Sedimentation equilibrium analysis of protein interactions with global implicit mass conservation constraints and systematic noise decomposition.

PubMed

Vistica, Jennifer; Dam, Julie; Balbo, Andrea; Yikilmaz, Emine; Mariuzza, Roy A; Rouault, Tracey A; Schuck, Peter

2004-03-15

Sedimentation equilibrium is a powerful tool for the characterization of protein self-association and heterogeneous protein interactions. Frequently, it is applied in a configuration with relatively long solution columns and with equilibrium profiles being acquired sequentially at several rotor speeds. The present study proposes computational tools, implemented in the software SEDPHAT, for the global analysis of equilibrium data at multiple rotor speeds with multiple concentrations and multiple optical detection methods. The detailed global modeling of such equilibrium data can be a nontrivial computational problem. It was shown previously that mass conservation constraints can significantly improve and extend the analysis of heterogeneous protein interactions. Here, a method for using conservation of mass constraints for the macromolecular redistribution is proposed in which the effective loading concentrations are calculated from the sedimentation equilibrium profiles. The approach is similar to that described by Roark (Biophys. Chem. 5 (1976) 185-196), but its utility is extended by determining the bottom position of the solution columns from the macromolecular redistribution. For analyzing heterogeneous associations at multiple protein concentrations, additional constraints that relate the effective loading concentrations of the different components or their molar ratio in the global analysis are introduced. Equilibrium profiles at multiple rotor speeds also permit the algebraic determination of radial-dependent baseline profiles, which can govern interference optical ultracentrifugation data, but usually also occur, to a smaller extent, in absorbance optical data. Finally, the global analysis of equilibrium profiles at multiple rotor speeds with implicit mass conservation and computation of the bottom of the solution column provides an unbiased scale for determining molar mass distributions of noninteracting species. The properties of these tools are studied with theoretical and experimental data sets.

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.

Testing Interaction Effects without Discarding Variance.

ERIC Educational Resources Information Center

Lopez, Kay A.

Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

Reconstruction of interatomic vectors by principle component analysis of nuclear magnetic resonance data in multiple alignments

NASA Astrophysics Data System (ADS)

Hus, Jean-Christophe; Bruschweiler, Rafael

2002-07-01

A general method is presented for the reconstruction of interatomic vector orientations from nuclear magnetic resonance (NMR) spectroscopic data of tensor interactions of rank 2, such as dipolar coupling and chemical shielding anisotropy interactions, in solids and partially aligned liquid-state systems. The method, called PRIMA, is based on a principal component analysis of the covariance matrix of the NMR parameters collected for multiple alignments. The five nonzero eigenvalues and their eigenvectors efficiently allow the approximate reconstruction of the vector orientations of the underlying interactions. The method is demonstrated for an isotropic distribution of sample orientations as well as for finite sets of orientations and internuclear vectors encountered in protein systems.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

NASA Technical Reports Server (NTRS)

Dawicke, D. S.; Newman, J. C., Jr.

1992-01-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores.

PubMed

Chikkagoudar, Satish; Wang, Kai; Li, Mingyao

2011-05-26

Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.

GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

PubMed Central

2011-01-01

Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/. PMID:21615923

Untangling the Diverse Interior and Multiple Exterior Guest Interactions of a Supramolecular Host by the Simultaneous Analysis of Complementary Observables.

PubMed

Sgarlata, Carmelo; Raymond, Kenneth N

2016-07-05

The entropic and enthalpic driving forces for encapsulation versus sequential exterior guest binding to the [Ga4L6](12-) supramolecular host in solution are very different, which significantly complicates the determination of these thermodynamic parameters. The simultaneous use of complementary techniques, such as NMR, UV-vis, and isothermal titration calorimetry, enables the disentanglement of such multiple host-guest interactions. Indeed, data collected by each technique measure different components of the host-guest equilibria and together provide a complete picture of the solution thermodynamics. Unfortunately, commercially available programs do not allow for global analysis of different physical observables. We thus resorted to a novel procedure for the simultaneous refinement of multiple parameters (ΔG°, ΔH°, and ΔS°) by treating different observables through a weighted nonlinear least-squares analysis of a constrained model. The refinement procedure is discussed for the multiple binding of the Et4N(+) guest, but it is broadly applicable to the deconvolution of other intricate host-guest equilibria.

The Use of Multiple Regression Models to Determine if Conjoint Analysis Should Be Conducted on Aggregate Data.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1996-01-01

In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Using Infrared Thermography to Assess Emotional Responses to Infants

ERIC Educational Resources Information Center

Esposito, Gianluca; Nakazawa, Jun; Ogawa, Shota; Stival, Rita; Putnick, Diane L.; Bornstein, Marc H.

2015-01-01

Adult-infant interactions operate simultaneously across multiple domains and at multiple levels -- from physiology to behaviour. Unpackaging and understanding them, therefore, involve analysis of multiple data streams. In this study, we tested physiological responses and cognitive preferences for infant and adult faces in adult females and males.…

INTERSPIA: a web application for exploring the dynamics of protein-protein interactions among multiple species.

PubMed

Kwon, Daehong; Lee, Daehwan; Kim, Juyeon; Lee, Jongin; Sim, Mikang; Kim, Jaebum

2018-05-09

Proteins perform biological functions through cascading interactions with each other by forming protein complexes. As a result, interactions among proteins, called protein-protein interactions (PPIs) are not completely free from selection constraint during evolution. Therefore, the identification and analysis of PPI changes during evolution can give us new insight into the evolution of functions. Although many algorithms, databases and websites have been developed to help the study of PPIs, most of them are limited to visualize the structure and features of PPIs in a chosen single species with limited functions in the visualization perspective. This leads to difficulties in the identification of different patterns of PPIs in different species and their functional consequences. To resolve these issues, we developed a web application, called INTER-Species Protein Interaction Analysis (INTERSPIA). Given a set of proteins of user's interest, INTERSPIA first discovers additional proteins that are functionally associated with the input proteins and searches for different patterns of PPIs in multiple species through a server-side pipeline, and second visualizes the dynamics of PPIs in multiple species using an easy-to-use web interface. INTERSPIA is freely available at http://bioinfo.konkuk.ac.kr/INTERSPIA/.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Quantitative Trait Loci for Resistance to Aspergillus Ear Rot: Analysis by Linkage Mapping, Characterization of Near-Isogenic Lines and Meta-Analysis

USDA-ARS?s Scientific Manuscript database

High levels of aflatoxin contamination of maize can be deadly for exposed human populations. Resistance to aflatoxin accumulation in maize has been reported in multiple studies and acts at multiple steps where there is fungal-plant interaction. In this study, we report the identification and mapping...

Technology Integration in a One-to-One Laptop Initiative: A Multiple Case Study Analysis

ERIC Educational Resources Information Center

Jones, Marsha B.

2013-01-01

The purpose of this multiple case study analysis was to examine teachers' experiences and perceptions in order to understand what actions and interactions supported or inhibited technology integration during a one-to-one laptop initiative. This research sought to gain teachers' perspectives on the challenges and successes they faced as classroom…

Multiple Interactive Pollutants in Water Quality Trading

NASA Astrophysics Data System (ADS)

Sarang, Amin; Lence, Barbara J.; Shamsai, Abolfazl

2008-10-01

Efficient environmental management calls for the consideration of multiple pollutants, for which two main types of transferable discharge permit (TDP) program have been described: separate permits that manage each pollutant individually in separate markets, with each permit based on the quantity of the pollutant or its environmental effects, and weighted-sum permits that aggregate several pollutants as a single commodity to be traded in a single market. In this paper, we perform a mathematical analysis of TDP programs for multiple pollutants that jointly affect the environment (i.e., interactive pollutants) and demonstrate the practicality of this approach for cost-efficient maintenance of river water quality. For interactive pollutants, the relative weighting factors are functions of the water quality impacts, marginal damage function, and marginal treatment costs at optimality. We derive the optimal set of weighting factors required by this approach for important scenarios for multiple interactive pollutants and propose using an analytical elasticity of substitution function to estimate damage functions for these scenarios. We evaluate the applicability of this approach using a hypothetical example that considers two interactive pollutants. We compare the weighted-sum permit approach for interactive pollutants with individual permit systems and TDP programs for multiple additive pollutants. We conclude by discussing practical considerations and implementation issues that result from the application of weighted-sum permit programs.

Interaction dynamics of multiple mobile robots with simple navigation strategies

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions.

PubMed

Price, Bertram; MacNicoll, Michael

2015-05-01

A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed. © 2015 Society for Risk Analysis.

Systematic study of rapidity dispersion parameter in high energy nucleus-nucleus interactions

NASA Astrophysics Data System (ADS)

Bhattacharyya, Swarnapratim; Haiduc, Maria; Neagu, Alina Tania; Firu, Elena

2014-03-01

A systematic study of rapidity dispersion parameter as a quantitative measure of clustering of particles has been carried out in the interactions of 16O, 28Si and 32S projectiles at 4.5 A GeV/c with heavy (AgBr) and light (CNO) groups of targets present in the nuclear emulsion. For all the interactions, the total ensemble of events has been divided into four overlapping multiplicity classes depending on the number of shower particles. For all the interactions and for each multiplicity class, the rapidity dispersion parameter values indicate the occurrence of clusterization during the multiparticle production at Dubna energy. The measured rapidity dispersion parameter values are found to decrease with the increase of average multiplicity for all the interactions. The dependence of rapidity dispersion parameter on the average multiplicity can be successfully described by a relation D(η) = a + b + c2. The experimental results have been compared with the results obtained from the analysis of Monte Carlo simulated (MC-RAND) events. MC-RAND events show weaker clusterization among the pions in comparison to the experimental data.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Virtual-Reality-Based Social Interaction Training for Children with High-Functioning Autism

ERIC Educational Resources Information Center

Ke, Fengfeng; Im, Tami

2013-01-01

Employing the multiple-baseline across-subjects design, the authors examined the implementation and potential effect of a virtual-reality-based social interaction program on the interaction and communication performance of children with high functioning autism. The data were collected via behavior observation and analysis, questionnaires, and…

Falcon: A Temporal Visual Analysis System

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

Steed, Chad A.

2016-09-05

Flexible visible exploration of long, high-resolution time series from multiple sensor streams is a challenge in several domains. Falcon is a visual analytics approach that helps researchers acquire a deep understanding of patterns in log and imagery data. Falcon allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations with multiple levels of detail. These capabilities are applicable to the analysis of any quantitative time series.

Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

ERIC Educational Resources Information Center

Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

2011-01-01

Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

How should periods without social interaction be scheduled? Children's preference for practical schedules of positive reinforcement.

PubMed

Luczynski, Kevin C; Hanley, Gregory P

2014-01-01

Several studies have shown that children prefer contingent reinforcement (CR) rather than yoked noncontingent reinforcement (NCR) when continuous reinforcement is programmed in the CR schedule. Preference has not, however, been evaluated for practical schedules that involve CR. In Study 1, we assessed 5 children's preference for obtaining social interaction via a multiple schedule (periods of fixed-ratio 1 reinforcement alternating with periods of extinction), a briefly signaled delayed reinforcement schedule, and an NCR schedule. The multiple schedule promoted the most efficient level of responding. In general, children chose to experience the multiple schedule and avoided the delay and NCR schedules, indicating that they preferred multiple schedules as the means to arrange practical schedules of social interaction. In Study 2, we evaluated potential controlling variables that influenced 1 child's preference for the multiple schedule and found that the strong positive contingency was the primary variable. © Society for the Experimental Analysis of Behavior.

The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

Using audio script fading and multiple-exemplar training to increase vocal interactions in children with autism.

PubMed

Garcia-Albea, Elena; Reeve, Sharon A; Brothers, Kevin J; Reeve, Kenneth F

2014-01-01

Script-fading procedures have been shown to be effective for teaching children with autism to initiate and participate in social interactions without vocal prompts from adults. In previous script and script-fading research, however, there has been no demonstration of a generalized repertoire of vocal interactions under the control of naturally occurring relevant stimuli. In this study, 4 boys with autism were taught to initiate a conversation in the presence of toys through the use of a script and script-fading procedure. Training with multiple categories and exemplars of toys was used to increase the likelihood of generalization of vocal interactions across novel toys. A multiple-probe design across participants was used to assess the effects of these procedures. The intervention successfully brought interactions by children with autism under the control of relevant stimuli in the environment. Future research pertaining to the specific implementation of these procedures (e.g., fading, script placement, participant characteristics) is discussed. © Society for the Experimental Analysis of Behavior.

Analysis of the interaction between experimental and applied behavior analysis.

PubMed

Virues-Ortega, Javier; Hurtado-Parrado, Camilo; Cox, Alison D; Pear, Joseph J

2014-01-01

To study the influences between basic and applied research in behavior analysis, we analyzed the coauthorship interactions of authors who published in JABA and JEAB from 1980 to 2010. We paid particular attention to authors who published in both JABA and JEAB (dual authors) as potential agents of cross-field interactions. We present a comprehensive analysis of dual authors' coauthorship interactions using social networks methodology and key word analysis. The number of dual authors more than doubled (26 to 67) and their productivity tripled (7% to 26% of JABA and JEAB articles) between 1980 and 2010. Dual authors stood out in terms of number of collaborators, number of publications, and ability to interact with multiple groups within the field. The steady increase in JEAB and JABA interactions through coauthors and the increasing range of topics covered by dual authors provide a basis for optimism regarding the progressive integration of basic and applied behavior analysis. © Society for the Experimental Analysis of Behavior.

Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice

PubMed Central

Giancardo, Luca; Sona, Diego; Huang, Huiping; Sannino, Sara; Managò, Francesca; Scheggia, Diego; Papaleo, Francesco; Murino, Vittorio

2013-01-01

Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain) and BTBR T+tf/J (a mouse model for autism spectrum disorders). Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2) interacting mice, and its versatility to deal with different experimental settings and scenarios. PMID:24066146

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.

PubMed

Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PubMed Central

Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811

Interactive effects of global change factors on soil respiration and its components: a meta-analysis.

PubMed

Zhou, Lingyan; Zhou, Xuhui; Shao, Junjiong; Nie, Yuanyuan; He, Yanghui; Jiang, Liling; Wu, Zhuoting; Hosseini Bai, Shahla

2016-09-01

As the second largest carbon (C) flux between the atmosphere and terrestrial ecosystems, soil respiration (Rs) plays vital roles in regulating atmospheric CO2 concentration ([CO2 ]) and climatic dynamics in the earth system. Although numerous manipulative studies and a few meta-analyses have been conducted to determine the responses of Rs and its two components [i.e., autotrophic (Ra) and heterotrophic (Rh) respiration] to single global change factors, the interactive effects of the multiple factors are still unclear. In this study, we performed a meta-analysis of 150 multiple-factor (≥2) studies to examine the main and interactive effects of global change factors on Rs and its two components. Our results showed that elevated [CO2 ] (E), nitrogen addition (N), irrigation (I), and warming (W) induced significant increases in Rs by 28.6%, 8.8%, 9.7%, and 7.1%, respectively. The combined effects of the multiple factors, EN, EW, DE, IE, IN, IW, IEW, and DEW, were also significantly positive on Rs to a greater extent than those of the single-factor ones. For all the individual studies, the additive interactions were predominant on Rs (90.6%) and its components (≈70.0%) relative to synergistic and antagonistic ones. However, the different combinations of global change factors (e.g., EN, NW, EW, IW) indicated that the three types of interactions were all important, with two combinations for synergistic effects, two for antagonistic, and five for additive when at least eight independent experiments were considered. In addition, the interactions of elevated [CO2 ] and warming had opposite effects on Ra and Rh, suggesting that different processes may influence their responses to the multifactor interactions. Our study highlights the crucial importance of the interactive effects among the multiple factors on Rs and its components, which could inform regional and global models to assess the climate-biosphere feedbacks and improve predictions of the future states of the ecological and climate systems. © 2016 John Wiley & Sons Ltd.

Brought-Along Identities and the Dynamics of Ideology: Accomplishing Bivalent Stances in a Multilingual Interaction

ERIC Educational Resources Information Center

Williams, Ashley M.

2008-01-01

This paper examines how the interconnected aspects of the stance triangle (Du Bois 2007) allow speakers to tap into multiple ideological layers as they take a stance and reveal intra-ethnic group tensions. Using a detailed interaction analysis of a Chinese American family's multilingual interaction, the paper explores how such ideological dynamics…

Numerical Analysis of Intra-Cavity and Power-Stream Flow Interaction in Multiple Gas-Turbine Disk-Cavities

NASA Technical Reports Server (NTRS)

Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.; Steinetz, B. M.

1995-01-01

A numerical analysis methodology and solutions of the interaction between the power stream and multiply-connected multi-cavity sealed secondary flow fields are presented. Flow solutions for a multi-cavity experimental rig were computed and compared with experimental data of Daniels and Johnson. The flow solutions illustrate the complex coupling between the main-path and the cavity flows as well as outline the flow thread that exists throughout the subplatform multiple cavities and seals. The analysis also shows that the de-coupled solutions on single cavities is inadequate. The present results show trends similar to the T-700 engine data that suggests the changes in the CDP seal altered the flow fields throughout the engine and affected the engine performance.

Early Design Choices: Capture, Model, Integrate, Analyze, Simulate

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2004-01-01

I. Designs are constructed incrementally to meet requirements and solve problems: a) Requirements types: objectives, scenarios, constraints, ilities. etc. b) Problem/issue types: risk/safety, cost/difficulty, interaction, conflict, etc. II. Capture requirements, problems and solutions: a) Collect design and analysis products and make them accessible for integration and analysis; b) Link changes in design requirements, problems and solutions; and c) Harvest design data for design models and choice structures. III. System designs are constructed by multiple groups designing interacting subsystems a) Diverse problems, choice criteria, analysis methods and point solutions. IV. Support integration and global analysis of repercussions: a) System implications of point solutions; b) Broad analysis of interactions beyond totals of mass, cost, etc.

Multiplicity distributions of charged hadrons in vp and charged current interactions

NASA Astrophysics Data System (ADS)

Jones, G. T.; Jones, R. W. L.; Kennedy, B. W.; Morrison, D. R. O.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hantke, D.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Borner, H. P.; Myatt, G.; Radojicic, D.; Burke, S.

1992-03-01

Using data on vp andbar vp charged current interactions from a bubble chamber experiment with BEBC at CERN, the multiplicity distributions of charged hadrons are investigated. The analysis is based on ˜20000 events with incident v and ˜10000 events with incidentbar v. The invariant mass W of the total hadronic system ranges from 3 GeV to ˜14 GeV. The experimental multiplicity distributions are fitted by the binomial function (for different intervals of W and in different intervals of the rapidity y), by the Levy function and the lognormal function. All three parametrizations give acceptable values for X 2. For fixed W, forward and backward multiplicities are found to be uncorrelated. The normalized moments of the charged multiplicity distributions are measured as a function of W. They show a violation of KNO scaling.

Investigating student communities with network analysis of interactions in a physics learning center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-06-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

Multi-Dimensional Analysis of Dynamic Human Information Interaction

ERIC Educational Resources Information Center

Park, Minsoo

2013-01-01

Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

Discovering communicative competencies in a nonspeaking child with autism.

PubMed

Stiegler, Lillian N

2007-10-01

This article is intended to demonstrate that adapted conversation analysis (CA) and speech act analysis (SAA) may be applied by speech-language pathologists (SLPs) to (a) identify communicative competencies in nonspeaking children with autism spectrum disorder (ASD), especially during particularly successful interactions, and (b) identify communicative patterns that are exhibited by interventionists and communication partners that may positively or negatively impact interactions with such children. A case example involving an 8-year-old boy with autism and the author, an SLP, is explicated. A videotaped segment from an intervention session was transcribed and subjected to adapted forms of CA and SAA. CA and SAA helped reveal several underlying competencies in the boy's communicative output, including an awareness of conversational structure and sequence, diversity of communicative acts, functional use of gaze and smile behavior, and the ability to spontaneously initiate interactions. Observations regarding the SLP's interactive style included the use of multiple instances of "asking" as well as multiple "derailments" of the boy's obvious communicative bids. CA and SAA may be adapted to gain a clearer picture of what takes place during especially positive communicative interactions with nonspeaking children with ASD.

Interaction between IL-6 and TNF-α genotypes associated with bacteremia in multiple myeloma patients submitted to autologous stem cell transplantation (ASCT).

PubMed

Trigo, Fernanda M B; Luizon, Marcelo R; Dutra, Hélio S; Maiolino, Angelo; Nucci, Márcio; Simões, Belinda P

2014-01-01

Stem cell transplantation affects patient׳s vulnerability to infections due to immunological changes related to chemotherapy. Multiple myeloma is characterized by susceptibility to infections, and IL-6 and TNF-α increased levels affect immune response (IR). Polymorphisms in promoter region of cytokine genes may alter expression levels and affect IR. We performed interaction analysis of IL-6 (-174G/C) and TNF-α (-308G/A) polymorphisms with infection susceptibility in 148 patients classified accordingly to infection status and found an interaction when compared groups with and without bacteremia (p=0.0380). The interaction may be more important than single effects for the IR associated with the infection susceptibility in ASCT.

Experiment in multiple-criteria energy policy analysis

NASA Astrophysics Data System (ADS)

Ho, J. K.

1980-07-01

An international panel of energy analysts participated in an experiment to use HOPE (holistic preference evaluation): an interactive parametric linear programming method for multiple criteria optimization. The criteria of cost, environmental effect, crude oil, and nuclear fuel were considered, according to BESOM: an energy model for the US in the year 2000.

Conformational dynamics of L-lysine, L-arginine, L-ornithine binding protein reveals ligand-dependent plasticity.

PubMed

Silva, Daniel-Adriano; Domínguez-Ramírez, Lenin; Rojo-Domínguez, Arturo; Sosa-Peinado, Alejandro

2011-07-01

The molecular basis of multiple ligand binding affinity for amino acids in periplasmic binding proteins (PBPs) and in the homologous domain for class C G-protein coupled receptors is an unsolved question. Here, using unrestrained molecular dynamic simulations, we studied the ligand binding mechanism present in the L-lysine, L-arginine, L-ornithine binding protein. We developed an analysis based on dihedral angles for the description of the conformational changes upon ligand binding. This analysis has an excellent correlation with each of the two main movements described by principal component analysis (PCA) and it's more convenient than RMSD measurements to describe the differences in the conformational ensembles observed. Furthermore, an analysis of hydrogen bonds showed specific interactions for each ligand studied as well as the ligand interaction with the aromatic residues Tyr-14 and Phe-52. Using uncharged histidine tautomers, these interactions are not observed. On the basis of these results, we propose a model in which hydrogen bond interactions place the ligand in the correct orientation to induce a cation-π interaction with Tyr-14 and Phe-52 thereby stabilizing the closed state. Our results also show that this protein adopts slightly different closed conformations to make available specific hydrogen bond interactions for each ligand thus, allowing a single mechanism to attain multiple ligand specificity. These results shed light on the experimental evidence for ligand-dependent conformational plasticity not explained by the previous crystallographic data. Copyright © 2011 Wiley-Liss, Inc.

Trends in Human-Computer Interaction to Support Future Intelligence Analysis Capabilities

DTIC Science & Technology

2011-06-01

that allows data to be moved between different computing systems and displays. Figure 4- G-Speak gesture interaction (Oblong, 2011) 5.2 Multitouch ... Multitouch refers to a touchscreen interaction technique in which multiple simultaneous touchpoints and movements can be detected and used to...much of the style of interaction (such as rotate, pinch, zoom and flick movements) found in multitouch devices but can typically recognize more than

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

Inferring consistent functional interaction patterns from natural stimulus FMRI data

PubMed Central

Sun, Jiehuan; Hu, Xintao; Huang, Xiu; Liu, Yang; Li, Kaiming; Li, Xiang; Han, Junwei; Guo, Lei

2014-01-01

There has been increasing interest in how the human brain responds to natural stimulus such as video watching in the neuroimaging field. Along this direction, this paper presents our effort in inferring consistent and reproducible functional interaction patterns under natural stimulus of video watching among known functional brain regions identified by task-based fMRI. Then, we applied and compared four statistical approaches, including Bayesian network modeling with searching algorithms: greedy equivalence search (GES), Peter and Clark (PC) analysis, independent multiple greedy equivalence search (IMaGES), and the commonly used Granger causality analysis (GCA), to infer consistent and reproducible functional interaction patterns among these brain regions. It is interesting that a number of reliable and consistent functional interaction patterns were identified by the GES, PC and IMaGES algorithms in different participating subjects when they watched multiple video shots of the same semantic category. These interaction patterns are meaningful given current neuroscience knowledge and are reasonably reproducible across different brains and video shots. In particular, these consistent functional interaction patterns are supported by structural connections derived from diffusion tensor imaging (DTI) data, suggesting the structural underpinnings of consistent functional interactions. Our work demonstrates that specific consistent patterns of functional interactions among relevant brain regions might reflect the brain's fundamental mechanisms of online processing and comprehension of video messages. PMID:22440644

Young Adult and Usual Adult Body Mass Index and Multiple Myeloma Risk: A Pooled Analysis in the International Multiple Myeloma Consortium (IMMC).

PubMed

Birmann, Brenda M; Andreotti, Gabriella; De Roos, Anneclaire J; Camp, Nicola J; Chiu, Brian C H; Spinelli, John J; Becker, Nikolaus; Benhaim-Luzon, Véronique; Bhatti, Parveen; Boffetta, Paolo; Brennan, Paul; Brown, Elizabeth E; Cocco, Pierluigi; Costas, Laura; Cozen, Wendy; de Sanjosé, Silvia; Foretová, Lenka; Giles, Graham G; Maynadié, Marc; Moysich, Kirsten; Nieters, Alexandra; Staines, Anthony; Tricot, Guido; Weisenburger, Dennis; Zhang, Yawei; Baris, Dalsu; Purdue, Mark P

2017-06-01

Background: Multiple myeloma risk increases with higher adult body mass index (BMI). Emerging evidence also supports an association of young adult BMI with multiple myeloma. We undertook a pooled analysis of eight case-control studies to further evaluate anthropometric multiple myeloma risk factors, including young adult BMI. Methods: We conducted multivariable logistic regression analysis of usual adult anthropometric measures of 2,318 multiple myeloma cases and 9,609 controls, and of young adult BMI (age 25 or 30 years) for 1,164 cases and 3,629 controls. Results: In the pooled sample, multiple myeloma risk was positively associated with usual adult BMI; risk increased 9% per 5-kg/m 2 increase in BMI [OR, 1.09; 95% confidence interval (CI), 1.04-1.14; P = 0.007]. We observed significant heterogeneity by study design ( P = 0.04), noting the BMI-multiple myeloma association only for population-based studies ( P trend = 0.0003). Young adult BMI was also positively associated with multiple myeloma (per 5-kg/m 2 ; OR, 1.2; 95% CI, 1.1-1.3; P = 0.0002). Furthermore, we observed strong evidence of interaction between younger and usual adult BMI ( P interaction <0.0001); we noted statistically significant associations with multiple myeloma for persons overweight (25-<30 kg/m 2 ) or obese (30+ kg/m 2 ) in both younger and usual adulthood (vs. individuals consistently <25 kg/m 2 ), but not for those overweight or obese at only one time period. Conclusions: BMI-associated increases in multiple myeloma risk were highest for individuals who were overweight or obese throughout adulthood. Impact: These findings provide the strongest evidence to date that earlier and later adult BMI may increase multiple myeloma risk and suggest that healthy BMI maintenance throughout life may confer an added benefit of multiple myeloma prevention. Cancer Epidemiol Biomarkers Prev; 26(6); 876-85. ©2017 AACR . ©2017 American Association for Cancer Research.

C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search.

PubMed

Sowpati, Divya Tej; Srivastava, Surabhi; Dhawan, Jyotsna; Mishra, Rakesh K

2017-09-13

Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

Evidence for multiple stressor interactions and effects on coral reefs.

PubMed

Ban, Stephen S; Graham, Nicholas A J; Connolly, Sean R

2014-03-01

Concern is growing about the potential effects of interacting multiple stressors, especially as the global climate changes. We provide a comprehensive review of multiple stressor interactions in coral reef ecosystems, which are widely considered to be one of the most sensitive ecosystems to global change. First, we synthesized coral reef studies that examined interactions of two or more stressors, highlighting stressor interactions (where one stressor directly influences another) and potentially synergistic effects on response variables (where two stressors interact to produce an effect that is greater than purely additive). For stressor-stressor interactions, we found 176 studies that examined at least 2 of the 13 stressors of interest. Applying network analysis to analyze relationships between stressors, we found that pathogens were exacerbated by more costressors than any other stressor, with ca. 78% of studies reporting an enhancing effect by another stressor. Sedimentation, storms, and water temperature directly affected the largest number of other stressors. Pathogens, nutrients, and crown-of-thorns starfish were the most-influenced stressors. We found 187 studies that examined the effects of two or more stressors on a third dependent variable. The interaction of irradiance and temperature on corals has been the subject of more research (62 studies, 33% of the total) than any other combination of stressors, with many studies reporting a synergistic effect on coral symbiont photosynthetic performance (n = 19). Second, we performed a quantitative meta-analysis of existing literature on this most-studied interaction (irradiance and temperature). We found that the mean effect size of combined treatments was statistically indistinguishable from a purely additive interaction, although it should be noted that the sample size was relatively small (n = 26). Overall, although in aggregate a large body of literature examines stressor effects on coral reefs and coral organisms, considerable gaps remain for numerous stressor interactions and effects, and insufficient quantitative evidence exists to suggest that the prevailing type of stressor interaction is synergistic.

Spectral Analysis: From Additive Perspective to Multiplicative Perspective

NASA Astrophysics Data System (ADS)

Wu, Z.

2017-12-01

The early usage of trigonometric functions can be traced back to at least 17th century BC. It was Bhaskara II of the 12th century CE who first proved the mathematical equivalence between the sum of two trigonometric functions of any given angles and the product of two trigonometric functions of related angles, which has been taught these days in middle school classroom. The additive perspective of trigonometric functions led to the development of the Fourier transform that is used to express any functions as the sum of a set of trigonometric functions and opened a new mathematical field called harmonic analysis. Unfortunately, Fourier's sum cannot directly express nonlinear interactions between trigonometric components of different periods, and thereby lacking the capability of quantifying nonlinear interactions in dynamical systems. In this talk, the speaker will introduce the Huang transform and Holo-spectrum which were pioneered by Norden Huang and emphasizes the multiplicative perspective of trigonometric functions in expressing any function. Holo-spectrum is a multi-dimensional spectral expression of a time series that explicitly identifies the interactions among different scales and quantifies nonlinear interactions hidden in a time series. Along with this introduction, the developing concepts of physical, rather than mathematical, analysis of data will be explained. Various enlightening applications of Holo-spectrum analysis in atmospheric and climate studies will also be presented.

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Interactive systems design and synthesis of future spacecraft concepts

NASA Technical Reports Server (NTRS)

Wright, R. L.; Deryder, D. D.; Ferebee, M. J., Jr.

1984-01-01

An interactive systems design and synthesis is performed on future spacecraft concepts using the Interactive Design and Evaluation of Advanced spacecraft (IDEAS) computer-aided design and analysis system. The capabilities and advantages of the systems-oriented interactive computer-aided design and analysis system are described. The synthesis of both large antenna and space station concepts, and space station evolutionary growth is demonstrated. The IDEAS program provides the user with both an interactive graphics and an interactive computing capability which consists of over 40 multidisciplinary synthesis and analysis modules. Thus, the user can create, analyze and conduct parametric studies and modify Earth-orbiting spacecraft designs (space stations, large antennas or platforms, and technologically advanced spacecraft) at an interactive terminal with relative ease. The IDEAS approach is useful during the conceptual design phase of advanced space missions when a multiplicity of parameters and concepts must be analyzed and evaluated in a cost-effective and timely manner.

Linking stressors and ecological responses

USGS Publications Warehouse

Gentile, J.H.; Solomon, K.R.; Butcher, J.B.; Harrass, M.; Landis, W.G.; Power, M.; Rattner, B.A.; Warren-Hicks, W.J.; Wenger, R.; Foran, Jeffery A.; Ferenc, Susan A.

1999-01-01

To characterize risk, it is necessary to quantify the linkages and interactions between chemical, physical and biological stressors and endpoints in the conceptual framework for ecological risk assessment (ERA). This can present challenges in a multiple stressor analysis, and it will not always be possible to develop a quantitative stressor-response profile. This review commences with a conceptual representation of the problem of developing a linkage analysis for multiple stressors and responses. The remainder of the review surveys a variety of mathematical and statistical methods (e.g., ranking methods, matrix models, multivariate dose-response for mixtures, indices, visualization, simulation modeling and decision-oriented methods) for accomplishing the linkage analysis for multiple stressors. Describing the relationships between multiple stressors and ecological effects are critical components of 'effects assessment' in the ecological risk assessment framework.

Measurement of Reconstructed Charged Particle Multiplicities of Neutrino Interactions in MicroBooNE

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

Rafique, Aleena

2017-09-25

Here, we compare the observed charged particle multiplicity distributions in the MicroBooNE liquid argon time projection chamber from neutrino interactions in a restricted final state phase space to predictions of this distribution from several GENIE models. The measurement uses a data sample consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2015-2016 with the Fermilab Booster Neutrino Beam (BNB), which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction andmore » uses a data-driven technique to determine the contribution to each multiplicity bin from neutrino interactions and cosmic-induced backgrounds. The restricted phase space employed makes the measurement most sensitive to the higher-energy charged particles expected from primary neutrino-argon collisions and less sensitive to lower energy protons expected to be produced in final state interactions of collision products with the target argon nucleus.« less

High-Multiplicity Lead-Lead Interactions at 158 GeV/c per nucleon

NASA Technical Reports Server (NTRS)

Deines-Jones, P.; Cherry, M. L.; Dabrowska, A.; Holynski, R.; Jones, W. V.; Kolganova, E. D.; Kudzia, D.; Nilsen, B. S.; Olszewski, A.; Pozharova, E. A.;

Interaction-Dominant Dynamics in Human Cognition: Beyond 1/f[superscript [alpha

ERIC Educational Resources Information Center

Ihlen, Espen A. F.; Vereijken, Beatrix

2010-01-01

It has been suggested that human behavior in general and cognitive performance in particular emerge from coordination between multiple temporal scales. In this article, we provide quantitative support for such a theory of interaction-dominant dynamics in human cognition by using wavelet-based multifractal analysis and accompanying multiplicative…

Main and interactive effects of multiple global-change factors on soil respiration and its components: a meta-analysis

NASA Astrophysics Data System (ADS)

Zhou, Xuhui

2014-05-01

Global change usually involves simultaneous changes in multiple environmental factors, which may considerably affect ecosystem structure and functioning and alter ecosystem services to human society. With increased awareness of their potential interactions, some multi-factorial studies have been conducted to investigate their main and interactive effects on carbon (C) cycling in terrestrial ecosystem. However, how multiple global-change factors affected soil respiration (Rs) and its components (i.e., autotrophic (Ra) and heterotrophic respiration (Rh)) remains controversial among individual studies. In this study, we conducted a meta-analysis to examine the main and possible 2- or 3-factor interactive effects with warming (W), elevated CO2 (E), nitrogen addition (N), increased precipitation (I) and drought (D) on Rs and its components from 150 published papers. Our results show that E, W, I and N significantly stimulated Rs by 29.23%, 7.19%, 22.95%, and 16.90% (p<0.05), respectively, while I depressed it by 16.90% (p<0.01). E consistently induced a significant positive effect on both Ra and Rh, while I affected them with an opposite trend. Among nine two-way interactive effects on Rs, synergistic interaction (i.e., the effect of combined treatment > the additive effects of single two main factors) occurred in E×N, E×W, I×N, and D×W, while neutral interaction (i.e., the effect of combined treatment ≡ the additive one) and antagonistic interaction (i.e., the effect of combined treatment < the additive one)was rare, only in I×W for neutral one and in N×W and I×E for the latter. In addition, E×W and E×N displayed synergistic interactions on Rh. The more dominance of synergistic interactions in two-way interactive effects on Rs and Rh may determine a central positive tendency of Rs in future, and affect the feedback of terrestrial C cycle to the climate system correspondingly.

