim has been compromised, the remote attacker can easily cause further damage. In order to infect, compromise and monitor, rootkits adopt Native Application Programming Interface (API hooking technique. To reveal the hidden rootkits, current rootkit detection techniques check different data structures which hold reference to Native APIs. To verify these data structures, a large amount of system resources are required. This is because of the number of APIs in these data structures being quite large. Game theoretic approach is a useful mathematical tool to simulate network attacks. In this paper, a mathematical model is framed to optimize resource consumption using game-theory. To the best of our knowledge, this is the first work to be proposed for optimizing resource consumption while revealing rootkit presence using game theory. Non-cooperative game model is taken to discuss the problem. Analysis and simulation results show that our game theoretic model can effectively reduce the resource consumption by selectively monitoring the number of APIs in windows platform.

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome.

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Jens Christian Claussen

2017-06-01

Full Text Available The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.

Multiplex Brain Proteomic Analysis Revealed the Molecular Therapeutic Effects of Buyang Huanwu Decoction on Cerebral Ischemic Stroke Mice.

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Hong-Jhang Chen

Full Text Available Stroke is the second-leading cause of death worldwide, and tissue plasminogen activator (TPA is the only drug used for a limited group of stroke patients in the acute phase. Buyang Huanwu Decoction (BHD, a traditional Chinese medicine prescription, has long been used for improving neurological functional recovery in stroke. In this study, we characterized the therapeutic effect of TPA and BHD in a cerebral ischemia/reperfusion (CIR injury mouse model using multiplex proteomics approach. After the iTRAQ-based proteomics analysis, 1310 proteins were identified from the mouse brain with <1% false discovery rate. Among them, 877 quantitative proteins, 10.26% (90/877, 1.71% (15/877, and 2.62% (23/877 of the proteins was significantly changed in the CIR, BHD treatment, and TPA treatment, respectively. Functional categorization analysis showed that BHD treatment preserved the integrity of the blood-brain barrier (BBB (Alb, Fga, and Trf, suppressed excitotoxicity (Grm5, Gnai, and Gdi, and enhanced energy metabolism (Bdh, thereby revealing its multiple effects on ischemic stroke mice. Moreover, the neurogenesis marker doublecortin was upregulated, and the activity of glycogen synthase kinase 3 (GSK-3 and Tau was inhibited, which represented the neuroprotective effects. However, TPA treatment deteriorated BBB breakdown. This study highlights the potential of BHD in clinical applications for ischemic stroke.

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

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Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

2016-06-01

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate analysis: models and method

International Nuclear Information System (INIS)

Sanz Perucha, J.

1990-01-01

Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

Analysis of 16S libraries of mouse gastrointestinal microflora reveals a large new group of mouse intestinal bacteria

NARCIS (Netherlands)

Salzman, NH; de Jong, H; Paterson, Y; Harmsen, HJM; Welling, GW; Bos, NA

2002-01-01

Total genomic DNA from samples of intact mouse small intestine, large intestine, caecum and faeces was used as template for PCR amplification of 16S rRNA gene sequences with conserved bacterial primers. Phylogenetic analysis of the amplification products revealed 40 unique 16S rDNA sequences. Of

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

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Kiuru Aaro

2003-01-01

Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

Chain networking revealed by molecular dynamics simulation

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Zheng, Yexin; Tsige, Mesfin; Wang, Shi-Qing

Based on Kremer-Grest model for entangled polymer melts, we demonstrate how the response of a polymer glass depends critically on the chain length. After quenching two melts of very different chain lengths (350 beads per chain and 30 beads per chain) into deeply glassy states, we subject them to uniaxial extension. Our MD simulations show that the glass of long chains undergoes stable necking after yielding whereas the system of short chains is unable to neck and breaks up after strain localization. During ductile extension of the polymer glass made of long chain significant chain tension builds up in the load-bearing strands (LBSs). Further analysis is expected to reveal evidence of activation of the primary structure during post-yield extension. These results lend support to the recent molecular model 1 and are the simulations to demonstrate the role of chain networking. This work is supported, in part, by a NSF Grant (DMR-EAGER-1444859)

Multilayer Stochastic Block Models Reveal the Multilayer Structure of Complex Networks

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Toni Vallès-Català

2016-03-01

Full Text Available In complex systems, the network of interactions we observe between systems components is the aggregate of the interactions that occur through different mechanisms or layers. Recent studies reveal that the existence of multiple interaction layers can have a dramatic impact in the dynamical processes occurring on these systems. However, these studies assume that the interactions between systems components in each one of the layers are known, while typically for real-world systems we do not have that information. Here, we address the issue of uncovering the different interaction layers from aggregate data by introducing multilayer stochastic block models (SBMs, a generalization of single-layer SBMs that considers different mechanisms of layer aggregation. First, we find the complete probabilistic solution to the problem of finding the optimal multilayer SBM for a given aggregate-observed network. Because this solution is computationally intractable, we propose an approximation that enables us to verify that multilayer SBMs are more predictive of network structure in real-world complex systems.

Determination of equilibrium structures of bromothymol blue revealed by using quantum chemistry with an aid of multivariate analysis of electronic absorption spectra

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Shimada, Toru; Hasegawa, Takeshi

2017-10-01

The pH dependent chemical structures of bromothymol blue (BTB), which have long been under controversy, are determined by employing a combined technique of multivariate analysis of electronic absorption spectra and quantum chemistry. Principle component analysis (PCA) of the pH dependent spectra apparently reveals that only two chemical species are adequate to fully account for the color changes, with which the spectral decomposition is readily performed by using augmented alternative least-squares (ALS) regression analysis. The quantity variation by the ALS analysis also reveals the practical acid dissociation constant, pKa‧. The determination of pKa‧ is performed for various ionic strengths, which reveals the thermodynamic acid constant (pKa = 7.5) and the number of charge on each chemical species; the yellow form is negatively charged species of - 1 and the blue form that of - 2. On this chemical information, the quantum chemical calculation is carried out to find that BTB molecules take the pure quinoid form in an acid solution and the quinoid-phenolate form in an alkaline solution. The time-dependent density functional theory (TD-DFT) calculations for the theoretically determined chemical structures account for the peak shift of the electronic spectra. In this manner, the structures of all the chemical species appeared in equilibrium have finally been confirmed.

Genome Wide Transcriptome Analysis reveals ABA mediated response in Arabidopsis during Gold (AuCl4- treatment

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Devesh eShukla

2014-11-01

Full Text Available The unique physico-chemical properties of gold nanoparticles (AuNPs find manifold applications in diagnostics, medicine and catalysis. Chemical synthesis produces reactive AuNPs and generates hazardous by-products. Alternatively, plants can be utilized to produce AuNPs in an eco-friendly manner. To better control the biosynthesis of AuNPs, we need to first understand the detailed molecular response induced by AuCl4- In this study, we carried out global transcriptome analysis in root tissue of Arabidopsis grown for 12- hours in presence of gold solution (HAuCl4 using the novel unbiased Affymetrix exon array. Transcriptomics analysis revealed differential regulation of a total of 704 genes and 4900 exons. Of these, 492 and 212 genes were up- and downregulated, respectively. The validation of the expressed key genes, such as glutathione-S-transferases, auxin responsive genes, cytochrome P450 82C2, methyl transferases, transducin (G protein beta subunit, ERF transcription factor, ABC, and MATE transporters, was carried out through quantitative RT-PCR. These key genes demonstrated specific induction under AuCl4- treatment relative to other heavy metals, suggesting a unique plant-gold interaction. GO enrichment analysis reveals the upregulation of processes like oxidative stress, glutathione binding, metal binding, transport, and plant hormonal responses. Changes predicted in biochemical pathways indicated major modulation in glutathione mediated detoxification, flavones and derivatives, and plant hormone biosynthesis. Motif search analysis identified a highly significant enriched motif, ACGT, which is an abscisic acid responsive core element (ABRE, suggesting the possibility of ABA- mediated signaling. Identification of abscisic acid response element (ABRE points to the operation of a predominant signaling mechanism in response to AuCl4- exposure. Overall, this study presents a useful picture of plant-gold interaction with an identification of

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

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Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of

Stability Analysis for Li-Ion Battery Model Parameters and State of Charge Estimation by Measurement Uncertainty Consideration

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Shifei Yuan

2015-07-01

Full Text Available Accurate estimation of model parameters and state of charge (SoC is crucial for the lithium-ion battery management system (BMS. In this paper, the stability of the model parameters and SoC estimation under measurement uncertainty is evaluated by three different factors: (i sampling periods of 1/0.5/0.1 s; (ii current sensor precisions of ±5/±50/±500 mA; and (iii voltage sensor precisions of ±1/±2.5/±5 mV. Firstly, the numerical model stability analysis and parametric sensitivity analysis for battery model parameters are conducted under sampling frequency of 1–50 Hz. The perturbation analysis is theoretically performed of current/voltage measurement uncertainty on model parameter variation. Secondly, the impact of three different factors on the model parameters and SoC estimation was evaluated with the federal urban driving sequence (FUDS profile. The bias correction recursive least square (CRLS and adaptive extended Kalman filter (AEKF algorithm were adopted to estimate the model parameters and SoC jointly. Finally, the simulation results were compared and some insightful findings were concluded. For the given battery model and parameter estimation algorithm, the sampling period, and current/voltage sampling accuracy presented a non-negligible effect on the estimation results of model parameters. This research revealed the influence of the measurement uncertainty on the model parameter estimation, which will provide the guidelines to select a reasonable sampling period and the current/voltage sensor sampling precisions in engineering applications.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

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Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

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Moritz eBoos

2016-05-01

Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Kinematic Analysis of a Six-Degrees-of-Freedom Model Based on ISB Recommendation: A Repeatability Analysis and Comparison with Conventional Gait Model.

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Żuk, Magdalena; Pezowicz, Celina

2015-01-01

Objective. The purpose of the present work was to assess the validity of a six-degrees-of-freedom gait analysis model based on the ISB recommendation on definitions of joint coordinate systems (ISB 6DOF) through a quantitative comparison with the Helen Hays model (HH) and repeatability assessment. Methods. Four healthy subjects were analysed with both marker sets: an HH marker set and four marker clusters in ISB 6DOF. A navigated pointer was used to indicate the anatomical landmark position in the cluster reference system according to the ISB recommendation. Three gait cycles were selected from the data collected simultaneously for the two marker sets. Results. Two protocols showed good intertrial repeatability, which apart from pelvic rotation did not exceed 2°. The greatest differences between protocols were observed in the transverse plane as well as for knee angles. Knee internal/external rotation revealed the lowest subject-to-subject and interprotocol repeatability and inconsistent patterns for both protocols. Knee range of movement in transverse plane was overestimated for the HH set (the mean is 34°), which could indicate the cross-talk effect. Conclusions. The ISB 6DOF anatomically based protocol enabled full 3D kinematic description of joints according to the current standard with clinically acceptable intertrial repeatability and minimal equipment requirements.

Distribution of triclosan-resistant genes in major pathogenic microorganisms revealed by metagenome and genome-wide analysis.

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Raees Khan

Full Text Available The substantial use of triclosan (TCS has been aimed to kill pathogenic bacteria, but TCS resistance seems to be prevalent in microbial species and limited knowledge exists about TCS resistance determinants in a majority of pathogenic bacteria. We aimed to evaluate the distribution of TCS resistance determinants in major pathogenic bacteria (N = 231 and to assess the enrichment of potentially pathogenic genera in TCS contaminated environments. A TCS-resistant gene (TRG database was constructed and experimentally validated to predict TCS resistance in major pathogenic bacteria. Genome-wide in silico analysis was performed to define the distribution of TCS-resistant determinants in major pathogens. Microbiome analysis of TCS contaminated soil samples was also performed to investigate the abundance of TCS-resistant pathogens. We experimentally confirmed that TCS resistance could be accurately predicted using genome-wide in silico analysis against TRG database. Predicted TCS resistant phenotypes were observed in all of the tested bacterial strains (N = 17, and heterologous expression of selected TCS resistant genes from those strains conferred expected levels of TCS resistance in an alternative host Escherichia coli. Moreover, genome-wide analysis revealed that potential TCS resistance determinants were abundant among the majority of human-associated pathogens (79% and soil-borne plant pathogenic bacteria (98%. These included a variety of enoyl-acyl carrier protein reductase (ENRs homologues, AcrB efflux pumps, and ENR substitutions. FabI ENR, which is the only known effective target for TCS, was either co-localized with other TCS resistance determinants or had TCS resistance-associated substitutions. Furthermore, microbiome analysis revealed that pathogenic genera with intrinsic TCS-resistant determinants exist in TCS contaminated environments. We conclude that TCS may not be as effective against the majority of bacterial pathogens as previously

Distribution of triclosan-resistant genes in major pathogenic microorganisms revealed by metagenome and genome-wide analysis

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Khan, Raees; Roy, Nazish; Choi, Kihyuck

2018-01-01

The substantial use of triclosan (TCS) has been aimed to kill pathogenic bacteria, but TCS resistance seems to be prevalent in microbial species and limited knowledge exists about TCS resistance determinants in a majority of pathogenic bacteria. We aimed to evaluate the distribution of TCS resistance determinants in major pathogenic bacteria (N = 231) and to assess the enrichment of potentially pathogenic genera in TCS contaminated environments. A TCS-resistant gene (TRG) database was constructed and experimentally validated to predict TCS resistance in major pathogenic bacteria. Genome-wide in silico analysis was performed to define the distribution of TCS-resistant determinants in major pathogens. Microbiome analysis of TCS contaminated soil samples was also performed to investigate the abundance of TCS-resistant pathogens. We experimentally confirmed that TCS resistance could be accurately predicted using genome-wide in silico analysis against TRG database. Predicted TCS resistant phenotypes were observed in all of the tested bacterial strains (N = 17), and heterologous expression of selected TCS resistant genes from those strains conferred expected levels of TCS resistance in an alternative host Escherichia coli. Moreover, genome-wide analysis revealed that potential TCS resistance determinants were abundant among the majority of human-associated pathogens (79%) and soil-borne plant pathogenic bacteria (98%). These included a variety of enoyl-acyl carrier protein reductase (ENRs) homologues, AcrB efflux pumps, and ENR substitutions. FabI ENR, which is the only known effective target for TCS, was either co-localized with other TCS resistance determinants or had TCS resistance-associated substitutions. Furthermore, microbiome analysis revealed that pathogenic genera with intrinsic TCS-resistant determinants exist in TCS contaminated environments. We conclude that TCS may not be as effective against the majority of bacterial pathogens as previously presumed

A global sensitivity analysis approach for morphogenesis models

KAUST Repository

Boas, Sonja E. M.

2015-11-21

Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

A global sensitivity analysis approach for morphogenesis models.

Science.gov (United States)

Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

2015-11-21

Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Experimental Design for Sensitivity Analysis of Simulation Models

NARCIS (Netherlands)

Kleijnen, J.P.C.

2001-01-01

This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivity analysis in simulation.This analysis uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as

Site effect classification based on microtremor data analysis using a concentration-area fractal model

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Adib, A.; Afzal, P.; Heydarzadeh, K.

2015-01-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modelling reveal that proper soil types are located around the central city. The results derived via the fractal modelling were utilized to improve the Nogoshi and Igarashi (1970, 1971) classification results in the Meybod city. The resulting categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.

Transformation of chlorpyrifos in integrated recirculating constructed wetlands (IRCWs) as revealed by compound-specific stable isotope (CSIA) and microbial community structure analysis.

Science.gov (United States)

Tang, Xiaoyan; Yang, Yang; Huang, Wenda; McBride, Murray B; Guo, Jingjing; Tao, Ran; Dai, Yunv

2017-06-01

Carbon isotope analysis and 454 pyrosequencing methods were used to investigate in situ biodegradation of chlorpyrifos during its transport through three model integrated recirculating constructed wetlands (IRCWs). Results show that plant and Fe-impregnated biochar promoted degradation of chlorpyrifos and its metabolite 3,5,6-trichloro-2-pyridinol (TCP). Carbon isotope ratios in the IRCWs shifted to -31.24±0.58‰ (IRCW1, plant free), -26.82±0.60‰ (IRCW2, with plant) and -24.76±0.94‰ (IRCW3, with plant and Fe-biochar). The enrichment factors (Ɛ bulk,c ) were determined as -0.69±0.06‰ (IRCW1), -0.91±0.07‰ (IRCW2) and -1.03±0.09‰ (IRCW3). Microbial community analysis showed that IRCW3 was dominated by members of Bacillus, which can utilize and degrade chlorpyrifos. These results reveal that plant and Fe-biochar can induce carbon isotope fractionation and have a positive impact on the chlorpyrifos degradation efficiency by influencing the development of beneficial microbial communities. Copyright © 2017. Published by Elsevier Ltd.

Dysconnection topography in schizophrenia revealed with state-space analysis of EEG.

Science.gov (United States)

Jalili, Mahdi; Lavoie, Suzie; Deppen, Patricia; Meuli, Reto; Do, Kim Q; Cuénod, Michel; Hasler, Martin; De Feo, Oscar; Knyazeva, Maria G

2007-10-24

The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals. To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels) EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series-the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity. The new method of

Dysconnection topography in schizophrenia revealed with state-space analysis of EEG.

Directory of Open Access Journals (Sweden)

Mahdi Jalili

2007-10-01

Full Text Available The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals.To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series-the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity.The new

Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans.

Science.gov (United States)

Cenik, Can; Cenik, Elif Sarinay; Byeon, Gun W; Grubert, Fabian; Candille, Sophie I; Spacek, Damek; Alsallakh, Bilal; Tilgner, Hagen; Araya, Carlos L; Tang, Hua; Ricci, Emiliano; Snyder, Michael P

2015-11-01

Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding, and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy--many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation. © 2015 Cenik et al.; Published by Cold Spring Harbor Laboratory Press.

Demographic analysis reveals gradual senescence in the flatworm Macrostomum lignano

Directory of Open Access Journals (Sweden)

Braeckman Bart P

2009-07-01

Full Text Available Abstract Free-living flatworms ("Turbellaria" are appropriate model organisms to gain better insight into the role of stem cells in ageing and rejuvenation. Ageing research in flatworms is, however, still scarce. This is partly due to culture difficulties and the lack of a complete set of demographic data, including parameters such as median lifespan and age-specific mortality rate. In this paper, we report on the first flatworm survival analysis. We used the species Macrostomum lignano, which is an emerging model for studying the reciprocal influence between stem cells, ageing and rejuvenation. This species has a median lifespan of 205 ± 13 days (average ± standard deviation [SD] and a 90th percentile lifespan of 373 ± 32 days. The maximum lifespan, however, is more than 745 days, and the average survival curve is characterised by a long tail because a small number of individuals lives twice as long as 90% of the population. Similar to earlier observations in a wide range of animals, in M. lignano the age-specific mortality rate increases exponentially, but levels off at the oldest ages. To compare the senescence of M. lignano with that of other ageing models, we determined the mortality rate doubling time, which is 0.20 ± 0.02 years. As a result, we can conclude that M. lignano shows gradual senescence at a rate similar to the vertebrate ageing models Rattus norvegicus and Mus musculus. We argue that M. lignano is a suitable model for ageing and rejuvenation research, and especially for the role of stem cells in these processes, due to its accessible stem cell system and regeneration capacity, and the possibility of combining stem cell studies with demographic analyses.

A Fault Prognosis Strategy Based on Time-Delayed Digraph Model and Principal Component Analysis

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Ningyun Lu

2012-01-01

Full Text Available Because of the interlinking of process equipments in process industry, event information may propagate through the plant and affect a lot of downstream process variables. Specifying the causality and estimating the time delays among process variables are critically important for data-driven fault prognosis. They are not only helpful to find the root cause when a plant-wide disturbance occurs, but to reveal the evolution of an abnormal event propagating through the plant. This paper concerns with the information flow directionality and time-delay estimation problems in process industry and presents an information synchronization technique to assist fault prognosis. Time-delayed mutual information (TDMI is used for both causality analysis and time-delay estimation. To represent causality structure of high-dimensional process variables, a time-delayed signed digraph (TD-SDG model is developed. Then, a general fault prognosis strategy is developed based on the TD-SDG model and principle component analysis (PCA. The proposed method is applied to an air separation unit and has achieved satisfying results in predicting the frequently occurred “nitrogen-block” fault.

A Bayesian multidimensional scaling procedure for the spatial analysis of revealed choice data

NARCIS (Netherlands)

DeSarbo, WS; Kim, Y; Fong, D

1999-01-01

We present a new Bayesian formulation of a vector multidimensional scaling procedure for the spatial analysis of binary choice data. The Gibbs sampler is gainfully employed to estimate the posterior distribution of the specified scalar products, bilinear model parameters. The computational procedure

FAME, the Flux Analysis and Modeling Environment

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Boele Joost

2012-01-01

Full Text Available Abstract Background The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoint code, which adds additional actions to the analysis routine and, in our experience, renders these applications suboptimal for routine use by (systems biologists. Results The Flux Analysis and Modeling Environment (FAME is the first web-based modeling tool that combines the tasks of creating, editing, running, and analyzing/visualizing stoichiometric models into a single program. Analysis results can be automatically superimposed on familiar KEGG-like maps. FAME is written in PHP and uses the Python-based PySCeS-CBM for its linear solving capabilities. It comes with a comprehensive manual and a quick-start tutorial, and can be accessed online at http://f-a-m-e.org/. Conclusions With FAME, we present the community with an open source, user-friendly, web-based "one stop shop" for stoichiometric modeling. We expect the application will be of substantial use to investigators and educators alike.