Comparative Analysis of Enrollment and Financial Strength of Private Institutions. AIR 1989 Annual Forum Paper.

ERIC Educational Resources Information Center

Glover, Robert H.; Mills, Michael R.

A research design, decision support system, and results of a comparative analysis of enrollment and financial strength (of private institutions granting masters and doctoral degrees) are presented. Cluster analysis, discriminant analysis, multiple regression, and an interactive decision support system are used to compare the enrollment and…

Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis.

PubMed

Fröhlich, Kilian; Winder, Klemens; Linker, Ralf A; Engelhorn, Tobias; Dörfler, Arnd; Lee, De-Hyung; Hilz, Max J; Schwab, Stefan; Seifert, Frank

2018-06-01

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.

Mainstream Teachers' Experiences of Communicating with Students with Multiple and Severe Disabilities

ERIC Educational Resources Information Center

De Bortoli, Tania; Balandin, Susan; Foreman, Phil; Arthur-Kelly, Michael; Mathisen, Bernice

2012-01-01

The aim of this study was to explore regular teachers' perceptions and experiences of supports and obstacles to communicative interactions for students with multiple and severe disabilities (MSD). Five teachers of students with MSD participated in two in-depth interviews. Interview transcripts were analysed using content analysis. Transcripts were…

Mexican American Adolescents' Profiles of Risk and Mental Health: A Person-Centered Longitudinal Approach

ERIC Educational Resources Information Center

Zeiders, Katharine H.; Roosa, Mark W.; Knight, George P.; Gonzales, Nancy A.

2013-01-01

Although Mexican American adolescents experience multiple risk factors in their daily lives, most research examines the influences of risk factors on adjustment independently, ignoring the additive and interactive effects of multiple risk factors. Guided by a person-centered perspective and utilizing latent profile analysis, this study identified…

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

PubMed

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

Temporal profile of inflammatory response to fracture and hemorrhagic shock: Proposal of a novel long-term survival murine multiple trauma model.

PubMed

Kleber, Christian; Becker, Christopher A; Malysch, Tom; Reinhold, Jens M; Tsitsilonis, Serafeim; Duda, Georg N; Schmidt-Bleek, Katharina; Schaser, Klaus D

2015-07-01

Hemorrhagic shock (hS) interacts with the posttraumatic immune response and fracture healing in multiple trauma. Due to the lack of a long-term survival multiple trauma animal models, no standardized analysis of fracture healing referring the impact of multiple trauma on fracture healing was performed. We propose a new long-term survival (21 days) murine multiple trauma model combining hS (microsurgical cannulation of carotid artery, withdrawl of blood and continuously blood pressure measurement), femoral (osteotomy/external fixation) and tibial fracture (3-point bending technique/antegrade nail). The posttraumatic immune response was measured via IL-6, sIL-6R ELISA. The hS was investigated via macrohemodynamics, blood gas analysis, wet-dry lung ration and histologic analysis of the shock organs. We proposed a new murine long-term survival (21 days) multiple trauma model mimicking clinical relevant injury patterns and previously published human posttraumatic immune response. Based on blood gas analysis and histologic analysis of shock organs we characterized and standardized our murine multiple trauma model. Furthermore, we revealed hemorrhagic shock as a causative factor that triggers sIL-6R formation underscoring the fundamental pathophysiologic role of the transsignaling mechanism in multiple trauma. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Clanton, S. T.; Shah, A. S.; Truccolo, W. A.; Ding, M.; Bressler, S. L.; Trejo, L. J.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Multiple mobility edges in a 1D Aubry chain with Hubbard interaction in presence of electric field: Controlled electron transport

NASA Astrophysics Data System (ADS)

Saha, Srilekha; Maiti, Santanu K.; Karmakar, S. N.

2016-09-01

Electronic behavior of a 1D Aubry chain with Hubbard interaction is critically analyzed in presence of electric field. Multiple energy bands are generated as a result of Hubbard correlation and Aubry potential, and, within these bands localized states are developed under the application of electric field. Within a tight-binding framework we compute electronic transmission probability and average density of states using Green's function approach where the interaction parameter is treated under Hartree-Fock mean field scheme. From our analysis we find that selective transmission can be obtained by tuning injecting electron energy, and thus, the present model can be utilized as a controlled switching device.

The impact of attachment and depression symptoms on multiple risk behaviors in post-war adolescents in northern Uganda.

PubMed

Okello, J; Nakimuli-Mpungu, E; Klasen, F; Voss, C; Musisi, S; Broekaert, E; Derluyn, I

2015-07-15

We have previously shown that depression symptoms are associated with multiple risk behaviors and that parental attachments are protective against depression symptoms in post-war adolescents. Accumulating literature indicates that low levels of attachment may sensitize individuals to increased multiple risk behaviors when depression symptoms exist. This investigation examined the interactive effects of attachment and depression symptoms on multiple risk behavior. We conducted hierarchical logistic regression analyses to examine the impact of attachment and depression symptoms on multiple risk behavior in our post-war sample of 551 adolescents in Gulu district. Analyses revealed interactive effects for only maternal attachment-by-depression interaction. Interestingly, high levels of maternal attachment exacerbated the relationship between depression symptoms and multiple risk behaviors while low levels of maternal attachment attenuated this relationship. It is possible that this analysis could be biased by a common underlying factor that influences self-reporting and therefore is correlated with each of self-reported attachment security, depressive symptoms, and multiple risk behaviors. These findings suggest that maternal attachment serves as a protective factor at low levels while serving as an additional risk factor at high levels. Findings support and expand current knowledge about the roles that attachment and depression symptoms play in the development of multiple risk behaviors and suggest a more complex etiology for post-war adolescents. Copyright © 2015 Elsevier B.V. All rights reserved.

Conceptual spacecraft systems design and synthesis

NASA Technical Reports Server (NTRS)

Wright, R. L.; Deryder, D. D.; Ferebee, M. J., Jr.

1984-01-01

An interactive systems design and synthesis is performed on future spacecraft concepts using the Interactive Design and Evaluation of Advanced Systems (IDEAS) computer-aided design and analysis system. The capabilities and advantages of the systems-oriented interactive computer-aided design and analysis system are described. The synthesis of both large antenna and space station concepts, and space station evolutionary growth designs is demonstrated. The IDEAS program provides the user with both an interactive graphics and an interactive computing capability which consists of over 40 multidisciplinary synthesis and analysis modules. Thus, the user can create, analyze, and conduct parametric studies and modify earth-orbiting spacecraft designs (space stations, large antennas or platforms, and technologically advanced spacecraft) at an interactive terminal with relative ease. The IDEAS approach is useful during the conceptual design phase of advanced space missions when a multiplicity of parameters and concepts must be analyzed and evaluated in a cost-effective and timely manner.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

PubMed

Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh

2018-02-01

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Predominant Non-additive Effects of Multiple Stressors on Autotroph C:N:P Ratios Propagate in Freshwater and Marine Food Webs

PubMed Central

Villar-Argaiz, Manuel; Medina-Sánchez, Juan M.; Biddanda, Bopaiah A.; Carrillo, Presentación

2018-01-01

A continuing challenge for scientists is to understand how multiple interactive stressor factors affect biological interactions, and subsequently, ecosystems–in ways not easily predicted by single factor studies. In this review, we have compiled and analyzed available research on how multiple stressor pairs composed of temperature (T), light (L), ultraviolet radiation (UVR), nutrients (Nut), carbon dioxide (CO2), dissolved organic carbon (DOC), and salinity (S) impact the stoichiometry of autotrophs which in turn shapes the nature of their ecological interactions within lower trophic levels in streams, lakes and oceans. Our analysis from 66 studies with 320 observations of 11 stressor pairs, demonstrated that non-additive responses predominate across aquatic ecosystems and their net interactive effect depends on the stressor pair at play. Across systems, there was a prevalence of antagonism in freshwater (60–67% vs. 47% in marine systems) compared to marine systems where synergism was more common (49% vs. 33–40% in freshwaters). While the lack of data impeded comparisons among all of the paired stressors, we found pronounced system differences for the L × Nut interactions. For this interaction, our data for C:P and N:P is consistent with the initial hypothesis that the interaction was primarily synergistic in the oceans, but not for C:N. Our study found a wide range of variability in the net effects of the interactions in freshwater systems, with some observations supporting antagonism, and others synergism. Our results suggest that the nature of the stressor pairs interactions on C:N:P ratios regulates the “continuum” commensalistic-competitive-predatory relationship between algae and bacteria and the food chain efficiency at the algae-herbivore interface. Overall, the scarce number of studies with even more fewer replications in each study that are available for freshwater systems have prevented a more detailed, insightful analysis. Our findings highlighting the preponderance of antagonistic and synergistic effects of stressor interactions in aquatic ecosystems—effects that play key roles in the functioning of feedback loops in the biosphere—also stress the need for further studies evaluating the interactive effects of multiple stressors in a rapidly changing world facing a confluence of tipping points. PMID:29441051

Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: a GWAS data analysis.

PubMed

Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-01-01

Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.

Different aspects of multiplicity distribution of shower particles in central collisions with AgBr target

NASA Astrophysics Data System (ADS)

Bhattacharyya, Swarnapratim; Haiduc, Maria; Neagu, Alina Tania; Firu, Elena

Different aspects like multiplicity moments, Dq moments and multiplicity fluctuations in terms of scaled variance of the shower particles has been carried out for central events of 16O-AgBr, 22Ne-AgBr and 32S-AgBr interactions at (4.1-4.5) AGeV/c. Comparison of our results with different experimental analysis of central collisions of emulsion data has been performed whenever available.

SysBioCube: A Data Warehouse and Integrative Data Analysis Platform Facilitating Systems Biology Studies of Disorders of Military Relevance

DTIC Science & Technology

2013-12-18

include interactive gene and methylation profiles, interactive heatmaps, cytoscape network views, integrative genomics viewer ( IGV ), and protein-protein...single chart. The website also provides an option to include multiple genes. Integrative Genomics Viewer ( IGV )1, is a high-performance desktop tool for

Evolutionary Game Theory Analysis of Tumor Progression

NASA Astrophysics Data System (ADS)

Wu, Amy; Liao, David; Sturm, James; Austin, Robert

2014-03-01

Evolutionary game theory applied to two interacting cell populations can yield quantitative prediction of the future densities of the two cell populations based on the initial interaction terms. We will discuss how in a complex ecology that evolutionary game theory successfully predicts the future densities of strains of stromal and cancer cells (multiple myeloma), and discuss the possible clinical use of such analysis for predicting cancer progression. Supported by the National Science Foundation and the National Cancer Institute.

Solar energy conversion through the interaction of plasmons with tunnel junctions. Part A: Solar cell analysis. Part B: Photoconductor analysis

NASA Technical Reports Server (NTRS)

Welsh, P. E.; Schwartz, R. J.

1988-01-01

A solar cell utilizing guided optical waves and tunnel junctions was analyzed to determine its feasibility. From this analysis, it appears that the limits imposed upon conventional multiple cell systems also limit this solar cell. Due to this limitation, it appears that the relative simplicity of the conventional multiple cell systems over the solar cell make the conventional multiple cell systems the more promising candidate for improvement. It was discovered that some superlattice structures studied could be incorporated into an infrared photodetector. This photoconductor appears to be promising as a high speed, sensitive (high D sup star sub BLIP) detector in the wavelength range from 15 to over 100 micrometers.

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

Communicative conduct in commercial medicine: initial consultations between plastic surgeons and prospective clients.

PubMed

Mirivel, Julien C

2010-06-01

In this study, I investigated naturally occurring medical interaction in commercial medicine. Drawing on 30+ hours of videotaped data and 9 months of fieldwork in a cosmetic surgery clinic, this analysis focuses on how plastic surgeons interact with patients who seek to alter their bodily appearance. The ethnographically informed discourse analysis reveals how plastic surgeons manage multiple and competing interactive demands. Specifically, I describe plastic surgeons' key strategies for meeting both health-related and institutional goals. In the conclusion, I reflect on the communication challenges that medical professionals and patients face when consumerism and medicine meet.

Mediation Analysis with Multiple Mediators

PubMed Central

VanderWeele, T.J.; Vansteelandt, S.

2014-01-01

Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects through other pathways. The approaches proposed here accommodate exposure-mediator interactions and, to a certain extent, mediator-mediator interactions as well. The methods handle binary or continuous mediators and binary, continuous or count outcomes. When the mediators affect one another, the strategy of trying to assess direct and indirect effects one mediator at a time will in general fail; the approach given in this paper can still be used. A characterization is moreover given as to when the sum of the mediated effects for multiple mediators considered separately will be equal to the mediated effect of all of the mediators considered jointly. The approach proposed in this paper is robust to unmeasured common causes of two or more mediators. PMID:25580377

Mediation Analysis with Multiple Mediators.

PubMed

VanderWeele, T J; Vansteelandt, S

2014-01-01

Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects through other pathways. The approaches proposed here accommodate exposure-mediator interactions and, to a certain extent, mediator-mediator interactions as well. The methods handle binary or continuous mediators and binary, continuous or count outcomes. When the mediators affect one another, the strategy of trying to assess direct and indirect effects one mediator at a time will in general fail; the approach given in this paper can still be used. A characterization is moreover given as to when the sum of the mediated effects for multiple mediators considered separately will be equal to the mediated effect of all of the mediators considered jointly. The approach proposed in this paper is robust to unmeasured common causes of two or more mediators.

Interactive graphical system for small-angle scattering analysis of polydisperse systems

NASA Astrophysics Data System (ADS)

Konarev, P. V.; Volkov, V. V.; Svergun, D. I.

2016-09-01

A program suite for one-dimensional small-angle scattering analysis of polydisperse systems and multiple data sets is presented. The main program, POLYSAS, has a menu-driven graphical user interface calling computational modules from ATSAS package to perform data treatment and analysis. The graphical menu interface allows one to process multiple (time, concentration or temperature-dependent) data sets and interactively change the parameters for the data modelling using sliders. The graphical representation of the data is done via the Winteracter-based program SASPLOT. The package is designed for the analysis of polydisperse systems and mixtures, and permits one to obtain size distributions and evaluate the volume fractions of the components using linear and non-linear fitting algorithms as well as model-independent singular value decomposition. The use of the POLYSAS package is illustrated by the recent examples of its application to study concentration-dependent oligomeric states of proteins and time kinetics of polymer micelles for anticancer drug delivery.

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Interactive effects of age-of-acquisition and repetition priming in the lexical decision task. A multiple-loci account.

PubMed

Spataro, Pietro; Longobardi, Emiddia; Saraulli, Daniele; Rossi-Arnaud, Clelia

2013-01-01

The analysis of the interaction between repetition priming and age of acquisition may be used to shed further light on the question of which stages of elaboration are affected by this psycholinguistic variable. In the present study we applied this method in the context of two versions of a lexical decision task that differed in the type of non-words employed at test. When the non-words were illegal and unpronounceable, repetition priming was primarily based on the analysis of orthographic information, while phonological processes were additionally recruited only when using legal pronounceable non-words. The results showed a significant interaction between repetition priming and age of acquisition in both conditions, with priming being greater for late- than for early-acquired words. These findings support a multiple-loci account, indicating that age of acquisition influences implicit memory by facilitating the retrieval of both the orthographic and the phonological representations of studied words.

Linkages and Interactions Analysis of Major Effect Drought Grain Yield QTLs in Rice.

PubMed

Vikram, Prashant; Swamy, B P Mallikarjuna; Dixit, Shalabh; Trinidad, Jennylyn; Sta Cruz, Ma Teresa; Maturan, Paul C; Amante, Modesto; Kumar, Arvind

2016-01-01

Quantitative trait loci conferring high grain yield under drought in rice are important genomic resources for climate resilient breeding. Major and consistent drought grain yield QTLs usually co-locate with flowering and/or plant height QTLs, which could be due to either linkage or pleiotropy. Five mapping populations used for the identification of major and consistent drought grain yield QTLs underwent multiple-trait, multiple-interval mapping test (MT-MIM) to estimate the significance of pleiotropy effects. Results indicated towards possible linkages between the drought grain yield QTLs with co-locating flowering and/or plant height QTLs. Linkages of days to flowering and plant height were eliminated through a marker-assisted breeding approach. Drought grain yield QTLs also showed interaction effects with flowering QTLs. Drought responsiveness of the flowering locus on chromosome 3 (qDTY3.2) has been revealed through allelic analysis. Considering linkage and interaction effects associated with drought QTLs, a comprehensive marker-assisted breeding strategy was followed to develop rice genotypes with improved grain yield under drought stress.

I. Excluded volume effects in Ising cluster distributions and nuclear multifragmentation. II. Multiple-chance effects in alpha-particle evaporation

NASA Astrophysics Data System (ADS)

Breus, Dimitry Eugene

In Part I, geometric clusters of the Ising model are studied as possible model clusters for nuclear multifragmentation. These clusters may not be considered as non-interacting (ideal gas) due to excluded volume effect which predominantly is the artifact of the cluster's finite size. Interaction significantly complicates the use of clusters in the analysis of thermodynamic systems. Stillinger's theory is used as a basis for the analysis, which within the RFL (Reiss, Frisch, Lebowitz) fluid-of-spheres approximation produces a prediction for cluster concentrations well obeyed by geometric clusters of the Ising model. If thermodynamic condition of phase coexistence is met, these concentrations can be incorporated into a differential equation procedure of moderate complexity to elucidate the liquid-vapor phase diagram of the system with cluster interaction included. The drawback of increased complexity is outweighted by the reward of greater accuracy of the phase diagram, as it is demonstrated by the Ising model. A novel nuclear-cluster analysis procedure is developed by modifying Fisher's model to contain cluster interaction and employing the differential equation procedure to obtain thermodynamic variables. With this procedure applied to geometric clusters, the guidelines are developed to look for excluded volume effect in nuclear multifragmentation. In Part II, an explanation is offered for the recently observed oscillations in the energy spectra of alpha-particles emitted from hot compound nuclei. Contrary to what was previously expected, the oscillations are assumed to be caused by the multiple-chance nature of alpha-evaporation. In a semi-empirical fashion this assumption is successfully confirmed by a technique of two-spectra decomposition which treats experimental alpha-spectra as having contributions from at least two independent emitters. Building upon the success of the multiple-chance explanation of the oscillations, Moretto's single-chance evaporation theory is augmented to include multiple-chance emission and tested on experimental data to yield positive results.

Analysis of multiple jets in a cross-flow

NASA Astrophysics Data System (ADS)

Isaac, K. M.; Schetz, J. A.

1982-12-01

The analysis of Campbell and Schetz (1973) is extended to the study of multiple jets in a cross flow, where the interaction of two jets is taken into account by a modification of the drag coefficient that is sensed by each jet. Results show that the rear jet trajectory is significantly modified by the presence of the front one even when the jets are spaced far apart. The analysis is applicable to such phenomena as the exhaust of chimney stack smoke into a wind and the lift jets of a V/STOL aircraft during takeoff or landing in strong winds.

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

Pachuilo, Andrew R; Ragan, Eric; Goodall, John R

Visualization tools can take advantage of multiple coordinated views to support analysis of large, multidimensional data sets. Effective design of such views and layouts can be challenging, but understanding users analysis strategies can inform design improvements. We outline an approach for intelligent design configuration of visualization tools with multiple coordinated views, and we discuss a proposed software framework to support the approach. The proposed software framework could capture and learn from user interaction data to automate new compositions of views and widgets. Such a framework could reduce the time needed for meta analysis of the visualization use and lead tomore » more effective visualization design.« less

Islamic Education and Individual Requirements in Interaction and Media Use

ERIC Educational Resources Information Center

Khashab, Hamdollah Karimi; Vaezi, Seyed Hossein; Golestani, Seyed Hashem; Taghipour, Faezeh

2016-01-01

This article aims to analyze the views and teachings of Islam and the Islamic religion in order to determine the requirements of interaction and media use. This article is of qualitative kind and content analysis approach and has done based on the study of Islamic texts and sources associated with the media. Because of the multiplicity and…

Girls Discuss Choice of an All-Girl Middle School: Narrative Analysis of an Early Adolescent Identity Project

ERIC Educational Resources Information Center

Baron, Emilia; Bell, Nancy J.; Corson, Kimberly; Kostina-Ritchey, Erin; Frederick, Helyne

2012-01-01

The narrative creation of identity by young adolescents has so far been addressed mainly from an identity-in-interaction perspective, focusing attention on the multiplicity and variability of identity negotiation as adolescents interact with others, typically with peers. In contrast, a sociocultural/dialogical perspective draws attention to the…

Authentic Early Experience in Medical Education: A Socio-Cultural Analysis Identifying Important Variables in Learning Interactions within Workplaces

ERIC Educational Resources Information Center

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-01-01

This paper addresses the question "what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?" AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually…

Helping Students Assess the Relative Importance of Different Intermolecular Interactions

ERIC Educational Resources Information Center

Jasien, Paul G.

2008-01-01

A semi-quantitative model has been developed to estimate the relative effects of dispersion, dipole-dipole interactions, and H-bonding on the normal boiling points ("T[subscript b]") for a subset of simple organic systems. The model is based upon a statistical analysis using multiple linear regression on a series of straight-chain organic…

An Introduction to the Special Issue on Advances in Process and Dynamic System Analysis of Social Interaction and the Development of Antisocial Behavior

ERIC Educational Resources Information Center

Dishion, Thomas J.; Snyder, James

2004-01-01

A thorough understanding of how social relationships contribute to child and adolescent trajectories for antisocial behavior may be facilitated by: (a) ascertaining multiple relationship processes (e.g., warmth and reciprocity, coercion and deviancy training); (b) focusing on multiple relationships (e.g., with parents, peers, siblings, and…

Genomic and Epigenomic Insights into Nutrition and Brain Disorders

PubMed Central

Dauncey, Margaret Joy

2013-01-01

Considerable evidence links many neuropsychiatric, neurodevelopmental and neurodegenerative disorders with multiple complex interactions between genetics and environmental factors such as nutrition. Mental health problems, autism, eating disorders, Alzheimer’s disease, schizophrenia, Parkinson’s disease and brain tumours are related to individual variability in numerous protein-coding and non-coding regions of the genome. However, genotype does not necessarily determine neurological phenotype because the epigenome modulates gene expression in response to endogenous and exogenous regulators, throughout the life-cycle. Studies using both genome-wide analysis of multiple genes and comprehensive analysis of specific genes are providing new insights into genetic and epigenetic mechanisms underlying nutrition and neuroscience. This review provides a critical evaluation of the following related areas: (1) recent advances in genomic and epigenomic technologies, and their relevance to brain disorders; (2) the emerging role of non-coding RNAs as key regulators of transcription, epigenetic processes and gene silencing; (3) novel approaches to nutrition, epigenetics and neuroscience; (4) gene-environment interactions, especially in the serotonergic system, as a paradigm of the multiple signalling pathways affected in neuropsychiatric and neurological disorders. Current and future advances in these four areas should contribute significantly to the prevention, amelioration and treatment of multiple devastating brain disorders. PMID:23503168

Study of the peculiarities of multiparticle production via event-by-event analysis in asymmetric nucleus-nucleus interactions

NASA Astrophysics Data System (ADS)

Fedosimova, Anastasiya; Gaitinov, Adigam; Grushevskaya, Ekaterina; Lebedev, Igor

2017-06-01

In this work the study on the peculiarities of multiparticle production in interactions of asymmetric nuclei to search for unusual features of such interactions, is performed. A research of long-range and short-range multiparticle correlations in the pseudorapidity distribution of secondary particles on the basis of analysis of individual interactions of nuclei of 197 Au at energy 10.7 AGeV with photoemulsion nuclei, is carried out. Events with long-range multiparticle correlations (LC), short-range multiparticle correlations (SC) and mixed type (MT) in pseudorapidity distribution of secondary particles, are selected by the Hurst method in accordance with Hurst curve behavior. These types have significantly different characteristics. At first, they have different fragmentation parameters. Events of LC type are processes of full destruction of the projectile nucleus, in which multicharge fragments are absent. In events of mixed type several multicharge fragments of projectile nucleus are discovered. Secondly, these two types have significantly different multiplicity distribution. The mean multiplicity of LC type events is significantly more than in mixed type events. On the basis of research of the dependence of multiplicity versus target-nuclei fragments number for events of various types it is revealed, that the most considerable multiparticle correlations are observed in interactions of the mixed type, which correspond to the central collisions of gold nuclei and nuclei of CNO-group, i.e. nuclei with strongly asymmetric volume, nuclear mass, charge, etc. Such events are characterised by full destruction of the target-nucleus and the disintegration of the projectile-nucleus on several multi-charged fragments.

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

NASA Astrophysics Data System (ADS)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy.

PubMed

de Haas, Sanne; Delmar, Paul; Bansal, Aruna T; Moisse, Matthieu; Miles, David W; Leighl, Natasha; Escudier, Bernard; Van Cutsem, Eric; Carmeliet, Peter; Scherer, Stefan J; Pallaud, Celine; Lambrechts, Diether

2014-10-01

Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

New Software for Market Segmentation Analysis: A Chi-Square Interaction Detector. AIR 1983 Annual Forum Paper.

ERIC Educational Resources Information Center

Lay, Robert S.

The advantages and disadvantages of new software for market segmentation analysis are discussed, and the application of this new, chi-square based procedure (CHAID), is illustrated. A comparison is presented of an earlier, binary segmentation technique (THAID) and a multiple discriminant analysis. It is suggested that CHAID is superior to earlier…

Twentieth Annual Conference on Manual Control, Volume 2

NASA Technical Reports Server (NTRS)

Hart, S. G. (Compiler); Hartzell, E. J. (Compiler)

1984-01-01

Volume II contains thirty two complete manuscripts and five abstracts. The topics covered include the application of event-related brain potential analysis to operational problems, the subjective evaluation of workload, mental models, training, crew interaction analysis, multiple task performance, and the measurement of workload and performance in simulation.

NEEDED RESEARCH ON DIFFUSION WITHIN EDUCATIONAL ORGANIZATIONS.

ERIC Educational Resources Information Center

JAIN, NEMI C.; ROGERS, EVERETT M.

IN SPITE OF THE VOLUME OF RESEARCH ATTENTION DEVOTED TO THE DIFFUSION OF INNOVATIONS, RELATIVELY LITTLE EMPHASIS HAS BEEN PLACED UPON DIFFUSION WITHIN ORGANIZATIONAL STRUCTURES. METHODOLOGICALLY, RELATIONAL ANALYSIS IN WHICH THE UNIT OF ANALYSIS IS A TWO-PERSON INTERACTING PAIR, A MULTIPLE PERSON COMMUNICATION CHAIN, OR CLIQUES OR SUBSYSTEMS IS…

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

Ratto, T V; Rudd, R E; Langry, K C

We present evidence of multivalent interactions between a single protein molecule and multiple carbohydrates at a pH where the protein can bind four ligands. The evidence is based not only on measurements of the force required to rupture the bonds formed between ConcanavalinA (ConA) and {alpha}-D-mannose, but also on an analysis of the polymer-extension force curves to infer the polymer architecture that binds the protein to the cantilever and the ligands to the substrate. We find that although the rupture forces for multiple carbohydrate connections to a single protein are larger than the rupture force for a single connection, theymore » do not scale additively with increasing number. Specifically, the most common rupture forces are approximately 46, 66, and 85 pN, which we argue corresponds to 1, 2, and 3 ligands being pulled simultaneously from a single protein as corroborated by an analysis of the linkage architecture. As in our previous work polymer tethers allow us to discriminate between specific and non-specific binding. We analyze the binding configuration (i.e. serial versus parallel connections) through fitting the polymer stretching data with modified Worm-Like Chain (WLC) models that predict how the effective stiffness of the tethers is affected by multiple connections. This analysis establishes that the forces we measure are due to single proteins interacting with multiple ligands, the first force spectroscopy study that establishes single-molecule multivalent binding unambiguously.« less

Dynamic interactions between cells and their extracellular matrix mediate embryonic development.

PubMed

Goody, Michelle F; Henry, Clarissa A

2010-06-01

Cells and their surrounding extracellular matrix microenvironment interact throughout all stages of life. Understanding the continuously changing scope of cell-matrix interactions in vivo is crucial to garner insights into both congenital birth defects and disease progression. A current challenge in the field of developmental biology is to adapt in vitro tools and rapidly evolving imaging technology to study cell-matrix interactions in a complex 4-D environment. In this review, we highlight the dynamic modulation of cell-matrix interactions during development. We propose that individual cell-matrix adhesion proteins are best considered as complex proteins that can play multiple, often seemingly contradictory roles, depending upon the context of the microenvironment. In addition, cell-matrix proteins can also exert different short versus long term effects. It is thus important to consider cell behavior in light of the microenvironment because of the constant and dynamic reciprocal interactions occurring between them. Finally, we suggest that analysis of cell-matrix interactions at multiple levels (molecules, cells, tissues) in vivo is critical for an integrated understanding because different information can be acquired from all size scales. Copyright 2010 Wiley-Liss, Inc.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

Using Discursis to enhance the qualitative analysis of hospital pharmacist-patient interactions.

PubMed

Chevalier, Bernadette A M; Watson, Bernadette M; Barras, Michael A; Cottrell, William N; Angus, Daniel J

2018-01-01

Pharmacist-patient communication during medication counselling has been successfully investigated using Communication Accommodation Theory (CAT). Communication researchers in other healthcare professions have utilised Discursis software as an adjunct to their manual qualitative analysis processes. Discursis provides a visual, chronological representation of communication exchanges and identifies patterns of interactant engagement. The aim of this study was to describe how Discursis software was used to enhance previously conducted qualitative analysis of pharmacist-patient interactions (by visualising pharmacist-patient speech patterns, episodes of engagement, and identifying CAT strategies employed by pharmacists within these episodes). Visual plots from 48 transcribed audio recordings of pharmacist-patient exchanges were generated by Discursis. Representative plots were selected to show moderate-high and low- level speaker engagement. Details of engagement were investigated for pharmacist application of CAT strategies (approximation, interpretability, discourse management, emotional expression, and interpersonal control). Discursis plots allowed for identification of distinct patterns occurring within pharmacist-patient exchanges. Moderate-high pharmacist-patient engagement was characterised by multiple off-diagonal squares while alternating single coloured squares depicted low engagement. Engagement episodes were associated with multiple CAT strategies such as discourse management (open-ended questions). Patterns reflecting pharmacist or patient speaker dominance were dependant on clinical setting. Discursis analysis of pharmacist-patient interactions, a novel application of the technology in health communication, was found to be an effective visualisation tool to pin-point episodes for CAT analysis. Discursis has numerous practical and theoretical applications for future health communication research and training. Researchers can use the software to support qualitative analysis where large data sets can be quickly reviewed to identify key areas for concentrated analysis. Because Discursis plots are easily generated from audio recorded transcripts, they are conducive as teaching tools for both students and practitioners to assess and develop their communication skills.

Interaction of Hb Grey Lynn (Vientiane) [α91(FG3)Leu>Phe (α1)] with Hb E [β26(B8) Glu>Lys] and α(+)-thalassemia: Molecular and Hematological Analysis.

PubMed

Singha, Kritsada; Fucharoen, Goonnapa; Fucharoen, Supan

2015-01-01

Hemoglobin (Hb) Grey Lynn is a Hb variant caused by a mutation at codon 91 of α1-globin gene whereas Hb E is a common β-globin chain variant among Southeast Asian population. We report two hitherto undescribed conditions of Hb Grey Lynn found in Thai individuals. The study was done on two unrelated Thai subjects. Hematological parameters were recorded and Hb analysis was carried out using automated Hb analyzers. Mutations were identified by DNA analysis. Hematological features of the patients were compared with those of various forms of Hb Grey Lynn documented previously. Hb and DNA analyses identified a heterozygous Hb Grey Lynn in one patient and a double heterozygous Hb Grey Lynn and Hb E with α(+)-thalassemia in another. Interaction of α(Grey Lynn) with β(E) chains leads to the formation of a new Hb variant, namely the Hb Grey Lynn E (α(GL)2β(E)2), detectable by liquid chromatography (10.3%) but masked by Hb E on capillary electrophoresis. Interaction of these multiple globin gene defects could lead to complex hemoglobinopathies requiring combined analysis with multiple Hb analyzers followed by DNA testing to provide accurate diagnosis of the cases.

ISS Mini AERCam Radio Frequency (RF) Coverage Analysis Using iCAT Development Tool

NASA Technical Reports Server (NTRS)

Bolen, Steve; Vazquez, Luis; Sham, Catherine; Fredrickson, Steven; Fink, Patrick; Cox, Jan; Phan, Chau; Panneton, Robert

2003-01-01

The long-term goals of the National Aeronautics and Space Administration's (NASA's) Human Exploration and Development of Space (HEDS) enterprise may require the development of autonomous free-flier (FF) robotic devices to operate within the vicinity of low-Earth orbiting spacecraft to supplement human extravehicular activities (EVAs) in space. Future missions could require external visual inspection of the spacecraft that would be difficult, or dangerous, for humans to perform. Under some circumstance, it may be necessary to employ an un-tethered communications link between the FF and the users. The interactive coverage analysis tool (ICAT) is a software tool that has been developed to perform critical analysis of the communications link performance for a FF operating in the vicinity of the International Space Station (ISS) external environment. The tool allows users to interactively change multiple parameters of the communications link parameters to efficiently perform systems engineering trades on network performance. These trades can be directly translated into design and requirements specifications. This tool significantly reduces the development time in determining a communications network topology by allowing multiple parameters to be changed, and the results of link coverage to be statistically characterized and plotted interactively.

Development of Techniques for Multiple Data Stream Analysis and Short- Term Forecasting. Volume I. Multiple Data Stream Analysis

DTIC Science & Technology

1975-11-15

ir in» l.iit.ii-nlrl-i . i ifr .-Viii ^„,„^>,,,,,.,,.,„.,,,.,™„„,^^^^ I ’Ulis Cable shows great similarity between the NYT and TOL as follows; o...from which the data have been derived. The authors challenge the contention by other data collectors that variation in interaction data derived from...LIC Luxemburg LUX Malagasy MAG Malawi MAW Malaysia MAL Maldive MAD Mali MLI Malta MLT Mauritius MAR Mauritania MAU Mexico MEX Monaco MOC

Diet and Colorectal Cancer: Analysis of a Candidate Pathway Using SNPS, Haplotypes, and Multi-Gene Assessment

PubMed Central

Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Caan, Bette J.; Potter, John D.; Wolff, Roger K.

2012-01-01

There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined. PMID:21999454

Tumble Graphs: Avoiding Misleading End Point Extrapolation When Graphing Interactions From a Moderated Multiple Regression Analysis

ERIC Educational Resources Information Center

Bodner, Todd E.

2016-01-01

This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…

Identification of More Feasible MicroRNA-mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction.