Multi-scale model analysis of boundary layer ozone over East Asia

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M. Lin

2009-05-01

Full Text Available This study employs the regional Community Multiscale Air Quality (CMAQ model to examine seasonal and diurnal variations of boundary layer ozone (O₃ over East Asia. We evaluate the response of model simulations of boundary layer O₃ to the choice of chemical mechanisms, meteorological fields, boundary conditions, and model resolutions. Data obtained from surface stations, aircraft measurements, and satellites are used to advance understanding of O₃ chemistry and mechanisms over East Asia and evaluate how well the model represents the observed features. Satellite measurements and model simulations of summertime rainfall are used to assess the impact of the Asian monsoon on O₃ production. Our results suggest that summertime O₃ over Central Eastern China is highly sensitive to cloud cover and monsoonal rainfall over this region. Thus, accurate simulation of the East Asia summer monsoon is critical to model analysis of atmospheric chemistry over China. Examination of hourly summertime O₃ mixing ratios from sites in Japan confirms the important role of diurnal boundary layer fluctuations in controlling ground-level O₃. By comparing five different model configurations with observations at six sites, the specific mechanisms responsible for model behavior are identified and discussed. In particular, vertical mixing, urban chemistry, and dry deposition depending on boundary layer height strongly affect model ability to capture observed behavior. Central Eastern China appears to be the most sensitive region in our study to the choice of chemical mechanisms. Evaluation with TRACE-P aircraft measurements reveals that neither the CB4 nor the SAPRC99 mechanisms consistently capture observed behavior of key photochemical oxidants in springtime. However, our analysis finds that SAPRC99 performs somewhat better in simulating mixing ratios of H₂O₂ (hydrogen peroxide

Analysis of MADS-Box Gene Family Reveals Conservation in Floral Organ ABCDE Model of Moso Bamboo (Phyllostachys edulis

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Zhanchao Cheng

2017-05-01

Full Text Available Mini chromosome maintenance 1, agamous, deficiens, and serum response factor (MADS-box genes are transcription factors which play fundamental roles in flower development and regulation of floral organ identity. However, till date, identification and functions of MADS-box genes remain largely unclear in Phyllostachys edulis. In view of this, we performed a whole-genome survey and identified 34 MADS-box genes in P. edulis, and based on phylogeny, they were classified as MIKCC, MIKC∗, Mα, and Mβ. The detailed analysis about gene structure and motifs, phylogenetic classification, comparison of gene divergence and duplication are provided. Interestingly, expression patterns for most genes were found similar to those of Arabidopsis and rice, indicating that the well-established ABCDE model can be applied to P. edulis. Moreover, we overexpressed PheMADS15, an AP1-like gene, in Arabidopsis, and found that the transgenic plants have early flowering phenotype, suggesting that PheMADS15 might be a regulator of flowering transition in P. edulis. Taken together, this study provides not only insightful comprehension but also useful information for understanding the functions of MADS-box genes in P. edulis.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

DEFF Research Database (Denmark)

Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

2014-01-01

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

DEFF Research Database (Denmark)

Macé, Aurélien; Tuke, Marcus A; Deelen, Patrick

2017-01-01

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations......-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.......)). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m(2) for each Mb of total deletion burden (P = 2.5 × 10(-10), 6.0 × 10(-5), and 2.9 × 10(-3)). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor...

Sheep skeletal muscle transcriptome analysis reveals muscle growth regulatory lncRNAs.

Science.gov (United States)

Chao, Tianle; Ji, Zhibin; Hou, Lei; Wang, Jin; Zhang, Chunlan; Wang, Guizhi; Wang, Jianmin

2018-01-01

As widely distributed domestic animals, sheep are an important species and the source of mutton. In this study, we aimed to evaluate the regulatory lncRNAs associated with muscle growth and development between high production mutton sheep (Dorper sheep and Qianhua Mutton Merino sheep) and low production mutton sheep (Small-tailed Han sheep). In total, 39 lncRNAs were found to be differentially expressed. Using co-expression analysis and functional annotation, 1,206 co-expression interactions were found between 32 lncRNAs and 369 genes, and 29 of these lncRNAs were found to be associated with muscle development, metabolism, cell proliferation and apoptosis. lncRNA-mRNA interactions revealed 6 lncRNAs as hub lncRNAs. Moreover, three lncRNAs and their associated co-expressed genes were demonstrated by cis-regulatory gene analyses, and we also found a potential regulatory relationship between the pseudogene lncRNA LOC101121401 and its parent gene FTH1. This study provides a genome-wide resolution of lncRNA and mRNA regulation in muscles from mutton sheep.

NeuCode Proteomics Reveals Bap1 Regulation of Metabolism

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Joshua M. Baughman

2016-07-01

Full Text Available We introduce neutron-encoded (NeuCode amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology.

Representing Uncertainty on Model Analysis Plots

Science.gov (United States)

Smith, Trevor I.

2016-01-01

Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model.…

Agent-based organizational modelling for analysis of safety culture at an air navigation service provider

International Nuclear Information System (INIS)

Stroeve, Sybert H.; Sharpanskykh, Alexei; Kirwan, Barry

2011-01-01

Assessment of safety culture is done predominantly by questionnaire-based studies, which tend to reveal attitudes on immaterial characteristics (values, beliefs, norms). There is a need for a better understanding of the implications of the material aspects of an organization (structures, processes, etc.) for safety culture and their interactions with the immaterial characteristics. This paper presents a new agent-based organizational modelling approach for integrated and systematic evaluation of material and immaterial characteristics of socio-technical organizations in safety culture analysis. It uniquely considers both the formal organization and the value- and belief-driven behaviour of individuals in the organization. Results are presented of a model for safety occurrence reporting at an air navigation service provider. Model predictions consistent with questionnaire-based results are achieved. A sensitivity analysis provides insight in organizational factors that strongly influence safety culture indicators. The modelling approach can be used in combination with attitude-focused safety culture research, towards an integrated evaluation of material and immaterial characteristics of socio-technical organizations. By using this approach an organization is able to gain a deeper understanding of causes of diverse problems and inefficiencies both in the formal organization and in the behaviour of organizational agents, and to systematically identify and evaluate improvement options.

Eliciting mixed emotions: a meta-analysis comparing models, types, and measures

Science.gov (United States)

Berrios, Raul; Totterdell, Peter; Kellett, Stephen

2015-01-01

The idea that people can experience two oppositely valenced emotions has been controversial ever since early attempts to investigate the construct of mixed emotions. This meta-analysis examined the robustness with which mixed emotions have been elicited experimentally. A systematic literature search identified 63 experimental studies that instigated the experience of mixed emotions. Studies were distinguished according to the structure of the underlying affect model—dimensional or discrete—as well as according to the type of mixed emotions studied (e.g., happy-sad, fearful-happy, positive-negative). The meta-analysis using a random-effects model revealed a moderate to high effect size for the elicitation of mixed emotions (dIG+ = 0.77), which remained consistent regardless of the structure of the affect model, and across different types of mixed emotions. Several methodological and design moderators were tested. Studies using the minimum index (i.e., the minimum value between a pair of opposite valenced affects) resulted in smaller effect sizes, whereas subjective measures of mixed emotions increased the effect sizes. The presence of more women in the samples was also associated with larger effect sizes. The current study indicates that mixed emotions are a robust, measurable and non-artifactual experience. The results are discussed in terms of the implications for an affect system that has greater versatility and flexibility than previously thought. PMID:25926805

Revealing effective classifiers through network comparison

Science.gov (United States)

Gallos, Lazaros K.; Fefferman, Nina H.

2014-11-01

The ability to compare complex systems can provide new insight into the fundamental nature of the processes captured, in ways that are otherwise inaccessible to observation. Here, we introduce the n-tangle method to directly compare two networks for structural similarity, based on the distribution of edge density in network subgraphs. We demonstrate that this method can efficiently introduce comparative analysis into network science and opens the road for many new applications. For example, we show how the construction of a “phylogenetic tree” across animal taxa according to their social structure can reveal commonalities in the behavioral ecology of the populations, or how students create similar networks according to the University size. Our method can be expanded to study many additional properties, such as network classification, changes during time evolution, convergence of growth models, and detection of structural changes during damage.

Mathematical modeling reveals kinetics of lymphocyte recirculation in the whole organism.

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Vitaly V Ganusov

2014-05-01

Full Text Available The kinetics of recirculation of naive lymphocytes in the body has important implications for the speed at which local infections are detected and controlled by immune responses. With a help of a novel mathematical model, we analyze experimental data on migration of 51Cr-labeled thoracic duct lymphocytes (TDLs via major lymphoid and nonlymphoid tissues of rats in the absence of systemic antigenic stimulation. We show that at any point of time, 95% of lymphocytes in the blood travel via capillaries in the lung or sinusoids of the liver and only 5% migrate to secondary lymphoid tissues such as lymph nodes, Peyer's patches, or the spleen. Interestingly, our analysis suggests that lymphocytes travel via lung capillaries and liver sinusoids at an extremely rapid rate with the average residence time in these tissues being less than 1 minute. The model also predicts a relatively short average residence time of TDLs in the spleen (2.5 hours and a longer average residence time of TDLs in major lymph nodes and Peyer's patches (10 hours. Surprisingly, we find that the average residence time of lymphocytes is similar in lymph nodes draining the skin (subcutaneous LNs or the gut (mesenteric LNs or in Peyer's patches. Applying our model to an additional dataset on lymphocyte migration via resting and antigen-stimulated lymph nodes we find that enlargement of antigen-stimulated lymph nodes occurs mainly due to increased entrance rate of TDLs into the nodes and not due to decreased exit rate as has been suggested in some studies. Taken together, our analysis for the first time provides a comprehensive, systems view of recirculation kinetics of thoracic duct lymphocytes in the whole organism.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

Science.gov (United States)

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

ANALYSIS AND MODELING OF GENEVA MECHANISM

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HARAGA Georgeta

2015-06-01

Full Text Available The paper presents some aspects theoretical and practical based on the finite element analysis and modelling of Geneva mechanism with four slots, using the CATIA graphic program. This type of mechanism is an example of intermittent gearing that translates a continuous rotation into an intermittent rotary motion. It consists of alternate periods of motion and rest without reversing direction. In this paper, some design parameters with specify a Geneva mechanism will be defined precisely such as number of driving cranks, number of slots, wheel diameter, pin diameter, etc. Finite element analysis (FEA can be used for creating a finite element model (preprocessing and visualizing the analysis results (postprocessing, and use other solvers for processing.

Examining Pedestrian Injury Severity Using Alternative Disaggregate Models

DEFF Research Database (Denmark)

Abay, Kibrom Araya

2013-01-01

This paper investigates the injury severity of pedestrians considering detailed road user characteristics and alternative model specification using a high-quality Danish road accident data. Such detailed and alternative modeling approach helps to assess the sensitivity of empirical inferences...... to the choice of these models. The empirical analysis reveals that detailed road user characteristics such as crime history of drivers and momentary activities of road users at the time of the accident provides an interesting insight in the injury severity analysis. Likewise, the alternative analytical...... specification of the models reveals that some of the conventionally employed fixed parameters injury severity models could underestimate the effect of some important behavioral attributes of the accidents. For instance, the standard ordered logit model underestimated the marginal effects of some...

Intrinsic Dynamics Analysis of a DNA Octahedron by Elastic Network Model

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Guang Hu

2017-01-01

Full Text Available DNA is a fundamental component of living systems where it plays a crucial role at both functional and structural level. The programmable properties of DNA make it an interesting building block for the construction of nanostructures. However, molecular mechanisms for the arrangement of these well-defined DNA assemblies are not fully understood. In this paper, the intrinsic dynamics of a DNA octahedron has been investigated by using two types of Elastic Network Models (ENMs. The application of ENMs to DNA nanocages include the analysis of the intrinsic flexibilities of DNA double-helices and hinge sites through the calculation of the square fluctuations, as well as the intrinsic collective dynamics in terms of cross-collective map calculation coupled with global motions analysis. The dynamics profiles derived from ENMs have then been evaluated and compared with previous classical molecular dynamics simulation trajectories. The results presented here revealed that ENMs can provide useful insights into the intrinsic dynamics of large DNA nanocages and represent a useful tool in the field of structural DNA nanotechnology.

Introducing Synchronisation in Deterministic Network Models

DEFF Research Database (Denmark)

Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

2006-01-01

The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

Determination of equilibrium structures of bromothymol blue revealed by using quantum chemistry with an aid of multivariate analysis of electronic absorption spectra.

Science.gov (United States)

Shimada, Toru; Hasegawa, Takeshi

2017-10-05

The pH dependent chemical structures of bromothymol blue (BTB), which have long been under controversy, are determined by employing a combined technique of multivariate analysis of electronic absorption spectra and quantum chemistry. Principle component analysis (PCA) of the pH dependent spectra apparently reveals that only two chemical species are adequate to fully account for the color changes, with which the spectral decomposition is readily performed by using augmented alternative least-squares (ALS) regression analysis. The quantity variation by the ALS analysis also reveals the practical acid dissociation constant, pK a '. The determination of pK a ' is performed for various ionic strengths, which reveals the thermodynamic acid constant (pK a =7.5) and the number of charge on each chemical species; the yellow form is negatively charged species of -1 and the blue form that of -2. On this chemical information, the quantum chemical calculation is carried out to find that BTB molecules take the pure quinoid form in an acid solution and the quinoid-phenolate form in an alkaline solution. The time-dependent density functional theory (TD-DFT) calculations for the theoretically determined chemical structures account for the peak shift of the electronic spectra. In this manner, the structures of all the chemical species appeared in equilibrium have finally been confirmed. Copyright © 2017 Elsevier B.V. All rights reserved.

Model Performance Evaluation and Scenario Analysis (MPESA)

Science.gov (United States)

Model Performance Evaluation and Scenario Analysis (MPESA) assesses the performance with which models predict time series data. The tool was developed Hydrological Simulation Program-Fortran (HSPF) and the Stormwater Management Model (SWMM)

Development of Wolsong Unit 2 Containment Analysis Model

Energy Technology Data Exchange (ETDEWEB)

Hoon, Choi [Korea Hydro and Nuclear Power Co., Ltd., Daejeon (Korea, Republic of); Jin, Ko Bong; Chan, Park Young [Hanbat National Univ., Daejeon (Korea, Republic of)

2014-05-15

To be prepared for the full scope safety analysis of Wolsong unit 2 with modified fuel, input decks for the various objectives, which can be read by GOTHIC 7.2b(QA), are developed and tested for the steady state simulation. A detailed nodalization of 39 control volumes and 92 flow paths is constructed to determine the differential pressure across internal walls or hydrogen concentration and distribution inside containment. A lumped model with 15 control volumes and 74 flow paths has also been developed to reduce the computer run time for the assessments in which the analysis results are not sensitive to detailed thermal hydraulic distribution inside containment such as peak pressure, pressure dependent signal and radionuclide release. The input data files provide simplified representations of the geometric layout of the containment building (volumes, dimensions, flow paths, doors, panels, etc.) and the performance characteristics of the various containment subsystems. The parameter values are based on best estimate or design values for that parameter. The analysis values are determined by conservatism depending on the analysis objective and may be different for various analysis objectives. Basic input decks of Wolsong unit 2 were developed for the various analysis purposes with GOTHIC 7.2b(QA). Depend on the analysis objective, two types of models are prepared. Detailed model models each confined room in the containment as a separate node. All of the geometric data are based on the drawings of Wolsong unit 2. Developed containment models are simulating the steady state well to the designated initial condition. These base models will be used for Wolsong unit 2 in case of safety analysis of full scope is needed.

Global analysis of threat status reveals higher extinction risk in tropical than in temperate bird sister species

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Reif Jiří

2016-06-01

Full Text Available Given increasing pressures upon biodiversity, identification of species’ traits related to elevated extinction risk is useful for more efficient allocation of limited resources for nature conservation. Despite its need, such a global analysis was lacking in the case of birds. Therefore, we performed this exercise for avian sister species using information about their global extinction risk from IUCN Red List. We focused on 113 pairs of sister species, each containing a threatened and an unthreatened species to factor out the effects of common evolutionary history on the revealed relationship. We collected data on five traits with expected relationships to species’ extinction risk based on previous studies performed at regional or national levels: breeding habitat (recognizing forest, grassland, wetland and oceanic species, latitudinal range position (temperate and tropics species, migration strategy (migratory and resident species, diet (carnivorous, insectivorous, herbivorous and omnivorous species and body mass. We related the extinction risk using IUCN threat level categories to species’ traits using generalised linear mixed effects models expecting lower risk for forest, temperate, omnivorous and smaller-bodied species. Our expectation was confirmed only in the case of latitudinal range position, as we revealed higher threat level for tropical than for temperate species. This relationship was robust to different methods of threat level expression and cannot be explained by a simple association of high bird species richness with the tropical zone. Instead, it seems that tropical species are more threatened because of their intrinsic characteristics such as slow life histories, adaptations to stable environments and small geographic ranges. These characteristics are obviously disadvantageous in conditions of current human-induced environmental perturbations. Moreover, given the absence of habitat effects, our study indicates that such

Model Selection in Data Analysis Competitions

DEFF Research Database (Denmark)

Wind, David Kofoed; Winther, Ole

2014-01-01

The use of data analysis competitions for selecting the most appropriate model for a problem is a recent innovation in the field of predictive machine learning. Two of the most well-known examples of this trend was the Netflix Competition and recently the competitions hosted on the online platform...... performers from Kaggle and use previous personal experiences from competing in Kaggle competitions. The stated hypotheses about feature engineering, ensembling, overfitting, model complexity and evaluation metrics give indications and guidelines on how to select a proper model for performing well...... Kaggle. In this paper, we will state and try to verify a set of qualitative hypotheses about predictive modelling, both in general and in the scope of data analysis competitions. To verify our hypotheses we will look at previous competitions and their outcomes, use qualitative interviews with top...

Self-pressurization analysis of the natural circulation integral nuclear reactor using a new dynamic model

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Ali Farsoon Pilehvar

2018-06-01

Full Text Available Self-pressurization analysis of the natural circulation integral nuclear reactor through a new dynamic model is studied. Unlike conventional pressurized water reactors, this reactor type controls the system pressure using saturated coolant water in the steam dome at the top of the pressure vessel. Self-pressurization model is developed based on conservation of mass, volume, and energy by predicting the condensation that occurs in the steam dome and the flashing inside the chimney using the partial differential equation. A simple but functional model is adopted for the steam generator. The obtained results indicate that the variable measurement is consistent with design data and that this new model is able to predict the dynamics of the reactor in different situations. It is revealed that flashing and condensation power are in direct relation with the stability of the system pressure, without which pressure convergence cannot be established. Keywords: Condensation Power, Flashing Phenomenon, Natural Circulation, Self-Pressurization, Small Modular Reactor

Homology-based Modeling of Rhodopsin-like Family Members in the Inactive State: Structural Analysis and Deduction of Tips for Modeling and Optimization.

Science.gov (United States)

Pappalardo, Matteo; Rayan, Mahmoud; Abu-Lafi, Saleh; Leonardi, Martha E; Milardi, Danilo; Guccione, Salvatore; Rayan, Anwar

2017-08-01

Modeling G-Protein Coupled Receptors (GPCRs) is an emergent field of research, since utility of high-quality models in receptor structure-based strategies might facilitate the discovery of interesting drug candidates. The findings from a quantitative analysis of eighteen resolved structures of rhodopsin family "A" receptors crystallized with antagonists and 153 pairs of structures are described. A strategy termed endeca-amino acids fragmentation was used to analyze the structures models aiming to detect the relationship between sequence identity and Root Mean Square Deviation (RMSD) at each trans-membrane-domain. Moreover, we have applied the leave-one-out strategy to study the shiftiness likelihood of the helices. The type of correlation between sequence identity and RMSD was studied using the aforementioned set receptors as representatives of membrane proteins and 98 serine proteases with 4753 pairs of structures as representatives of globular proteins. Data analysis using fragmentation strategy revealed that there is some extent of correlation between sequence identity and global RMSD of 11AA width windows. However, spatial conservation is not always close to the endoplasmic side as was reported before. A comparative study with globular proteins shows that GPCRs have higher standard deviation and higher slope in the graph with correlation between sequence identity and RMSD. The extracted information disclosed in this paper could be incorporated in the modeling protocols while using technique for model optimization and refinement. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling and Analysis of Inter-Vehicle Communication: A Stochastic Geometry Approach

KAUST Repository

Farooq, Muhammad Junaid

2015-05-01

Vehicular communication is the enabling technology for the development of the intelligent transportation systems (ITS), which aims to improve the efficiency and safety of transportation. It can be used for a variety of useful applications such as adaptive traffic control, coordinated braking, emergency messaging, peer-to-peer networking for infotainment services and automatic toll collection etc... Accurate yet simple models for vehicular networks are required in order to understand and optimize their operation. For reliable communication between vehicles, the spectrum access is coordinated via carrier sense multiple access (CSMA) protocol. Existing models either use a simplified network abstraction and access control scheme for analysis or depend on simulation studies. Therefore it is important to develop an analytical model for CSMA coordinated communication between vehicles. In the first part of the thesis, stochastic geometry is exploited to develop a modeling framework for CSMA coordinated inter-vehicle communication (IVC) in a multi-lane highway scenario. The performance of IVC is studied in multi-lane highways taking into account the inter-lane separations and the number of traffic lanes and it is shown that for wide multi-lane highways, the line abstraction model that is widely used in literature loses accuracy and hence the analysis is not reliable. Since the analysis of CSMA in the vehicular setting makes the analysis intractable, an aggressive interference approximation and a conservative interference approximation is proposed for the probability of transmission success. These approximations are tight in the low traffic and high traffic densities respectively. In the subsequent part of the thesis, the developed model is extended to multi-hop IVC because several vehicular applications require going beyond the local communication and efficiently disseminate information across the roads via multi-hops. Two well-known greedy packet forwarding schemes are

Model Based Analysis and Test Generation for Flight Software

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Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

Quantitative 2- and 3-dimensional analysis of pharmacokinetic model-derived variables for breast lesions in dynamic, contrast-enhanced MR mammography

International Nuclear Information System (INIS)

Hauth, E.A.M.; Jaeger, H.J.; Maderwald, S.; Muehler, A.; Kimmig, R.; Forsting, M.

2008-01-01

Purpose: 2- and 3-dimensional evaluation of quantitative pharmacokinetic parameters derived from the Tofts model modeling dynamic contrast enhancement of lesions in MR mammography. Materials and methods: In 95 patients, MR mammography revealed 127 suspicious lesions. The initial rate of enhancement was coded by color intensity, the post-initial enhancement change is coded by color hue. 2D and 3D analysis of distribution of color hue and intensity, vascular permeability and extracellular volume were performed. Results: In 2D, malignant lesions showed significant higher number of bright red, medium red, dark red, bright green, medium green, dark green and bright blue pixels than benign lesions. In 3D, statistical significant differences between malignant and benign lesions was found for all this parameters. Vascular permeability was significant higher in malignant lesions than in benign lesions. Regression model using the 3D data found that the best discriminator between malignant and benign lesions was combined number of voxels and medium green pixels, with a sensitivity of 79.4% and a specificity of 83.1%. Conclusions: Quantitative analysis of pharmacokinetic variables of contrast kinetics showed significant differences between malignant and benign lesions. 3D analysis showed superior diagnostic differentiation between malignant and benign lesions than 2D analysis. The parametric analysis using a pharmacokinetic model allows objective analysis of contrast enhancement in breast lesions

Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed.