PubMed

Taguchi, Y-H

2016-05-10

MicroRNA(miRNA)-mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should be verified by integrated analyses of mRNA and miRNA expression. The drawback of this strategy is the vast number of identified interactions, which prevents an experimental or detailed investigation of each pair. In this paper, we overcome this difficulty by the recently proposed principal component analysis (PCA)-based unsupervised feature extraction (FE), which reduces the number of identified miRNA-mRNA interactions that properly discriminate between patients and healthy controls without losing biological feasibility. The approach is applied to six cancers: hepatocellular carcinoma, non-small cell lung cancer, esophageal squamous cell carcinoma, prostate cancer, colorectal/colon cancer and breast cancer. In PCA-based unsupervised FE, the significance does not depend on the number of samples (as in the standard case) but on the number of features, which approximates the number of miRNAs/mRNAs. To our knowledge, we have newly identified miRNA-mRNA interactions in multiple cancers based on a single common (universal) criterion. Moreover, the number of identified interactions was sufficiently small to be sequentially curated by literature searches.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations.

PubMed

Sheth, Harsh; Northwood, Emma; Ulrich, Cornelia M; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H; Forman, David; Wolf, C Roland; Smith, Gillian; Jackson, Michael S; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L; Marchand, Loic Le; Lindor, Noralane M; Thibodeau, Stephen N; Potter, John D; Burn, John; Bishop, D Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin's chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68-0.86; rs1105879 OR = 0.77 95% CI = 0.69-0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations

PubMed Central

Ulrich, Cornelia M.; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H.; Forman, David; Wolf, C. Roland; Smith, Gillian; Jackson, Michael S.; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L.; Marchand, Loic Le; Lindor, Noralane M.; Thibodeau, Stephen N.; Potter, John D.; Burn, John; Bishop, D. Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin’s chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68–0.86; rs1105879 OR = 0.77 95% CI = 0.69–0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk. PMID:29425227

Co-Creativity and Interactive Repair: Commentary on Berta Bornstein's "The Analysis of a Phobic Child".

PubMed

Harrison, Alexandra

2014-01-01

My comments focus on a consideration of three issues central to child psychoanalysis stimulated by rereading the classic paper by Berta Bornstein, "The Analysis of a Phobic Child: Some Problems of Theory and Technique in Child Analysis": (1) the importance of "co-creativity" and its use in analysis to repair disruptions in the mother-child relationship; (2) working analytically with the "inner world of the child "; and (3) the fundamental importance of multiple simultaneous meaning-making processes. I begin with a discussion of current thinking about the importance of interactive processes in developmental and therapeutic change and then lead to the concepts of "co-creativity" and interactive repair, elements that are missing in the "Frankie" paper. The co-creative process that I outline includes multiple contributions that Frankie and his caregivers brought to their relationships--his mother, his father, his nurse, and even his analyst. I then address the question of how child analysts can maintain a central focus on the inner world of the child while still taking into account the complex nature of co-creativity in the change process. Finally, I discuss insights into the multiple simultaneous meaning-making processes in the analytic relationship to effect therapeutic change, including what I call the "sandwich model," an attempt to organize this complexity so that is more accessible to the practicing clinician. In terms of the specific case of Frankie, my reading of the case suggests that failure to repair disruptions in the mother-child relationship from infancy through the time of the analytic treatment was central to Frankie's problems. My hypothesis is that, rather than the content of his analyst's interpretations, what was helpful to Frankie in the analysis was the series of attempts at interactive repair in the analytic process. Unfortunately, the case report does not offer data to test this hypothesis. Indeed, one concluding observation from my reading of this classic case is how useful it would be for the contemporary analyst to pay attention to the multifaceted co-creative process in order to explain and foster the therapeutic change that can occur in analysis.

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

EDITORIAL: SPECTROSCOPIC IMAGING

EPA Science Inventory

A foremost goal in biology is understanding the molecular basis of single cell behavior, as well as cell interactions that result in functioning tissues. Accomplishing this goal requires quantitative analysis of multiple, specific macromolecules (e.g. proteins, ligands and enzyme...

Papaya nutritional analysis

USDA-ARS?s Scientific Manuscript database

Papayas are sweet, flavorful tropical fruit, rich in vitamin C and carotenoids. Multiple interactions among preharvest environmental conditions, genetics, and physiology determine papaya nutritional composition at harvest. Selecting a cultivar with the genetic potential for high nutrient content and...

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

NASA Astrophysics Data System (ADS)

Chaudhari, Rajan; Heim, Andrew J.; Li, Zhijun

2015-05-01

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.

Challenges in Wireless System Integration as Enablers for Indoor Context Aware Environments

PubMed Central

Aguirre, Erik

2017-01-01

The advent of fully interactive environments within Smart Cities and Smart Regions requires the use of multiple wireless systems. In the case of user-device interaction, which finds multiple applications such as Ambient Assisted Living, Intelligent Transportation Systems or Smart Grids, among others, large amount of transceivers are employed in order to achieve anytime, anyplace and any device connectivity. The resulting combination of heterogeneous wireless network exhibits fundamental limitations derived from Coverage/Capacity relations, as a function of required Quality of Service parameters, required bit rate, energy restrictions and adaptive modulation and coding schemes. In this context, inherent transceiver density poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. In this work, a deterministic based analysis applied to variable density wireless sensor network operation within complex indoor scenarios is presented, as a function of topological node distribution. The extensive analysis derives interference characterizations, both for conventional transceivers as well as wearables, which provide relevant information in terms of individual node configuration as well as complete network layout. PMID:28704963

Relating improvisational music therapy with severely and multiply disabled children to communication development.

PubMed

Rainey Perry, Mary M

2003-01-01

The effect of different levels of preintentional and intentional communication development on musical interaction with children with severe and multiple disabilities has not been explored in the music therapy literature. Aside from stage of communication development, what are the particular influences of disability on musical interaction with children who have preintentional and early intentional communication? A qualitative research project explored these issues. Ten school-aged children with severe and multiple disabilities participated in the project. The most common medical diagnosis was cerebral palsy. Analysis of video recordings and other data confirmed that the children's level of communication development was reflected in individual music therapy. Specifically, children at different levels of communication development varied in their abilities to initiate, anticipate, and sustain participation in turn taking, and to maintain attention to and engagement in the interaction. Both turn taking and playing and singing together were found to be important forms of communication during music therapy. Communication problems related to disability included: difficulties in using objects as a focus of joint attention, difficulties in interpreting the interactive environment, being sufficiently motivated to communicate, severely limited means of interaction, attaining and maintaining an appropriate level of arousal, and lack of interest in interaction and the outside environment. Further study of how music therapy can be related to general issues in communication for individuals with severe and multiple disabilities is recommended.

Shared periodic performer movements coordinate interactions in duo improvisations.

PubMed

Eerola, Tuomas; Jakubowski, Kelly; Moran, Nikki; Keller, Peter E; Clayton, Martin

2018-02-01

Human interaction involves the exchange of temporally coordinated, multimodal cues. Our work focused on interaction in the visual domain, using music performance as a case for analysis due to its temporally diverse and hierarchical structures. We made use of two improvising duo datasets-(i) performances of a jazz standard with a regular pulse and (ii) non-pulsed, free improvizations-to investigate whether human judgements of moments of interaction between co-performers are influenced by body movement coordination at multiple timescales. Bouts of interaction in the performances were manually annotated by experts and the performers' movements were quantified using computer vision techniques. The annotated interaction bouts were then predicted using several quantitative movement and audio features. Over 80% of the interaction bouts were successfully predicted by a broadband measure of the energy of the cross-wavelet transform of the co-performers' movements in non-pulsed duos. A more complex model, with multiple predictors that captured more specific, interacting features of the movements, was needed to explain a significant amount of variance in the pulsed duos. The methods developed here have key implications for future work on measuring visual coordination in musical ensemble performances, and can be easily adapted to other musical contexts, ensemble types and traditions.

Mass Spectrometry Theatre: A Model for Big-Screen Instrumental Analysis

ERIC Educational Resources Information Center

Allison, John

2008-01-01

Teaching lecture or lab courses in instrumental analysis can be a source of frustration since one can only crowd a small number of students around a single instrument, typically leading to round-robin approaches. Round-robin labs can spread students into multiple labs and limit instructor-student interactions. We discuss "Mass Spectrometry…

A Crack Growth Evaluation Method for Interacting Multiple Cracks

NASA Astrophysics Data System (ADS)

Kamaya, Masayuki

When stress corrosion cracking or corrosion fatigue occurs, multiple cracks are frequently initiated in the same area. According to section XI of the ASME Boiler and Pressure Vessel Code, multiple cracks are considered as a single combined crack in crack growth analysis, if the specified conditions are satisfied. In crack growth processes, however, no prescription for the interference between multiple cracks is given in this code. The JSME Post-Construction Code, issued in May 2000, prescribes the conditions of crack coalescence in the crack growth process. This study aimed to extend this prescription to more general cases. A simulation model was applied, to simulate the crack growth process, taking into account the interference between two cracks. This model made it possible to analyze multiple crack growth behaviors for many cases (e. g. different relative position and length) that could not be studied by experiment only. Based on these analyses, a new crack growth analysis method was suggested for taking into account the interference between multiple cracks.

Visualization techniques for computer network defense

NASA Astrophysics Data System (ADS)

Beaver, Justin M.; Steed, Chad A.; Patton, Robert M.; Cui, Xiaohui; Schultz, Matthew

2011-06-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Interaction Analysis of Longevity Interventions Using Survival Curves.

PubMed

Nowak, Stefan; Neidhart, Johannes; Szendro, Ivan G; Rzezonka, Jonas; Marathe, Rahul; Krug, Joachim

2018-01-06

A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard interaction analysis compares the extension of mean lifespan achieved by a combination of interventions to the prediction under an additive or multiplicative null model, but neither model is fundamentally justified. Moreover, the target of longevity interventions is not mean life span but the entire survival curve. Here we formulate a mathematical approach for predicting the survival curve resulting from a combination of two independent interventions based on the survival curves of the individual treatments, and quantify interaction between interventions as the deviation from this prediction. We test the method on a published data set comprising survival curves for all combinations of four different longevity interventions in Caenorhabditis elegans . We find that interactions are generally weak even when the standard analysis indicates otherwise.

Interaction Analysis of Longevity Interventions Using Survival Curves

PubMed Central

Nowak, Stefan; Neidhart, Johannes; Szendro, Ivan G.; Rzezonka, Jonas; Marathe, Rahul; Krug, Joachim

2018-01-01

A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard interaction analysis compares the extension of mean lifespan achieved by a combination of interventions to the prediction under an additive or multiplicative null model, but neither model is fundamentally justified. Moreover, the target of longevity interventions is not mean life span but the entire survival curve. Here we formulate a mathematical approach for predicting the survival curve resulting from a combination of two independent interventions based on the survival curves of the individual treatments, and quantify interaction between interventions as the deviation from this prediction. We test the method on a published data set comprising survival curves for all combinations of four different longevity interventions in Caenorhabditis elegans. We find that interactions are generally weak even when the standard analysis indicates otherwise. PMID:29316622

Reconceptualizing synergism and antagonism among multiple stressors.

PubMed

Piggott, Jeremy J; Townsend, Colin R; Matthaei, Christoph D

2015-04-01

The potential for complex synergistic or antagonistic interactions between multiple stressors presents one of the largest uncertainties when predicting ecological change but, despite common use of the terms in the scientific literature, a consensus on their operational definition is still lacking. The identification of synergism or antagonism is generally straightforward when stressors operate in the same direction, but if individual stressor effects oppose each other, the definition of synergism is paradoxical because what is synergistic to one stressor's effect direction is antagonistic to the others. In their highly cited meta-analysis, Crain et al. (Ecology Letters, 11, 2008: 1304) assumed in situations with opposing individual effects that synergy only occurs when the cumulative effect is more negative than the additive sum of the opposing individual effects. We argue against this and propose a new systematic classification based on an additive effects model that combines the magnitude and response direction of the cumulative effect and the interaction effect. A new class of "mitigating synergism" is identified, where cumulative effects are reversed and enhanced. We applied our directional classification to the dataset compiled by Crain et al. (Ecology Letters, 11, 2008: 1304) to determine the prevalence of synergistic, antagonistic, and additive interactions. Compared to their original analysis, we report differences in the representation of interaction classes by interaction type and we document examples of mitigating synergism, highlighting the importance of incorporating individual stressor effect directions in the determination of synergisms and antagonisms. This is particularly pertinent given a general bias in ecology toward investigating and reporting adverse multiple stressor effects (double negative). We emphasize the need for reconsideration by the ecological community of the interpretation of synergism and antagonism in situations where individual stressor effects oppose each other or where cumulative effects are reversed and enhanced.

Chronodes: Interactive Multifocus Exploration of Event Sequences

PubMed Central

POLACK, PETER J.; CHEN, SHANG-TSE; KAHNG, MINSUK; DE BARBARO, KAYA; BASOLE, RAHUL; SHARMIN, MOUSHUMI; CHAU, DUEN HORNG

2018-01-01

The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques to support explorative analysis of longitudinal mHealth data. Chronodes extracts and visualizes frequent event sequences that reveal chronological patterns across multiple participant timelines of mHealth data. It then combines novel interaction and visualization techniques to enable multifocus event sequence analysis, which allows health researchers to interactively define, explore, and compare groups of participant behaviors using event sequence combinations. Through summarizing insights gained from a pilot study with 20 behavioral and biomedical health experts, we discuss Chronodes’s efficacy and potential impact in the mHealth domain. Ultimately, we outline important open challenges in mHealth, and offer recommendations and design guidelines for future research. PMID:29515937

VIBRA: An interactive computer program for steady-state vibration response analysis of linear damped structures

NASA Technical Reports Server (NTRS)

Bowman, L. M.

1984-01-01

An interactive steady state frequency response computer program with graphics is documented. Single or multiple forces may be applied to the structure using a modal superposition approach to calculate response. The method can be reapplied to linear, proportionally damped structures in which the damping may be viscous or structural. The theoretical approach and program organization are described. Example problems, user instructions, and a sample interactive session are given to demonstate the program's capability in solving a variety of problems.

VESPA: Software to Facilitate Genomic Annotation of Prokaryotic Organisms Through Integration of Proteomic and Transcriptomic Data

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

Peterson, Elena S.; McCue, Lee Ann; Rutledge, Alexandra C.

2012-04-25

Visual Exploration and Statistics to Promote Annotation (VESPA) is an interactive visual analysis software tool that facilitates the discovery of structural mis-annotations in prokaryotic genomes. VESPA integrates high-throughput peptide-centric proteomics data and oligo-centric or RNA-Seq transcriptomics data into a genomic context. The data may be interrogated via visual analysis across multiple levels of genomic resolution, linked searches, exports and interaction with BLAST to rapidly identify location of interest within the genome and evaluate potential mis-annotations.

Instantiating the multiple levels of analysis perspective in a program of study on externalizing behavior

PubMed Central

Beauchaine, Theodore P.; Gatzke-Kopp, Lisa M.

2014-01-01

During the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide. PMID:22781868

Multiple-Localization and Hub Proteins

PubMed Central

Ota, Motonori; Gonja, Hideki; Koike, Ryotaro; Fukuchi, Satoshi

2016-01-01

Protein-protein interactions are fundamental for all biological phenomena, and protein-protein interaction networks provide a global view of the interactions. The hub proteins, with many interaction partners, play vital roles in the networks. We investigated the subcellular localizations of proteins in the human network, and found that the ones localized in multiple subcellular compartments, especially the nucleus/cytoplasm proteins (NCP), the cytoplasm/cell membrane proteins (CMP), and the nucleus/cytoplasm/cell membrane proteins (NCMP), tend to be hubs. Examinations of keywords suggested that among NCP, those related to post-translational modifications and transcription functions are the major contributors to the large number of interactions. These types of proteins are characterized by a multi-domain architecture and intrinsic disorder. A survey of the typical hub proteins with prominent numbers of interaction partners in the type revealed that most are either transcription factors or co-regulators involved in signaling pathways. They translocate from the cytoplasm to the nucleus, triggered by the phosphorylation and/or ubiquitination of intrinsically disordered regions. Among CMP and NCMP, the contributors to the numerous interactions are related to either kinase or ubiquitin ligase activity. Many of them reside on the cytoplasmic side of the cell membrane, and act as the upstream regulators of signaling pathways. Overall, these hub proteins function to transfer external signals to the nucleus, through the cell membrane and the cytoplasm. Our analysis suggests that multiple-localization is a crucial concept to characterize groups of hub proteins and their biological functions in cellular information processing. PMID:27285823

Parental Depression and Child Cognitive Vulnerability Predict Children’s Cortisol Reactivity

PubMed Central

Hayden, Elizabeth P.; Hankin, Benjamin L.; Mackrell, Sarah V.M.; Sheikh, Haroon I.; Jordan, Patricia L.; Dozois, David J.A.; Singh, Shiva M.; Olino, Thomas M.; Badanes, Lisa S.

2015-01-01

Risk for depression is expressed across multiple levels of analysis. For example, parental depression and cognitive vulnerability are known markers of depression risk, but no study has examined their interactive effects on children’s cortisol reactivity, a likely mediator of early depression risk. We examined relations across these different levels of vulnerability using cross-sectional and longitudinal methods in two community samples of children. Children were assessed for cognitive vulnerability using self-reports (Study 1; n = 244) and tasks tapping memory and attentional bias (Study 2; n = 205), and their parents were assessed for depression history using structured clinical interviews. In both samples, children participated in standardized stress tasks and cortisol reactivity was assessed. Cross-sectionally and longitudinally, parental depression history and child cognitive vulnerability interacted to predict children’s cortisol reactivity; specifically, associations between parent depression and elevated child cortisol activity were found when children also showed elevated depressotypic attributions, as well as attentional and memory biases. Findings indicate that models of children’s emerging depression risk may benefit from the examination of the interactive effects of multiple sources of vulnerability across levels of analysis. PMID:25422972

Toward a community ecology of landscapes: predicting multiple predator-prey interactions across geographic space.

PubMed

Schmitz, Oswald J; Miller, Jennifer R B; Trainor, Anne M; Abrahms, Briana

2017-09-01

Community ecology was traditionally an integrative science devoted to studying interactions between species and their abiotic environments in order to predict species' geographic distributions and abundances. Yet for philosophical and methodological reasons, it has become divided into two enterprises: one devoted to local experimentation on species interactions to predict community dynamics; the other devoted to statistical analyses of abiotic and biotic information to describe geographic distribution. Our goal here is to instigate thinking about ways to reconnect the two enterprises and thereby return to a tradition to do integrative science. We focus specifically on the community ecology of predators and prey, which is ripe for integration. This is because there is active, simultaneous interest in experimentally resolving the nature and strength of predator-prey interactions as well as explaining patterns across landscapes and seascapes. We begin by describing a conceptual theory rooted in classical analyses of non-spatial food web modules used to predict species interactions. We show how such modules can be extended to consideration of spatial context using the concept of habitat domain. Habitat domain describes the spatial extent of habitat space that predators and prey use while foraging, which differs from home range, the spatial extent used by an animal to meet all of its daily needs. This conceptual theory can be used to predict how different spatial relations of predators and prey could lead to different emergent multiple predator-prey interactions such as whether predator consumptive or non-consumptive effects should dominate, and whether intraguild predation, predator interference or predator complementarity are expected. We then review the literature on studies of large predator-prey interactions that make conclusions about the nature of multiple predator-prey interactions. This analysis reveals that while many studies provide sufficient information about predator or prey spatial locations, and thus meet necessary conditions of the habitat domain conceptual theory for drawing conclusions about the nature of the predator-prey interactions, several studies do not. We therefore elaborate how modern technology and statistical approaches for animal movement analysis could be used to test the conceptual theory, using experimental or quasi-experimental analyses at landscape scales. © 2017 by the Ecological Society of America.

Dissecting Situational Strength: Theoretical Analysis and Empirical Tests

DTIC Science & Technology

2012-09-01

behavior , and to the complexity of personality and its multiple and interacting determinants ” (Mischel, 1999; p. 456; see also Mischel, 1968). Mischel...outcome relationships. Specifically, he posited that traits have less of a determining impact on behaviors in “strong” situations, which provide: (1...which situations interact with personality in determining voluntary work behavior (Project One) and the extent to which people respond adversely to

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis.

PubMed

Piepho, H P

1994-11-01

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.

AMMI adjustment for statistical analysis of an international wheat yield trial.

PubMed

Crossa, J; Fox, P N; Pfeiffer, W H; Rajaram, S; Gauch, H G

1991-01-01

Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.

Forecasting the Relative and Cumulative Effects of Multiple Stressors on At-risk Populations

DTIC Science & Technology

2011-08-01

Vitals (observed vital rates), Movement, Ranges, Barriers (barrier interactions), Stochasticity (a time series of stochasticity indices...Simulation Viewer are themselves stochastic . They can change each time it is run. B. 196 Analysis If multiple Census events are present in the life...30-year period. A monthly time series was generated for the 20th-century using monthly anomalies for temperature, precipitation, and percent

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

PubMed

Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2004-09-22

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Verification of nonlinear dynamic structural test results by combined image processing and acoustic analysis

NASA Astrophysics Data System (ADS)

Tene, Yair; Tene, Noam; Tene, G.

1993-08-01

An interactive data fusion methodology of video, audio, and nonlinear structural dynamic analysis for potential application in forensic engineering is presented. The methodology was developed and successfully demonstrated in the analysis of heavy transportable bridge collapse during preparation for testing. Multiple bridge elements failures were identified after the collapse, including fracture, cracks and rupture of high performance structural materials. Videotape recording by hand held camcorder was the only source of information about the collapse sequence. The interactive data fusion methodology resulted in extracting relevant information form the videotape and from dynamic nonlinear structural analysis, leading to full account of the sequence of events during the bridge collapse.

Phylo-VISTA: Interactive visualization of multiple DNA sequence alignments

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

Shah, Nameeta; Couronne, Olivier; Pennacchio, Len A.

The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. Results: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a frameworkmore » based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. Availability: Phylo-VISTA is available at http://www-gsd.lbl. gov/phylovista. It requires an Internet browser with Java Plugin 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu« less

Mouse Social Interaction Test (MoST): a quantitative computer automated analysis of behavior.

PubMed

Thanos, Panayotis K; Restif, Christophe; O'Rourke, Joseph R; Lam, Chiu Yin; Metaxas, Dimitris

2017-01-01

Rodents are the most commonly used preclinical model of human disease assessing the mechanism(s) involved as well as the role of genetics, epigenetics, and pharmacotherapy on this disease as well as identifying vulnerability factors and risk assessment for disease critical in the development of improved treatment strategies. Unfortunately, the majority of rodent preclinical studies utilize single housed approaches where animals are either entirely housed and tested in solitary environments or group housed but tested in solitary environments. This approach, however, ignores the important contribution of social interaction and social behavior. Social interaction in rodents is found to be a major criterion for the ethological validity of rodent species-specific behavioral characteristics (Zurn et al. 2007; Analysis 2011). It is also well established that there is significant and growing number of reports, which illustrates the important role of social environment and social interaction in all diseases, with particularly significance in all neuropsychiatric diseases. Thus, it is imperative that research studies be able to add large-scale evaluations of social interaction and behavior in mice and benefit from automated tracking of behaviors and measurements by removing user bias and by quantifying aspects of behaviors that cannot be assessed by a human observer. Single mouse setups have been used routinely, but cannot be easily extended to multiple-animal studies where social behavior is key, e.g., autism, depression, anxiety, substance and non-substance addictive disorders, aggression, sexual behavior, or parenting. While recent efforts are focusing on multiple-animal tracking alone, a significant limitation remains the lack of insightful measures of social interactions. We present a novel, non-invasive single camera-based automated tracking method described as Mouse Social Test (MoST) and set of measures designed for estimating the interactions of multiple mice at the same time in the same environment interacting freely. Our results show measurement of social interactions and designed to be adaptable and applicable to most existing home cage systems used in research, and provide a greater level of detailed analysis of social behavior than previously possible. The present study describes social behaviors assessed in a home cage environment setup containing six mice that interact freely over long periods of time, and we illustrate how these measures can be interpreted and combined to classify rodent social behaviors. In addition, we illustrate how these measures can be interpreted and combined to classify and analyze comprehensively rodent behaviors involved in several neuropsychiatric diseases as well as provide opportunity for the basic research of rodent behavior previously not possible.

Decreased cerebellar-cerebral connectivity contributes to complex task performance

PubMed Central

Knops, André

2016-01-01

The cerebellum's role in nonmotor processes is now well accepted, but cerebellar interaction with cerebral targets is not well understood. Complex cognitive tasks activate cerebellar, parietal, and frontal regions, but the effective connectivity between these regions has never been tested. To this end, we used psycho-physiological interactions (PPI) analysis to test connectivity changes of cerebellar and parietal seed regions in complex (2-digit by 1-digit multiplication, e.g., 12 × 3) vs. simple (1-digit by 1-digit multiplication, e.g., 4 × 3) task conditions (“complex − simple”). For cerebellar seed regions (lobule VI, hemisphere and vermis), we found significantly decreased cerebellar-parietal, cerebellar-cingulate, and cerebellar-frontal connectivity in complex multiplication. For parietal seed regions (PFcm, PFop, PFm) we found significantly increased parietal-parietal and parietal-frontal connectivity in complex multiplication. These results suggest that decreased cerebellar-cerebral connectivity contributes to complex task performance. Interestingly, BOLD activity contrasts revealed partially overlapping parietal areas of increased BOLD activity but decreased cerebellar-parietal PPI connectivity. PMID:27334957

Innovative Visualization Techniques applied to a Flood Scenario

NASA Astrophysics Data System (ADS)

Falcão, António; Ho, Quan; Lopes, Pedro; Malamud, Bruce D.; Ribeiro, Rita; Jern, Mikael

2013-04-01

The large and ever-increasing amounts of multi-dimensional, time-varying and geospatial digital information from multiple sources represent a major challenge for today's analysts. We present a set of visualization techniques that can be used for the interactive analysis of geo-referenced and time sampled data sets, providing an integrated mechanism and that aids the user to collaboratively explore, present and communicate visually complex and dynamic data. Here we present these concepts in the context of a 4 hour flood scenario from Lisbon in 2010, with data that includes measures of water column (flood height) every 10 minutes at a 4.5 m x 4.5 m resolution, topography, building damage, building information, and online base maps. Techniques we use include web-based linked views, multiple charts, map layers and storytelling. We explain two of these in more detail that are not currently in common use for visualization of data: storytelling and web-based linked views. Visual storytelling is a method for providing a guided but interactive process of visualizing data, allowing more engaging data exploration through interactive web-enabled visualizations. Within storytelling, a snapshot mechanism helps the author of a story to highlight data views of particular interest and subsequently share or guide others within the data analysis process. This allows a particular person to select relevant attributes for a snapshot, such as highlighted regions for comparisons, time step, class values for colour legend, etc. and provide a snapshot of the current application state, which can then be provided as a hyperlink and recreated by someone else. Since data can be embedded within this snapshot, it is possible to interactively visualize and manipulate it. The second technique, web-based linked views, includes multiple windows which interactively respond to the user selections, so that when selecting an object and changing it one window, it will automatically update in all the other windows. These concepts can be part of a collaborative platform, where multiple people share and work together on the data, via online access, which also allows its remote usage from a mobile platform. Storytelling augments analysis and decision-making capabilities allowing to assimilate complex situations and reach informed decisions, in addition to helping the public visualize information. In our visualization scenario, developed in the context of the VA-4D project for the European Space Agency (see http://www.ca3-uninova.org/project_va4d), we make use of the GAV (GeoAnalytics Visualization) framework, a web-oriented visual analytics application based on multiple interactive views. The final visualization that we produce includes multiple interactive views, including a dynamic multi-layer map surrounded by other visualizations such as bar charts, time graphs and scatter plots. The map provides flood and building information, on top of a base city map (street maps and/or satellite imagery provided by online map services such as Google Maps, Bing Maps etc.). Damage over time for selected buildings, damage for all buildings at a chosen time period, correlation between damage and water depth can be analysed in the other views. This interactive web-based visualization that incorporates the ideas of storytelling, web-based linked views, and other visualization techniques, for a 4 hour flood event in Lisbon in 2010, can be found online at http://www.ncomva.se/flash/projects/esa/flooding/.

Multiple methods integration for structural mechanics analysis and design

NASA Technical Reports Server (NTRS)

Housner, J. M.; Aminpour, M. A.

1991-01-01

A new research area of multiple methods integration is proposed for joining diverse methods of structural mechanics analysis which interact with one another. Three categories of multiple methods are defined: those in which a physical interface are well defined; those in which a physical interface is not well-defined, but selected; and those in which the interface is a mathematical transformation. Two fundamental integration procedures are presented that can be extended to integrate various methods (e.g., finite elements, Rayleigh Ritz, Galerkin, and integral methods) with one another. Since the finite element method will likely be the major method to be integrated, its enhanced robustness under element distortion is also examined and a new robust shell element is demonstrated.

Analysis of SI models with multiple interacting populations using subpopulations.

PubMed

Thomas, Evelyn K; Gurski, Katharine F; Hoffman, Kathleen A

2015-02-01

Computing endemic equilibria and basic reproductive numbers for systems of differential equations describing epidemiological systems with multiple connections between subpopulations is often algebraically intractable. We present an alternative method which deconstructs the larger system into smaller subsystems and captures the interactions between the smaller systems as external forces using an approximate model. We bound the basic reproductive numbers of the full system in terms of the basic reproductive numbers of the smaller systems and use the alternate model to provide approximations for the endemic equilibrium. In addition to creating algebraically tractable reproductive numbers and endemic equilibria, we can demonstrate the influence of the interactions between subpopulations on the basic reproductive number of the full system. The focus of this paper is to provide analytical tools to help guide public health decisions with limited intervention resources.

Exciton multiplication from first principles.

PubMed

Jaeger, Heather M; Hyeon-Deuk, Kim; Prezhdo, Oleg V

2013-06-18

Third-generation photovolatics require demanding cost and power conversion efficiency standards, which may be achieved through efficient exciton multiplication. Therefore, generating more than one electron-hole pair from the absorption of a single photon has vast ramifications on solar power conversion technology. Unlike their bulk counterparts, irradiated semiconductor quantum dots exhibit efficient exciton multiplication, due to confinement-enhanced Coulomb interactions and slower nonradiative losses. The exact characterization of the complicated photoexcited processes within quantum-dot photovoltaics is a work in progress. In this Account, we focus on the photophysics of nanocrystals and investigate three constituent processes of exciton multiplication, including photoexcitation, phonon-induced dephasing, and impact ionization. We quantify the role of each process in exciton multiplication through ab initio computation and analysis of many-electron wave functions. The probability of observing a multiple exciton in a photoexcited state is proportional to the magnitude of electron correlation, where correlated electrons can be simultaneously promoted across the band gap. Energies of multiple excitons are determined directly from the excited state wave functions, defining the threshold for multiple exciton generation. This threshold is strongly perturbed in the presence of surface defects, dopants, and ionization. Within a few femtoseconds following photoexcitation, the quantum state loses coherence through interactions with the vibrating atomic lattice. The phase relationship between single excitons and multiple excitons dissipates first, followed by multiple exciton fission. Single excitons are coupled to multiple excitons through Coulomb and electron-phonon interactions, and as a consequence, single excitons convert to multiple excitons and vice versa. Here, exciton multiplication depends on the initial energy and coupling magnitude and competes with electron-phonon energy relaxation. Multiple excitons are generated through impact ionization within picoseconds. The basis of exciton multiplication in quantum dots is the collective result of photoexcitation, dephasing, and nonadiabatic evolution. Each process is characterized by a distinct time-scale, and the overall multiple exciton generation dynamics is complete by about 10 ps. Without relying on semiempirical parameters, we computed quantum mechanical probabilities of multiple excitons for small model systems. Because exciton correlations and coherences are microscopic, quantum properties, results for small model systems can be extrapolated to larger, realistic quantum dots.

Transforming Parent-Child Interaction in Family Routines: Longitudinal Analysis with Families of Children with Developmental Disabilities.

PubMed

Lucyshyn, Joseph M; Fossett, Brenda; Bakeman, Roger; Cheremshynski, Christy; Miller, Lynn; Lohrmann, Sharon; Binnendyk, Lauren; Khan, Sophia; Chinn, Stephen; Kwon, Samantha; Irvin, Larry K

2015-12-01

The efficacy and consequential validity of an ecological approach to behavioral intervention with families of children with developmental disabilities was examined. The approach aimed to transform coercive into constructive parent-child interaction in family routines. Ten families participated, including 10 mothers and fathers and 10 children 3-8 years old with developmental disabilities. Thirty-six family routines were selected (2 to 4 per family). Dependent measures included child problem behavior, routine steps completed, and coercive and constructive parent-child interaction. For each family, a single case, multiple baseline design was employed with three phases: baseline, intervention, and follow-up. Visual analysis evaluated the functional relation between intervention and improvements in child behavior and routine participation. Nonparametric tests across families evaluated the statistical significance of these improvements. Sequential analyses within families and univariate analyses across families examined changes from baseline to intervention in the percentage and odds ratio of coercive and constructive parent-child interaction. Multiple baseline results documented functional or basic effects for 8 of 10 families. Nonparametric tests showed these changes to be significant. Follow-up showed durability at 11 to 24 months postintervention. Sequential analyses documented the transformation of coercive into constructive processes for 9 of 10 families. Univariate analyses across families showed significant improvements in 2- and 4-step coercive and constructive processes but not in odds ratio. Results offer evidence of the efficacy of the approach and consequential validity of the ecological unit of analysis, parent-child interaction in family routines. Future studies should improve efficiency, and outcomes for families experiencing family systems challenges.

Genome-wide interaction study of smoking and bladder cancer risk

PubMed Central

Figueroa, Jonine D.; Han, Summer S.; Garcia-Closas, Montserrat; Baris, Dalsu; Jacobs, Eric J.; Kogevinas, Manolis; Schwenn, Molly; Malats, Nuria; Johnson, Alison; Purdue, Mark P.; Caporaso, Neil; Landi, Maria Teresa; Prokunina-Olsson, Ludmila; Wang, Zhaoming; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Vineis, Paolo; Siddiq, Afshan; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Bueno-de-Mesquita, H.Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Karagas, Margaret R.; Schned, Alan; Armenti, Karla R.; Hosain, G.M.Monawar; Haiman, Chris A.; Fraumeni, Joseph F.; Chanock, Stephen J.; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T.

2014-01-01

Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10− 5 were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20–1.50, P value = 5.18 × 10− 7]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67–0.84, P value = 6.35 × 10− 7). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers—including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene–environment interactions for tobacco and bladder cancer. PMID:24662972

Heuristics for Understanding the Concepts of Interaction, Polynomial Trend, and the General Linear Model.

ERIC Educational Resources Information Center

Thompson, Bruce

The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…

Beyond Logging of Fingertip Actions: Analysis of Collaborative Learning Using Multiple Sources of Data

ERIC Educational Resources Information Center

Avouris, N.; Fiotakis, G.; Kahrimanis, G.; Margaritis, M.; Komis, V.

2007-01-01

In this article, we discuss key requirements for collecting behavioural data concerning technology-supported collaborative learning activities. It is argued that the common practice of analysis of computer generated log files of user interactions with software tools is not enough for building a thorough view of the activity. Instead, more…

Assessment of Innovation Competency: A Thematic Analysis of Upper Secondary School Teachers' Talk

ERIC Educational Resources Information Center

Nielsen, Jan Alexis

2015-01-01

The author employed a 3-step qualitative research design with multiple instances of source validation to capture expert teachers' (n = 28) reflections on which manifest signs they would look for when they asses students' innovation competency. The author reports on the thematic analysis of the recorded talk in interaction that occurred in teacher…

Causal mediation analysis with multiple causally non-ordered mediators.

PubMed

Taguri, Masataka; Featherstone, John; Cheng, Jing

2018-01-01

In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

PIVOT: platform for interactive analysis and visualization of transcriptomics data.

PubMed

Zhu, Qin; Fisher, Stephen A; Dueck, Hannah; Middleton, Sarah; Khaladkar, Mugdha; Kim, Junhyong

2018-01-05

Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermore, exploratory data analyses often generate multiple derived datasets such as data subsets or data transformations, which can be difficult to track. Here we present PIVOT, an R-based platform that wraps open source transcriptome analysis packages with a uniform user interface and graphical data management that allows non-programmers to interactively explore transcriptomics data. PIVOT supports more than 40 popular open source packages for transcriptome analysis and provides an extensive set of tools for statistical data manipulations. A graph-based visual interface is used to represent the links between derived datasets, allowing easy tracking of data versions. PIVOT further supports automatic report generation, publication-quality plots, and program/data state saving, such that all analysis can be saved, shared and reproduced. PIVOT will allow researchers with broad background to easily access sophisticated transcriptome analysis tools and interactively explore transcriptome datasets.

p-barp interactions at 2. 32 GeV/c

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

Chen, C.K.; Fields, T.; Rhines, D.S.

1978-01-01

A bubble-chamber experiment based on 304 000 events of p-barp interactions at 2.32 GeV/c is described. The film was automatically scanned and measured by the POLLY II system. Details of the data-analysis methods are given. We report results on cross sections for constrained final states, tests of C invariance, and inclusive pion and rho/sup 0/ multiplicity parameters for annihilation final states.

On Bayesian methods of exploring qualitative interactions for targeted treatment.

PubMed

Chen, Wei; Ghosh, Debashis; Raghunathan, Trivellore E; Norkin, Maxim; Sargent, Daniel J; Bepler, Gerold

2012-12-10

Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A. Copyright © 2012 John Wiley & Sons, Ltd.

Tests of neutrino interaction models with the MicroBooNE detector

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

Rafique, Aleena

2018-01-01

I measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. I evaluate three neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy ofmore » $800$ MeV, using an exposure corresponding to $$5.0\\times10^{19}$$ protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. I find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity, but I show an indication that the observed multiplicity fractions deviate from GENIE expectations.« less

Characterization of recombinant monoclonal antibody variants detected by hydrophobic interaction chromatography and imaged capillary isoelectric focusing electrophoresis.

PubMed

King, Cory; Patel, Rekha; Ponniah, Gomathinayagam; Nowak, Christine; Neill, Alyssa; Gu, Zhenyu; Liu, Hongcheng

2018-05-15

In-depth characterization of the commonly observed variants is critical to the successful development of recombinant monoclonal antibody therapeutics. Multiple peaks of a recombinant monoclonal antibody were observed when analyzed by hydrophobic interaction chromatography and imaged capillary isoelectric focusing. The potential modification causing the heterogeneity was localized to F(ab')2 region by analyzing the antibody after IdeS digestion using hydrophobic interaction chromatography. LC-MS analysis identified asparagine deamidation as the root cause of the observed multiple variants. While the isoelectric focusing method is expected to separate deamidated species, the similar profile observed in hydrophobic interaction chromatography indicates that the single site deamidation caused differences in hydrophobicity. Forced degradation demonstrated that the susceptible asparagine residue is highly exposed, which is expected as it is located in the light chain complementarity determining region. Deamidation of this single site decreased the mAb binding affinity to its specific antigen. Copyright © 2018 Elsevier B.V. All rights reserved.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

Factor VIII Interacts with the Endocytic Receptor Low-density Lipoprotein Receptor-related Protein 1 via an Extended Surface Comprising "Hot-Spot" Lysine Residues.

PubMed

van den Biggelaar, Maartje; Madsen, Jesper J; Faber, Johan H; Zuurveld, Marleen G; van der Zwaan, Carmen; Olsen, Ole H; Stennicke, Henning R; Mertens, Koen; Meijer, Alexander B

2015-07-03

Lysine residues are implicated in driving the ligand binding to the LDL receptor family. However, it has remained unclear how specificity is regulated. Using coagulation factor VIII as a model ligand, we now study the contribution of individual lysine residues in the interaction with the largest member of the LDL receptor family, low-density lipoprotein receptor-related protein (LRP1). Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and SPR interaction analysis on a library of lysine replacement variants as two independent approaches, we demonstrate that the interaction between factor VIII (FVIII) and LRP1 occurs over an extended surface containing multiple lysine residues. None of the individual lysine residues account completely for LRP1 binding, suggesting an additive binding model. Together with structural docking studies, our data suggest that FVIII interacts with LRP1 via an extended surface of multiple lysine residues that starts at the bottom of the C1 domain and winds around the FVIII molecule. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

PubMed Central

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

Shifting from Stewardship to Analytics of Massive Science Data

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Doyle, R.; Law, E.; Hughes, S.; Huang, T.; Mahabal, A.

2015-12-01

Currently, the analysis of large data collections is executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Data collection, archiving and analysis from future remote sensing missions, be it from earth science satellites, planetary robotic missions, or massive radio observatories may not scale as more capable instruments stress existing architectural approaches and systems due to more continuous data streams, data from multiple observational platforms, and measurements and models from different agencies. A new paradigm is needed in order to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural choices, data processing, management, analysis, etc are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections. Future observational systems, including satellite and airborne experiments, and research in climate modeling will significantly increase the size of the data requiring new methodological approaches towards data analytics where users can more effectively interact with the data and apply automated mechanisms for data reduction, reduction and fusion across these massive data repositories. This presentation will discuss architecture, use cases, and approaches for developing a big data analytics strategy across multiple science disciplines.

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed Central

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group. PMID:28034175

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

Shared periodic performer movements coordinate interactions in duo improvisations

PubMed Central

Jakubowski, Kelly; Moran, Nikki; Keller, Peter E.

2018-01-01

Human interaction involves the exchange of temporally coordinated, multimodal cues. Our work focused on interaction in the visual domain, using music performance as a case for analysis due to its temporally diverse and hierarchical structures. We made use of two improvising duo datasets—(i) performances of a jazz standard with a regular pulse and (ii) non-pulsed, free improvizations—to investigate whether human judgements of moments of interaction between co-performers are influenced by body movement coordination at multiple timescales. Bouts of interaction in the performances were manually annotated by experts and the performers’ movements were quantified using computer vision techniques. The annotated interaction bouts were then predicted using several quantitative movement and audio features. Over 80% of the interaction bouts were successfully predicted by a broadband measure of the energy of the cross-wavelet transform of the co-performers’ movements in non-pulsed duos. A more complex model, with multiple predictors that captured more specific, interacting features of the movements, was needed to explain a significant amount of variance in the pulsed duos. The methods developed here have key implications for future work on measuring visual coordination in musical ensemble performances, and can be easily adapted to other musical contexts, ensemble types and traditions. PMID:29515867

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.

PubMed

Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L

2017-12-18

Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region ( p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region ( p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Saturated fat intake modulates the association between a genetic risk score of obesity and BMI in two US populations

PubMed Central

Casas-Agustench, Patricia; Arnett, Donna K.; Smith, Caren E.; Lai, Chao-Qiang; Parnell, Laurence D.; Borecki, Ingrid B.; Frazier-Wood, Alexis C.; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D.; Rich, Stephen S.; Rotter, Jerome I.; Lee, Yu-Chi; Ordovás, José M.

2014-01-01

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and BMI in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake and to replicate findings in Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 US Caucasian participants from GOLDN and 2035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although to determine the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. PMID:24794412

Using Discursis to enhance the qualitative analysis of hospital pharmacist-patient interactions

PubMed Central

Barras, Michael A.; Angus, Daniel J.

2018-01-01

Introduction Pharmacist-patient communication during medication counselling has been successfully investigated using Communication Accommodation Theory (CAT). Communication researchers in other healthcare professions have utilised Discursis software as an adjunct to their manual qualitative analysis processes. Discursis provides a visual, chronological representation of communication exchanges and identifies patterns of interactant engagement. Aim The aim of this study was to describe how Discursis software was used to enhance previously conducted qualitative analysis of pharmacist-patient interactions (by visualising pharmacist-patient speech patterns, episodes of engagement, and identifying CAT strategies employed by pharmacists within these episodes). Methods Visual plots from 48 transcribed audio recordings of pharmacist-patient exchanges were generated by Discursis. Representative plots were selected to show moderate-high and low- level speaker engagement. Details of engagement were investigated for pharmacist application of CAT strategies (approximation, interpretability, discourse management, emotional expression, and interpersonal control). Results Discursis plots allowed for identification of distinct patterns occurring within pharmacist-patient exchanges. Moderate-high pharmacist-patient engagement was characterised by multiple off-diagonal squares while alternating single coloured squares depicted low engagement. Engagement episodes were associated with multiple CAT strategies such as discourse management (open-ended questions). Patterns reflecting pharmacist or patient speaker dominance were dependant on clinical setting. Discussion and conclusions Discursis analysis of pharmacist-patient interactions, a novel application of the technology in health communication, was found to be an effective visualisation tool to pin-point episodes for CAT analysis. Discursis has numerous practical and theoretical applications for future health communication research and training. Researchers can use the software to support qualitative analysis where large data sets can be quickly reviewed to identify key areas for concentrated analysis. Because Discursis plots are easily generated from audio recorded transcripts, they are conducive as teaching tools for both students and practitioners to assess and develop their communication skills. PMID:29787568

Modeling Complex Equilibria in ITC Experiments: Thermodynamic Parameters Estimation for a Three Binding Site Model

PubMed Central

Le, Vu H.; Buscaglia, Robert; Chaires, Jonathan B.; Lewis, Edwin A.

2013-01-01

Isothermal Titration Calorimetry, ITC, is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g. Keq (or ΔG), ΔH, ΔS, and n) for a ligand binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combination of equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding need to be developed on a case by case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the non-linear regression analysis of a multiple binding site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g. up to nine parameters in the three binding site model) yields thermodynamic parameters with acceptable accuracy. PMID:23262283

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

2012-01-01

Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897

Supporting secure programming in web applications through interactive static analysis.

PubMed

Zhu, Jun; Xie, Jing; Lipford, Heather Richter; Chu, Bill

2014-07-01

Many security incidents are caused by software developers' failure to adhere to secure programming practices. Static analysis tools have been used to detect software vulnerabilities. However, their wide usage by developers is limited by the special training required to write rules customized to application-specific logic. Our approach is interactive static analysis, to integrate static analysis into Integrated Development Environment (IDE) and provide in-situ secure programming support to help developers prevent vulnerabilities during code construction. No additional training is required nor are there any assumptions on ways programs are built. Our work is motivated in part by the observation that many vulnerabilities are introduced due to failure to practice secure programming by knowledgeable developers. We implemented a prototype interactive static analysis tool as a plug-in for Java in Eclipse. Our technical evaluation of our prototype detected multiple zero-day vulnerabilities in a large open source project. Our evaluations also suggest that false positives may be limited to a very small class of use cases.

Supporting secure programming in web applications through interactive static analysis

PubMed Central

Zhu, Jun; Xie, Jing; Lipford, Heather Richter; Chu, Bill

2013-01-01

Many security incidents are caused by software developers’ failure to adhere to secure programming practices. Static analysis tools have been used to detect software vulnerabilities. However, their wide usage by developers is limited by the special training required to write rules customized to application-specific logic. Our approach is interactive static analysis, to integrate static analysis into Integrated Development Environment (IDE) and provide in-situ secure programming support to help developers prevent vulnerabilities during code construction. No additional training is required nor are there any assumptions on ways programs are built. Our work is motivated in part by the observation that many vulnerabilities are introduced due to failure to practice secure programming by knowledgeable developers. We implemented a prototype interactive static analysis tool as a plug-in for Java in Eclipse. Our technical evaluation of our prototype detected multiple zero-day vulnerabilities in a large open source project. Our evaluations also suggest that false positives may be limited to a very small class of use cases. PMID:25685513

Visualization Techniques for Computer Network Defense

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

Beaver, Justin M; Steed, Chad A; Patton, Robert M

2011-01-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operatormore » to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.« less

Describing and understanding behavioral responses to multiple stressors and multiple stimuli.

PubMed

Hale, Robin; Piggott, Jeremy J; Swearer, Stephen E

2017-01-01

Understanding the effects of environmental change on natural ecosystems is a major challenge, particularly when multiple stressors interact to produce unexpected "ecological surprises" in the form of complex, nonadditive effects that can amplify or reduce their individual effects. Animals often respond behaviorally to environmental change, and multiple stressors can have both population-level and community-level effects. However, the individual, not combined, effects of stressors on animal behavior are commonly studied. There is a need to understand how animals respond to the more complex combinations of stressors that occur in nature, which requires a systematic and rigorous approach to quantify the various potential behavioral responses to the independent and interactive effects of stressors. We illustrate a robust, systematic approach for understanding behavioral responses to multiple stressors based on integrating schemes used to quantitatively classify interactions in multiple-stressor research and to qualitatively view interactions between multiple stimuli in behavioral experiments. We introduce and unify the two frameworks, highlighting their conceptual and methodological similarities, and use four case studies to demonstrate how this unification could improve our interpretation of interactions in behavioral experiments and guide efforts to manage the effects of multiple stressors. Our unified approach: (1) provides behavioral ecologists with a more rigorous and systematic way to quantify how animals respond to interactions between multiple stimuli, an important theoretical advance, (2) helps us better understand how animals behave when they encounter multiple, potentially interacting stressors, and (3) contributes more generally to the understanding of "ecological surprises" in multiple stressors research.

SoS Notebook: An Interactive Multi-Language Data Analysis Environment.

PubMed

Peng, Bo; Wang, Gao; Ma, Jun; Leong, Man Chong; Wakefield, Chris; Melott, James; Chiu, Yulun; Du, Di; Weinstein, John N

2018-05-22

Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share, and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking. We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications. SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license. bpeng@mdanderson.org.

High Performance Computing and Cutting-Edge Analysis Can Open New

Science.gov Websites

Realms March 1, 2018 Two people looking at a 3D interactive graphical data the Visualization Center in capabilities to visualize complex, 3D images of the wakes from multiple wind turbines so that we can better

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

An Arctic Ice/Ocean Coupled Model with Wave Interactions

DTIC Science & Technology

2015-09-30

seas within and in the waters adjoining MIZs, using a conservative, multiple wave scattering approach in a medium with random geometrical properties...relating to wave-ice interactions have been collected since the MIZEX campaign of the 1980s, aside from a small number of ad hoc field experiments. This...from the better technology and analysis tools now available, including those related to the field experiments supported by an intensive remote sensing

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

NASA Astrophysics Data System (ADS)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

Education and health and well-being: direct and indirect effects with multiple mediators and interactions with multiple imputed data in Stata.

PubMed

Sheikh, Mashhood Ahmed; Abelsen, Birgit; Olsen, Jan Abel

2017-11-01

Previous methods for assessing mediation assume no multiplicative interactions. The inverse odds weighting (IOW) approach has been presented as a method that can be used even when interactions exist. The substantive aim of this study was to assess the indirect effect of education on health and well-being via four indicators of adult socioeconomic status (SES): income, management position, occupational hierarchy position and subjective social status. 8516 men and women from the Tromsø Study (Norway) were followed for 17 years. Education was measured at age 25-74 years, while SES and health and well-being were measured at age 42-91 years. Natural direct and indirect effects (NIE) were estimated using weighted Poisson regression models with IOW. Stata code is provided that makes it easy to assess mediation in any multiple imputed dataset with multiple mediators and interactions. Low education was associated with lower SES. Consequently, low SES was associated with being unhealthy and having a low level of well-being. The effect (NIE) of education on health and well-being is mediated by income, management position, occupational hierarchy position and subjective social status. This study contributes to the literature on mediation analysis, as well as the literature on the importance of education for health-related quality of life and subjective well-being. The influence of education on health and well-being had different pathways in this Norwegian sample. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments.

PubMed

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E; Rost, Burkhard; Goldberg, Tatyana

2016-11-15

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is 'web ready': written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online. msa@bio.sh. © The Author 2016. Published by Oxford University Press.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments

PubMed Central

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E.; Rost, Burkhard; Goldberg, Tatyana

2016-01-01

Summary: The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. Availability and Implementation: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: msa@bio.sh PMID:27412096

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

NASTRAN data generation of helicopter fuselages using interactive graphics. [preprocessor system for finite element analysis using IBM computer

NASA Technical Reports Server (NTRS)

Sainsbury-Carter, J. B.; Conaway, J. H.

1973-01-01

The development and implementation of a preprocessor system for the finite element analysis of helicopter fuselages is described. The system utilizes interactive graphics for the generation, display, and editing of NASTRAN data for fuselage models. It is operated from an IBM 2250 cathode ray tube (CRT) console driven by an IBM 370/145 computer. Real time interaction plus automatic data generation reduces the nominal 6 to 10 week time for manual generation and checking of data to a few days. The interactive graphics system consists of a series of satellite programs operated from a central NASTRAN Systems Monitor. Fuselage structural models including the outer shell and internal structure may be rapidly generated. All numbering systems are automatically assigned. Hard copy plots of the model labeled with GRID or elements ID's are also available. General purpose programs for displaying and editing NASTRAN data are included in the system. Utilization of the NASTRAN interactive graphics system has made possible the multiple finite element analysis of complex helicopter fuselage structures within design schedules.

Forward-Backward Emission of Target Evaporated Fragments at High Energy Nucleus-Nucleus Collisions

NASA Astrophysics Data System (ADS)

Zhang, Zhi; Ma, Tian-Li; Zhang, Dong-Hai

The multiplicity distribution, multiplicity moments, scaled variance and entropy of target evaporated fragment emitted in forward and backward hemispheres in relativistic heavy ions induced emulsion heavy targets (AgBr) interactions are investigated. It is found that the multiplicity distribution can be fitted by the Gaussian distribution, and the fitting parameters are different between two hemispheres for all the interactions. The multiplicity moment increases with the order of the moment q, and second-order multiplicity moment is energy independent over the entire energy for all the interactions. The scaled variance is close to one for all the interactions. The entropy in forward hemisphere is greater than that in backward hemisphere for all the interactions.

Structural comparison of four different antibodies interacting with human papillomavirus 16 and mechanisms of neutralization

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

Guan, Jian; Bywaters, Stephanie M.; Brendle, Sarah A.

2015-09-15

Cryo-electron microscopy (cryo-EM) was used to solve the structures of human papillomavirus type 16 (HPV16) complexed with fragments of antibody (Fab) from three different neutralizing monoclonals (mAbs): H16.1A, H16.14J, and H263.A2. The structure-function analysis revealed predominantly monovalent binding of each Fab with capsid interactions that involved multiple loops from symmetry related copies of the major capsid protein. The residues identified in each Fab-virus interface map to a conformational groove on the surface of the capsomer. In addition to the known involvement of the FG and HI loops, the DE loop was also found to constitute the core of each epitope.more » Surprisingly, the epitope mapping also identified minor contributions by EF and BC loops. Complementary immunological assays included mAb and Fab neutralization. The specific binding characteristics of mAbs correlated with different neutralizing behaviors in pre- and post-attachment neutralization assays. - Highlights: • We present HPV16-Fab complexes from neutralizing mAbs: H16.1A, H16.14J, and H263.A2. • The structure-function analysis revealed predominantly monovalent binding of each mAb. • Capsid–Fab interactions involved multiple loops from symmetry related L1 proteins. • Besides the known FG and HI loops, epitope mapping also identified DE, EF, and BC loops. • Neutralizing assays complement the structures to show multiple neutralization mechanisms.« less

Elasticity and dislocation anelasticity of crystals

NASA Astrophysics Data System (ADS)

Nikanorov, S. P.; Kardashev, B. K.

The book is concerned with the application of the results of physical acoustic studies of elasticity and dislocation anelasticity to the investigation of interatomic interactions and interactions between lattice defects. The analysis of the potential functions determining the energy of interatomic interactions is based on a study of the elastic properties of crystals over a wide temperature range; data on the dislocation structure and on the interaction between dislocations and point defects are based mainly on a study of inelastic effects. Particular attention is given to the relationship between microplastic effects and the initial stage of plastic deformation under conditions of elastic oscillations, when the multiplication of dislocations is negligible.

Effects of the interaction range on structural phases of flexible polymers.

PubMed

Gross, J; Neuhaus, T; Vogel, T; Bachmann, M

2013-02-21

We systematically investigate how the range of interaction between non-bonded monomers influences the formation of structural phases of elastic, flexible polymers. Massively parallel replica-exchange simulations of a generic, coarse-grained model, performed partly on graphics processing units and in multiple-gaussian modified ensembles, pave the way for the construction of the structural phase diagram, parametrized by interaction range and temperature. Conformational transitions between gas-like, liquid, and diverse solid (pseudo) phases are identified by microcanonical statistical inflection-point analysis. We find evidence for finite-size effects that cause the crossover of "collapse" and "freezing" transitions for very short interaction ranges.

Trophic and Non-Trophic Interactions in a Biodiversity Experiment Assessed by Next-Generation Sequencing

PubMed Central

Tiede, Julia; Wemheuer, Bernd; Traugott, Michael; Daniel, Rolf; Tscharntke, Teja; Ebeling, Anne; Scherber, Christoph

2016-01-01

Plant diversity affects species richness and abundance of taxa at higher trophic levels. However, plant diversity effects on omnivores (feeding on multiple trophic levels) and their trophic and non-trophic interactions are not yet studied because appropriate methods were lacking. A promising approach is the DNA-based analysis of gut contents using next generation sequencing (NGS) technologies. Here, we integrate NGS-based analysis into the framework of a biodiversity experiment where plant taxonomic and functional diversity were manipulated to directly assess environmental interactions involving the omnivorous ground beetle Pterostichus melanarius. Beetle regurgitates were used for NGS-based analysis with universal 18S rDNA primers for eukaryotes. We detected a wide range of taxa with the NGS approach in regurgitates, including organisms representing trophic, phoretic, parasitic, and neutral interactions with P. melanarius. Our findings suggest that the frequency of (i) trophic interactions increased with plant diversity and vegetation cover; (ii) intraguild predation increased with vegetation cover, and (iii) neutral interactions with organisms such as fungi and protists increased with vegetation cover. Experimentally manipulated plant diversity likely affects multitrophic interactions involving omnivorous consumers. Our study therefore shows that trophic and non-trophic interactions can be assessed via NGS to address fundamental questions in biodiversity research. PMID:26859146

Modification and evaluation of a Barnes-type objective analysis scheme for surface meteorological data

NASA Technical Reports Server (NTRS)

Smith, D. R.

1982-01-01

The Purdue Regional Objective Analysis of the Mesoscale (PROAM) is a Barness-type scheme for the analysis of surface meteorological data. Modifications are introduced to the original version in order to increase its flexibility and to permit greater ease of usage. The code was rewritten for an interactive computer environment. Furthermore, a multiple iteration technique suggested by Barnes was implemented for greater accuracy. PROAM was subjected to a series of experiments in order to evaluate its performance under a variety of analysis conditions. The tests include use of a known analytic temperature distribution in order to quantify error bounds for the scheme. Similar experiments were conducted using actual atmospheric data. Results indicate that the multiple iteration technique increases the accuracy of the analysis. Furthermore, the tests verify appropriate values for the analysis parameters in resolving meso-beta scale phenomena.

Exploring contribution of intermolecular interactions in supramolecular layered assembly of naphthyridine co-crystals: Insights from Hirshfeld surface analysis of their crystalline states

NASA Astrophysics Data System (ADS)

Seth, Saikat Kumar; Das, Nirmal Kumar; Aich, Krishnendu; Sen, Debabrata; Fun, Hoong-Kun; Goswami, Shyamaprasad

2013-09-01

Co-crystals of 1a and 1b have been prepared by slow evaporation of the solutions of mixtures of 2,7-dimethyl-1,8-naphthyridine (1), urea (a) and thiourea (b). The structures of the complexes are determined by the single crystal X-ray diffraction and a detailed investigation of the crystal packing and classification of intermolecular interactions is presented by means of Hirshfeld surface analysis which is of considerable current interest in crystal engineering. The X-ray study reveals that the co-crystal formers are envisioned to produce N-H⋯N hydrogen bond as well as N-H⋯O/N-H⋯S pair-wise hydrogen bonds and also the weaker aromatic π⋯π interactions which cooperatively take part in the crystal packing. The recurring feature of the self-assembly in the compounds is the appearance of the molecular ribbon through multiple hydrogen bonding which are further stacked into molecular layers by π⋯π stacking interactions. Hirshfeld surface analysis for visually analyzing intermolecular interactions in crystal structures employing molecular surface contours and 2D Fingerprint plots have been used to examine molecular shapes. Crystal structure analysis supported with the Hirshfeld surface and fingerprint plots enabled the identification of the significant intermolecular interactions.

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W

2017-03-01

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Sequential Exposure of Bortezomib and Vorinostat is Synergistic in Multiple Myeloma Cells

PubMed Central

Nanavati, Charvi; Mager, Donald E.

2018-01-01

Purpose To examine the combination of bortezomib and vorinostat in multiple myeloma cells (U266) and xenografts, and to assess the nature of their potential interactions with semi-mechanistic pharmacodynamic models and biomarkers. Methods U266 proliferation was examined for a range of bortezomib and vorinostat exposure times and concentrations (alone and in combination). A non-competitive interaction model was used with interaction parameters that reflect the nature of drug interactions after simultaneous and sequential exposures. p21 and cleaved PARP were measured using immunoblotting to assess critical biomarker dynamics. For xenografts, data were extracted from literature and modeled with a PK/PD model with an interaction parameter. Results Estimated model parameters for simultaneous in vitro and xenograft treatments suggested additive drug effects. The sequence of bortezomib preincubation for 24 hours, followed by vorinostat for 24 hours, resulted in an estimated interaction term significantly less than 1, suggesting synergistic effects. p21 and cleaved PARP were also up-regulated the most in this sequence. Conclusions Semi-mechanistic pharmacodynamic modeling suggests synergistic pharmacodynamic interactions for the sequential administration of bortezomib followed by vorinostat. Increased p21 and cleaved PARP expression can potentially explain mechanisms of their enhanced effects, which require further PK/PD systems analysis to suggest an optimal dosing regimen. PMID:28101809

W 2 and Q 2 dependence of charged hadron and pion multiplicities in vp andbar vp charged current interactionscharged current interactions

NASA Astrophysics Data System (ADS)

Jones, G. T.; Jones, R. W. L.; Morrison, D. R. O.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hantke, D.; Hoffmann, E.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Allport, P.; Borner, H. P.; Myatt, G.; Radojicic, D.; Bullock, F. W.; Burke, S.

1990-03-01

Using data on vp andbar vp charged current interactions from a bubble chamber experiment with BEBC at CERN, the average multiplicities of charged hadrons and pions are determined as functions of W 2 and Q 2. The analysis is based on ˜20000 events with incident v and ˜10000 events with incidentbar v. In addition to the known dependence of the average multiplicity on W 2 a weak dependence on Q 2 for fixed intervals of W is observed. For W>2 GeV and Q 2>0.1 GeV2 the average multiplicity of charged hadrons is well described by =a 1+ a 2ln( W 2/GeV2)+ a 3ln( Q 2/GeV2) with a 1=0.465±0.053, a 2=1.211±0.021, a 3=0.103±0.014 for the vp and a 1=-0.372±0.073, a 2=1.245±0.028, a 3=0.093±0.015 for thebar vp reaction.

Impact of Multiple Pharmacy Use on Medication Adherence and Drug-drug Interactions in Older Adults with Medicare Part D

PubMed Central

Marcum, Zachary A.; Driessen, Julia; Thorpe, Carolyn T.; Gellad, Walid F.; Donohue, Julie M.

2014-01-01

Objective To assess the association between multiple pharmacy use and medication adherence and potential drug-drug interactions (DDIs) among older adults. Design, Setting, and Participants Cross-sectional propensity score-weighted analysis of 2009 claims data from a nationally representative sample of 926,956 Medicare Part D beneficiaries aged >65 continuously enrolled in fee-for-service Medicare and Part D that year, and filled >1 prescription at a community/retail or mail order pharmacy. Multiple pharmacy use was defined as concurrent (overlapping time periods) or sequential use (non-overlapping time periods) of >2 pharmacies in the year. Measurements Medication adherence was calculated using a proportion of days covered ≥0.80 for eight therapeutic categories (β-blockers, renin angiotensin system antagonists, calcium channel blockers, statins, sulfonylureas, biguanides [i.e., metformin], thiazolidinediones, and dipeptidyl peptidase-IV inhibitors). Potential DDIs arising from use of certain drugs across a broad set of classes were defined as the concurrent filling of two interacting drugs. Results Overall, 38.1% of the sample used multiple pharmacies. Those using multiple pharmacies (both concurrently and sequentially) consistently had higher adjusted odds of non-adherence (ranging from 1.10 to 1.31, p<0.001) across all chronic medication classes assessed after controlling for socio-demographic, health status and access to care factors, compared to single pharmacy users. The adjusted predicted probability of exposure to a DDI was also slightly higher for those using multiple pharmacies concurrently (3.6%) compared to single pharmacy users (3.2%, AOR 1.11, 95% CI 1.08–1.15) but lower in individuals using multiple pharmacies sequentially (2.8%, AOR 0.85, 95% CI 0.81–0.91). Conclusions Filling prescriptions at multiple pharmacies was associated with lower medication adherence across multiple chronic medications, and a small but statistically significant increase in DDIs among concurrent pharmacy users. PMID:24521363

[SYNERGISM OF PRECONCEPTIVE RADIATION EXPOSURE AND PARENTS' ONCO-PATHOLOGY IN THE RISE OF CARCINOGENIC RISK IN THE OFFSPRINGS OF PROFESSIONAL EMPLOYEES].

PubMed

Telnov, V I; Kabirova, N R; Okatenko, P V

2015-01-01

The problem of carcinogenic risk in offsprings of individuals exposed to radiation is challenging and insufficiently studied. In that there are no evaluations of the interaction between radiation and non-radiation factors. The aim of the study was the analysis of interaction of preconceptive radiation exposure and parents' onco-pathology in cancer mortality in offsprings (F1) of workers (fathers) of the Mayak Production Association exposed to a wide range of doses of radiation over a year prior conception. The number of offspring is 8191 individuals (4180 men and 4011 women). The analysis was performed with the use of fourfold table and eightfold tables. The interaction offactors was estimated on the base of the additive and multiplicative models. The studied factors were independent. The odds ratio (OR) of cancer mortality in the offspring with parents' oncopathology (1.43) was insignificant. OR of cancer mortality in preconceptive radiation exposure in a dose over 110 mGy and without parents' onco-pathology was 2.61 (1.52-4.49), and in their combination--3.86 (1.93-7.71). Index of synergism of preconceptive radiation exposure and parents' onco-patholog in the rise of carcinogenic risk in the offspring was 1.34 and the character of their interaction was multiplicative. Thus, for the first time there was established the interaction between radiation and non-radiation factors in the synergism sort in the increase of carcinogenic risk in the offspring of people exposed to radiation.

Modeling of Beams’ Multiple-Contact Mode with an Application in the Design of a High-g Threshold Microaccelerometer

PubMed Central

Li, Kai; Chen, Wenyuan; Zhang, Weiping

2011-01-01

Beam’s multiple-contact mode, characterized by multiple and discrete contact regions, non-uniform stoppers’ heights, irregular contact sequence, seesaw-like effect, indirect interaction between different stoppers, and complex coupling relationship between loads and deformation is studied. A novel analysis method and a novel high speed calculation model are developed for multiple-contact mode under mechanical load and electrostatic load, without limitations on stopper height and distribution, providing the beam has stepped or curved shape. Accurate values of deflection, contact load, contact region and so on are obtained directly, with a subsequent validation by CoventorWare. A new concept design of high-g threshold microaccelerometer based on multiple-contact mode is presented, featuring multiple acceleration thresholds of one sensitive component and consequently small sensor size. PMID:22163897

Proteomic analysis of a model fish species exposed to individual pesticides and a binary mixture

EPA Science Inventory

Aquatic organisms are often exposed to multiple pesticides simultaneously. Due to the relatively poor characterization of mixture constituent interactions and the potential for highly complex exposure scenarios, there is considerable uncertainty in understanding the toxicity of m...

Integrating Human Factors into Space Vehicle Processing for Risk Management

NASA Technical Reports Server (NTRS)

Woodbury, Sarah; Richards, Kimberly J.

2008-01-01

This presentation will discuss the multiple projects performed in United Space Alliance's Human Engineering Modeling and Performance (HEMAP) Lab, improvements that resulted from analysis, and the future applications of the HEMAP Lab for risk assessment by evaluating human/machine interaction and ergonomic designs.

The RSV F and G glycoproteins interact to form a complex on the surface of infected cells

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

Low, Kit-Wei; Tan, Timothy; Ng, Ken

2008-02-08

In this study, the interaction between the respiratory syncytial virus (RSV) fusion (F) protein, attachment (G) protein, and small hydrophobic (SH) proteins was examined. Immunoprecipitation analysis suggested that the F and G proteins exist as a protein complex on the surface of RSV-infected cells, and this conclusion was supported by ultracentrifugation analysis that demonstrated co-migration of surface-expressed F and G proteins. Although our analysis provided evidence for an interaction between the G and SH proteins, no evidence was obtained for a single protein complex involving all three of the virus proteins. These data suggest the existence of multiple virus glycoproteinmore » complexes within the RSV envelope. Although the stimulus that drives RSV-mediated membrane fusion is unknown, the association between the G and F proteins suggest an indirect role for the G protein in this process.« less

Multidimensional joint coupling: a case study visualisation approach to movement coordination and variability.

PubMed

Irwin, Gareth; Kerwin, David G; Williams, Genevieve; Van Emmerik, Richard E A; Newell, Karl M; Hamill, Joseph

2018-06-18

A case study visualisation approach to examining the coordination and variability of multiple interacting segments is presented using a whole-body gymnastic skill as the task example. One elite male gymnast performed 10 trials of 10 longswings whilst three-dimensional locations of joint centres were tracked using a motion analysis system. Segment angles were used to define coupling between the arms and trunk, trunk and thighs and thighs and shanks. Rectified continuous relative phase profiles for each interacting couple for 80 longswings were produced. Graphical representations of coordination couplings are presented that include the traditional single coupling, followed by the relational dynamics of two couplings and finally three couplings simultaneously plotted. This method highlights the power of visualisation of movement dynamics and identifies properties of the global interacting segmental couplings that a more formal analysis may not reveal. Visualisation precedes and informs the appropriate qualitative and quantitative analysis of the dynamics.

Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies.

PubMed

Nettleton, Jennifer A; McKeown, Nicola M; Kanoni, Stavroula; Lemaitre, Rozenn N; Hivert, Marie-France; Ngwa, Julius; van Rooij, Frank J A; Sonestedt, Emily; Wojczynski, Mary K; Ye, Zheng; Tanaka, Tosh; Garcia, Melissa; Anderson, Jennifer S; Follis, Jack L; Djousse, Luc; Mukamal, Kenneth; Papoutsakis, Constantina; Mozaffarian, Dariush; Zillikens, M Carola; Bandinelli, Stefania; Bennett, Amanda J; Borecki, Ingrid B; Feitosa, Mary F; Ferrucci, Luigi; Forouhi, Nita G; Groves, Christopher J; Hallmans, Goran; Harris, Tamara; Hofman, Albert; Houston, Denise K; Hu, Frank B; Johansson, Ingegerd; Kritchevsky, Stephen B; Langenberg, Claudia; Launer, Lenore; Liu, Yongmei; Loos, Ruth J; Nalls, Michael; Orho-Melander, Marju; Renstrom, Frida; Rice, Kenneth; Riserus, Ulf; Rolandsson, Olov; Rotter, Jerome I; Saylor, Georgia; Sijbrands, Eric J G; Sjogren, Per; Smith, Albert; Steingrímsdóttir, Laufey; Uitterlinden, André G; Wareham, Nicholas J; Prokopenko, Inga; Pankow, James S; van Duijn, Cornelia M; Florez, Jose C; Witteman, Jacqueline C M; Dupuis, Josée; Dedoussis, George V; Ordovas, Jose M; Ingelsson, Erik; Cupples, L Adrienne; Siscovick, David S; Franks, Paul W; Meigs, James B

2010-12-01

Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

PubMed Central

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Complementary or competing climates? Examining the interactive effect of service and ethical climates on company-level financial performance.