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Chocholova, Erika; Bertok, Tomas; Jane, Eduard; Lorencova, Lenka; Holazova, Alena; Belicka, Ludmila; Belicky, Stefan; Mislovicova, Danica; Vikartovska, Alica; Imrich, Richard; Kasak, Peter; Tkac, Jan

2018-06-01

In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay formats with several lectins were applied for each serum sample. A dataset containing 2000 data points was data mined using artificial neural networks (ANN). We identified key RA markers, which can discriminate between healthy people and seropositive RA patients (serum containing autoantibodies) with accuracy of 83.3%. Combination of RA markers with glycan analysis provided much better discrimination accuracy of 92.5%. Immunoassays completely failed to identify seronegative RA patients (serum not containing autoantibodies), while glycan analysis correctly identified 43.8% of these patients. Further, we revealed other critical parameters for successful glycan analysis such as type of a sample, format of analysis and orientation of captured antibodies for glycan analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative genomic analysis of Brucella abortus vaccine strain 104M reveals a set of candidate genes associated with its virulence attenuation.

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Yu, Dong; Hui, Yiming; Zai, Xiaodong; Xu, Junjie; Liang, Long; Wang, Bingxiang; Yue, Junjie; Li, Shanhu

2015-01-01

The Brucella abortus strain 104M, a spontaneously attenuated strain, has been used as a vaccine strain in humans against brucellosis for 6 decades in China. Despite many studies, the molecular mechanisms that cause the attenuation are still unclear. Here, we determined the whole-genome sequence of 104M and conducted a comprehensive comparative analysis against the whole genome sequences of the virulent strain, A13334, and other reference strains. This analysis revealed a highly similar genome structure between 104M and A13334. The further comparative genomic analysis between 104M and A13334 revealed a set of genes missing in 104M. Some of these genes were identified to be directly or indirectly associated with virulence. Similarly, a set of mutations in the virulence-related genes was also identified, which may be related to virulence alteration. This study provides a set of candidate genes associated with virulence attenuation in B.abortus vaccine strain 104M.

SDI CFD MODELING ANALYSIS

Energy Technology Data Exchange (ETDEWEB)

Lee, S.

2011-05-05

The Savannah River Remediation (SRR) Organization requested that Savannah River National Laboratory (SRNL) develop a Computational Fluid Dynamics (CFD) method to mix and blend the miscible contents of the blend tanks to ensure the contents are properly blended before they are transferred from the blend tank; such as, Tank 50H, to the Salt Waste Processing Facility (SWPF) feed tank. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The transient CFD governing equations consisting of three momentum equations, one mass balance, two turbulence transport equations for kinetic energy and dissipation rate, and one species transport were solved by an iterative technique until the species concentrations of tank fluid were in equilibrium. The steady-state flow solutions for the entire tank fluid were used for flow pattern analysis, for velocity scaling analysis, and the initial conditions for transient blending calculations. A series of the modeling calculations were performed to estimate the blending times for various jet flow conditions, and to investigate the impact of the cooling coils on the blending time of the tank contents. The modeling results were benchmarked against the pilot scale test results. All of the flow and mixing models were performed with the nozzles installed at the mid-elevation, and parallel to the tank wall. From the CFD modeling calculations, the main results are summarized as follows: (1) The benchmark analyses for the CFD flow velocity and blending models demonstrate their consistency with Engineering Development Laboratory (EDL) and literature test results in terms of local velocity measurements and experimental observations. Thus, an application of the established criterion to SRS full scale tank will provide a better, physically-based estimate of the required mixing time, and

Perturbation analysis of nonlinear matrix population models

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Hal Caswell

2008-03-01

Full Text Available Perturbation analysis examines the response of a model to changes in its parameters. It is commonly applied to population growth rates calculated from linear models, but there has been no general approach to the analysis of nonlinear models. Nonlinearities in demographic models may arise due to density-dependence, frequency-dependence (in 2-sex models, feedback through the environment or the economy, and recruitment subsidy due to immigration, or from the scaling inherent in calculations of proportional population structure. This paper uses matrix calculus to derive the sensitivity and elasticity of equilibria, cycles, ratios (e.g. dependency ratios, age averages and variances, temporal averages and variances, life expectancies, and population growth rates, for both age-classified and stage-classified models. Examples are presented, applying the results to both human and non-human populations.

Novel gene function revealed by mouse mutagenesis screens for models of age-related disease.

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Potter, Paul K; Bowl, Michael R; Jeyarajan, Prashanthini; Wisby, Laura; Blease, Andrew; Goldsworthy, Michelle E; Simon, Michelle M; Greenaway, Simon; Michel, Vincent; Barnard, Alun; Aguilar, Carlos; Agnew, Thomas; Banks, Gareth; Blake, Andrew; Chessum, Lauren; Dorning, Joanne; Falcone, Sara; Goosey, Laurence; Harris, Shelley; Haynes, Andy; Heise, Ines; Hillier, Rosie; Hough, Tertius; Hoslin, Angela; Hutchison, Marie; King, Ruairidh; Kumar, Saumya; Lad, Heena V; Law, Gemma; MacLaren, Robert E; Morse, Susan; Nicol, Thomas; Parker, Andrew; Pickford, Karen; Sethi, Siddharth; Starbuck, Becky; Stelma, Femke; Cheeseman, Michael; Cross, Sally H; Foster, Russell G; Jackson, Ian J; Peirson, Stuart N; Thakker, Rajesh V; Vincent, Tonia; Scudamore, Cheryl; Wells, Sara; El-Amraoui, Aziz; Petit, Christine; Acevedo-Arozena, Abraham; Nolan, Patrick M; Cox, Roger; Mallon, Anne-Marie; Brown, Steve D M

2016-08-18

Determining the genetic bases of age-related disease remains a major challenge requiring a spectrum of approaches from human and clinical genetics to the utilization of model organism studies. Here we report a large-scale genetic screen in mice employing a phenotype-driven discovery platform to identify mutations resulting in age-related disease, both late-onset and progressive. We have utilized N-ethyl-N-nitrosourea mutagenesis to generate pedigrees of mutagenized mice that were subject to recurrent screens for mutant phenotypes as the mice aged. In total, we identify 105 distinct mutant lines from 157 pedigrees analysed, out of which 27 are late-onset phenotypes across a range of physiological systems. Using whole-genome sequencing we uncover the underlying genes for 44 of these mutant phenotypes, including 12 late-onset phenotypes. These genes reveal a number of novel pathways involved with age-related disease. We illustrate our findings by the recovery and characterization of a novel mouse model of age-related hearing loss.

Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation network

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Chamovitz Daniel A

2009-09-01

Full Text Available Abstract Background Analyses of gene expression data from microarray experiments has become a central tool for identifying co-regulated, functional gene modules. A crucial aspect of such analysis is the integration of data from different experiments and different laboratories. How to weigh the contribution of different experiments is an important point influencing the final outcomes. We have developed a novel method for this integration, and applied it to genome-wide data from multiple Arabidopsis microarray experiments performed under a variety of experimental conditions. The goal of this study is to identify functional globally co-regulated gene modules in the Arabidopsis genome. Results Following the analysis of 21,000 Arabidopsis genes in 43 datasets and about 2 × 108 gene pairs, we identified a globally co-expressed gene network. We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations. Two types of modules were identified in the regulatory network that differed in their sensitivity to the node-scoring parameter; we further showed these two pertain to general and specialized modules. Some of these modules were further investigated using the Genevestigator compendium of microarray experiments. Analyses of smaller subsets of data lead to the identification of condition-specific modules. Conclusion Our method for identification of gene clusters allows the integration of diverse microarray experiments from many sources. The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules. Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

The first Chameleon transcriptome: comparative genomic analysis of the OXPHOS system reveals loss of COX8 in Iguanian lizards.

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Bar-Yaacov, Dan; Bouskila, Amos; Mishmar, Dan

2013-01-01

Recently, we found dramatic mitochondrial DNA divergence of Israeli Chamaeleo chamaeleon populations into two geographically distinct groups. We aimed to examine whether the same pattern of divergence could be found in nuclear genes. However, no genomic resource is available for any chameleon species. Here we present the first chameleon transcriptome, obtained using deep sequencing (SOLiD). Our analysis identified 164,000 sequence contigs of which 19,000 yielded unique BlastX hits. To test the efficacy of our sequencing effort, we examined whether the chameleon and other available reptilian transcriptomes harbored complete sets of genes comprising known biochemical pathways, focusing on the nDNA-encoded oxidative phosphorylation (OXPHOS) genes as a model. As a reference for the screen, we used the human 86 (including isoforms) known structural nDNA-encoded OXPHOS subunits. Analysis of 34 publicly available vertebrate transcriptomes revealed orthologs for most human OXPHOS genes. However, OXPHOS subunit COX8 (Cytochrome C oxidase subunit 8), including all its known isoforms, was consistently absent in transcriptomes of iguanian lizards, implying loss of this subunit during the radiation of this suborder. The lack of COX8 in the suborder Iguania is intriguing, since it is important for cellular respiration and ATP production. Our sequencing effort added a new resource for comparative genomic studies, and shed new light on the evolutionary dynamics of the OXPHOS system.

Proteome analysis of schizophrenia patients Wernicke's area reveals an energy metabolism dysregulation

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Marangoni Sérgio

2009-04-01

Full Text Available Abstract Background Schizophrenia is likely to be a consequence of DNA alterations that, together with environmental factors, will lead to protein expression differences and the ultimate establishment of the illness. The superior temporal gyrus is implicated in schizophrenia and executes functions such as the processing of speech, language skills and sound processing. Methods We performed an individual comparative proteome analysis using two-dimensional gel electrophoresis of 9 schizophrenia and 6 healthy control patients' left posterior superior temporal gyrus (Wernicke's area – BA22p identifying by mass spectrometry several protein expression alterations that could be related to the disease. Results Our analysis revealed 11 downregulated and 14 upregulated proteins, most of them related to energy metabolism. Whereas many of the identified proteins have been previously implicated in schizophrenia, such as fructose-bisphosphate aldolase C, creatine kinase and neuron-specific enolase, new putative disease markers were also identified such as dihydrolipoyl dehydrogenase, tropomyosin 3, breast cancer metastasis-suppressor 1, heterogeneous nuclear ribonucleoproteins C1/C2 and phosphate carrier protein, mitochondrial precursor. Besides, the differential expression of peroxiredoxin 6 (PRDX6 and glial fibrillary acidic protein (GFAP were confirmed by western blot in schizophrenia prefrontal cortex. Conclusion Our data supports a dysregulation of energy metabolism in schizophrenia as well as suggests new markers that may contribute to a better understanding of this complex disease.