PubMed

Myer, Adam T; Thoroughgood, Christian N; Mohammed, Susan

2016-08-01

By bending rules to please their customers, companies with high service climates may be less ethical but ultimately more profitable. In this article, we pose the question of whether being ethical comes at a cost to profits in customer-oriented firms. Despite the organizational reality that multiple climates coexist at a given time, research has largely ignored these types of questions, and the simultaneous analysis of multiple climate dimensions has received little empirical attention to date. Given their scientific and practical importance, this study tested complementary and conflicting perspectives regarding interactions between service (outcome-focused) and ethical (process-focused) climates on company-level financial performance. Drawing on a sample of 16,862 medical sales representatives spread across 77 subsidiary companies of a large multinational corporation in the health care product industry, we found support for a complementary view. More precisely, results revealed that profitability was enhanced, not diminished, in service-oriented firms that also stressed the importance of ethics. Results suggest studying the interactive effects of multiple climates is a more fruitful approach than examining main effects alone. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Organizational Justice and Physiological Coronary Heart Disease Risk Factors in Japanese Employees: a Cross-Sectional Study.

PubMed

Inoue, Akiomi; Kawakami, Norito; Eguchi, Hisashi; Miyaki, Koichi; Tsutsumi, Akizumi

2015-12-01

Growing evidence has shown that lack of organizational justice (i.e., procedural justice and interactional justice) is associated with coronary heart disease (CHD) while biological mechanisms underlying this association have not yet been fully clarified. The purpose of the present study was to investigate the cross-sectional association of organizational justice with physiological CHD risk factors (i.e., blood pressure, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein [LDL] cholesterol, and triglyceride) in Japanese employees. Overall, 3598 male and 901 female employees from two manufacturing companies in Japan completed self-administered questionnaires measuring organizational justice, demographic characteristics, and lifestyle factors. They completed health checkup, which included blood pressure and serum lipid measurements. Multiple logistic regression analyses and trend tests were conducted. Among male employees, multiple logistic regression analyses and trend tests showed significant associations of low procedural justice and low interactional justice with high triglyceride (defined as 150 mg/dL or greater) after adjusting for demographic characteristics and lifestyle factors. Among female employees, trend tests showed significant dose-response relationship between low interactional justice and high LDL cholesterol (defined as 140 mg/dL or greater) while multiple logistic regression analysis showed only marginally significant or insignificant odds ratio of high LDL cholesterol among the low interactional justice group. Neither procedural justice nor interactional justice was associated with blood pressure or HDL cholesterol. Organizational justice may be an important psychosocial factor associated with increased triglyceride at least among Japanese male employees.

Quantitative Imaging In Pathology (QUIP) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This site hosts web accessible applications, tools and data designed to support analysis, management, and exploration of whole slide tissue images for cancer research. The following tools are included: caMicroscope: A digital pathology data management and visualization plaform that enables interactive viewing of whole slide tissue images and segmentation results. caMicroscope can be also used independently of QUIP. FeatureExplorer: An interactive tool to allow patient-level feature exploration across multiple dimensions.

Analysis of Multiple Cracks in an Infinite Functionally Graded Plate

NASA Technical Reports Server (NTRS)

Shbeeb, N. I.; Binienda, W. K.; Kreider, K. L.

1999-01-01

A general methodology was constructed to develop the fundamental solution for a crack embedded in an infinite non-homogeneous material in which the shear modulus varies exponentially with the y coordinate. The fundamental solution was used to generate a solution to fully interactive multiple crack problems for stress intensity factors and strain energy release rates. Parametric studies were conducted for two crack configurations. The model displayed sensitivity to crack distance, relative angular orientation, and to the coefficient of nonhomogeneity.

Public-Private Cooperation in the Department of Defense: A Framework for Analysis and Recommendations for Action (Defense Horizons, October 2012)

DTIC Science & Technology

2012-10-01

requirements de - fined by the public sector. CRADAs leverage private sector resources and knowledge to meet the needs of government agencies at no financial...situations helps resolve barriers to cooperation. The evolution of CRA- DAs offers insight into how DOD can interact with multiple partners in a mutually...actions among multiple private power companies, the public sector (at Federal, state, local, and tribal levels), and third parties (hos- pitals

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

A Bayesian Poisson-lognormal Model for Count Data for Multiple-Trait Multiple-Environment Genomic-Enabled Prediction

PubMed Central

Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H.; Montesinos-López, José C.; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat

2017-01-01

When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. PMID:28364037

Double jeopardy: interaction effects of marital and poverty status on the risk of mortality.

PubMed

Smith, K R; Waitzman, N J

1994-08-01

The purpose of this paper is to examine the hypothesis that marital and poverty status interact in their effects on mortality risks beyond their main effects. This study examines the epidemiological bases for applying an additive rather than a multiplicative specification when testing for interaction between two discrete risk factors. We specifically predict that risks associated with being nonmarried and with being poor interact to produce mortality risks that are greater than each risk acting independently. The analysis is based on men and women who were ages 25-74 during the 1971-1975 National Health and Nutrition Examination Survey I (NHANES I) and who were traced successfully in the NHANES I Epidemiologic Follow-Up Study in 1982-1984. Overall, being both poor and nonmarried places nonelderly (ages 25-64) men, but not women, at risk of mortality greater than that expected from the main effects. This study shows that for all-cause mortality, marital and poverty status interact for men but less so for women; these findings exist when interaction is assessed with either a multiplicative or an additive standard. This difference is most pronounced for poor, widowed men and (to a lesser degree) poor, divorced men. For violent/accidental deaths among men, the interaction effects are large on the basis of an additive model. Weak main and interaction effects were detected for the elderly (age 65+).

Biogeographical Analysis of Chemical Co-Occurrence Data to Identify Priorities for Mixtures Research

EPA Science Inventory

A challenge with multiple chemical risk assessment is the need to consider the joint behavior of chemicals in mixtures. To address this need, pharmacologists and toxicologists have developed methods over the years to evaluate and test chemical interaction. In practice, however, t...

Latino Adolescents' Academic Motivation: The Role of Siblings

ERIC Educational Resources Information Center

Alfaro, Edna C.; Umana-Taylor, Adriana J.

2010-01-01

Guided by an ecological perspective, two competing models were tested to examine how sibling relationship quality directly predicted or interacted with academic support from siblings to predict Latino adolescents' academic motivation (N = 258). Gender differences were examined utilizing multiple group analysis in structural equation modeling.…

Integrated Analysis of Genetic and Proteomic Data Identifies Biomarkers Associated with Adverse Events Following Smallpox Vaccination

EPA Science Inventory

Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experi...

Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

PubMed

Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

2017-07-21

Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

TIGER: Turbomachinery interactive grid generation

NASA Technical Reports Server (NTRS)

Soni, Bharat K.; Shih, Ming-Hsin; Janus, J. Mark

1992-01-01

A three dimensional, interactive grid generation code, TIGER, is being developed for analysis of flows around ducted or unducted propellers. TIGER is a customized grid generator that combines new technology with methods from general grid generation codes. The code generates multiple block, structured grids around multiple blade rows with a hub and shroud for either C grid or H grid topologies. The code is intended for use with a Euler/Navier-Stokes solver also being developed, but is general enough for use with other flow solvers. TIGER features a silicon graphics interactive graphics environment that displays a pop-up window, graphics window, and text window. The geometry is read as a discrete set of points with options for several industrial standard formats and NASA standard formats. Various splines are available for defining the surface geometries. Grid generation is done either interactively or through a batch mode operation using history files from a previously generated grid. The batch mode operation can be done either with a graphical display of the interactive session or with no graphics so that the code can be run on another computer system. Run time can be significantly reduced by running on a Cray-YMP.

ITA, a portable program for the interactive analysis of data from tracer experiments

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

Wootton, R.; Ashley, K.

ITA is a portable program for analyzing data from tracer experiments, most of the mathematical and graphical work being carried out by subroutines from the NAG and DASL libraries. The program can be used in batch or interactive mode, commands being typed in an English-like language, in free format. Data can be entered from a terminal keyboard or read from a file, and can be validated by printing or plotting them. Erroneous values can be corrected by appropriate editing. Analysis can involve elementary statistics, multiple-isotope crossover corrections, convolution or deconvolution, polyexponential curve-fitting, spline interpolation and/or compartmental analysis. On those installationsmore » with the appropriate hardware, high-resolution graphs can be drawn.« less

Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

Rapid and sensitive MRM-based mass spectrometry approach for systematically exploring ganglioside-protein interactions.

PubMed

Tian, Ruijun; Jin, Jing; Taylor, Lorne; Larsen, Brett; Quaggin, Susan E; Pawson, Tony

2013-04-01

Gangliosides are ubiquitous components of cell membranes. Their interactions with bacterial toxins and membrane-associated proteins (e.g. receptor tyrosine kinases) have important roles in the regulation of multiple cellular functions. Currently, an effective approach for measuring ganglioside-protein interactions especially in a large-scale fashion is largely missing. To this end, we report a facile MS-based approach to explore gangliosides extracted from cells and measure their interactions with protein of interest globally. We optimized a two-step protocol for extracting total gangliosides from cells within 2 h. Easy-to-use magnetic beads conjugated with a protein of interest were used to capture interacting gangliosides. To measure ganglioside-protein interaction on a global scale, we applied a high-sensitive LC-MS system, containing hydrophilic interaction LC separation and multiple reaction monitoring-based MS for ganglioside detection. Sensitivity for ganglioside GM1 is below 100 pg, and the whole analysis can be done in 20 min with isocratic elution. To measure ganglioside interactions with soluble vascular endothelial growth factor receptor 1 (sFlt1), we extracted and readily detected 36 species of gangliosides from perivascular retinal pigment epithelium cells across eight different classes. Twenty-three ganglioside species have significant interactions with sFlt1 as compared with IgG control based on p value cutoff <0.05. These results show that the described method provides a rapid and high-sensitive approach for systematically measuring ganglioside-protein interactions. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computation of energy interaction parameters as well as electric dipole intensity parameters for the absorption spectral study of the interaction of Pr(III) with L-phenylalanine, L-glycine, L-alanine and L-aspartic acid in the presence and absence of Ca 2+ in organic solvents

NASA Astrophysics Data System (ADS)

Moaienla, T.; Singh, Th. David; Singh, N. Rajmuhon; Devi, M. Indira

2009-10-01

Studying the absorption difference and comparative absorption spectra of the interaction of Pr(III) and Nd(III) with L-phenylalanine, L-glycine, L-alanine and L-aspartic acid in the presence and absence of Ca 2+ in organic solvents, various energy interaction parameters like Slater-Condon ( FK), Racah ( Ek), Lande factor ( ξ4f), nephelauxetic ratio ( β), bonding ( b1/2), percentage-covalency ( δ) have been evaluated applying partial and multiple regression analysis. The values of oscillator strength ( P) and Judd-Ofelt electric dipole intensity parameter Tλ ( λ = 2, 4, 6) for different 4f-4f transitions have been computed. On analysis of the variation of the various energy interaction parameters as well as the changes in the oscillator strength ( P) and Tλ values reveal the mode of binding with different ligands.

Analysis of a Near Field MIMO Wireless Channel Using 5.6 GHz Dipole Antennas

NASA Astrophysics Data System (ADS)

Maricar, Mohamed Ismaeel; Gradoni, Gabriele; Greedy, Steve; Ivrlac, Michel T.; Nossek, Josef A.; Phang, Sendy; Creagh, Stephen C.; Tanner, Gregor; Thomas, David W. P.

2016-05-01

Understanding the impact of interference upon the performance of a multiple input multiple output (MIMO) based device is of paramount importance in ensuring a design is both resilient and robust. In this work the effect of element-element interference in the creation of multiple channels of a wireless link approaching the near-field regime is studied. The elements of the 2-antenna transmit- and receive-arrays are chosen to be identical folded dipole antennas operating at 5.6 GHz. We find that two equally strong channels can be created even if the antennas interact at sub-wavelength distances, thus confirming previous theoretical predictions.

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

The Experience of Persons With Multiple Sclerosis Using MS INFoRm: An Interactive Fatigue Management Resource.

PubMed

Pétrin, Julie; Akbar, Nadine; Turpin, Karen; Smyth, Penelope; Finlayson, Marcia

2018-04-01

We aimed to understand participants' experiences with a self-guided fatigue management resource, Multiple Sclerosis: An Interactive Fatigue Management Resource ( MS INFoRm), and the extent to which they found its contents relevant and useful to their daily lives. We recruited 35 persons with MS experiencing mild to moderate fatigue, provided them with MS INFoRm, and then conducted semistructured interviews 3 weeks and 3 months after they received the resource. Interpretive description guided the analysis process. Findings indicate that participants' experience of using MS INFoRm could be understood as a process of change, influenced by their initial reactions to the resource. They reported experiencing a shift in knowledge, expectations, and behaviors with respect to fatigue self-management. These shifts led to multiple positive outcomes, including increased levels of self-confidence and improved quality of life. These findings suggest that MS INFoRm may have a place in the continuum of fatigue management interventions for people with MS.

Transition of Femtosecond-Filament-Solid Interactions from Single to Multiple Filament Regime

DOE PAGES

Skrodzki, P. J.; Burger, M.; Jovanovic, I.

2017-10-06

High-peak-power fs-laser filaments offer unique characteristics attractive to remote sensing via techniques such as remote laser-induced breakdown spectroscopy (R-LIBS). The dynamics of several ablation mechanisms following the interaction between a filament and a solid determines the emission strength and reproducibility of target plasma, which is of relevance for R-LIBS applications. Here, we investigate the space- and time-resolved dynamics of ionic and atomic emission from copper as well as the surrounding atmosphere in order to understand limitations of fs-filament-ablation for standoff energy delivery. Furthermore, we probe the shock front produced from filament-target interaction using time-resolved shadowgraphy and infer laser-material coupling efficienciesmore » for both single and multiple filament regimes through analysis of shock expansion with the Sedov model for point detonation. The results provide insight into plasma structure for the range of peak powers up to 30 times the critical power for filamentation P cr. Despite the stochastic nucleation of multiple filaments at peak-powers greater than 16 P cr, emission of ionic and neutral species increases with pump beam intensity, and short-lived nitrogen emission originating from the ambient is consistently observed. Ultimately, results suggest favorable scaling of emission intensity from target species on the laser pump energy, furthering the prospects for use of filament-solid interactions for remote sensing.« less

Transition of Femtosecond-Filament-Solid Interactions from Single to Multiple Filament Regime

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

Skrodzki, P. J.; Burger, M.; Jovanovic, I.

High-peak-power fs-laser filaments offer unique characteristics attractive to remote sensing via techniques such as remote laser-induced breakdown spectroscopy (R-LIBS). The dynamics of several ablation mechanisms following the interaction between a filament and a solid determines the emission strength and reproducibility of target plasma, which is of relevance for R-LIBS applications. Here, we investigate the space- and time-resolved dynamics of ionic and atomic emission from copper as well as the surrounding atmosphere in order to understand limitations of fs-filament-ablation for standoff energy delivery. Furthermore, we probe the shock front produced from filament-target interaction using time-resolved shadowgraphy and infer laser-material coupling efficienciesmore » for both single and multiple filament regimes through analysis of shock expansion with the Sedov model for point detonation. The results provide insight into plasma structure for the range of peak powers up to 30 times the critical power for filamentation P cr. Despite the stochastic nucleation of multiple filaments at peak-powers greater than 16 P cr, emission of ionic and neutral species increases with pump beam intensity, and short-lived nitrogen emission originating from the ambient is consistently observed. Ultimately, results suggest favorable scaling of emission intensity from target species on the laser pump energy, furthering the prospects for use of filament-solid interactions for remote sensing.« less

Analysis of components of variance in multiple-reader studies of computer-aided diagnosis with different tasks

NASA Astrophysics Data System (ADS)

Beiden, Sergey V.; Wagner, Robert F.; Campbell, Gregory; Metz, Charles E.; Chan, Heang-Ping; Nishikawa, Robert M.; Schnall, Mitchell D.; Jiang, Yulei

2001-06-01

In recent years, the multiple-reader, multiple-case (MRMC) study paradigm has become widespread for receiver operating characteristic (ROC) assessment of systems for diagnostic imaging and computer-aided diagnosis. We review how MRMC data can be analyzed in terms of the multiple components of the variance (case, reader, interactions) observed in those studies. Such information is useful for the design of pivotal studies from results of a pilot study and also for studying the effects of reader training. Recently, several of the present authors have demonstrated methods to generalize the analysis of multiple variance components to the case where unaided readers of diagnostic images are compared with readers who receive the benefit of a computer assist (CAD). For this case it is necessary to model the possibility that several of the components of variance might be reduced when readers incorporate the computer assist, compared to the unaided reading condition. We review results of this kind of analysis on three previously published MRMC studies, two of which were applications of CAD to diagnostic mammography and one was an application of CAD to screening mammography. The results for the three cases are seen to differ, depending on the reader population sampled and the task of interest. Thus, it is not possible to generalize a particular analysis of variance components beyond the tasks and populations actually investigated.

Position Affects Performance in Multiple-Object Tracking in Rugby Union Players

PubMed Central

Martín, Andrés; Sfer, Ana M.; D'Urso Villar, Marcela A.; Barraza, José F.

2017-01-01

We report an experiment that examines the performance of rugby union players and a control group composed of graduate student with no sport experience, in a multiple-object tracking task. It compares the ability of 86 high level rugby union players grouped as Backs and Forwards and the control group, to track a subset of randomly moving targets amongst the same number of distractors. Several difficulties were included in the experimental design in order to evaluate possible interactions between the relevant variables. Results show that the performance of the Backs is better than that of the other groups, but the occurrence of interactions precludes an isolated groups analysis. We interpret the results within the framework of visual attention and discuss both, the implications of our results and the practical consequences. PMID:28951725

Interaction of pulsating and spinning waves in condensed phase combustion

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

Booty, M.R.; Margolis, S.B.; Matkowsky, B.J.

1986-10-01

The authors employ a nonlinear stability analysis in the neighborhood of a multiple bifurcation point to describe the interaction of pulsating and spinning modes of condensed phase combustion. Such phenomena occur in the synthesis of refractory materials. In particular, they consider the propagation of combustion waves in a long thermally insulated cylindrical sample and show that steady, planar combustion is stable for a modified activation energy/melting parameter less than a critical value. Above this critical value primary bifurcation states, corresponding to time-periodic pulsating and spinning modes of combustion, emanate from the steadily propagating solution. By varying the sample radius, themore » authors split a multiple bifurcation point to obtain bifurcation diagrams which exhibit secondary, tertiary, and quarternary branching to various types of quasi-periodic combustion waves.« less

Multiplicity of Charged Particles in Pion - Nucleus Interactions in an Emulsion at 200-GeV/c

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

Anzon, Z.V.; Gaitinov, A.Sh.; Eremenko, L.E.

1977-01-01

The experimental data on multiplicities of charged secondaries produced in pion-nucleus interactions in an emulsion at 200 Gev/c and correlations bet6ween them are presented and discussed. Parameters of multiplicity distributions are compared with the relevant ones at lower energies and with data from pA-interactions at 200 Gev/c. The multiplicity of heavily ionizing particles in {Pi}{sup -}A-interactions weakly depend on the incident energy. The KNO scaling is observed being the same for incident protons and pions.

A Simple Tool for the Design and Analysis of Multiple-Reflector Antennas in a Multi-Disciplinary Environment

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Cwik, Tom; Fu, Chuigang; Imbriale, William A.; Jamnejad, Vahraz; Springer, Paul L.; Borgioli, Andrea

2000-01-01

The process of designing and analyzing a multiple-reflector system has traditionally been time-intensive, requiring large amounts of both computational and human time. At many frequencies, a discrete approximation of the radiation integral may be used to model the system. The code which implements this physical optics (PO) algorithm was developed at the Jet Propulsion Laboratory. It analyzes systems of antennas in pairs, and for each pair, the analysis can be computationally time-consuming. Additionally, the antennas must be described using a local coordinate system for each antenna, which makes it difficult to integrate the design into a multi-disciplinary framework in which there is traditionally one global coordinate system, even before considering deforming the antenna as prescribed by external structural and/or thermal factors. Finally, setting up the code to correctly analyze all the antenna pairs in the system can take a fair amount of time, and introduces possible human error. The use of parallel computing to reduce the computational time required for the analysis of a given pair of antennas has been previously discussed. This paper focuses on the other problems mentioned above. It will present a methodology and examples of use of an automated tool that performs the analysis of a complete multiple-reflector system in an integrated multi-disciplinary environment (including CAD modeling, and structural and thermal analysis) at the click of a button. This tool, named MOD Tool (Millimeter-wave Optics Design Tool), has been designed and implemented as a distributed tool, with a client that runs almost identically on Unix, Mac, and Windows platforms, and a server that runs primarily on a Unix workstation and can interact with parallel supercomputers with simple instruction from the user interacting with the client.

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

Toshiba TDF-500 High Resolution Viewing And Analysis System

NASA Astrophysics Data System (ADS)

Roberts, Barry; Kakegawa, M.; Nishikawa, M.; Oikawa, D.

1988-06-01

A high resolution, operator interactive, medical viewing and analysis system has been developed by Toshiba and Bio-Imaging Research. This system provides many advanced features including high resolution displays, a very large image memory and advanced image processing capability. In particular, the system provides CRT frame buffers capable of update in one frame period, an array processor capable of image processing at operator interactive speeds, and a memory system capable of updating multiple frame buffers at frame rates whilst supporting multiple array processors. The display system provides 1024 x 1536 display resolution at 40Hz frame and 80Hz field rates. In particular, the ability to provide whole or partial update of the screen at the scanning rate is a key feature. This allows multiple viewports or windows in the display buffer with both fixed and cine capability. To support image processing features such as windowing, pan, zoom, minification, filtering, ROI analysis, multiplanar and 3D reconstruction, a high performance CPU is integrated into the system. This CPU is an array processor capable of up to 400 million instructions per second. To support the multiple viewer and array processors' instantaneous high memory bandwidth requirement, an ultra fast memory system is used. This memory system has a bandwidth capability of 400MB/sec and a total capacity of 256MB. This bandwidth is more than adequate to support several high resolution CRT's and also the fast processing unit. This fully integrated approach allows effective real time image processing. The integrated design of viewing system, memory system and array processor are key to the imaging system. It is the intention to describe the architecture of the image system in this paper.

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Effects of Writing Instruction on Kindergarten Students' Writing Achievement: An Experimental Study

ERIC Educational Resources Information Center

Jones, Cindy D'On

2015-01-01

This full-year experimental study examined how methods of writing instruction contribute to kindergarten students' acquisition of foundational and compositional early writing skills. Multiple regression with cluster analysis was used to compare 3 writing instructional groups: an interactive writing group, a writing workshop group, and a…

Scaffolding the Communication of People with Congenital Deafblindness: An Analysis of Sequential Interaction Patterns

ERIC Educational Resources Information Center

Damen, Saskia; Janssen, Marleen J.; Ruijssenaars, Wied A. J. J. M.; Schuengel, Carlo

2017-01-01

The High Quality Communication intervention aims to stimulate interpersonal communication between individuals with congenital deaf-blindness (CDB) and their social partners. Found effective in multiple-case experiments, the intervention is based on Trevarthen's theory of intersubjective development (Bråten & Trevarthen, 2007), which describes…

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

PubMed

McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

2012-04-01

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. Copyright © 2011 Elsevier Inc. All rights reserved.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

PubMed Central

McGuire, Mary F.; Iyengar, M. Sriram; Mercer, David W.

2012-01-01

Motivation Although trauma is the leading cause of death for those below 45 years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. Results In the node/molecular analysis of the first 24 hours from trauma, PSA uncovered 7 molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which 3 molecules had not been previously associated with any shock / trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships – activation, expression, inhibition, and transcription – and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship. PMID:22200681

Multiple brain atlas database and atlas-based neuroimaging system.

PubMed

Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

1997-01-01

For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

An Integrated Nursing Management Information System: From Concept to Reality

PubMed Central

Pinkley, Connie L.; Sommer, Patricia K.

1988-01-01

This paper addresses the transition from the conceptualization of a Nursing Management Information System (NMIS) integrated and interdependent with the Hospital Information System (HIS) to its realization. Concepts of input, throughout, and output are presented to illustrate developmental strategies used to achieve nursing information products. Essential processing capabilities include: 1) ability to interact with multiple data sources; 2) database management, statistical, and graphics software packages; 3) online, batch and reporting; and 4) interactive data analysis. Challenges encountered in system construction are examined.

Ready, willing, and able to divorce: an economic and cultural history of divorce in twentieth-century Sweden.

PubMed

Simonsson, Per; Sandström, Glenn

2011-01-01

This study outlines a long history of divorce in Sweden, recognizing the importance of considering both economic and cultural factors in the analysis of marital dissolution. Following Ansley Coale, the authors examine how a framework of multiple theoretical constructs, in interaction, can be applied to the development toward mass divorce. Applying a long historical perspective, the authors argue that an analysis of gendered aspects of the interaction between culture and economics is crucial for the understanding of the rise of mass divorce. The empirical analysis finds support for a marked decrease in legal and cultural obstacles to divorce already during the first decades of the twentieth century. However, economic structures remained a severe obstacle that prohibited significant increases in divorce rate prior to World War II. It was only during the 1940s and 1960s, when cultural change was complemented by marked decreases in economic interdependence between spouses, that the divorce rate exhibited significant increases. The authors find that there are advantages to looking at the development of divorce as a history in which multiple empirical factors are examined in conjunction, recognizing that these factors played different roles during different time periods.

Comparison of $$\

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

Adams, C.; et al.

We measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab. We evaluate three neutrino interaction models based on the widely used GENIE event generator using these observables. The measurement uses a data set consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2016 with the Fermilab Booster Neutrino Beam, which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic eventmore » selection and charged particle track reconstruction and uses a data-driven technique to separate neutrino interactions from cosmic ray background events. We find that GENIE models consistently describe the shapes of a large number of kinematic distributions for fixed observed multiplicity, but we show an indication that the observed multiplicity fractions deviate from GENIE expectations.« less

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

PubMed Central

Hu, Jianfei; Neiswinger, Johnathan; Zhang, Jin; Zhu, Heng; Qian, Jiang

2015-01-01

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process. PMID:26393507

A web server for analysis, comparison and prediction of protein ligand binding sites.

PubMed

Singh, Harinder; Srivastava, Hemant Kumar; Raghava, Gajendra P S

2016-03-25

One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. In order to address this problem, we developed a web server named 'LPIcom' to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the "LPIcom' server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom .

Functional importance of different patterns of correlation between adjacent cassette exons in human and mouse.

PubMed

Peng, Tao; Xue, Chenghai; Bi, Jianning; Li, Tingting; Wang, Xiaowo; Zhang, Xuegong; Li, Yanda

2008-04-26

Alternative splicing expands transcriptome diversity and plays an important role in regulation of gene expression. Previous studies focus on the regulation of a single cassette exon, but recent experiments indicate that multiple cassette exons within a gene may interact with each other. This interaction can increase the potential to generate various transcripts and adds an extra layer of complexity to gene regulation. Several cases of exon interaction have been discovered. However, the extent to which the cassette exons coordinate with each other remains unknown. Based on EST data, we employed a metric of correlation coefficients to describe the interaction between two adjacent cassette exons and then categorized these exon pairs into three different groups by their interaction (correlation) patterns. Sequence analysis demonstrates that strongly-correlated groups are more conserved and contain a higher proportion of pairs with reading frame preservation in a combinatorial manner. Multiple genome comparison further indicates that different groups of correlated pairs have different evolutionary courses: (1) The vast majority of positively-correlated pairs are old, (2) most of the weakly-correlated pairs are relatively young, and (3) negatively-correlated pairs are a mixture of old and young events. We performed a large-scale analysis of interactions between adjacent cassette exons. Compared with weakly-correlated pairs, the strongly-correlated pairs, including both the positively and negatively correlated ones, show more evidence that they are under delicate splicing control and tend to be functionally important. Additionally, the positively-correlated pairs bear strong resemblance to constitutive exons, which suggests that they may evolve from ancient constitutive exons, while negatively and weakly correlated pairs are more likely to contain newly emerging exons.

Genome-wide analysis of epistasis in body mass index using multiple human populations.

PubMed

Wei, Wen-Hua; Hemani, Gib; Gyenesei, Attila; Vitart, Veronique; Navarro, Pau; Hayward, Caroline; Cabrera, Claudia P; Huffman, Jennifer E; Knott, Sara A; Hicks, Andrew A; Rudan, Igor; Pramstaller, Peter P; Wild, Sarah H; Wilson, James F; Campbell, Harry; Hastie, Nicholas D; Wright, Alan F; Haley, Chris S

2012-08-01

We surveyed gene-gene interactions (epistasis) in human body mass index (BMI) in four European populations (n<1200) via exhaustive pair-wise genome scans where interactions were computed as F ratios by testing a linear regression model fitting two single-nucleotide polymorphisms (SNPs) with interactions against the one without. Before the association tests, BMI was corrected for sex and age, normalised and adjusted for relatedness. Neither single SNPs nor SNP interactions were genome-wide significant in either cohort based on the consensus threshold (P=5.0E-08) and a Bonferroni corrected threshold (P=1.1E-12), respectively. Next we compared sub genome-wide significant SNP interactions (P<5.0E-08) across cohorts to identify common epistatic signals, where SNPs were annotated to genes to test for gene ontology (GO) enrichment. Among the epistatic genes contributing to the commonly enriched GO terms, 19 were shared across study cohorts of which 15 are previously published genome-wide association loci, including CDH13 (cadherin 13) associated with height and SORCS2 (sortilin-related VPS10 domain containing receptor 2) associated with circulating insulin-like growth factor 1 and binding protein 3. Interactions between the 19 shared epistatic genes and those involving BMI candidate loci (P<5.0E-08) were tested across cohorts and found eight replicated at the SNP level (P<0.05) in at least one cohort, which were further tested and showed limited replication in a separate European population (n>5000). We conclude that genome-wide analysis of epistasis in multiple populations is an effective approach to provide new insights into the genetic regulation of BMI but requires additional efforts to confirm the findings.

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.

Local interaction strategies and capacity for better care in nursing homes: a multiple case study

PubMed Central

2014-01-01

Background To describe relationship patterns and management practices in nursing homes (NHs) that facilitate or pose barriers to better outcomes for residents and staff. Methods We conducted comparative, multiple-case studies in selected NHs (N = 4). Data were collected over six months from managers and staff (N = 406), using direct observations, interviews, and document reviews. Manifest content analysis was used to identify and explore patterns within and between cases. Results Participants described interaction strategies that they explained could either degrade or enhance their capacity to achieve better outcomes for residents; people in all job categories used these ‘local interaction strategies’. We categorized these two sets of local interaction strategies as the ‘common pattern’ and the ‘positive pattern’ and summarize the results in two models of local interaction. Conclusions The findings suggest the hypothesis that when staff members in NHs use the set of positive local interaction strategies, they promote inter-connections, information exchange, and diversity of cognitive schema in problem solving that, in turn, create the capacity for delivering better resident care. We propose that these positive local interaction strategies are a critical driver of care quality in NHs. Our hypothesis implies that, while staffing levels and skill mix are important factors for care quality, improvement would be difficult to achieve if staff members are not engaged with each other in these ways. PMID:24903706

A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing.

PubMed

Schwertner, Ryan W; Garand, Kendrea L; Pearson, William G

2016-01-01

Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data.

A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing

PubMed Central

Schwertner, Ryan W.; Garand, Kendrea L.; Pearson, William G.

2016-01-01

Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data. PMID:28239682

CASAS: Cancer Survival Analysis Suite, a web based application

PubMed Central

Rupji, Manali; Zhang, Xinyan; Kowalski, Jeanne

2017-01-01

We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/. PMID:28928946

CASAS: Cancer Survival Analysis Suite, a web based application.

PubMed

Rupji, Manali; Zhang, Xinyan; Kowalski, Jeanne

2017-01-01

We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/.

Is there a link between the hospital-acquired injurious fall rates in US acute care hospitals and these institutions' implementation levels of computerized systems?

PubMed

Tzeng, Huey-Ming; Hu, Hsou Mei; Yin, Chang-Yi

2011-12-01

Medicare no longer reimburses acute care hospitals for the costs of additional care required due to hospital-acquired injuries. Consequently, this study explored the effective computerized systems to inform practice for better interventions to reduce fall risk. It provided a correlation between type of computerized system and hospital-acquired injurious fall rates at acute care hospitals in California, Florida, and New York. It used multiple publicly available data sets, with the hospital as the unit of analysis. Descriptive and Pearson correlation analyses were used. The analysis included 462 hospitals. Significant correlations could be categorized into two groups: (1) meaningful computerized systems that were associated with lower injurious fall rates: the decision support systems for drug allergy alerts, drug-drug interaction alerts, and drug-laboratory interaction alerts; and (2) computerized systems that were associated with higher injurious fall rates: the decision support system for drug-drug interaction alerts and the computerized provider order entry system for radiology tests. Future research may include additional states, multiple years of data, and patient-level data to validate this study's findings. This effort may further inform policy makers and the public about effective clinical computerized systems provided to clinicians to improve their practice decisions and care outcomes.

How much do we know about the coupling of G-proteins to serotonin receptors?

PubMed Central

2014-01-01

Serotonin receptors are G-protein-coupled receptors (GPCRs) involved in a variety of psychiatric disorders. G-proteins, heterotrimeric complexes that couple to multiple receptors, are activated when their receptor is bound by the appropriate ligand. Activation triggers a cascade of further signalling events that ultimately result in cell function changes. Each of the several known G-protein types can activate multiple pathways. Interestingly, since several G-proteins can couple to the same serotonin receptor type, receptor activation can result in induction of different pathways. To reach a better understanding of the role, interactions and expression of G-proteins a literature search was performed in order to list all the known heterotrimeric combinations and serotonin receptor complexes. Public databases were analysed to collect transcript and protein expression data relating to G-proteins in neural tissues. Only a very small number of heterotrimeric combinations and G-protein-receptor complexes out of the possible thousands suggested by expression data analysis have been examined experimentally. In addition this has mostly been obtained using insect, hamster, rat and, to a lesser extent, human cell lines. Besides highlighting which interactions have not been explored, our findings suggest additional possible interactions that should be examined based on our expression data analysis. PMID:25011628

How much do we know about the coupling of G-proteins to serotonin receptors?

PubMed

Giulietti, Matteo; Vivenzio, Viviana; Piva, Francesco; Principato, Giovanni; Bellantuono, Cesario; Nardi, Bernardo

2014-07-10

Serotonin receptors are G-protein-coupled receptors (GPCRs) involved in a variety of psychiatric disorders. G-proteins, heterotrimeric complexes that couple to multiple receptors, are activated when their receptor is bound by the appropriate ligand. Activation triggers a cascade of further signalling events that ultimately result in cell function changes. Each of the several known G-protein types can activate multiple pathways. Interestingly, since several G-proteins can couple to the same serotonin receptor type, receptor activation can result in induction of different pathways. To reach a better understanding of the role, interactions and expression of G-proteins a literature search was performed in order to list all the known heterotrimeric combinations and serotonin receptor complexes. Public databases were analysed to collect transcript and protein expression data relating to G-proteins in neural tissues. Only a very small number of heterotrimeric combinations and G-protein-receptor complexes out of the possible thousands suggested by expression data analysis have been examined experimentally. In addition this has mostly been obtained using insect, hamster, rat and, to a lesser extent, human cell lines. Besides highlighting which interactions have not been explored, our findings suggest additional possible interactions that should be examined based on our expression data analysis.

Multiple sclerosis patients need and want information on exercise promotion from healthcare providers: a qualitative study.

PubMed

Learmonth, Yvonne C; Adamson, Brynn C; Balto, Julia M; Chiu, Chung-Yi; Molina-Guzman, Isabel; Finlayson, Marcia; Riskin, Barry J; Motl, Robert W

2017-08-01

There is growing recognition of the benefits and safety of exercise and its importance in the comprehensive care of persons with multiple sclerosis (MS), yet uptake is low. We explored the needs and wants of patients with MS regarding exercise promotion through healthcare providers. Participants were adults with MS who had mild-or-moderate disability and a range of exercise levels. All participants lived in the Midwest of the United States. Fifty semi-structured interviews were conducted and analysed using thematic analysis. Two themes emerged, namely interactions between patients and healthcare providers and needs and wants of patients. Analysis of participant accounts illustrate that current exercise promotion by healthcare providers does not meet patient needs and wants. The identified needs and wants of persons with MS involved (i) information and knowledge on the benefits of exercise and exercise prescription, (ii) materials to allow home and community exercise and (iii) tools for initiating and maintaining exercise behaviour. Patients with MS frequently interact with healthcare providers and are generally unsatisfied with exercise promotion during interactions. Healthcare providers can address the low uptake of exercise among persons with MS by acting upon the identified unmet needs involving materials, knowledge and behaviour change strategies for exercise. © 2016 The Authors Health Expectations Published by John Wiley & Sons Ltd.

Multi-Harmony: detecting functional specificity from sequence alignment

PubMed Central

Brandt, Bernd W.; Feenstra, K. Anton; Heringa, Jaap

2010-01-01

Many protein families contain sub-families with functional specialization, such as binding different ligands or being involved in different protein–protein interactions. A small number of amino acids generally determine functional specificity. The identification of these residues can aid the understanding of protein function and help finding targets for experimental analysis. Here, we present multi-Harmony, an interactive web sever for detecting sub-type-specific sites in proteins starting from a multiple sequence alignment. Combining our Sequence Harmony (SH) and multi-Relief (mR) methods in one web server allows simultaneous analysis and comparison of specificity residues; furthermore, both methods have been significantly improved and extended. SH has been extended to cope with more than two sub-groups. mR has been changed from a sampling implementation to a deterministic one, making it more consistent and user friendly. For both methods Z-scores are reported. The multi-Harmony web server produces a dynamic output page, which includes interactive connections to the Jalview and Jmol applets, thereby allowing interactive analysis of the results. Multi-Harmony is available at http://www.ibi.vu.nl/ programs/shmrwww. PMID:20525785

Conservation of tubulin-binding sequences in TRPV1 throughout evolution.

PubMed

Sardar, Puspendu; Kumar, Abhishek; Bhandari, Anita; Goswami, Chandan

2012-01-01

Transient Receptor Potential Vanilloid sub type 1 (TRPV1), commonly known as capsaicin receptor can detect multiple stimuli ranging from noxious compounds, low pH, temperature as well as electromagnetic wave at different ranges. In addition, this receptor is involved in multiple physiological and sensory processes. Therefore, functions of TRPV1 have direct influences on adaptation and further evolution also. Availability of various eukaryotic genomic sequences in public domain facilitates us in studying the molecular evolution of TRPV1 protein and the respective conservation of certain domains, motifs and interacting regions that are functionally important. Using statistical and bioinformatics tools, our analysis reveals that TRPV1 has evolved about ∼420 million years ago (MYA). Our analysis reveals that specific regions, domains and motifs of TRPV1 has gone through different selection pressure and thus have different levels of conservation. We found that among all, TRP box is the most conserved and thus have functional significance. Our results also indicate that the tubulin binding sequences (TBS) have evolutionary significance as these stretch sequences are more conserved than many other essential regions of TRPV1. The overall distribution of positively charged residues within the TBS motifs is conserved throughout evolution. In silico analysis reveals that the TBS-1 and TBS-2 of TRPV1 can form helical structures and may play important role in TRPV1 function. Our analysis identifies the regions of TRPV1, which are important for structure-function relationship. This analysis indicates that tubulin binding sequence-1 (TBS-1) near the TRP-box forms a potential helix and the tubulin interactions with TRPV1 via TBS-1 have evolutionary significance. This interaction may be required for the proper channel function and regulation and may also have significance in the context of Taxol®-induced neuropathy.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

PubMed

Li, Yafang; Xiao, Xiangjun; Han, Younghun; Gorlova, Olga; Qian, David; Leighl, Natasha; Johansen, Jakob S; Barnett, Matt; Chen, Chu; Goodman, Gary; Cox, Angela; Taylor, Fiona; Woll, Penella; Wichmann, H-Erich; Manz, Judith; Muley, Thomas; Risch, Angela; Rosenberger, Albert; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Houlston, Richard; Soler Artigas, María; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Liu, Geoffrey; Bojesen, Stig E; Wu, Xifeng; Marchand, Loic Le; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Bertazzi, Pier Alberto; Pesatori, Angela C; Christiani, David C; Caporaso, Neil; Johansson, Mattias; McKay, James D; Brennan, Paul; Hung, Rayjean J; Amos, Christopher I

2018-03-08

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

Effects of threat management interactions on conservation priorities.

PubMed

Auerbach, Nancy A; Wilson, Kerrie A; Tulloch, Ayesha I T; Rhodes, Jonathan R; Hanson, Jeffrey O; Possingham, Hugh P

2015-12-01

Decisions need to be made about which biodiversity management actions are undertaken to mitigate threats and about where these actions are implemented. However, management actions can interact; that is, the cost, benefit, and feasibility of one action can change when another action is undertaken. There is little guidance on how to explicitly and efficiently prioritize management for multiple threats, including deciding where to act. Integrated management could focus on one management action to abate a dominant threat or on a strategy comprising multiple actions to abate multiple threats. Furthermore management could be undertaken at sites that are in close proximity to reduce costs. We used cost-effectiveness analysis to prioritize investments in fire management, controlling invasive predators, and reducing grazing pressure in a bio-diverse region of southeastern Queensland, Australia. We compared outcomes of 5 management approaches based on different assumptions about interactions and quantified how investment needed, benefits expected, and the locations prioritized for implementation differed when interactions were taken into account. Managing for interactions altered decisions about where to invest and in which actions to invest and had the potential to deliver increased investment efficiency. Differences in high priority locations and actions were greatest between the approaches when we made different assumptions about how management actions deliver benefits through threat abatement: either all threats must be managed to conserve species or only one management action may be required. Threatened species management that does not consider interactions between actions may result in misplaced investments or misguided expectations of the effort required to mitigate threats to species. © 2015 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of Society for Conservation Biology.

Social and Economic Analysis Branch: integrating policy, social, economic, and natural science

USGS Publications Warehouse

Schuster, Rudy; Walters, Katie D.

2015-01-01

The Fort Collins Science Center's Social and Economic Analysis Branch provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and natural science in the context of human–natural resource interactions. Our research provides scientific understanding and support for the management and conservation of our natural resources in support of multiple agency missions. We focus on meeting the scientific needs of the Department of the Interior natural resource management bureaus in addition to fostering partnerships with other Federal and State managers to protect, restore, and enhance our environment. The Social and Economic Analysis Branch has an interdisciplinary group of scientists whose primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to support the development of skills in natural resource management activities. Management and research issues associated with human-resource interactions typically occur in a unique context and require knowledge of both natural and social sciences, along with the skill to integrate multiple science disciplines. In response to these challenging contexts, Social and Economic Analysis Branch researchers apply a wide variety of social science concepts and methods which complement our rangeland/agricultural, wildlife, ecology, and biology capabilities. The goal of the Social and Economic Analysis Branch's research is to enhance natural-resource management, agency functions, policies, and decisionmaking.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Unraveling novel broad-spectrum antibacterial targets in food and waterborne pathogens using comparative genomics and protein interaction network analysis.

PubMed

Jadhav, Ankush; Shanmugham, Buvaneswari; Rajendiran, Anjana; Pan, Archana

2014-10-01

Food and waterborne diseases are a growing concern in terms of human morbidity and mortality worldwide, even in the 21st century, emphasizing the need for new therapeutic interventions for these diseases. The current study aims at prioritizing broad-spectrum antibacterial targets, present in multiple food and waterborne bacterial pathogens, through a comparative genomics strategy coupled with a protein interaction network analysis. The pathways unique and common to all the pathogens under study (viz., methane metabolism, d-alanine metabolism, peptidoglycan biosynthesis, bacterial secretion system, two-component system, C5-branched dibasic acid metabolism), identified by comparative metabolic pathway analysis, were considered for the analysis. The proteins/enzymes involved in these pathways were prioritized following host non-homology analysis, essentiality analysis, gut flora non-homology analysis and protein interaction network analysis. The analyses revealed a set of promising broad-spectrum antibacterial targets, present in multiple food and waterborne pathogens, which are essential for bacterial survival, non-homologous to host and gut flora, and functionally important in the metabolic network. The identified broad-spectrum candidates, namely, integral membrane protein/virulence factor (MviN), preprotein translocase subunits SecB and SecG, carbon storage regulator (CsrA), and nitrogen regulatory protein P-II 1 (GlnB), contributed by the peptidoglycan pathway, bacterial secretion systems and two-component systems, were also found to be present in a wide range of other disease-causing bacteria. Cytoplasmic proteins SecG, CsrA and GlnB were considered as drug targets, while membrane proteins MviN and SecB were classified as vaccine targets. The identified broad-spectrum targets can aid in the design and development of antibacterial agents not only against food and waterborne pathogens but also against other pathogens. Copyright © 2014 Elsevier B.V. All rights reserved.

Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two US populations.

PubMed

Casas-Agustench, Patricia; Arnett, Donna K; Smith, Caren E; Lai, Chao-Qiang; Parnell, Laurence D; Borecki, Ingrid B; Frazier-Wood, Alexis C; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D; Rich, Stephen S; Rotter, Jerome I; Lee, Yu-Chi; Ordovás, José M

2014-12-01

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Statechart Analysis with Symbolic PathFinder

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.

2012-01-01

We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.

AN INDIRECT SEARCH FOR WEAKLY INTERACTING MASSIVE PARTICLES IN THE SUN USING 3109.6 DAYS OF UPWARD-GOING MUONS IN SUPER-KAMIOKANDE

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

Tanaka, T.; Abe, K.; Hayato, Y.

2011-12-01

We present the result of an indirect search for high energy neutrinos from Weakly Interacting Massive Particle (WIMP) annihilation in the Sun using upward-going muon (upmu) events at Super-Kamiokande. Data sets from SKI-SKIII (3109.6 days) were used for the analysis. We looked for an excess of neutrino signal from the Sun as compared with the expected atmospheric neutrino background in three upmu categories: stopping, non-showering, and showering. No significant excess was observed. The 90% C.L. upper limits of upmu flux induced by WIMPs of 100 GeV c{sup -2} were 6.4 Multiplication-Sign 10{sup -15} cm{sup -2} s{sup -1} and 4.0 Multiplication-Signmore » 10{sup -15} cm{sup -2} s{sup -1} for the soft and hard annihilation channels, respectively. These limits correspond to upper limits of 4.5 Multiplication-Sign 10{sup -39} cm{sup -2} and 2.7 Multiplication-Sign 10{sup -40} cm{sup -2} for spin-dependent WIMP-nucleon scattering cross sections in the soft and hard annihilation channels, respectively.« less

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Interactive analysis of geographically distributed population imaging data collections over light-path data networks

NASA Astrophysics Data System (ADS)

van Lew, Baldur; Botha, Charl P.; Milles, Julien R.; Vrooman, Henri A.; van de Giessen, Martijn; Lelieveldt, Boudewijn P. F.

2015-03-01

The cohort size required in epidemiological imaging genetics studies often mandates the pooling of data from multiple hospitals. Patient data, however, is subject to strict privacy protection regimes, and physical data storage may be legally restricted to a hospital network. To enable biomarker discovery, fast data access and interactive data exploration must be combined with high-performance computing resources, while respecting privacy regulations. We present a system using fast and inherently secure light-paths to access distributed data, thereby obviating the need for a central data repository. A secure private cloud computing framework facilitates interactive, computationally intensive exploration of this geographically distributed, privacy sensitive data. As a proof of concept, MRI brain imaging data hosted at two remote sites were processed in response to a user command at a third site. The system was able to automatically start virtual machines, run a selected processing pipeline and write results to a user accessible database, while keeping data locally stored in the hospitals. Individual tasks took approximately 50% longer compared to a locally hosted blade server but the cloud infrastructure reduced the total elapsed time by a factor of 40 using 70 virtual machines in the cloud. We demonstrated that the combination light-path and private cloud is a viable means of building an analysis infrastructure for secure data analysis. The system requires further work in the areas of error handling, load balancing and secure support of multiple users.

An effective system for detecting protein-protein interaction based on in vivo cleavage by PPV NIa protease.

PubMed

Zheng, Nuoyan; Huang, Xiahe; Yin, Bojiao; Wang, Dan; Xie, Qi

2012-12-01

Detection of protein-protein interaction can provide valuable information for investigating the biological function of proteins. The current methods that applied in protein-protein interaction, such as co-immunoprecipitation and pull down etc., often cause plenty of working time due to the burdensome cloning and purification procedures. Here we established a system that characterization of protein-protein interaction was accomplished by co-expression and simply purification of target proteins from one expression cassette within E. coli system. We modified pET vector into co-expression vector pInvivo which encoded PPV NIa protease, two cleavage site F and two multiple cloning sites that flanking cleavage sites. The target proteins (for example: protein A and protein B) were inserted at multiple cloning sites and translated into polyprotein in the order of MBP tag-protein A-site F-PPV NIa protease-site F-protein B-His(6) tag. PPV NIa protease carried out intracellular cleavage along expression, then led to the separation of polyprotein components, therefore, the interaction between protein A-protein B can be detected through one-step purification and analysis. Negative control for protein B was brought into this system for monitoring interaction specificity. We successfully employed this system to prove two cases of reported protien-protein interaction: RHA2a/ANAC and FTA/FTB. In conclusion, a convenient and efficient system has been successfully developed for detecting protein-protein interaction.

Man-Machine Interaction Design and Analysis System (MIDAS): Memory Representation and Procedural Implications for Airborne Communication Modalities

NASA Technical Reports Server (NTRS)

Corker, Kevin M.; Pisanich, Gregory M.; Lebacqz, Victor (Technical Monitor)

1996-01-01

The Man-Machine Interaction Design and Analysis System (MIDAS) has been under development for the past ten years through a joint US Army and NASA cooperative agreement. MIDAS represents multiple human operators and selected perceptual, cognitive, and physical functions of those operators as they interact with simulated systems. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. Specific examples include: nuclear power plant crew simulation, military helicopter flight crew response, and police force emergency dispatch. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communications issues connected with aircraft-based separation assurance.

Consortium analysis of gene and gene-folate interactions in purine and pyrimidine metabolism pathways with ovarian carcinoma risk

PubMed Central

Kelemen, Linda E.; Terry, Kathryn L.; Goodman, Marc T.; Webb, Penelope M.; Bandera, Elisa V.; McGuire, Valerie; Rossing, Mary Anne; Wang, Qinggang; Dicks, Ed; Tyrer, Jonathan P.; Song, Honglin; Kupryjanczyk, Jolanta; Dansonka-Mieszkowska, Agnieszka; Plisiecka-Halasa, Joanna; Timorek, Agnieszka; Menon, Usha; Gentry-Maharaj, Aleksandra; Gayther, Simon A.; Ramus, Susan J.; Narod, Steven A.; Risch, Harvey A.; McLaughlin, John R.; Siddiqui, Nadeem; Glasspool, Rosalind; Paul, James; Carty, Karen; Gronwald, Jacek; Lubiński, Jan; Jakubowska, Anna; Cybulski, Cezary; Kiemeney, Lambertus A.; Massuger, Leon F. A. G.; van Altena, Anne M.; Aben, Katja K. H.; Olson, Sara H.; Orlow, Irene; Cramer, Daniel W.; Levine, Douglas A.; Bisogna, Maria; Giles, Graham G.; Southey, Melissa C.; Bruinsma, Fiona; Kjær, Susanne Krüger; Høgdall, Estrid; Jensen, Allan; Høgdall, Claus K.; Lundvall, Lene; Engelholm, Svend-Aage; Heitz, Florian; du Bois, Andreas; Harter, Philipp; Schwaab, Ira; Butzow, Ralf; Nevanlinna, Heli; Pelttari, Liisa M.; Leminen, Arto; Thompson, Pamela J.; Lurie, Galina; Wilkens, Lynne R.; Lambrechts, Diether; Van Nieuwenhuysen, Els; Lambrechts, Sandrina; Vergote, Ignace; Beesley, Jonathan; Fasching, Peter A.; Beckmann, Matthias W.; Hein, Alexander; Ekici, Arif B.; Doherty, Jennifer A.; Wu, Anna H.; Pearce, Celeste L.; Pike, Malcolm C.; Stram, Daniel; Chang-Claude, Jenny; Rudolph, Anja; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo B.; Bogdanova, Natalia; Antonenkova, Natalia; Odunsi, Kunle; Edwards, Robert P.; Kelley, Joseph L.; Modugno, Francesmary; Ness, Roberta B.; Karlan, Beth Y.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Fridley, Brooke L.; Vierkant, Robert A.; Cunningham, Julie M.; Wu, Xifeng; Lu, Karen; Liang, Dong; Hildebrandt, Michelle A.T.; Weber, Rachel Palmieri; Iversen, Edwin S.; Tworoger, Shelley S.; Poole, Elizabeth M.; Salvesen, Helga B.; Krakstad, Camilla; Bjorge, Line; Tangen, Ingvild L.; Pejovic, Tanja; Bean, Yukie; Kellar, Melissa; Wentzensen, Nicolas; Brinton, Louise A.; Lissowska, Jolanta; Garcia-Closas, Montserrat; Campbell, Ian G.; Eccles, Diana; Whittemore, Alice S.; Sieh, Weiva; Rothstein, Joseph H.; Anton-Culver, Hoda; Ziogas, Argyrios; Phelan, Catherine M.; Moysich, Kirsten B.; Goode, Ellen L.; Schildkraut, Joellen M.; Berchuck, Andrew; Pharoah, Paul D.P.; Sellers, Thomas A.; Brooks-Wilson, Angela; Cook, Linda S.; Le, Nhu D.

2014-01-01

Scope We re-evaluated previously reported associations between variants in pathways of one-carbon (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake. Methods and Results Odds ratios (OR) for 446 genetic variants were estimated among 13,410 OC cases and 22,635 controls and among 2,281 cases and 3,444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for DPYD variants rs11587873 (OR=0.92, P=6x10−5) and rs828054 (OR=1.06, P=1x10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT and TYMS, also interacted significantly with folate in a multi-variant analysis (corrected P=9.9x10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in one-carbon transfer, previously reported with OC, suggested lower risk at higher folate (Pinteraction=0.03-0.006). Conclusions Variation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP-byfolate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC. PMID:25066213

Expert Coaching in Weight Loss: Retrospective Analysis

PubMed Central

Kushner, Robert F; Hill, James O; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2018-01-01

Background Providing coaches as part of a weight management program is a common practice to increase participant engagement and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices. Objective The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight management and Web-based disease prevention solution. The study specifically examined the association between different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome. Methods A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least one weight measurement beyond baseline. First, a detailed analysis of different coach-participant interaction was performed using both intent-to-treat and completer populations. Next, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving expert coaching sessions, live weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the impact on weight loss outcome. Results Participants in the Retrofit weight loss program lost a mean 5.14% (SE 0.14) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R2=.158, P<.001) identified the following top 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per week were associated with clinically significant weight loss. Conclusions Participant’s one-on-one expert coaching session attendance, live weekly expert-led interactive Web-based class attendance, and the number of food log feedback days per week from expert coach were significant predictors of weight loss in a 6-month intervention. PMID:29535082

Human detection and motion analysis at security points

NASA Astrophysics Data System (ADS)

Ozer, I. Burak; Lv, Tiehan; Wolf, Wayne H.

2003-08-01

This paper presents a real-time video surveillance system for the recognition of specific human activities. Specifically, the proposed automatic motion analysis is used as an on-line alarm system to detect abnormal situations in a campus environment. A smart multi-camera system developed at Princeton University is extended for use in smart environments in which the camera detects the presence of multiple persons as well as their gestures and their interaction in real-time.

Generalisation of the identity method for determination of high-order moments of multiplicity distributions with a software implementation

NASA Astrophysics Data System (ADS)

Maćkowiak-Pawłowska, Maja; Przybyła, Piotr

2018-05-01

The incomplete particle identification limits the experimentally-available phase space region for identified particle analysis. This problem affects ongoing fluctuation and correlation studies including the search for the critical point of strongly interacting matter performed on SPS and RHIC accelerators. In this paper we provide a procedure to obtain nth order moments of the multiplicity distribution using the identity method, generalising previously published solutions for n=2 and n=3. Moreover, we present an open source software implementation of this computation, called Idhim, that allows one to obtain the true moments of identified particle multiplicity distributions from the measured ones provided the response function of the detector is known.

A 3D interactive multi-object segmentation tool using local robust statistics driven active contours.

PubMed

Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

2012-08-01

Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: first, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction-this not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. Copyright © 2012 Elsevier B.V. All rights reserved.

A 3D Interactive Multi-object Segmentation Tool using Local Robust Statistics Driven Active Contours

PubMed Central

Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

2012-01-01

Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: First, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction — This not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. PMID:22831773

The Slope Test: Applications in Formative Evaluation.

ERIC Educational Resources Information Center

Baggaley, Jon; Brauer, Aaron-Henry

1989-01-01

Discusses problems with formative evaluation of educational materials and examines the slope test when used in a pretest/posttest multiple group (PPMG) design to adjust posttest scores treatment interaction studies. An example is given of the utility of the slope test and analysis of covariance procedure using an educational film about AIDS. (five…

Analysis of Peer Learning Behaviors Using Multiple Representations in Virtual Reality and Their Impacts on Geometry Problem Solving

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Hu, Shih-Shin

2013-01-01

Learning geometry emphasizes the importance of exploring different representations such as virtual manipulatives, written math formulas, and verbal explanations, which help students build math concepts and develop critical thinking. Besides helping individuals construct math knowledge, peer interaction also plays a crucial role in promoting an…

On Free-Form Gaming,

DTIC Science & Technology

1985-08-01

which the competitive interactions can occur simultaneously in several "arenas" (political, military, etc.). This gaming format has been used to...10 E . Post- Game Analysis .. ..................................... 13 F. Limitations ... ............................................ 15 III...preparation of game papers and an electronic message handling system for moving papers from room to room. This satisfies the requirement for legible, multiple

A Comparison of Four Approaches to Account for Method Effects in Latent State-Trait Analyses

ERIC Educational Resources Information Center

Geiser, Christian; Lockhart, Ginger

2012-01-01

Latent state-trait (LST) analysis is frequently applied in psychological research to determine the degree to which observed scores reflect stable person-specific effects, effects of situations and/or person-situation interactions, and random measurement error. Most LST applications use multiple repeatedly measured observed variables as indicators…

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

Efficiency analysis of a multiple axle vehicle with hydrostatic transmission overcoming obstacles

NASA Astrophysics Data System (ADS)

Comellas, M.; Pijuan, J.; Nogués, M.; Roca, J.

2018-01-01

Transmission configurations in off-road vehicles with multiple driven axles can be a determining factor in the obstacle surmounting capacity and also in the vehicle efficiency. An off-road articulated vehicle with four driven axles, four bogies and two modules has been considered for the global hydrostatic transmission efficiency analysis and for the vehicle functional efficiency analysis. The power flow through the transmission system has been quantified from the combustion engine shaft to each axle of the wheels. It has been done for different the operating conditions and taking into account the wheel-terrain interaction and the transmission configuration, that could lead to a forced slippage of some of the wheels. Results show the influence of the different wheels' requirements, the transmission configuration limitations and the considered control strategy on the global transmission and vehicle functional efficiencies.

Coupling detrended fluctuation analysis for multiple warehouse-out behavioral sequences

NASA Astrophysics Data System (ADS)

Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou

2017-01-01

Interaction patterns among different warehouses could make the warehouse-out behavioral sequences less predictable. We firstly take a coupling detrended fluctuation analysis on the warehouse-out quantity, and find that the multivariate sequences exhibit significant coupling multifractal characteristics regardless of the types of steel products. Secondly, we track the sources of multifractal warehouse-out sequences by shuffling and surrogating original ones, and we find that fat-tail distribution contributes more to multifractal features than the long-term memory, regardless of types of steel products. From perspective of warehouse contribution, some warehouses steadily contribute more to multifractal than other warehouses. Finally, based on multiscale multifractal analysis, we propose Hurst surface structure to investigate coupling multifractal, and show that multiple behavioral sequences exhibit significant coupling multifractal features that emerge and usually be restricted within relatively greater time scale interval.

A Bayesian Poisson-lognormal Model for Count Data for Multiple-Trait Multiple-Environment Genomic-Enabled Prediction.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H; Montesinos-López, José C; Singh, Pawan; Juliana, Philomin; Salinas-Ruiz, Josafhat

2017-05-05

When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait at a time taking into account genotype × environment interaction (G × E), because there is a lack of comprehensive models that simultaneously take into account the correlated counting traits and G × E. For this reason, in this study we propose a multiple-trait and multiple-environment model for count data. The proposed model was developed under the Bayesian paradigm for which we developed a Markov Chain Monte Carlo (MCMC) with noninformative priors. This allows obtaining all required full conditional distributions of the parameters leading to an exact Gibbs sampler for the posterior distribution. Our model was tested with simulated data and a real data set. Results show that the proposed multi-trait, multi-environment model is an attractive alternative for modeling multiple count traits measured in multiple environments. Copyright © 2017 Montesinos-López et al.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

PubMed Central

Liu, Hua; Wu, Wen

2017-01-01

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF). PMID:28608843

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

Untangling the effects of multiple human stressors and their impacts on fish assemblages in European running waters.

PubMed

Schinegger, Rafaela; Palt, Martin; Segurado, Pedro; Schmutz, Stefan

2016-12-15

This work addresses human stressors and their impacts on fish assemblages at pan-European scale by analysing single and multiple stressors and their interactions. Based on an extensive dataset with 3105 fish sampling sites, patterns of stressors, their combination and nature of interactions, i.e. synergistic, antagonistic and additive were investigated. Geographical distribution and patterns of seven human stressor variables, belonging to four stressor groups (hydrological-, morphological-, water quality- and connectivity stressors), were examined, considering both single and multiple stressor combinations. To quantify the stressors' ecological impact, a set of 22 fish metrics for various fish assemblage types (headwaters, medium gradient rivers, lowland rivers and Mediterranean streams) was analysed by comparing their observed and expected response to different stressors, both acting individually and in combination. Overall, investigated fish sampling sites are affected by 15 different stressor combinations, including 4 stressors acting individually and 11 combinations of two or more stressors; up to 4 stressor groups per fish sampling site occur. Stressor-response analysis shows divergent results among different stressor categories, even though a general trend of decreasing ecological integrity with increasing stressor quantity can be observed. Fish metrics based on density of species 'intolerant to water quality degradation' and 'intolerant to oxygen depletion" responded best to single and multiple stressors and their interactions. Interactions of stressors were additive (40%), synergistic (30%) or antagonistic (30%), emphasizing the importance to consider interactions in multi-stressor analyses. While antagonistic effects are only observed in headwaters and medium-gradient rivers, synergistic effects increase from headwaters over medium gradient rivers and Mediterranean streams to large lowland rivers. The knowledge gained in this work provides a basis for advanced investigations in European river basins and helps prioritizing further restoration and management actions. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Hyperhomocysteinaemia is an independent risk factor of abdominal aortic aneurysm in a Chinese Han population

PubMed Central

Liu, Jie; Wei Zuo, Shang; Li, Yue; Jia, Xin; Jia, Sen Hao; Zhang, Tao; Xiang Song, Yu; Qi Wei, Ying; Xiong, Jiang; Hua Hu, Yong; Guo, Wei

2016-01-01

The associations between hyperhomocysteinaemia (HHcy), methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, and abdominal aortic aneurysm (AAA) remain controversial, with only few studies focused on these associations within the Chinese population. We performed subgroup and interaction analyses in a Chinese Han population to investigate these associations. In all, 155 AAA patients and 310 control subjects were evaluated for serum total homocysteine levels and MTHFR C677T polymorphisms. Multiple logistic regression models were used to evaluate the aforementioned associations. Interaction and stratified analyses were conducted according to age, sex, smoking status, drinking status, and chronic disease histories. The multiple logistic analyses showed a significant association between HHcy and AAA but no significant association between MTHFR C677T polymorphism and AAA. The interaction analysis showed that age and peripheral arterial disease played an interactive role in the association between HHcy and AAA, while drinking status played an interactive role in the association between MTHFR C677T polymorphism and AAA. In conclusion, HHcy is an independent risk factor of AAA in a Chinese Han population, especially in the elderly and peripheral arterial disease subgroups. Longitudinal studies and clinical trials aimed to reduce homocysteine levels are warranted to assess the causal nature of these relationships PMID:26865327

Nonlinear force dependence on optically bound micro-particle arrays in the evanescent fields of fundamental and higher order microfibre modes

PubMed Central

Maimaiti, Aili; Holzmann, Daniela; Truong, Viet Giang; Ritsch, Helmut; Nic Chormaic, Síle

2016-01-01

Particles trapped in the evanescent field of an ultrathin optical fibre interact over very long distances via multiple scattering of the fibre-guided fields. In ultrathin fibres that support higher order modes, these interactions are stronger and exhibit qualitatively new behaviour due to the coupling of different fibre modes, which have different propagation wave-vectors, by the particles. Here, we study one dimensional longitudinal optical binding interactions of chains of 3 μm polystyrene spheres under the influence of the evanescent fields of a two-mode microfibre. The observation of long-range interactions, self-ordering and speed variation of particle chains reveals strong optical binding effects between the particles that can be modelled well by a tritter scattering-matrix approach. The optical forces, optical binding interactions and the velocity of bounded particle chains are calculated using this method. Results show good agreement with finite element numerical simulations. Experimental data and theoretical analysis show that higher order modes in a microfibre offer a promising method to not only obtain stable, multiple particle trapping or faster particle propulsion speeds, but that they also allow for better control over each individual trapped object in particle ensembles near the microfibre surface. PMID:27451935

P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

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

Webb-Robertson, Bobbie-Jo M.; Bramer, Lisa M.; Jensen, Jeffrey L.

P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternativelymore » available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).« less

Analysis and application of opinion model with multiple topic interactions.

PubMed

Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

2017-08-01

To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement

PubMed Central

Barany, Deborah A.; Della-Maggiore, Valeria; Viswanathan, Shivakumar; Cieslak, Matthew

2014-01-01

Neurophysiology and neuroimaging evidence shows that the brain represents multiple environmental and body-related features to compute transformations from sensory input to motor output. However, it is unclear how these features interact during goal-directed movement. To investigate this issue, we examined the representations of sensory and motor features of human hand movements within the left-hemisphere motor network. In a rapid event-related fMRI design, we measured cortical activity as participants performed right-handed movements at the wrist, with either of two postures and two amplitudes, to move a cursor to targets at different locations. Using a multivoxel analysis technique with rigorous generalization tests, we reliably distinguished representations of task-related features (primarily target location, movement direction, and posture) in multiple regions. In particular, we identified an interaction between target location and movement direction in the superior parietal lobule, which may underlie a transformation from the location of the target in space to a movement vector. In addition, we found an influence of posture on primary motor, premotor, and parietal regions. Together, these results reveal the complex interactions between different sensory and motor features that drive the computation of sensorimotor transformations. PMID:24828640

Classification of group behaviors in social media via social behavior grammars

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Getoor, Lise; Smith, Marc

2014-06-01

The increasing use of online collaboration and information sharing in the last decade has resulted in explosion of criminal and anti-social activities in online communities. Detection of such behaviors are of interest to commercial enterprises who want to guard themselves from cyber criminals, and the military intelligence analysts who desire to detect and counteract cyberwars waged by adversarial states and organizations. The most challenging behaviors to detect are those involving multiple individuals who share actions and roles in the hostile activities and individually appear benign. To detect these behaviors, the theories of group behaviors and interactions must be developed. In this paper we describe our exploration of the data from collaborative social platform to categorize the behaviors of multiple individuals. We applied graph matching algorithms to explore consistent social interactions. Our research led us to a conclusion that complex collaborative behaviors can be modeled and detected using a concept of group behavior grammars, in a manner analogous to natural language processing. These grammars capture constraints on how people take on roles in virtual environments, form groups, and interact over time, providing the building blocks for scalable and accurate multi-entity interaction analysis and social behavior hypothesis testing.

Reconstituting protein interaction networks using parameter-dependent domain-domain interactions

PubMed Central

2013-01-01

Background We can describe protein-protein interactions (PPIs) as sets of distinct domain-domain interactions (DDIs) that mediate the physical interactions between proteins. Experimental data confirm that DDIs are more consistent than their corresponding PPIs, lending support to the notion that analyses of DDIs may improve our understanding of PPIs and lead to further insights into cellular function, disease, and evolution. However, currently available experimental DDI data cover only a small fraction of all existing PPIs and, in the absence of structural data, determining which particular DDI mediates any given PPI is a challenge. Results We present two contributions to the field of domain interaction analysis. First, we introduce a novel computational strategy to merge domain annotation data from multiple databases. We show that when we merged yeast domain annotations from six annotation databases we increased the average number of domains per protein from 1.05 to 2.44, bringing it closer to the estimated average value of 3. Second, we introduce a novel computational method, parameter-dependent DDI selection (PADDS), which, given a set of PPIs, extracts a small set of domain pairs that can reconstruct the original set of protein interactions, while attempting to minimize false positives. Based on a set of PPIs from multiple organisms, our method extracted 27% more experimentally detected DDIs than existing computational approaches. Conclusions We have provided a method to merge domain annotation data from multiple sources, ensuring large and consistent domain annotation for any given organism. Moreover, we provided a method to extract a small set of DDIs from the underlying set of PPIs and we showed that, in contrast to existing approaches, our method was not biased towards DDIs with low or high occurrence counts. Finally, we used these two methods to highlight the influence of the underlying annotation density on the characteristics of extracted DDIs. Although increased annotations greatly expanded the possible DDIs, the lack of knowledge of the true biological false positive interactions still prevents an unambiguous assignment of domain interactions responsible for all protein network interactions. Executable files and examples are given at: http://www.bhsai.org/downloads/padds/ PMID:23651452

Social Peer Interactions in Persons with Profound Intellectual and Multiple Disabilities: A Literature Review

ERIC Educational Resources Information Center

Nijs, Sara; Maes, Bea

2014-01-01

Social interactions may positively influence developmental and quality of life outcomes. Research in persons with profound intellectual and multiple disabilities (PIMD) mostly investigated interactions with caregivers. This literature review focuses on peer interactions of persons with PIMD. A computerized literature search of three databases was…

Structured plant metabolomics for the simultaneous exploration of multiple factors.