Structure-based capacitance modeling and power loss analysis for the latest high-performance slant field-plate trench MOSFET

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Kobayashi, Kenya; Sudo, Masaki; Omura, Ichiro

2018-04-01

Field-plate trench MOSFETs (FP-MOSFETs), with the features of ultralow on-resistance and very low gate–drain charge, are currently the mainstream of high-performance applications and their advancement is continuing as low-voltage silicon power devices. However, owing to their structure, their output capacitance (C oss), which leads to main power loss, remains to be a problem, especially in megahertz switching. In this study, we propose a structure-based capacitance model of FP-MOSFETs for calculating power loss easily under various conditions. Appropriate equations were modeled for C oss curves as three divided components. Output charge (Q oss) and stored energy (E oss) that were calculated using the model corresponded well to technology computer-aided design (TCAD) simulation, and we validated the accuracy of the model quantitatively. In the power loss analysis of FP-MOSFETs, turn-off loss was sufficiently suppressed, however, mainly Q oss loss increased depending on switching frequency. This analysis reveals that Q oss may become a significant issue in next-generation high-efficiency FP-MOSFETs.

K -shell decomposition reveals hierarchical cortical organization of the human brain

International Nuclear Information System (INIS)

Lahav, Nir; Ksherim, Baruch; Havlin, Shlomo; Ben-Simon, Eti; Maron-Katz, Adi; Cohen, Reuven

2016-01-01

In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features ‘small world’ characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs, and how their profile reflect the brain’s global functional organization, one needs to go beyond the properties of a specific hub and examine the various structural layers that make up the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI/DSI data of six participants. Such analysis enables us to portray a detailed account of cortical connectivity focusing on different neighborhoods of inter-connected layers across the cortex. Our findings reveal that the human cortex is highly connected and efficient, and unlike the internet network contains no isolated nodes. The cortical network is comprised of a nucleus alongside shells of increasing connectivity that formed one connected giant component, revealing the human brain’s global functional organization. All these components were further categorized into three hierarchies in accordance with their connectivity profile, with each hierarchy reflecting different functional roles. Such a model may explain an efficient flow of information from the lowest hierarchy to the highest one, with each step enabling increased data integration. At the top, the highest hierarchy (the nucleus) serves as a global interconnected collective and demonstrates high correlation with consciousness related regions, suggesting that the nucleus might serve as a

Macroeconomic effects on mortality revealed by panel analysis with nonlinear trends.

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Ionides, Edward L; Wang, Zhen; Tapia Granados, José A

2013-10-03

Many investigations have used panel methods to study the relationships between fluctuations in economic activity and mortality. A broad consensus has emerged on the overall procyclical nature of mortality: perhaps counter-intuitively, mortality typically rises above its trend during expansions. This consensus has been tarnished by inconsistent reports on the specific age groups and mortality causes involved. We show that these inconsistencies result, in part, from the trend specifications used in previous panel models. Standard econometric panel analysis involves fitting regression models using ordinary least squares, employing standard errors which are robust to temporal autocorrelation. The model specifications include a fixed effect, and possibly a linear trend, for each time series in the panel. We propose alternative methodology based on nonlinear detrending. Applying our methodology on data for the 50 US states from 1980 to 2006, we obtain more precise and consistent results than previous studies. We find procyclical mortality in all age groups. We find clear procyclical mortality due to respiratory disease and traffic injuries. Predominantly procyclical cardiovascular disease mortality and countercyclical suicide are subject to substantial state-to-state variation. Neither cancer nor homicide have significant macroeconomic association.

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

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Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

Application of QSAR models in analysis of antibacterial activity of some benzimidazole derivatives against Sarcina lutea

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Podunavac-Kuzmanović Sanja O.

2013-01-01

Full Text Available In the present paper, a quantitative structure activity relationship (QSAR has been carried out on a series of 2-methyl and 2-aminobenzimidazole derivatives to identify the lipophilicity requirements for their inhibitory activity against bacteria Sarcina lutea. The tested compounds displayed in vitro antibacterial activity and minimum inhibitory concentration (MIC was determined for all compounds. The partition coefficients of the studied compounds were measured by the shake flask method (log P and by theoretical calculation (Clog P. The relationships between lipophilicity descriptors and antibacterial activities were investigated and the mathematical models have been developed as a calibration models for predicting the inhibitory activity of this class of compounds. The models were validated by leave-one-out (LOO technique as well as by the calculation of statistical parameters for the established models. Therefore, QSAR analysis reveals that lipophilicity descriptor govern the inhibitory activity of benzimidazoles studied against Sarcina lutea.

Comparative and Evolutionary Analysis of Grass Pollen Allergens Using Brachypodium distachyon as a Model System.

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Akanksha Sharma

Full Text Available Comparative genomics have facilitated the mining of biological information from a genome sequence, through the detection of similarities and differences with genomes of closely or more distantly related species. By using such comparative approaches, knowledge can be transferred from the model to non-model organisms and insights can be gained in the structural and evolutionary patterns of specific genes. In the absence of sequenced genomes for allergenic grasses, this study was aimed at understanding the structure, organisation and expression profiles of grass pollen allergens using the genomic data from Brachypodium distachyon as it is phylogenetically related to the allergenic grasses. Combining genomic data with the anther RNA-Seq dataset revealed 24 pollen allergen genes belonging to eight allergen groups mapping on the five chromosomes in B. distachyon. High levels of anther-specific expression profiles were observed for the 24 identified putative allergen-encoding genes in Brachypodium. The genomic evidence suggests that gene encoding the group 5 allergen, the most potent trigger of hay fever and allergic asthma originated as a pollen specific orphan gene in a common grass ancestor of Brachypodium and Triticiae clades. Gene structure analysis showed that the putative allergen-encoding genes in Brachypodium either lack or contain reduced number of introns. Promoter analysis of the identified Brachypodium genes revealed the presence of specific cis-regulatory sequences likely responsible for high anther/pollen-specific expression. With the identification of putative allergen-encoding genes in Brachypodium, this study has also described some important plant gene families (e.g. expansin superfamily, EF-Hand family, profilins etc for the first time in the model plant Brachypodium. Altogether, the present study provides new insights into structural characterization and evolution of pollen allergens and will further serve as a base for their

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

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Qing Zhu

2014-01-01

Full Text Available As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Comparative Analysis of Membrane Vesicles from Three Piscirickettsia salmonis Isolates Reveals Differences in Vesicle Characteristics.

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Julia I Tandberg

Full Text Available Membrane vesicles (MVs are spherical particles naturally released from the membrane of Gram-negative bacteria. Bacterial MV production is associated with a range of phenotypes including biofilm formation, horizontal gene transfer, toxin delivery, modulation of host immune responses and virulence. This study reports comparative profiling of MVs from bacterial strains isolated from three widely disperse geographical areas. Mass spectrometry identified 119, 159 and 142 proteins in MVs from three different strains of Piscirickettsia salmonis isolated from salmonids in Chile (LF-89, Norway (NVI 5692 and Canada (NVI 5892, respectively. MV comparison revealed several strain-specific differences related to higher virulence capability for LF-89 MVs, both in vivo and in vitro, and stronger similarities between the NVI 5692 and NVI 5892 MV proteome. The MVs were similar in size and appearance as analyzed by electron microscopy and dynamic light scattering. The MVs from all three strains were internalized by both commercial and primary immune cell cultures, which suggest a potential role of the MVs in the bacterium's utilization of leukocytes. When MVs were injected into an adult zebrafish infection model, an upregulation of several pro-inflammatory genes were observed in spleen and kidney, indicating a modulating effect on the immune system. The present study is the first comparative analysis of P. salmonis derived MVs, highlighting strain-specific vesicle characteristics. The results further illustrate that the MV proteome from one bacterial strain is not representative of all bacterial strains within one species.

Catchment tracers reveal discharge, recharge and sources of groundwater-borne pollutants in a novel lake modelling approach

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Kristensen, Emil; Madsen-Østerbye, Mikkel; Massicotte, Philippe; Pedersen, Ole; Markager, Stiig; Kragh, Theis

2018-02-01

groundwater discharge sites located mainly in the eastern part of the lake with a single site in the southern part. Observations from the eastern part of the lake revealed an impermeable clay layer that promotes discharge during heavy precipitation events, which would otherwise be difficult to identify using traditional hydrological methods. In comparison to the lake concentrations, high tracer concentrations in the southern part showed that only a smaller fraction of water could originate from this area, thereby confirming the model results. A Euclidean cluster analysis of δ18O isotopes identified recharge sites corresponding to areas adjacent to drainage channels, and a cluster analysis of the microbially influenced FDOM component C4 further identified five sites that showed a tendency towards high groundwater recharge rate. In conclusion, it was found that this methodology can be applied to smaller lakes within a short time frame, providing useful information regarding the WRT of the lake and more importantly the groundwater recharge and discharge sites around the lake. Thus, it is a tool for specific management of the catchment.

Computer modelling reveals new conformers of the ATP binding loop of Na+/K+-ATPase involved in the transphosphorylation process of the sodium pump

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Gracian Tejral

2017-03-01

Full Text Available Hydrolysis of ATP by Na+/K+-ATPase, a P-Type ATPase, catalyzing active Na+ and K+ transport through cellular membranes leads transiently to a phosphorylation of its catalytical α-subunit. Surprisingly, three-dimensional molecular structure analysis of P-type ATPases reveals that binding of ATP to the N-domain connected by a hinge to the P-domain is much too far away from the Asp369 to allow the transfer of ATP’s terminal phosphate to its aspartyl-phosphorylation site. In order to get information for how the transfer of the γ-phosphate group of ATP to the Asp369 is achieved, analogous molecular modeling of the M4–M5 loop of ATPase was performed using the crystal data of Na+/K+-ATPase of different species. Analogous molecular modeling of the cytoplasmic loop between Thr338 and Ile760 of the α2-subunit of Na+/K+-ATPase and the analysis of distances between the ATP binding site and phosphorylation site revealed the existence of two ATP binding sites in the open conformation; the first one close to Phe475 in the N-domain, the other one close to Asp369 in the P-domain. However, binding of Mg2+•ATP to any of these sites in the “open conformation” may not lead to phosphorylation of Asp369. Additional conformations of the cytoplasmic loop were found wobbling between “open conformation”  “semi-open conformation  “closed conformation” in the absence of 2Mg2+•ATP. The cytoplasmic loop’s conformational change to the “semi-open conformation”—characterized by a hydrogen bond between Arg543 and Asp611—triggers by binding of 2Mg2+•ATP to a single ATP site and conversion to the “closed conformation” the phosphorylation of Asp369 in the P-domain, and hence the start of Na+/K+-activated ATP hydrolysis.

Two-Segment Foot Model for the Biomechanical Analysis of Squat.

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Panero, E; Gastaldi, L; Rapp, W

2017-01-01

Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model that considers separately the forefoot and the hindfoot. The forefoot and hindfoot are articulated by the midtarsal joint. Five subjects performed a series of three trials, and results were averaged. Joint kinematics and dynamics were obtained using motion capture system, two force plates closed together, and inverse dynamics techniques. The midtarsal joint reached a dorsiflexion peak of 4°. Different strategies between subjects revealed 4° supination and 2.5° pronation of the forefoot. Vertical GRF showed 20% of body weight concentrated on the forefoot and 30% on the hindfoot. The percentages varied during motion, with a peak of 40% on the hindfoot and correspondently 10% on the forefoot, while the traditional model depicted the unique constant 50% value. Ankle peak of plantarflexion moment, power absorption, and power generation was consistent with values estimated by the one-segment model, without statistical significance.