PubMed

Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

Lipid-associated Oral Delivery: Mechanisms and Analysis of Oral Absorption Enhancement

PubMed Central

Rezhdo, Oljora; Speciner, Lauren; Carrier, Rebecca L.

2016-01-01

The majority of newly discovered oral drugs are poorly water soluble, and co-administration with lipids has proven effective in significantly enhancing bioavailability of some compounds with low aqueous solubility. Yet, lipid-based delivery technologies have not been widely employed in commercial oral products. Lipids can impact drug transport and fate in the gastrointestinal (GI) tract through multiple mechanisms including enhancement of solubility and dissolution kinetics, enhancement of permeation through the intestinal mucosa, and triggering drug precipitation upon lipid emulsion depletion (e.g., by digestion). The effect of lipids on drug absorption is currently not quantitatively predictable, in part due to the multiple complex dynamic processes that can be impacted by lipids. Quantitative mechanistic analysis of the processes significant to lipid system function and overall impact on drug absorption can aid understanding of drug-lipid interactions in the GI tract and exploitation of such interactions to achieve optimal lipid-based drug delivery. In this review, we discuss the impact of co-delivered lipids and lipid digestion on drug dissolution, partitioning, and absorption in the context of the experimental tools and associated kinetic expressions used to study and model these processes. The potential benefit of a systems-based consideration of the concurrent multiple dynamic processes occurring upon co-dosing lipids and drugs to predict the impact of lipids on drug absorption and enable rational design of lipid-based delivery systems is presented. PMID:27520734

The Perseus computational platform for comprehensive analysis of (prote)omics data.

PubMed

Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

2016-09-01

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population.

PubMed

Xavier, Alencar; Jarquin, Diego; Howard, Reka; Ramasubramanian, Vishnu; Specht, James E; Graef, George L; Beavis, William D; Diers, Brian W; Song, Qijian; Cregan, Perry B; Nelson, Randall; Mian, Rouf; Shannon, J Grover; McHale, Leah; Wang, Dechun; Schapaugh, William; Lorenz, Aaron J; Xu, Shizhong; Muir, William M; Rainey, Katy M

2018-02-02

Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations. Copyright © 2018 Xavier et al.

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes.

PubMed

Uchikoga, Nobuyuki; Hirokawa, Takatsugu

2010-05-11

Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG), CaM kinase kinase (CaMKK) and the plasma membrane Ca2+ ATPase pump (PMCA), and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

PubMed

Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

2017-11-01

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

The Role of Multiphysics Simulation in Multidisciplinary Analysis

NASA Technical Reports Server (NTRS)

Rifai, Steven M.; Ferencz, Robert M.; Wang, Wen-Ping; Spyropoulos, Evangelos T.; Lawrence, Charles; Melis, Matthew E.

1998-01-01

This article describes the applications of the Spectrum(Tm) Solver in Multidisciplinary Analysis (MDA). Spectrum, a multiphysics simulation software based on the finite element method, addresses compressible and incompressible fluid flow, structural, and thermal modeling as well as the interaction between these disciplines. Multiphysics simulation is based on a single computational framework for the modeling of multiple interacting physical phenomena. Interaction constraints are enforced in a fully-coupled manner using the augmented-Lagrangian method. Within the multiphysics framework, the finite element treatment of fluids is based on Galerkin-Least-Squares (GLS) method with discontinuity capturing operators. The arbitrary-Lagrangian-Eulerian method is utilized to account for deformable fluid domains. The finite element treatment of solids and structures is based on the Hu-Washizu variational principle. The multiphysics architecture lends itself naturally to high-performance parallel computing. Aeroelastic, propulsion, thermal management and manufacturing applications are presented.

Principal component analysis of chemical shift perturbation data of a multiple-ligand-binding system for elucidation of respective binding mechanism.

PubMed

Konuma, Tsuyoshi; Lee, Young-Ho; Goto, Yuji; Sakurai, Kazumasa

2013-01-01

Chemical shift perturbations (CSPs) in NMR spectra provide useful information about the interaction of a protein with its ligands. However, in a multiple-ligand-binding system, determining quantitative parameters such as a dissociation constant (K(d) ) is difficult. Here, we used a method we named CS-PCA, a principal component analysis (PCA) of chemical shift (CS) data, to analyze the interaction between bovine β-lactoglobulin (βLG) and 1-anilinonaphthalene-8-sulfonate (ANS), which is a multiple-ligand-binding system. The CSP on the binding of ANS involved contributions from two distinct binding sites. PCA of the titration data successfully separated the CSP pattern into contributions from each site. Docking simulations based on the separated CSP patterns provided the structures of βLG-ANS complexes for each binding site. In addition, we determined the K(d) values as 3.42 × 10⁻⁴ M² and 2.51 × 10⁻³ M for Sites 1 and 2, respectively. In contrast, it was difficult to obtain reliable K(d) values for respective sites from the isothermal titration calorimetry experiments. Two ANS molecules were found to bind at Site 1 simultaneously, suggesting that the binding occurs cooperatively with a partial unfolding of the βLG structure. On the other hand, the binding of ANS to Site 2 was a simple attachment without a significant conformational change. From the present results, CS-PCA was confirmed to provide not only the positions and the K(d) values of binding sites but also information about the binding mechanism. Thus, it is anticipated to be a general method to investigate protein-ligand interactions. Copyright © 2012 Wiley Periodicals, Inc.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for improving the model physics parameterizations.

A leader-follower-interactive method for regional water resources management with considering multiple water demands and eco-environmental constraints

NASA Astrophysics Data System (ADS)

Chen, Yizhong; Lu, Hongwei; Li, Jing; Ren, Lixia; He, Li

2017-05-01

This study presents the mathematical formulation and implementations of a synergistic optimization framework based on an understanding of water availability and reliability together with the characteristics of multiple water demands. This framework simultaneously integrates a set of leader-followers-interactive objectives established by different decision makers during the synergistic optimization. The upper-level model (leader's one) determines the optimal pollutants discharge to satisfy the environmental target. The lower-level model (follower's one) accepts the dispatch requirement from the upper-level one and dominates the optimal water-allocation strategy to maximize economic benefits representing the regional authority. The complicated bi-level model significantly improves upon the conventional programming methods through the mutual influence and restriction between the upper- and lower-level decision processes, particularly when limited water resources are available for multiple completing users. To solve the problem, a bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for measuring to what extent the constraints are met and the objective reaches its optima. The capabilities of the proposed model are illustrated through a real-world case study of water resources management system in the district of Fengtai located in Beijing, China. Feasible decisions in association with water resources allocation, wastewater emission and pollutants discharge would be sequentially generated for balancing the objectives subject to the given water-related constraints, which can enable Stakeholders to grasp the inherent conflicts and trade-offs between the environmental and economic interests. The performance of the developed bi-level model is enhanced by comparing with single-level models. Moreover, in consideration of the uncertainty in water demand and availability, sensitivity analysis and policy analysis are employed for identifying their impacts on the final decisions and improving the practical applications.

Modeling the interaction and toxicity of Cu-Cd mixture to wheat roots affected by humic acids, in terms of cell membrane surface characteristics.

PubMed

Wang, Yi-Min; Zhou, Dong-Mei; Yuan, Xu-Yin; Zhang, Xiao-Hui; Li, Yi

2018-05-01

Responses of wheat (Triticum aestivum L.) seedling roots to the mixtures of copper (Cu), cadmium (Cd) and humic acids (HA) were investigated using the solution culture experiments, focusing on the interaction patterns between multiple metals and their influences on root proton release. A concentration-addition multiplication (CA) model was introduced into the modeling analysis. In comparison with metal ion activities in bulk-phase solutions, the incorporation of ion activities at the root cell membrane surfaces (CMs) (denoted as {Cu 2+ } 0 and {Cd 2+ } 0 ) into the CA model could significantly improve their correlation with RRE (relative root elongation) from 0.819 to 0.927. Modeling analysis indicated that the co-existence of {Cu 2+ } 0 significantly enhanced the rhizotoxicity of {Cd 2+ } 0 , while no significant effect of {Cd 2+ } 0 on the {Cu 2+ } 0 rhizotoxicity. 10 mg/L HA stimulated the root elongation even under metal stress. Although high concentration of metal ions inhibited the root proton release rate (ΔH + ), both the low concentration of metal ions and HA treatments increased the values of ΔH + . In HA-Cu-Cd mixtures, actions of metal ions on ΔH + values were varied intricately among treatments but well modeled by the CA model. We concluded from the CA models that the electrostatic effect is vitally important for explaining the effect of {Cu 2+ } 0 on the rhizotoxicity of {Cd 2+ } 0 , while it plays no unique role in understanding the influence of {Cd 2+ } 0 on the rhizotoxicity of {Cu 2+ } 0. Thus our study provide a novel way for modeling multiple metals behaviors in the environment and understanding the mechanisms of ion interactions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Winter NH low-frequency variability in a hierarchy of low-order stochastic dynamical models of earth-atmosphere system

NASA Astrophysics Data System (ADS)

Zhao, Nan

2018-02-01

The origin of winter Northern Hemispheric low-frequency variability (hereafter, LFV) is regarded to be related to the coupled earth-atmosphere system characterized by the interaction of the jet stream with mid-latitude mountain ranges. On the other hand, observed LFV usually appears as transitions among multiple planetary-scale flow regimes of Northern Hemisphere like NAO + , AO +, AO - and NAO - . Moreover, the interaction between synoptic-scale eddies and the planetary-scale disturbance is also inevitable in the origin of LFV. These raise a question regarding how to incorporate all these aspects into just one framework to demonstrate (1) a planetary-scale dynamics of interaction of the jet stream with mid-latitude mountain ranges can really produce LFV, (2) such a dynamics can be responsible for the existence of above multiple flow regimes, and (3) the role of interaction with eddy is also clarified. For this purpose, a hierarchy of low-order stochastic dynamical models of the coupled earth-atmosphere system derived empirically from different timescale ranges of indices of Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific/North American (PNA), and length of day (LOD) and related probability density function (PDF) analysis are employed in this study. The results seem to suggest that the origin of LFV cannot be understood completely within the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain ranges, because (1) the existence of multiple flow regimes such as NAO+, AO+, AO- and NAO- resulted from processes with timescales much longer than LFV itself, which may have underlying dynamics other than topography-jet stream interaction, and (2) we find LFV seems not necessarily to come directly from the planetary-scale dynamics of the interaction of the jet stream with mid-latitude mountain, although it can produce similar oscillatory behavior. The feedback/forcing of synoptic-scale eddies on the planetary-scale dynamics seems to play a more essential role in its origin.

Quantitative analysis of single- vs. multiple-set programs in resistance training.

PubMed

Wolfe, Brian L; LeMura, Linda M; Cole, Phillip J

2004-02-01

The purpose of this study was to examine the existing research on single-set vs. multiple-set resistance training programs. Using the meta-analytic approach, we included studies that met the following criteria in our analysis: (a) at least 6 subjects per group; (b) subject groups consisting of single-set vs. multiple-set resistance training programs; (c) pretest and posttest strength measures; (d) training programs of 6 weeks or more; (e) apparently "healthy" individuals free from orthopedic limitations; and (f) published studies in English-language journals only. Sixteen studies generated 103 effect sizes (ESs) based on a total of 621 subjects, ranging in age from 15-71 years. Across all designs, intervention strategies, and categories, the pretest to posttest ES in muscular strength was (chi = 1.4 +/- 1.4; 95% confidence interval, 0.41-3.8; p < 0.001). The results of 2 x 2 analysis of variance revealed simple main effects for age, training status (trained vs. untrained), and research design (p < 0.001). No significant main effects were found for sex, program duration, and set end point. Significant interactions were found for training status and program duration (6-16 weeks vs. 17-40 weeks) and number of sets performed (single vs. multiple). The data indicated that trained individuals performing multiple sets generated significantly greater increases in strength (p < 0.001). For programs with an extended duration, multiple sets were superior to single sets (p < 0.05). This quantitative review indicates that single-set programs for an initial short training period in untrained individuals result in similar strength gains as multiple-set programs. However, as progression occurs and higher gains are desired, multiple-set programs are more effective.

Genome-wide gene phylogeny of CIPK family in cassava and expression analysis of partial drought-induced genes

PubMed Central

Hu, Wei; Xia, Zhiqiang; Yan, Yan; Ding, Zehong; Tie, Weiwei; Wang, Lianzhe; Zou, Meiling; Wei, Yunxie; Lu, Cheng; Hou, Xiaowan; Wang, Wenquan; Peng, Ming

2015-01-01

Cassava is an important food and potential biofuel crop that is tolerant to multiple abiotic stressors. The mechanisms underlying these tolerances are currently less known. CBL-interacting protein kinases (CIPKs) have been shown to play crucial roles in plant developmental processes, hormone signaling transduction, and in the response to abiotic stress. However, no data is currently available about the CPK family in cassava. In this study, a total of 25 CIPK genes were identified from cassava genome based on our previous genome sequencing data. Phylogenetic analysis suggested that 25 MeCIPKs could be classified into four subfamilies, which was supported by exon-intron organizations and the architectures of conserved protein motifs. Transcriptomic analysis of a wild subspecies and two cultivated varieties showed that most MeCIPKs had different expression patterns between wild subspecies and cultivatars in different tissues or in response to drought stress. Some orthologous genes involved in CIPK interaction networks were identified between Arabidopsis and cassava. The interaction networks and co-expression patterns of these orthologous genes revealed that the crucial pathways controlled by CIPK networks may be involved in the differential response to drought stress in different accessions of cassava. Nine MeCIPK genes were selected to investigate their transcriptional response to various stimuli and the results showed the comprehensive response of the tested MeCIPK genes to osmotic, salt, cold, oxidative stressors, and ABA signaling. The identification and expression analysis of CIPK family suggested that CIPK genes are important components of development and multiple signal transduction pathways in cassava. The findings of this study will help lay a foundation for the functional characterization of the CIPK gene family and provide an improved understanding of abiotic stress responses and signaling transduction in cassava. PMID:26579161

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

Study of cosmic ray events with high muon multiplicity using the ALICE detector at the CERN Large Hadron Collider

DOE PAGES

Adam, J.

2016-01-19

ALICE is one of four large experiments at the CERN Large Hadron Collider near Geneva, specially designed to study particle production in ultra-relativistic heavy-ion collisions. Located 52 meters underground with 28 meters of overburden rock, it has also been used to detect muons produced by cosmic ray interactions in the upper atmosphere. Here, we present the multiplicity distribution of these atmospheric muons and its comparison with Monte Carlo simulations. Our analysis exploits the large size and excellent tracking capability of the ALICE Time Projection Chamber. A special emphasis is given to the study of high multiplicity events containing more thanmore » 100 reconstructed muons and corresponding to a muon areal density rho(mu) > 5.9 m(-2). Similar events have been studied in previous underground experiments such as ALEPH and DELPHI at LEP. While these experiments were able to reproduce the measured muon multiplicity distribution with Monte Carlo simulations at low and intermediate multiplicities, their simulations failed to describe the frequency of the highest multiplicity events. In this work we show that the high multiplicity events observed in ALICE stem from primary cosmic rays with energies above 10(16) eV and that the frequency of these events can be successfully described by assuming a heavy mass composition of primary cosmic rays in this energy range. Furthermore, the development of the resulting air showers was simulated using the latest version of QGSJET to model hadronic interactions. This observation places significant constraints on alternative, more exotic, production mechanisms for these events.« less

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis.

PubMed

Xia, Wei; Wu, Jian; Deng, Fei-Yan; Wu, Long-Fei; Zhang, Yong-Hong; Guo, Yu-Fan; Lei, Shu-Feng

2017-02-01

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Teaching Radiology Physics Interactively with Scientific Notebook Software.

PubMed

Richardson, Michael L; Amini, Behrang

2018-06-01

The goal of this study is to demonstrate how the teaching of radiology physics can be enhanced with the use of interactive scientific notebook software. We used the scientific notebook software known as Project Jupyter, which is free, open-source, and available for the Macintosh, Windows, and Linux operating systems. We have created a scientific notebook that demonstrates multiple interactive teaching modules we have written for our residents using the Jupyter notebook system. Scientific notebook software allows educators to create teaching modules in a form that combines text, graphics, images, data, interactive calculations, and image analysis within a single document. These notebooks can be used to build interactive teaching modules, which can help explain complex topics in imaging physics to residents. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Identification of Binding Modes for Amino Naphthalene 2-Cyanoacrylate (ANCA) Probes to Amyloid Fibrils from Molecular Dynamics Simulations.

PubMed

He, Huan; Xu, Juan; Cheng, Dan-Yang; Fu, Li; Ge, Yu-Shu; Jiang, Feng-Lei; Liu, Yi

2017-02-16

The amino naphthalene 2-cyanoacrylate (ANCA) probe is a kind of fluorescent amyloid binding probe that can report different fluorescence emissions when bound to various amyloid deposits in tissue, while their interactions with amyloid fibrils remain unclear due to the insoluble nature of amyloid fibrils. Here, all-atom molecular dynamics simulations were used to investigate the interaction between ANCA probes with three different amyloid fibrils. Two common binding modes of ANCA probes on Aβ40 amyloid fibrils were identified by cluster analysis of multiple simulations. The van der Waals and electrostatic interactions were found to be major driving forces for the binding. Atomic contacts analysis and binding free energy decomposition results suggested that the hydrophobic part of ANCA mainly interacts with aromatic side chains on the fibril surface and the hydrophilic part mainly interacts with positive charged residues in the β-sheet region. By comparing the binding modes with different fibrils, we can find that ANCA adopts different conformations while interacting with residues of different hydrophobicity, aromaticity, and electrochemical properties in the β-sheet region, which accounts for its selective mechanism toward different amyloid fibrils.

Nursing home cost and ownership type: evidence of interaction effects.

PubMed

Arling, G; Nordquist, R H; Capitman, J A

1987-06-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed.

Multiverse data-flow control.

PubMed

Schindler, Benjamin; Waser, Jürgen; Ribičić, Hrvoje; Fuchs, Raphael; Peikert, Ronald

2013-06-01

In this paper, we present a data-flow system which supports comparative analysis of time-dependent data and interactive simulation steering. The system creates data on-the-fly to allow for the exploration of different parameters and the investigation of multiple scenarios. Existing data-flow architectures provide no generic approach to handle modules that perform complex temporal processing such as particle tracing or statistical analysis over time. Moreover, there is no solution to create and manage module data, which is associated with alternative scenarios. Our solution is based on generic data-flow algorithms to automate this process, enabling elaborate data-flow procedures, such as simulation, temporal integration or data aggregation over many time steps in many worlds. To hide the complexity from the user, we extend the World Lines interaction techniques to control the novel data-flow architecture. The concept of multiple, special-purpose cursors is introduced to let users intuitively navigate through time and alternative scenarios. Users specify only what they want to see, the decision which data are required is handled automatically. The concepts are explained by taking the example of the simulation and analysis of material transport in levee-breach scenarios. To strengthen the general applicability, we demonstrate the investigation of vortices in an offline-simulated dam-break data set.

Statistical analysis of the electrocatalytic activity of Pt nanoparticles supported on novel functionalized reduced graphene oxide-chitosan for methanol electrooxidation

NASA Astrophysics Data System (ADS)

Ekrami-Kakhki, Mehri-Saddat; Abbasi, Sedigheh; Farzaneh, Nahid

2018-01-01

The purpose of this study is to statistically analyze the anodic current density and peak potential of methanol oxidation at Pt nanoparticles supported on functionalized reduced graphene oxide (RGO), using design of experiments methodology. RGO is functionalized with methyl viologen (MV) and chitosan (CH). The novel Pt/MV-RGO-CH catalyst is successfully prepared and characterized with transmission electron microscopy (TEM) image. The electrocatalytic activity of Pt/MV-RGOCH catalyst is experimentally evaluated for methanol oxidation. The effects of methanol concentration and scan rate factors are also investigated experimentally and statistically. The effects of these two main factors and their interactions are investigated, using analysis of variance test, Duncan's multiple range test and response surface method. The results of the analysis of variance show that all the main factors and their interactions have a significant effect on anodic current density and peak potential of methanol oxidation at α = 0.05. The suggested models which encompass significant factors can predict the variation of the anodic current density and peak potential of methanol oxidation. The results of Duncan's multiple range test confirmed that there is a significant difference between the studied levels of the main factors. [Figure not available: see fulltext.

Nursing home cost and ownership type: evidence of interaction effects.

PubMed Central

Arling, G; Nordquist, R H; Capitman, J A

1987-01-01

Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed. PMID:3301746

Integration of statistical and physiological analyses of adaptation of near-isogenic barley lines.

PubMed

Romagosa, I; Fox, P N; García Del Moral, L F; Ramos, J M; García Del Moral, B; Roca de Togores, F; Molina-Cano, J L

1993-08-01

Seven near-isogenic barley lines, differing for three independent mutant genes, were grown in 15 environments in Spain. Genotype x environment interaction (G x E) for grain yield was examined with the Additive Main Effects and Multiplicative interaction (AMMI) model. The results of this statistical analysis of multilocation yield-data were compared with a morpho-physiological characterization of the lines at two sites (Molina-Cano et al. 1990). The first two principal component axes from the AMMI analysis were strongly associated with the morpho-physiological characters. The independent but parallel discrimination among genotypes reflects genetic differences and highlights the power of the AMMI analysis as a tool to investigate G x E. Characters which appear to be positively associated with yield in the germplasm under study could be identified for some environments.

Eccentricity Fluctuations Make Flow Measurable in High Multiplicity p-p Collisions

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

Casalderrey-Solana, Jorge; Wiedemann, Urs Achim

2010-03-12

Elliptic flow is a hallmark of collectivity in hadronic collisions. Its measurement relies on analysis techniques which require high event multiplicity and so far can only be applied to heavy ion collisions. Here, we delineate the conditions under which elliptic flow becomes measurable in the samples of high-multiplicity (dN{sub ch}/dy>=50) p-p collisions, which will soon be collected at the LHC. We observe that fluctuations in the p-p interaction region can result in a sizable spatial eccentricity even for the most central p-p collisions. Under relatively mild assumptions on the nature of such fluctuations and on the eccentricity scaling of ellipticmore » flow, we find that the resulting elliptic flow signal in high-multiplicity p-p collisions at the LHC becomes measurable with standard techniques.« less

Analysis of the Yule-Nielsen effect with the multiple-path point spread function in a frequency-modulated halftone.

PubMed

Rogers, Geoffrey

2018-06-01

The Yule-Nielsen effect is an influence on halftone color caused by the diffusion of light within the paper upon which the halftone ink is printed. The diffusion can be characterized by a point spread function. In this paper, a point spread function for paper is derived using the multiple-path model of reflection. This model treats the interaction of light with turbid media as a random walk. Using the multiple-path point spread function, a general expression is derived for the average reflectance of light from a frequency-modulated halftone, in which dot size is constant and the number of dots is varied, with the arrangement of dots random. It is also shown that the line spread function derived from the multiple-path model has the form of a Lorentzian function.

An Improved Wake Vortex Tracking Algorithm for Multiple Aircraft

NASA Technical Reports Server (NTRS)

Switzer, George F.; Proctor, Fred H.; Ahmad, Nashat N.; LimonDuparcmeur, Fanny M.

2010-01-01

The accurate tracking of vortex evolution from Large Eddy Simulation (LES) data is a complex and computationally intensive problem. The vortex tracking requires the analysis of very large three-dimensional and time-varying datasets. The complexity of the problem is further compounded by the fact that these vortices are embedded in a background turbulence field, and they may interact with the ground surface. Another level of complication can arise, if vortices from multiple aircrafts are simulated. This paper presents a new technique for post-processing LES data to obtain wake vortex tracks and wake intensities. The new approach isolates vortices by defining "regions of interest" (ROI) around each vortex and has the ability to identify vortex pairs from multiple aircraft. The paper describes the new methodology for tracking wake vortices and presents application of the technique for single and multiple aircraft.

Thermal photons in heavy ion collisions at 158 A GeV

NASA Astrophysics Data System (ADS)

Dutt, Sunil

2018-05-01

The essence of experimental ultra-relativistic heavy ion collision physics is the production and study of strongly interacting matter at extreme energy densities, temperatures and consequent search for equation of state of nuclear matter. The focus of the analysis has been to examine pseudo-rapidity distributions obtained for the γ-like particles in pre-shower photon multiplicity detector. This allows the extension of scaled factorial moment analysis to bin sizes smaller than those accessible to other experimental techniques. Scaled factorial moments are calculated using horizontal corrected and vertical analysis. The results are compared with simulation analysis using VENUS event generator.

Design and Mechanical Stability Analysis of the Interaction Region for the Inverse Compton Scattering Gamma-Ray Source Using Finite Element Method

NASA Astrophysics Data System (ADS)

Khizhanok, Andrei

Development of a compact source of high-spectral brilliance and high impulse frequency gamma rays has been in scope of Fermi National Accelerator Laboratory for quite some time. Main goal of the project is to develop a setup to support gamma rays detection test and gamma ray spectroscopy. Potential applications include but not limited to nuclear astrophysics, nuclear medicine, oncology ('gamma knife'). Present work covers multiple interconnected stages of development of the interaction region to ensure high levels of structural strength and vibrational resistance. Inverse Compton scattering is a complex phenomenon, in which charged particle transfers a part of its energy to a photon. It requires extreme precision as the interaction point is estimated to be 20 microm. The slightest deflection of the mirrors will reduce effectiveness of conversion by orders of magnitude. For acceptable conversion efficiency laser cavity also must have >1000 finesse value, which requires a trade-off between size, mechanical stability, complexity, and price of the setup. This work focuses on advantages and weak points of different designs of interaction regions as well as in-depth description of analyses performed. This includes laser cavity amplification and finesse estimates, natural frequency mapping, harmonic analysis. Structural analysis is required as interaction must occur under high vacuum conditions.

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

Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulatemore » gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.« less

Multi-criteria comparative evaluation of spallation reaction models

NASA Astrophysics Data System (ADS)

Andrianov, Andrey; Andrianova, Olga; Konobeev, Alexandr; Korovin, Yury; Kuptsov, Ilya

2017-09-01

This paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb.

Ritualizing Expertise: Non-Montessorian View of the Montessori Method

ERIC Educational Resources Information Center

Cossentino, Jacqueline

2005-01-01

This article examines the practice of Montessori education through the lens of ritual. Anchored by description and analysis of a lesson in an elementary classroom, the lesson is viewed as a series of ritualized interactions in which both teacher and student act out multiple layers of expertise within the cultural frame of the Montessori method.…

Dendrochemistry of multiple releases of chlorinated solvents at a former industrial site

Treesearch

Jean Christophe ​Balouet; Joel G. Burken; Frank Karg; Don Vroblesky; Kevin T. Smith; Håkan Grudd; Anders Rindby; François Beaujard; Michel Chalot

2012-01-01

Trees can take up and assimilate contaminants from soil, subsurface, and groundwater. Contaminants in the transpiration stream can become bound or incorporated into the annual rings formed in trees of the temperate zones. The chemical analysis of precisely dated tree rings, called dendrochemistry, can be used to interpret past plant interactions with contaminants. This...

Model-based scenario planning to develop climate change adaptation strategies for rare plant populations in grassland reserves

Treesearch

Laura Phillips-Mao; Susan M. Galatowitsch; Stephanie A. Snyder; Robert G. Haight

2016-01-01

Incorporating climate change into conservation decision-making at site and population scales is challenging due to uncertainties associated with localized climate change impacts and population responses to multiple interacting impacts and adaptation strategies. We explore the use of spatially explicit population models to facilitate scenario analysis, a conservation...

Student and Staff Perceptions of a Learning Management System for Blended Learning in Teacher Education

ERIC Educational Resources Information Center

Holmes, Kathryn A.; Prieto-Rodriguez, Elena

2018-01-01

Higher education institutions routinely use Learning Management Systems (LMS) for multiple purposes; to organise coursework and assessment, to facilitate staff and student interactions, and to act as repositories of learning objects. The analysis reported here involves staff (n = 46) and student (n = 470) responses to surveys as well as data…

Strategies to Enhance Student Success: A Discourse Analysis of Academic Advice in International Student Handbooks

ERIC Educational Resources Information Center

Romerhausen, Nick J.

2013-01-01

As the population of international students continues to rise at U.S. colleges and universities, multiple academic obstacles pose barriers to success. Research on strategies of intervention has primarily included face-to-face interactions while an exploration of other assistance approaches is minimal in comparison. This study explored the role…

Knowledge Systems and Value Chain Integration: The Case of Linseed Production in Ethiopia

ERIC Educational Resources Information Center

Chagwiza, Clarietta; Muradian, Roldan; Ruben, Ruerd

2017-01-01

Purpose: This study uses data from a sample of 150 oilseed farming households from Arsi Robe, Ethiopia, to assess the impact of different knowledge bases (education, training and experience) and their interactions on linseed productivity. Methodology: A multiple regression analysis was employed to assess the combined effect of the knowledge bases,…

Relative Salience of Gender and Class in a Situation of Multiple Competing Norms.

ERIC Educational Resources Information Center

Cravens, Thomas D.; Giannelli, Luciano

1995-01-01

Examines the social parameters of acceptance and spread of intervocalic spirantization of "/p/,/t/,/k/" in Tuscany to test the salience of gender and class. This sociolinguistic analysis of the interaction of three options provides a more precise understanding of the significance of gender and class as (co)-conditioners of variation and…

The Multiple Modes of Ideological Becoming: An Analysis of Kindergarteners' Appropriation of School Language and Literacy Discourses

ERIC Educational Resources Information Center

Lee, Soo Won; Hassett, Dawnene D.

2017-01-01

This study explores Mikhail Bakhtin's notion of ideological becoming (IB) in a bilingual (Korean and English) kindergarten classroom. For Bakhtin, IB is the process of appropriating authoritative discourse as one's own dialogic interactions. In our study, we view the literacy and language discourses of schooling as one type of authoritative…

Exploring the bases for a mixed reality stroke rehabilitation system, Part II: design of interactive feedback for upper limb rehabilitation.

PubMed

Lehrer, Nicole; Chen, Yinpeng; Duff, Margaret; L Wolf, Steven; Rikakis, Thanassis

2011-09-08

Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time.

Exploring the bases for a mixed reality stroke rehabilitation system, Part II: Design of Interactive Feedback for upper limb rehabilitation

PubMed Central

2011-01-01

Background Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. Results The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. Conclusions The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time. PMID:21899779

Interactive Visualization of Healthcare Data Using Tableau.

PubMed

Ko, Inseok; Chang, Hyejung

2017-10-01

Big data analysis is receiving increasing attention in many industries, including healthcare. Visualization plays an important role not only in intuitively showing the results of data analysis but also in the whole process of collecting, cleaning, analyzing, and sharing data. This paper presents a procedure for the interactive visualization and analysis of healthcare data using Tableau as a business intelligence tool. Starting with installation of the Tableau Desktop Personal version 10.3, this paper describes the process of understanding and visualizing healthcare data using an example. The example data of colon cancer patients were obtained from health insurance claims in years 2012 and 2013, provided by the Health Insurance Review and Assessment Service. To explore the visualization of healthcare data using Tableau for beginners, this paper describes the creation of a simple view for the average length of stay of colon cancer patients. Since Tableau provides various visualizations and customizations, the level of analysis can be increased with small multiples, view filtering, mark cards, and Tableau charts. Tableau is a software that can help users explore and understand their data by creating interactive visualizations. The software has the advantages that it can be used in conjunction with almost any database, and it is easy to use by dragging and dropping to create an interactive visualization expressing the desired format.

Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data.

PubMed

Greenwald, William W; Li, He; Smith, Erin N; Benaglio, Paola; Nariai, Naoki; Frazer, Kelly A

2017-04-07

Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from "genomic interaction" studies. As genomic interaction sequencing data are becoming prevalent, a standard file format and tools for working with these data conveniently and efficiently are needed. This article details a file standard and novel software tool suite for working with paired-genomic-loci data. We present the paired-genomic-loci (PGL) file standard for genomic-interactions data, and the accompanying analysis tool suite "pgltools": a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses. Pgltools is a freely available, open source tool suite for manipulating paired-genomic-loci data. Source code, an in-depth manual, and a tutorial are available publicly at www.github.com/billgreenwald/pgltools , and a python module of the operations can be installed from PyPI via the PyGLtools module.

Structure of an Arrestin2-clathrin Complex Reveals a Novel Clathrin Binding Domain that Modulates Receptor Trafficking

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

Kang, D.; Kern, R; Puthenveedu, M

2009-01-01

Non-visual arrestins play a pivotal role as adaptor proteins in regulating the signaling and trafficking of multiple classes of receptors. Although arrestin interaction with clathrin, AP-2, and phosphoinositides contributes to receptor trafficking, little is known about the configuration and dynamics of these interactions. Here, we identify a novel interface between arrestin2 and clathrin through x-ray diffraction analysis. The intrinsically disordered clathrin binding box of arrestin2 interacts with a groove between blades 1 and 2 in the clathrin {beta}-propeller domain, whereas an 8-amino acid splice loop found solely in the long isoform of arrestin2 (arrestin2L) interacts with a binding pocket formedmore » by blades 4 and 5 in clathrin. The apposition of the two binding sites in arrestin2L suggests that they are exclusive and may function in higher order macromolecular structures. Biochemical analysis demonstrates direct binding of clathrin to the splice loop in arrestin2L, whereas functional analysis reveals that both binding domains contribute to the receptor-dependent redistribution of arrestin2L to clathrin-coated pits. Mutagenesis studies reveal that the clathrin binding motif in the splice loop is (L/I){sub 2}GXL. Taken together, these data provide a framework for understanding the dynamic interactions between arrestin2 and clathrin and reveal an essential role for this interaction in arrestin-mediated endocytosis.« less

Genotype by environment interaction in Nelore cattle from five Brazilian states

PubMed Central

Diaz, Iara Del Pilar Solar; de Oliveira, Henrique Nunes; Bezerra, Luis Antônio Framartino; Lôbo, Raysildo Barbosa

2011-01-01

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection. PMID:21931516

Interactive effects of multiple climate change factors on ammonia oxidizers and denitrifiers in a temperate steppe.

PubMed

Zhang, Cui-Jing; Shen, Ju-Pei; Sun, Yi-Fei; Wang, Jun-Tao; Zhang, Li-Mei; Yang, Zhong-Ling; Han, Hong-Yan; Wan, Shi-Qiang; He, Ji-Zheng

2017-04-01

Global climate change could have profound effects on belowground microbial communities and subsequently affect soil biogeochemical processes. The interactive effects of multiple co-occurring climate change factors on microbially mediated processes are not well understood. A four-factorial field experiment with elevated CO2, watering, nitrogen (N) addition and night warming was conducted in a temperate steppe of northern China. Real-time polymerase chain reaction and terminal-restriction fragment length polymorphism, combined with clone library techniques, were applied to examine the effects of those climate change factors on N-related microbial abundance and community composition. Only the abundance of ammonia-oxidizing bacteria significantly increased by nitrogen addition and decreased by watering. The interactions of watering × warming on the bacterial amoA community and warming × nitrogen addition on the nosZ community were found. Redundancy analysis indicated that the ammonia-oxidizing archaeal community was affected by total N and total carbon, while the community of bacterial amoA and nosZ were significantly affected by soil pH. According to a structural equation modeling analysis, climate change influenced net primary production indirectly by altering microbial abundance and activities. These results indicated that microbial responses to the combination of chronic global change tend to be smaller than expected from single-factor global change manipulations. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multi-Sensor Fusion with Interacting Multiple Model Filter for Improved Aircraft Position Accuracy

PubMed Central

Cho, Taehwan; Lee, Changho; Choi, Sangbang

2013-01-01

The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter. PMID:23535715

Multi-sensor fusion with interacting multiple model filter for improved aircraft position accuracy.