Two-Segment Foot Model for the Biomechanical Analysis of Squat

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E. Panero

2017-01-01

Full Text Available Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model that considers separately the forefoot and the hindfoot. The forefoot and hindfoot are articulated by the midtarsal joint. Five subjects performed a series of three trials, and results were averaged. Joint kinematics and dynamics were obtained using motion capture system, two force plates closed together, and inverse dynamics techniques. The midtarsal joint reached a dorsiflexion peak of 4°. Different strategies between subjects revealed 4° supination and 2.5° pronation of the forefoot. Vertical GRF showed 20% of body weight concentrated on the forefoot and 30% on the hindfoot. The percentages varied during motion, with a peak of 40% on the hindfoot and correspondently 10% on the forefoot, while the traditional model depicted the unique constant 50% value. Ankle peak of plantarflexion moment, power absorption, and power generation was consistent with values estimated by the one-segment model, without statistical significance.

Proteomic analysis of MG132-treated germinating pollen reveals expression signatures associated with proteasome inhibition.

Directory of Open Access Journals (Sweden)

Candida Vannini

Full Text Available Chemical inhibition of the proteasome has been previously found to effectively impair pollen germination and tube growth in vitro. However, the mediators of these effects at the molecular level are unknown. By performing 2DE proteomic analysis, 24 differentially expressed protein spots, representing 14 unique candidate proteins, were identified in the pollen of kiwifruit (Actinidia deliciosa germinated in the presence of the MG132 proteasome inhibitor. qPCR analysis revealed that 11 of these proteins are not up-regulated at the mRNA level, but are most likely stabilized by proteasome inhibition. These differentially expressed proteins are predicted to function in various pathways including energy and lipid metabolism, cell wall synthesis, protein synthesis/degradation and stress responses. In line with this evidence, the MG132-induced changes in the proteome were accompanied by an increase in ATP and ROS content and by an alteration in fatty acid composition.

Horizontal crash testing and analysis of model flatrols

International Nuclear Information System (INIS)

Dowler, H.J.; Soanes, T.P.T.

1985-01-01

To assess the behaviour of a full scale flask and flatrol during a proposed demonstration impact into a tunnel abutment, a mathematical modelling technique was developed and validated. The work was performed at quarter scale and comprised of both scale model tests and mathematical analysis in one and two dimensions. Good agreement between model test results of the 26.8m/s (60 mph) abutment impacts and the mathematical analysis, validated the modelling techniques. The modelling method may be used with confidence to predict the outcome of the proposed full scale demonstration. (author)

Economic analysis model for total energy and economic systems

International Nuclear Information System (INIS)

Shoji, Katsuhiko; Yasukawa, Shigeru; Sato, Osamu

1980-09-01

This report describes framing an economic analysis model developed as a tool of total energy systems. To prospect and analyze future energy systems, it is important to analyze the relation between energy system and economic structure. We prepared an economic analysis model which was suited for this purpose. Our model marks that we can analyze in more detail energy related matters than other economic ones, and can forecast long-term economic progress rather than short-term economic fluctuation. From view point of economics, our model is longterm multi-sectoral economic analysis model of open Leontief type. Our model gave us appropriate results for fitting test and forecasting estimation. (author)

Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles

Energy Technology Data Exchange (ETDEWEB)

Callister, S.J.; Wilkins, M.J.; Nicora, C.D.; Williams, K.H.; Banfield, J.F.; VerBerkmoes, N.C.; Hettich, R.L.; NGuessan, A.L.; Mouser, P.J.; Elifantz, H.; Smith, R.D.; Lovley, D.R.; Lipton, M.S.; Long, P.E.

2010-07-15

Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetate-amended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or “pseudo-metagenomes”, for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally, a shift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.

Applied data analysis and modeling for energy engineers and scientists

CERN Document Server

Reddy, T Agami

2011-01-01

""Applied Data Analysis and Modeling for Energy Engineers and Scientists"" discusses mathematical models, data analysis, and decision analysis in modeling. The approach taken in this volume focuses on the modeling and analysis of thermal systems in an engineering environment, while also covering a number of other critical areas. Other material covered includes the tools that researchers and engineering professionals will need in order to explore different analysis methods, use critical assessment skills and reach sound engineering conclusions. The book also covers process and system design and

Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models

Science.gov (United States)

Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris

2015-11-01

Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

Science.gov (United States)

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

REVEAL: Software Documentation and Platform Migration

Science.gov (United States)

Wilson, Michael A.; Veibell, Victoir T.; Freudinger, Lawrence C.

2008-01-01

The Research Environment for Vehicle Embedded Analysis on Linux (REVEAL) is reconfigurable data acquisition software designed for network-distributed test and measurement applications. In development since 2001, it has been successfully demonstrated in support of a number of actual missions within NASA s Suborbital Science Program. Improvements to software configuration control were needed to properly support both an ongoing transition to operational status and continued evolution of REVEAL capabilities. For this reason the project described in this report targets REVEAL software source documentation and deployment of the software on a small set of hardware platforms different from what is currently used in the baseline system implementation. This report specifically describes the actions taken over a ten week period by two undergraduate student interns and serves as a final report for that internship. The topics discussed include: the documentation of REVEAL source code; the migration of REVEAL to other platforms; and an end-to-end field test that successfully validates the efforts.

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways.

Science.gov (United States)

Äijö, Tarmo; Huang, Yun; Mannerström, Henrik; Chavez, Lukas; Tsagaratou, Ageliki; Rao, Anjana; Lähdesmäki, Harri

2016-03-14

We present a generative model, Lux, to quantify DNA methylation modifications from any combination of bisulfite sequencing approaches, including reduced, oxidative, TET-assisted, chemical-modification assisted, and methylase-assisted bisulfite sequencing data. Lux models all cytosine modifications (C, 5mC, 5hmC, 5fC, and 5caC) simultaneously together with experimental parameters, including bisulfite conversion and oxidation efficiencies, as well as various chemical labeling and protection steps. We show that Lux improves the quantification and comparison of cytosine modification levels and that Lux can process any oxidized methylcytosine sequencing data sets to quantify all cytosine modifications. Analysis of targeted data from Tet2-knockdown embryonic stem cells and T cells during development demonstrates DNA modification quantification at unprecedented detail, quantifies active demethylation pathways and reveals 5hmC localization in putative regulatory regions.

Application of Statistical Model in Wastewater Treatment Process Modeling Using Data Analysis

Directory of Open Access Journals (Sweden)

Alireza Raygan Shirazinezhad

2015-06-01

Full Text Available Background: Wastewater treatment includes very complex and interrelated physical, chemical and biological processes which using data analysis techniques can be rigorously modeled by a non-complex mathematical calculation models. Materials and Methods: In this study, data on wastewater treatment processes from water and wastewater company of Kohgiluyeh and Boyer Ahmad were used. A total of 3306 data for COD, TSS, PH and turbidity were collected, then analyzed by SPSS-16 software (descriptive statistics and data analysis IBM SPSS Modeler 14.2, through 9 algorithm. Results: According to the results on logistic regression algorithms, neural networks, Bayesian networks, discriminant analysis, decision tree C5, tree C & R, CHAID, QUEST and SVM had accuracy precision of 90.16, 94.17, 81.37, 70.48, 97.89, 96.56, 96.46, 96.84 and 88.92, respectively. Discussion and conclusion: The C5 algorithm as the best and most applicable algorithms for modeling of wastewater treatment processes were chosen carefully with accuracy of 97.899 and the most influential variables in this model were PH, COD, TSS and turbidity.

Proteomic analysis of pig (Sus scrofa olfactory soluble proteome reveals O-GlcNAcylation of secreted odorant-binding proteins

Directory of Open Access Journals (Sweden)

Patricia eNAGNAN-LE MEILLOUR

2014-12-01

Full Text Available The diversity of olfactory binding proteins (OBPs is a key point to understand their role in molecular olfaction. Since only few different sequences were characterized in each mammalian species, they have been considered as passive carriers of odors and pheromones. We have explored the soluble proteome of pig nasal mucus, taking benefit of the powerful tools of proteomics. Combining two-dimensional electrophoresis, mass spectrometry and western-blot with specific antibodies, our analyses revealed for the first time that the pig nasal mucus is mainly composed of secreted OBP isoforms, some of them being potentially modified by O-GlcNAcylation. An ortholog gene of the glycosyltransferase responsible of the O-GlcNAc linking on extracellular proteins in Drosophila and Mouse (EOGT was amplified from tissues of pigs of different ages and sex. The sequence was used in a phylogenetic analysis, which evidenced conservation of EOGT in insect and mammalian models studied in molecular olfaction. Extracellular O-GlcNAcylation of secreted OBPs could finely modulate their binding specificities to odors and pheromones. This constitutes a new mechanism for extracellular signaling by OBPs, suggesting that they act as the first step of odor discrimination.

Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses

DEFF Research Database (Denmark)

Brok, J.; Thorlund, K.; Gluud, C.

2008-01-01

in 80% (insufficient information size). TSA(15%) and TSA(LBHIS) found that 95% and 91% had absence of evidence. The remaining nonsignificant meta-analyses had evidence of lack of effect. CONCLUSION: TSA reveals insufficient information size and potentially false positive results in many meta......OBJECTIVES: To evaluate meta-analyses with trial sequential analysis (TSA). TSA adjusts for random error risk and provides the required number of participants (information size) in a meta-analysis. Meta-analyses not reaching information size are analyzed with trial sequential monitoring boundaries...... analogous to interim monitoring boundaries in a single trial. STUDY DESIGN AND SETTING: We applied TSA on meta-analyses performed in Cochrane Neonatal reviews. We calculated information sizes and monitoring boundaries with three different anticipated intervention effects of 30% relative risk reduction (TSA...

Analysis of VAWT aerodynamics and design using the Actuator Cylinder flow model

International Nuclear Information System (INIS)

Madsen, H Aa; Paulsen, U S; Vitae, L

2014-01-01

The actuator cylinder (AC) flow model is defined as the ideal VAWT rotor. Radial directed volume forces are applied on the circular path of the VAWT rotor airfoil and constitute an energy conversion in the flow. The power coefficient for the ideal as well as the real energy conversion is defined. The describing equations for the two-dimensional AC model are presented and a solution method splitting the final solution in a linear and non-linear part is briefly described. A family of loadforms approaching the uniform loading is used to study the ideal energy conversion indicating that the maximum power coefficient for the ideal energy conversion of a VAWT could exceed the Betz limit. The real energy conversion of the 5MW DeepWind rotor is simulated with the AC flow model in combination with the blade element analysis. Aerodynamic design aspects are discussed on this basis revealing that the maximum obtainable power coefficient for a fixed pitch VAWT is constrained by the fundamental cyclic variation of inflow angle and relative velocity leading to a loading that deviates considerably from the uniform loading

Interactive Visual Analysis within Dynamic Ocean Models

Science.gov (United States)

Butkiewicz, T.

2012-12-01

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

Cryogenic EBSD reveals structure of directionally solidified ice–polymer composite

Energy Technology Data Exchange (ETDEWEB)

Donius, Amalie E., E-mail: amalie.donius@gmail.com [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States); Department of Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104 (United States); Obbard, Rachel W., E-mail: Rachel.W.Obbard@dartmouth.edu [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States); Burger, Joan N., E-mail: ridge.of.the.ancients@gmail.com [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States); Department of Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104 (United States); Hunger, Philipp M., E-mail: philipp.m.hunger@gmail.com [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States); Department of Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104 (United States); Baker, Ian, E-mail: Ian.Baker@dartmouth.edu [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States); Doherty, Roger D., E-mail: dohertrd@drexel.edu [Department of Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104 (United States); Wegst, Ulrike G.K., E-mail: ulrike.wegst@dartmouth.edu [Thayer School of Engineering, Dartmouth College, 14 Engineering Drive, Hanover, NH 03755 (United States)

2014-07-01

Despite considerable research efforts on directionally solidified or freeze-cast materials in recent years, little fundamental knowledge has been gained that links model with experiment. In this contribution, the cryogenic characterization of directionally solidified polymer solutions illustrates, how powerful cryo-scanning electron microscopy combined with electron backscatter diffraction is for the structural characterization of ice–polymer composite materials. Under controlled sublimation, the freeze-cast polymer scaffold structure is revealed and imaged with secondary electrons. Electron backscatter diffraction fabric analysis shows that the ice crystals, which template the polymer scaffold and create the lamellar structure, have a-axes oriented parallel to the direction of solidification and the c-axes perpendicular to it. These results indicate the great potential of both cryo-scanning electron microscopy and cryo-electron backscatter diffraction in gaining fundamental knowledge of structure–property–processing correlations. - Highlights: • Cryo-SEM of freeze-cast polymer solution reveals an ice-templated structure. • Cryo-EBSD reveals the ice crystal a-axis to parallel the solidification direction. • The honeycomb-like polymer phase favors columnar ridges only on one side. • Combining cryo-SEM with EBSD links solidification theory with experiment.

Cryogenic EBSD reveals structure of directionally solidified ice–polymer composite

International Nuclear Information System (INIS)

Donius, Amalie E.; Obbard, Rachel W.; Burger, Joan N.; Hunger, Philipp M.; Baker, Ian; Doherty, Roger D.; Wegst, Ulrike G.K.

2014-01-01

Despite considerable research efforts on directionally solidified or freeze-cast materials in recent years, little fundamental knowledge has been gained that links model with experiment. In this contribution, the cryogenic characterization of directionally solidified polymer solutions illustrates, how powerful cryo-scanning electron microscopy combined with electron backscatter diffraction is for the structural characterization of ice–polymer composite materials. Under controlled sublimation, the freeze-cast polymer scaffold structure is revealed and imaged with secondary electrons. Electron backscatter diffraction fabric analysis shows that the ice crystals, which template the polymer scaffold and create the lamellar structure, have a-axes oriented parallel to the direction of solidification and the c-axes perpendicular to it. These results indicate the great potential of both cryo-scanning electron microscopy and cryo-electron backscatter diffraction in gaining fundamental knowledge of structure–property–processing correlations. - Highlights: • Cryo-SEM of freeze-cast polymer solution reveals an ice-templated structure. • Cryo-EBSD reveals the ice crystal a-axis to parallel the solidification direction. • The honeycomb-like polymer phase favors columnar ridges only on one side. • Combining cryo-SEM with EBSD links solidification theory with experiment

Revealing time bunching effect in single-molecule enzyme conformational dynamics.

Science.gov (United States)

Lu, H Peter

2011-04-21

In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a

Comparative genome analysis of Megasphaera sp. reveals niche specialization and its potential role in the human gut.

Directory of Open Access Journals (Sweden)

Sudarshan Anand Shetty

Full Text Available With increasing number of novel bacteria being isolated from the human gut ecosystem, there is a greater need to study their role in the gut ecosystem and their effect on the host health. In the present study, we carried out in silico genome-wide analysis of two novel Megasphaera sp. isolates NM10 (DSM25563 and BL7 (DSM25562, isolated from feces of two healthy individuals and validated the key features by in vitro studies. The analysis revealed the general metabolic potential, adaptive features and the potential effects of these isolates on the host. The comparative genome analysis of the two human gut isolates NM10 and BL7 with ruminal isolate Megasphaera elsdenii (DSM20460 highlighted the differential adaptive features for their survival in human gut. The key findings include features like bile resistance, presence of various sensory and regulatory systems, stress response systems, membrane transporters and resistance to antibiotics. Comparison of the "glycobiome" based on the genomes of the ruminal isolate with the human gut isolates NM10 and BL revealed the presence of diverse and unique sets of Carbohydrate-Active enzymes (CAZymes amongst these isolates, with a higher collection of CAZymes in the human gut isolates. This could be attributed to the difference in host diet and thereby the environment, consequently suggesting host specific adaptation in these isolates. In silico analysis of metabolic potential predicted the ability of these isolates to produce important metabolites like short chain fatty acids (butyrate, acetate, formate, and caproate, vitamins and essential amino acids, which was further validated by in vitro experiments. The ability of these isolates to produce important metabolites advocates for a potential healthy influence on the host. Further in vivo studies including transcriptomic and proteomic analysis will be required for better understanding the role and impact of these Megasphaera sp. isolates NM10 and BL7 on the

Gene expression analysis of zebrafish melanocytes, iridophores, and retinal pigmented epithelium reveals indicators of biological function and developmental origin.

Directory of Open Access Journals (Sweden)

Charles W Higdon

Full Text Available In order to facilitate understanding of pigment cell biology, we developed a method to concomitantly purify melanocytes, iridophores, and retinal pigmented epithelium from zebrafish, and analyzed their transcriptomes. Comparing expression data from these cell types and whole embryos allowed us to reveal gene expression co-enrichment in melanocytes and retinal pigmented epithelium, as well as in melanocytes and iridophores. We found 214 genes co-enriched in melanocytes and retinal pigmented epithelium, indicating the shared functions of melanin-producing cells. We found 62 genes significantly co-enriched in melanocytes and iridophores, illustrative of their shared developmental origins from the neural crest. This is also the first analysis of the iridophore transcriptome. Gene expression analysis for iridophores revealed extensive enrichment of specific enzymes to coordinate production of their guanine-based reflective pigment. We speculate the coordinated upregulation of specific enzymes from several metabolic pathways recycles the rate-limiting substrate for purine synthesis, phosphoribosyl pyrophosphate, thus constituting a guanine cycle. The purification procedure and expression analysis described here, along with the accompanying transcriptome-wide expression data, provide the first mRNA sequencing data for multiple purified zebrafish pigment cell types, and will be a useful resource for further studies of pigment cell biology.

Revealed preference with limited consideration

NARCIS (Netherlands)

Demuynck, T.; Seel, C.

2014-01-01

We derive revealed preference tests for models where individuals use consideration sets to simplify their consumption problem. Our basic test provides necessary and sufficient conditions for consistency of observed choices with the existence of consideration set restrictions. The same conditions can

Sensitivity Analysis of Biome-Bgc Model for Dry Tropical Forests of Vindhyan Highlands, India

Science.gov (United States)

Kumar, M.; Raghubanshi, A. S.

2011-08-01

A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to projected leaf area ratio and Canopy water interception coefficient (Wint). Therefore, these parameters need more precision and attention during estimation and observation in the field studies.

Meta-Analysis of Public Microarray Datasets Reveals Voltage-Gated Calcium Gene Signatures in Clinical Cancer Patients.

Directory of Open Access Journals (Sweden)

Chih-Yang Wang

Full Text Available Voltage-gated calcium channels (VGCCs are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org, a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment.

Network analysis of an in vitro model of androgen-resistance in prostate cancer

International Nuclear Information System (INIS)

Detchokul, Sujitra; Elangovan, Aparna; Crampin, Edmund J.; Davis, Melissa J.; Frauman, Albert G.

2015-01-01

The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer. We have developed an in vitro model of androgen-resistance to characterise molecular changes occurring as androgen resistance evolves over time. Our aim is to understand biological network profiles of transcriptomic changes occurring during the transition to androgen-resistance and to validate these changes between our in vitro model and clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced prostate cancer). We established an androgen-independent subline from LNCaP cells by prolonged exposure to androgen-deprivation. We examined phenotypic profiles and performed RNA-sequencing. The reads generated were compared to human clinical samples and were analysed using differential expression, pathway analysis and protein-protein interaction networks. After 24 weeks of androgen-deprivation, LNCaP cells had increased proliferative and invasive behaviour compared to parental LNCaP, and its growth was no longer responsive to androgen. We identified key genes and pathways that overlap between our cell line and clinical RNA sequencing datasets and analysed the overlapping protein-protein interaction network that shared the same pattern of behaviour in both datasets. Mechanisms bypassing androgen receptor signalling pathways are significantly enriched. Several steroid hormone receptors are differentially expressed in both datasets. In particular, the progesterone receptor is significantly differentially expressed and is part of the interaction network disrupted in both datasets. Other signalling pathways commonly altered in prostate cancer, MAPK and PI3K-Akt pathways, are significantly enriched in both datasets. The overlap between the human and cell-line differential expression profiles and protein networks was statistically significant showing that the cell-line model reproduces molecular patterns observed in

Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.

Science.gov (United States)

Wang, Yuzhi; Zhang, Yi; Huang, Qian; Li, Chengwen

2018-04-19

Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non‑tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t‑tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein‑protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM‑receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator‑activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2‑a, baculoviral inhibitor of apoptosis repeat‑containing protein 5, cyclin‑dependent kinase 1, G2/mitotic‑specific cyclin‑B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid‑body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide

Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.

Science.gov (United States)

Xi, W-D; Liu, Y-J; Sun, X-B; Shan, J; Yi, L; Zhang, T-T

2017-07-01

RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) 1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt. A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7. Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.

Modeling issues in nuclear plant fire risk analysis

International Nuclear Information System (INIS)

Siu, N.

1989-01-01

This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

Models as Tools of Analysis of a Network Organisation

Directory of Open Access Journals (Sweden)

Wojciech Pająk

2013-06-01

Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression.

Science.gov (United States)

Megger, Dominik A; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

Directory of Open Access Journals (Sweden)

Dominik A. Megger

2017-09-01

Full Text Available Interferons (IFNs are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction. In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

Sensitivity Analysis of Launch Vehicle Debris Risk Model

Science.gov (United States)

Gee, Ken; Lawrence, Scott L.

2010-01-01

As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

A sensitivity analysis of centrifugal compressors' empirical models

International Nuclear Information System (INIS)

Yoon, Sung Ho; Baek, Je Hyun

2001-01-01

The mean-line method using empirical models is the most practical method of predicting off-design performance. To gain insight into the empirical models, the influence of empirical models on the performance prediction results is investigated. We found that, in the two-zone model, the secondary flow mass fraction has a considerable effect at high mass flow-rates on the performance prediction curves. In the TEIS model, the first element changes the slope of the performance curves as well as the stable operating range. The second element makes the performance curves move up and down as it increases or decreases. It is also discovered that the slip factor affects pressure ratio, but it has little effect on efficiency. Finally, this study reveals that the skin friction coefficient has significant effect on both the pressure ratio curve and the efficiency curve. These results show the limitations of the present empirical models, and more reasonable empirical models are reeded

Revealing topographic lineaments through IHS enhancement of DEM data. [Digital Elevation Model