PubMed

Cho, Taehwan; Lee, Changho; Choi, Sangbang

2013-03-27

The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

PubMed

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

Assocplots: a Python package for static and interactive visualization of multiple-group GWAS results.

PubMed

Khramtsova, Ekaterina A; Stranger, Barbara E

2017-02-01

Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile–quantile (QQ) plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here, we present Assocplots, a Python package for viewing and exploring GWAS results not only using classic static Manhattan and QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies. The Assocplots package is open source and distributed under the MIT license via GitHub (https://github.com/khramts/assocplots) along with examples, documentation and installation instructions. ekhramts@medicine.bsd.uchicago.edu or bstranger@medicine.bsd.uchicago.edu

Sex differences and HIV risk behaviors: the interaction between the experience of multiple types of abuse and self-restraint on HIV risk behaviors.

PubMed

Conrad, Selby M; Swenson, Rebecca R; Hancock, Evan; Brown, Larry K

2014-01-01

Adolescents with abuse histories have been shown to be at increased risk to acquire human immunodeficiency virus and sexually transmitted infections. In addition, teens with lower levels of self-restraint or higher levels of distress, such as those with psychiatric concerns, have also demonstrated increased sexual risk behaviors. This study explored sex differences in sexual risk behaviors among a sample of adolescents in a therapeutic/alternative high school setting. Moderated regression analysis showed that a lower level of self-restraint was associated with sexual risk behaviors in boys but not in girls. Rather, the interaction of self-restraint and multiple types of abuse was associated with greater sex risk within girls in this sample. Results suggest that girls and boys with abuse histories and low levels of self-restraint may have different intervention needs related to sexual risk behaviors.

ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

NASA Astrophysics Data System (ADS)

Roberts, D. Aaron; Boller, Ryan; Rezapkin, V.; Coleman, J.; McGuire, R.; Goldstein, M.; Kalb, V.; Kulkarni, R.; Luckyanova, M.; Byrnes, J.; Kerbel, U.; Candey, R.; Holmes, C.; Chimiak, R.; Harris, B.

2018-04-01

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

PubMed

Collins, Anne G E; Frank, Michael J

2018-03-06

Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

Multiple period s-p hybridization in nano-strip embedded photonic crystal.

PubMed

Han, Seunghoon; Lee, Il-Min; Kim, Hwi; Lee, Byoungho

2005-04-04

We report and analyze hybridization of s-state and p-state modes in photonic crystal one-dimensional defect cavity array. When embedding a nano-strip into a dielectric rod photonic crystal, an effective cavity array is made, where each cavity possesses two cavity modes: s-state and p-state. The two modes are laterally even versus the nano-strip direction, and interact with each other, producing defect bands, of which the group velocity becomes zero within the first Brillouin zone. We could model and describe the phenomena by using the tight-binding method, well agreeing with the plane-wave expansion method analysis. We note that the reported s- and p-state mode interaction corresponds to the hybridization of atomic orbital in solid-state physics. The concept of multiple period s-p hybridization and the proposed model can be useful for analyzing and developing novel photonic crystal waveguides and devices.

Multiple-interactions among EMILIN1 and EMILIN2 N- and C-terminal domains.

PubMed

Bot, Simonetta; Andreuzzi, Eva; Capuano, Alessandra; Schiavinato, Alvise; Colombatti, Alfonso; Doliana, Roberto

2015-01-01

EMILIN1 and EMILIN2 belong to a family of extracellular matrix glycoproteins characterized by the N-terminal cysteine-rich EMI domain, a long segment with high probabilty for coiled-coil structure formation and a C-terminal gC1q domain. To study EMILIN1 and EMILIN2 interaction and assembly we have applied qualitative and quantitative two hybrid systems using constructs corresponding to the gC1q and EMI domains. The identified interactions were further confirmed in yeast extracts of co-transfected cells followed by co-immunoprecipitation. The data indicated that gC1q domains are able to self-interact as well as to interact one each other and with the EMI domains, but no self interactions were detected between the EMI domains. Furthermore EMILINs interactions were studied in 293-EBNA cells co-transfected with full lenght EMILIN1 and EMILIN2 constructs. Specific antibodies were able to co-immunoprecipitate EMILINs, indicating that also full-lenght proteins can give rise to non-covalent homo- and hetero-multimers even if reduced and alkylated before mixing. Immunofluorescence analysis on mouse cell cultures and tissues sections with specific antibodies showed co-distribution of EMILIN1 and EMILIN2. Thus, we can hypothesize that EMILINs multimers are formed by head-to-tail interaction between C-terminal and N-terminal domains of EMILIN1 and/or EMILIN2 but also by tail-to-tail interaction between gC1q domains. These multiple interactions may regulate homo-typic and/or hetero-typic linear and eventually lateral branching assemblies of EMILIN1 and EMILIN2 in tissues. Copyright © 2014. Published by Elsevier B.V.

HaloTag Technology: A Versatile Platform for Biomedical Applications

PubMed Central

2015-01-01

Exploration of protein function and interaction is critical for discovering links among genomics, proteomics, and disease state; yet, the immense complexity of proteomics found in biological systems currently limits our investigational capacity. Although affinity and autofluorescent tags are widely employed for protein analysis, these methods have been met with limited success because they lack specificity and require multiple fusion tags and genetic constructs. As an alternative approach, the innovative HaloTag protein fusion platform allows protein function and interaction to be comprehensively analyzed using a single genetic construct with multiple capabilities. This is accomplished using a simplified process, in which a variable HaloTag ligand binds rapidly to the HaloTag protein (usually linked to the protein of interest) with high affinity and specificity. In this review, we examine all current applications of the HaloTag technology platform for biomedical applications, such as the study of protein isolation and purification, protein function, protein–protein and protein–DNA interactions, biological assays, in vitro cellular imaging, and in vivo molecular imaging. In addition, novel uses of the HaloTag platform are briefly discussed along with potential future applications. PMID:25974629

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

A System Biology Perspective on Environment-Host-Microbe Interactions.

PubMed

Chen, Lianmin; Garmaeva, Sanzhima; Zherankova, Alexandra; Fu, Jingyuan; Wijmenga, Cisca

2018-04-16

A vast, complex and dynamic consortium of microorganisms known as the gut microbiome colonizes the human gut. Over the past few decades we have developed an increased awareness of its important role in human health. In this review we discuss the role of the gut microbiome in complex diseases and the possible causal scenarios behind its interactions with the host genome and environmental factors. We then propose a new analysis framework that combines a systems biology approach, cross-kingdom integration of multiple levels of omics data, and innovative in vitro models to yield an integrated picture of human host-microbe interactions. This new framework will lay the foundation for the development of the next phase in personalized medicine.

Anti-inflammatory genes associated with multiple sclerosis: a gene expression study.

PubMed

Perga, S; Montarolo, F; Martire, S; Berchialla, P; Malucchi, S; Bertolotto, A

2015-02-15

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system caused by a complex interaction between multiple genes and environmental factors. HLA region is the strongest susceptibility locus, but recent huge genome-wide association studies identified new susceptibility genes. Among these, BACH2, PTGER4, RGS1 and ZFP36L1 were highlighted. Here, a gene expression analysis revealed that three of them, namely BACH2, PTGER4 and ZFP36L1, are down-regulated in MS patients' blood cells compared to healthy subjects. Interestingly, all these genes are involved in the immune system regulation with predominant anti-inflammatory role and their reduction could predispose to MS development. Copyright © 2015 Elsevier B.V. All rights reserved.

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.

4D-LQTA-QSAR and docking study on potent Gram-negative specific LpxC inhibitors: a comparison to CoMFA modeling.

PubMed

Ghasemi, Jahan B; Safavi-Sohi, Reihaneh; Barbosa, Euzébio G

2012-02-01

A quasi 4D-QSAR has been carried out on a series of potent Gram-negative LpxC inhibitors. This approach makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. This new methodology is based on the generation of a conformational ensemble profile, CEP, for each compound instead of only one conformation, followed by the calculation intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are independent variables employed in a QSAR analysis. The comparison of the proposed methodology to comparative molecular field analysis (CoMFA) formalism was performed. This methodology explores jointly the main features of CoMFA and 4D-QSAR models. Step-wise multiple linear regression was used for the selection of the most informative variables. After variable selection, multiple linear regression (MLR) and partial least squares (PLS) methods used for building the regression models. Leave-N-out cross-validation (LNO), and Y-randomization were performed in order to confirm the robustness of the model in addition to analysis of the independent test set. Best models provided the following statistics: [Formula in text] (PLS) and [Formula in text] (MLR). Docking study was applied to investigate the major interactions in protein-ligand complex with CDOCKER algorithm. Visualization of the descriptors of the best model helps us to interpret the model from the chemical point of view, supporting the applicability of this new approach in rational drug design.

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data.

PubMed

He, Jiuming; Huang, Luojiao; Tian, Runtao; Li, Tiegang; Sun, Chenglong; Song, Xiaowei; Lv, Yiwei; Luo, Zhigang; Li, Xin; Abliz, Zeper

2018-07-26

Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Role of DISC1 interacting proteins in schizophrenia risk from genome-wide analysis of missense SNPs.

PubMed

Costas, Javier; Suárez-Rama, Jose Javier; Carrera, Noa; Paz, Eduardo; Páramo, Mario; Agra, Santiago; Brenlla, Julio; Ramos-Ríos, Ramón; Arrojo, Manuel

2013-11-01

A balanced translocation affecting DISC1 cosegregates with several psychiatric disorders, including schizophrenia, in a Scottish family. DISC1 is a hub protein of a network of protein-protein interactions involved in multiple developmental pathways within the brain. Gene set-based analysis has been proposed as an alternative to individual analysis of single nucleotide polymorphisms (SNPs) to get information from genome-wide association studies. In this work, we tested for an overrepresentation of the DISC1 interacting proteins within the top results of our ranked list of genes based on our previous genome-wide association study of missense SNPs in schizophrenia. Our data set consisted of 5100 common missense SNPs genotyped in 476 schizophrenic patients and 447 control subjects from Galicia, NW Spain. We used a modification of the Gene Set Enrichment Analysis adapted for SNPs, as implemented in the GenGen software. The analysis detected an overrepresentation of the DISC1 interacting proteins (permuted P-value=0.0158), indicative of the role of this gene set in schizophrenia risk. We identified seven leading-edge genes, MACF1, UTRN, DST, DISC1, KIF3A, SYNE1, and AKAP9, responsible for the overrepresentation. These genes are involved in neuronal cytoskeleton organization and intracellular transport through the microtubule cytoskeleton, suggesting that these processes may be impaired in schizophrenia. © 2013 John Wiley & Sons Ltd/University College London.

Biana: a software framework for compiling biological interactions and analyzing networks

PubMed Central

2010-01-01

Background The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. Results We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. Conclusions BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules. PMID:20105306

Biana: a software framework for compiling biological interactions and analyzing networks.

PubMed

Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

2010-01-27

The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

Synchronization within, and interactions between, the default mode and dorsal attention networks in relapsing-remitting multiple sclerosis.

PubMed

Huang, Muhua; Zhou, Fuqing; Wu, Lin; Wang, Bo; Wan, Hui; Li, Fangjun; Zeng, Xianjun; Gong, Honghan

2018-01-01

The effects of the interactions between the default mode network (DMN) and the dorsal attention network (DAN), which present anticorrelated behaviors, in relapsing-remitting multiple sclerosis (RRMS) are poorly understood. This study used resting-state functional connectivity (FC) and the Granger causality test (GCT) to examine changes in the undirected and effective functional network connectivity (FNC) between the two networks during the remitting phase in RRMS patients. Thirty-three patients experiencing a clinically diagnosed remitting phase of RRMS and 33 well-matched healthy control subjects participated in this study. First, an independent component (IC) analysis was performed to preprocess the functional magnetic resonance imaging data and select resting-state networks. Then, an FNC analysis and the GCT were combined to examine the temporal correlations between the ICs of the DMN and DAN and to identify correlations with clinical markers. Compared with the healthy subjects, the RRMS patients in the remitting phase showed the following: 1) significantly decreased FC within the DAN in the postcentral gyrus and decreased FC within the DMN in several regions except the parahippocampal gyrus, where increased FC was observed; 2) a relatively stable interaction between the two anticorrelated networks as well as a driving connectivity from the DAN to DMN (IC15); and 3) significantly positive correlations between the connectivity coefficient of the right superior temporal gyrus and the Modified Fatigue Impact Scale score ( ρ = 0.379, p = 0.036). Adaptive mechanisms that maintain stable interactions might occur between the DMN and DAN during the remitting phase in RRMS patients.

Aerodynamic preliminary analysis system 2. Part 2: User's manuals

NASA Technical Reports Server (NTRS)

Divan, P.

1981-01-01

An aerodynamic analysis system based on potential theory at subsonic/supersonic speeds and impact type finite element solutions at hypersonic conditions is described. Three dimensional configurations having multiple nonplanar surfaces of arbitrary planform and bodies of noncircular contour may be analyzed. Static, rotary, and control longitudinal and lateral directional chracteristics may be generated. The analysis has been implemented on a time sharing system in conjunction with an input tablet digitizer and an interactive graphics input/output display and editing terminal to maximize its responsiveness to the preliminary analysis problem. Typical simulation indicates that program provides an efficient analysis for systematically performing various aerodynamic configuration tradeoff and evaluation studies.

Aerodynamic preliminary analysis system 2. Part 1: Theory

NASA Technical Reports Server (NTRS)

Bonner, E.; Clever, W.; Dunn, K.

1991-01-01

An aerodynamic analysis system based on potential theory at subsonic and/or supersonic speeds and impact type finite element solutions at hypersonic conditions is described. Three dimensional configurations having multiple nonplanar surfaces of arbitrary planform and bodies of noncircular contour may be analyzed. Static, rotary, and control longitudinal and lateral directional characteristics may be generated. The analysis was implemented on a time sharing system in conjunction with an input tablet digitizer and an interactive graphics input/output display and editing terminal to maximize its responsiveness to the preliminary analysis problem. The program provides an efficient analysis for systematically performing various aerodynamic configuration tradeoff and evaluation studies.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Giovanni: The Bridge between Data and Science

NASA Technical Reports Server (NTRS)

Shen, Suhung; Lynnes, Christopher; Kempler, Steven J.

2012-01-01

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

An activity theory perspective of how scenario-based simulations support learning: a descriptive analysis.

PubMed

Battista, Alexis

2017-01-01

The dominant frameworks for describing how simulations support learning emphasize increasing access to structured practice and the provision of feedback which are commonly associated with skills-based simulations. By contrast, studies examining student participants' experiences during scenario-based simulations suggest that learning may also occur through participation. However, studies directly examining student participation during scenario-based simulations are limited. This study examined the types of activities student participants engaged in during scenario-based simulations and then analyzed their patterns of activity to consider how participation may support learning. Drawing from Engeström's first-, second-, and third-generation activity systems analysis, an in-depth descriptive analysis was conducted. The study drew from multiple qualitative methods, namely narrative, video, and activity systems analysis, to examine student participants' activities and interaction patterns across four video-recorded simulations depicting common motivations for using scenario-based simulations (e.g., communication, critical patient management). The activity systems analysis revealed that student participants' activities encompassed three clinically relevant categories, including (a) use of physical clinical tools and artifacts, (b) social interactions, and (c) performance of structured interventions. Role assignment influenced participants' activities and the complexity of their engagement. Importantly, participants made sense of the clinical situation presented in the scenario by reflexively linking these three activities together. Specifically, student participants performed structured interventions, relying upon the use of physical tools, clinical artifacts, and social interactions together with interactions between students, standardized patients, and other simulated participants to achieve their goals. When multiple student participants were present, such as in a team-based scenario, they distributed the workload to achieve their goals. The findings suggest that student participants learned as they engaged in these scenario-based simulations when they worked to make sense of the patient's clinical presentation. The findings may provide insight into how student participants' meaning-making efforts are mediated by the cultural artifacts (e.g., physical clinical tools) they access, the social interactions they engage in, the structured interventions they perform, and the roles they are assigned. The findings also highlight the complex and emergent properties of scenario-based simulations as well as how activities are nested. Implications for learning, instructional design, and assessment are discussed.

The first in situ observation of torsional Alfvén waves during the interaction of large-scale magnetic clouds

NASA Astrophysics Data System (ADS)

Raghav, Anil N.; Kule, Ankita

2018-05-01

The large-scale magnetic cloud such as coronal mass ejections (CMEs) is the fundamental driver of the space weather. The interaction of the multiple-CMEs in interplanetary space affects their dynamic evolution and geo-effectiveness. The complex and merged multiple magnetic clouds appear as the in situ signature of the interacting CMEs. The Alfvén waves are speculated to be one of the major possible energy exchange/dissipation mechanism during the interaction. However, no such observational evidence has been found in the literature. The case studies of CME-CME collision events suggest that the magnetic and thermal energy of the CME is converted into the kinetic energy. Moreover, magnetic reconnection process is justified to be responsible for merging of multiple magnetic clouds. Here, we present unambiguous evidence of sunward torsional Alfvén waves in the interacting region after the super-elastic collision of multiple CMEs. The Walén relation is used to confirm the presence of Alfvén waves in the interacting region of multiple CMEs/magnetic clouds. We conclude that Alfvén waves and magnetic reconnection are the possible energy exchange/dissipation mechanisms during large-scale magnetic clouds collisions. This study has significant implications not only in CME-magnetosphere interactions but also in the interstellar medium where interactions of large-scale magnetic clouds are possible.

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

2016-02-01

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Single-Molecule Studies of Actin Assembly and Disassembly Factors

PubMed Central

Smith, Benjamin A.; Gelles, Jeff; Goode, Bruce L.

2014-01-01

The actin cytoskeleton is very dynamic and highly regulated by multiple associated proteins in vivo. Understanding how this system of proteins functions in the processes of actin network assembly and disassembly requires methods to dissect the mechanisms of activity of individual factors and of multiple factors acting in concert. The advent of single-filament and single-molecule fluorescence imaging methods has provided a powerful new approach to discovering actin-regulatory activities and obtaining direct, quantitative insights into the pathways of molecular interactions that regulate actin network architecture and dynamics. Here we describe techniques for acquisition and analysis of single-molecule data, applied to the novel challenges of studying the filament assembly and disassembly activities of actin-associated proteins in vitro. We discuss the advantages of single-molecule analysis in directly visualizing the order of molecular events, measuring the kinetic rates of filament binding and dissociation, and studying the coordination among multiple factors. The methods described here complement traditional biochemical approaches in elucidating actin-regulatory mechanisms in reconstituted filamentous networks. PMID:24630103

Dispersion of Response Times Reveals Cognitive Dynamics

ERIC Educational Resources Information Center

Holden, John G.; Van Orden, Guy C.; Turvey, Michael T.

2009-01-01

Trial-to-trial variation in word-pronunciation times exhibits 1/f scaling. One explanation is that human performances are consequent on multiplicative interactions among interdependent processes-interaction dominant dynamics. This article describes simulated distributions of pronunciation times in a further test for multiplicative interactions and…

A Study of Multiplicities in Hadronic Interactions (in Spanish)

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

Estrada Tristan, Nora Patricia; /San Luis Potosi U.

Using data from the SELEX (Fermilab E781) experiment obtained with a minimum-bias trigger, we study multiplicity and angular distributions of secondary particles produced in interactions in the experimental targets. We observe interactions of {Sigma}{sup -}, proton, {pi}{sup -}, and {pi}{sup +}, at beam momenta between 250 GeV/c and 650 GeV/c, in copper, polyethylene, graphite, and beryllium targets. We show that the multiplicity and angular distributions for meson and baryon beams at the same momentum are identical. We also show that the mean multiplicity increases with beam momentum, and presents only small variations with the target material.

Hydrodynamic Stability Analysis of Multi-jet Effects in Swirling Jet Combustors

NASA Astrophysics Data System (ADS)

Emerson, Benjamin; Lieuwen, Tim

2016-11-01

Many practical combustion devices use multiple swirling jets to stabilize flames. However, much of the understanding of swirling jet dynamics has been generated from experimental and computational studies of single reacting, swirling jets. A smaller body of literature has begun to explore the effects of multi-jet systems and the role of jet-jet interactions on the macro-system dynamics. This work uses local temporal and spatio-temporal stability analyses to isolate the hydrodynamic interactions of multiple reacting, swirling jets, characterized by jet diameter, D, and spacing, L. The results first identify the familiar helical modes in the single jet. Comparison to the multi-jet configuration reveals these same familiar modes simultaneously oscillating in each of the jets. Jet-jet interaction is mostly limited to a spatial synchronization of each jet's oscillations at the jet spacing values analyzed here (L/D =3.5). The presence of multiple jets vs a single jet has little influence on the temporal and absolute growth rates. The biggest difference between the single and multi-jet configurations is the presence of nearly degenerate pairs of hydrodynamic modes in the multi-jet case, with one mode dominated by oscillations in the inner jet, and the other in the outer jets. The close similarity between the single and multi-jet hydrodynamics lends insight into experiments from our group.

Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.

PubMed

Gritsenko, Valeriya; Hardesty, Russell L; Boots, Mathew T; Yakovenko, Sergiy

2016-01-01

Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.

Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming.

PubMed

Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong

2011-01-21

Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.

Meta-Analysis of Multiple Simulation-Based Experiments

DTIC Science & Technology

2013-06-01

Alberts et al ., 2010), C2 Approaches differ on at least three major aspects: the allocation of decision rights (ADR), the pattern of interaction among...results obtained from the meta-analysis support the hypothesis that more network-enabled C2 Approaches are more agile (for details see Bernier et al ...consult Bernier, Chan et al . (2013) for more details. DoI PoI ADR Figure 2: Mapping of all CiCs into each axis of the C2 Approach Space. 18th

Enabling a systems biology knowledgebase with gaggle and firegoose

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

Baliga, Nitin S.

The overall goal of this project was to extend the existing Gaggle and Firegoose systems to develop an open-source technology that runs over the web and links desktop applications with many databases and software applications. This technology would enable researchers to incorporate workflows for data analysis that can be executed from this interface to other online applications. The four specific aims were to (1) provide one-click mapping of genes, proteins, and complexes across databases and species; (2) enable multiple simultaneous workflows; (3) expand sophisticated data analysis for online resources; and enhance open-source development of the Gaggle-Firegoose infrastructure. Gaggle is anmore » open-source Java software system that integrates existing bioinformatics programs and data sources into a user-friendly, extensible environment to allow interactive exploration, visualization, and analysis of systems biology data. Firegoose is an extension to the Mozilla Firefox web browser that enables data transfer between websites and desktop tools including Gaggle. In the last phase of this funding period, we have made substantial progress on development and application of the Gaggle integration framework. We implemented the workspace to the Network Portal. Users can capture data from Firegoose and save them to the workspace. Users can create workflows to start multiple software components programmatically and pass data between them. Results of analysis can be saved to the cloud so that they can be easily restored on any machine. We also developed the Gaggle Chrome Goose, a plugin for the Google Chrome browser in tandem with an opencpu server in the Amazon EC2 cloud. This allows users to interactively perform data analysis on a single web page using the R packages deployed on the opencpu server. The cloud-based framework facilitates collaboration between researchers from multiple organizations. We have made a number of enhancements to the cmonkey2 application to enable and improve the integration within different environments, and we have created a new tools pipeline for generating EGRIN2 models in a largely automated way.« less

Low Back Pain Subgroups using Fear-Avoidance Model Measures: Results of a Cluster Analysis

PubMed Central

Beneciuk, Jason M.; Robinson, Michael E.; George, Steven Z.

2012-01-01

Objectives The purpose of this secondary analysis was to test the hypothesis that an empirically derived psychological subgrouping scheme based on multiple Fear-Avoidance Model (FAM) constructs would provide additional capabilities for clinical outcomes in comparison to a single FAM construct. Methods Patients (n = 108) with acute or sub-acute low back pain (LBP) enrolled in a clinical trial comparing behavioral physical therapy interventions to classification based physical therapy completed baseline questionnaires for pain catastrophizing (PCS), fear-avoidance beliefs (FABQ-PA, FABQ-W), and patient-specific fear (FDAQ). Clinical outcomes were pain intensity and disability measured at baseline, 4-weeks, and 6-months. A hierarchical agglomerative cluster analysis was used to create distinct cluster profiles among FAM measures and discriminant analysis was used to interpret clusters. Changes in clinical outcomes were investigated with repeated measures ANOVA and differences in results based on cluster membership were compared to FABQ-PA subgrouping used in the original trial. Results Three distinct FAM subgroups (Low Risk, High Specific Fear, and High Fear & Catastrophizing) emerged from cluster analysis. Subgroups differed on baseline pain and disability (p’s<.01) with the High Fear & Catastrophizing subgroup associated with greater pain than the Low Risk subgroup (p<.01) and the greatest disability (p’s<.05). Subgroup × time interactions were detected for both pain and disability (p’s<.05) with the High Fear & Catastrophizing subgroup reporting greater changes in pain and disability than other subgroups (p’s<.05). In contrast, FABQ-PA subgroups used in the original trial were not associated with interactions for clinical outcomes. Discussion These data suggest that subgrouping based on multiple FAM measures may provide additional information on clinical outcomes in comparison to determining subgroup status by FABQ-PA alone. Subgrouping methods for patients with LBP should include multiple psychological factors to further explore if patients can be matched with appropriate interventions. PMID:22510537

Assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity.

PubMed

Lee, Wen-Chung

2013-01-01

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the 'peril'. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the 'peril ratio index of synergy based on multiplicativity' (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of 'relative excess risk due to interaction'. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.

Considering interactive effects in the identification of influential regions with extremely rare variants via fixed bin approach

PubMed Central

2014-01-01

In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3). PMID:25519400

Investigating Mixture Interactions of Astringent Stimuli Using the Isobole Approach

PubMed Central

Fleming, Erin E.; Ziegler, Gregory R.

2016-01-01

Abstract Astringents (alum, malic acid, tannic acid) representing 3 broad classes (multivalent salts, organic acids, and polyphenols) were characterized alone, and as 2- and 3-component mixtures using isoboles. In experiment 1, participants rated 7 attributes (“astringency,” the sub-qualities “drying,” “roughing,” and “puckering,” and the side tastes “bitterness,” “sourness,” and “sweetness”) using direct scaling. Quality specific power functions were calculated for each stimulus. In experiment 2, the same participants characterized 2- and 3-component mixtures. Multiple factor analysis (MFA) and hierarchical clustering on attribute ratings across stimuli indicate “astringency” is highly related to “bitterness” as well as “puckering,” and the subqualities “drying” and “roughing” are somewhat redundant. Moreover, power functions were used to calculate indices of interaction (I) for each attribute/mixture combination. For “astringency,” there was evidence of antagonism, regardless of the type of mixture. Conversely, for subqualities, the pattern of interaction depended on the mixture type. Alum/tannic acid and tannic acid/malic acid mixtures showed evidence of synergy for “drying” and “roughing”; alum/malic acid mixtures showed evidence of antagonism for “drying,” “roughing,” and “puckering.” Collectively, these data clarify some semantic ambiguity regarding astringency and its subqualities, as well as the nature of interactions of among different types of astringents. Present data are not inconsistent with the idea that astringency arises from multiple mechanisms, although it remains to be determined whether the synergy observed here might reflect simultaneous activation of these multiple mechanisms. PMID:27252355

Assessing interactions among multiple physiological systems during walking outside a laboratory: An Android based gait monitor

PubMed Central

Sejdić, E.; Millecamps, A.; Teoli, J.; Rothfuss, M. A.; Franconi, N. G.; Perera, S.; Jones, A. K.; Brach, J. S.; Mickle, M. H.

2015-01-01

Gait function is traditionally assessed using well-lit, unobstructed walkways with minimal distractions. In patients with subclinical physiological abnormalities, these conditions may not provide enough stress on their ability to adapt to walking. The introduction of challenging walking conditions in gait can induce responses in physiological systems in addition to the locomotor system. There is a need for a device that is capable of monitoring multiple physiological systems in various walking conditions. To address this need, an Android-based gait-monitoring device was developed that enabled the recording of a patient's physiological systems during walking. The gait-monitoring device was tested during self-regulated overground walking sessions of fifteen healthy subjects that included 6 females and 9 males aged 18 to 35 years. The gait-monitoring device measures the patient's stride interval, acceleration, electrocardiogram, skin conductance and respiratory rate. The data is stored on an Android phone and is analyzed offline through the extraction of features in the time, frequency and time-frequency domains. The analysis of the data depicted multisystem physiological interactions during overground walking in healthy subjects. These interactions included locomotion-electrodermal, locomotion-respiratory and cardiolocomotion couplings. The current results depicting strong interactions between the locomotion system and the other considered systems (i.e., electrodermal, respiratory and cardivascular systems) warrant further investigation into multisystem interactions during walking, particularly in challenging walking conditions with older adults. PMID:26390946

Cocrystal structures of NC6.8 Fab identify key interactions for high potency sweetener recognition: implications for the design of synthetic sweeteners.

PubMed

Gokulan, Kuppan; Khare, Sangeeta; Ronning, Donald R; Linthicum, Scott D; Sacchettini, James C; Rupp, Bernhard

2005-07-26

The crystal structures of the murine monoclonal IgG2b(kappa) antibody NC6.8 Fab fragment complexed with high-potency sweetener compound SC45647 and nontasting high-affinity antagonist TES have been determined. The crystal structures show how sweetener potency is fine-tuned by multiple interactions between specific receptor residues and the functionally different groups of the sweeteners. Comparative analysis with the structure of NC6.8 complexed with the super-potency sweetener NC174 reveals that although the same residues in the antigen binding pocket of NC6.8 interact with the zwitterionic, trisubstituted guanidinium sweeteners as well as TES, specific differences exist and provide guidance for the design of new artificial sweeteners. In case of the nonsweetener TES, the interactions with the receptor are indirectly mediated through a hydrogen bonded water network, while the sweeteners bind with high affinity directly to the receptor. The presence of a hydrophobic group interacting with multiple receptor residues as a major determinant for sweet taste has been confirmed. The nature of the hydrophobic group is likely a discriminator for super- versus high-potency sweeteners, which can be exploited in the design of new, highly potent sweetener compounds. Overall similarities and partial conservation of interactions indicate that the NC6.8 Fab surrogate is representing crucial features of the T1R2 taste receptor VFTM binding site.

Diversity of multilayer networks and its impact on collaborating epidemics

NASA Astrophysics Data System (ADS)

Min, Yong; Hu, Jiaren; Wang, Weihong; Ge, Ying; Chang, Jie; Jin, Xiaogang

2014-12-01

Interacting epidemics on diverse multilayer networks are increasingly important in modeling and analyzing the diffusion processes of real complex systems. A viral agent spreading on one layer of a multilayer network can interact with its counterparts by promoting (cooperative interaction), suppressing (competitive interaction), or inducing (collaborating interaction) its diffusion on other layers. Collaborating interaction displays different patterns: (i) random collaboration, where intralayer or interlayer induction has the same probability; (ii) concentrating collaboration, where consecutive intralayer induction is guaranteed with a probability of 1; and (iii) cascading collaboration, where consecutive intralayer induction is banned with a probability of 0. In this paper, we develop a top-bottom framework that uses only two distributions, the overlaid degree distribution and edge-type distribution, to model collaborating epidemics on multilayer networks. We then state the response of three collaborating patterns to structural diversity (evenness and difference of network layers). For viral agents with small transmissibility, we find that random collaboration is more effective in networks with higher diversity (high evenness and difference), while the concentrating pattern is more suitable in uneven networks. Interestingly, the cascading pattern requires a network with moderate difference and high evenness, and the moderately uneven coupling of multiple network layers can effectively increase robustness to resist cascading failure. With large transmissibility, however, we find that all collaborating patterns are more effective in high-diversity networks. Our work provides a systemic analysis of collaborating epidemics on multilayer networks. The results enhance our understanding of biotic and informative diffusion through multiple vectors.

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

Expert Coaching in Weight Loss: Retrospective Analysis.

PubMed

Painter, Stefanie Lynn; Ahmed, Rezwan; Kushner, Robert F; Hill, James O; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2018-03-13

Providing coaches as part of a weight management program is a common practice to increase participant engagement and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices. The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight management and Web-based disease prevention solution. The study specifically examined the association between different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome. A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least one weight measurement beyond baseline. First, a detailed analysis of different coach-participant interaction was performed using both intent-to-treat and completer populations. Next, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving expert coaching sessions, live weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the impact on weight loss outcome. Participants in the Retrofit weight loss program lost a mean 5.14% (SE 0.14) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R 2 =.158, P<.001) identified the following top 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per week were associated with clinically significant weight loss. Participant's one-on-one expert coaching session attendance, live weekly expert-led interactive Web-based class attendance, and the number of food log feedback days per week from expert coach were significant predictors of weight loss in a 6-month intervention. ©Stefanie Lynn Painter, Rezwan Ahmed, Robert F Kushner, James O Hill, Richard Lindquist, Scott Brunning, Amy Margulies. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.03.2018.

Reported experiences from occupational therapists interacting with teachers in inclusive early childhood classrooms.

PubMed

Bose, Pia; Hinojosa, Jim

2008-01-01

This grounded theory study described the perspectives of school-based occupational therapists working in inclusive early childhood classrooms emphasizing interactions with teaching staff. Six therapists were interviewed multiple times over several months. The participants viewed their interactions with teaching staff as challenging but potentially rewarding experiences. Viewing collaboration as valuable, their descriptions nonetheless generally omitted many collaborative features, with therapists often assigned the role of "expert." Data analysis revealed four major themes: (1) "It's Not Like I Don't Value Collaboration" (the benefits of collaboration); (2) "Collaboration--I Can't Do It Alone" (the challenges of interactions); (3) "My Opinion, Please Ask for It" (attachment to the expert status), and (4) "Is This Collaboration?" (interactions in practice). The results of this study suggest that current recommendations for collaboration for inclusion in school-based occupational therapy are not optimally implemented in all practice settings.

An Exploratory Study to Measure Excessive Involvement in Multitasking Interaction with Smart Devices.

PubMed

Zhang, Yubo; Rau, Pei-Luen Patrick

2016-06-01

This study developed a scale measuring excessive involvement in multitasking interaction with smart devices. An online questionnaire was designed and surveyed in a sample of 380 respondents. The sample was split into two groups for exploratory and confirmatory factor analysis, respectively. A four-factor structure was identified with an acceptable goodness of fit. The first two factors, "Obsession and neglect" and "Problematic control," described the obsessive feelings, neglect behaviors, and behavior control problems accompanied by excessive multitasking interaction with smart devices. The latter two factors, "Multitasking preference" and "Polychronic orientation," referred to multitaskers' preference of engaging in multiple media use or interaction tasks rather than a single task from the time orientation perspective. The four-factor structure indicates that excessive involvement in multitasking interaction with smart devices shares some similarities with other behavioral addiction types, but demonstrates uniqueness compared with excessive engagement in single media use.

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

Beck, Ashley; Hunt, Kristopher; Bernstein, Hans C.

Interest in microbial communities for bioprocessing has surged in recent years based on the potential to optimize multiple tasks simultaneously and to enhance process productivity and stability. The presence and magnitude of these desirable system properties often result from interactions between functionally distinct community members. The importance of interactions, while appreciated by some disciplines for decades, has gained interest recently due to the development of ‘omics techniques, polymicrobial culturing approaches, and computational methods which has made the systems-level analysis of interacting components more tractable. This review defines and categorizes natural and engineered system components, interactions, and emergent properties, as wellmore » as presents three ecological theories relevant to microbial communities. Case studies are interpreted to illustrate components, interactions, emergent properties and agreement with theoretical concepts. A general foundation is laid to facilitate interpretation of current systems and to aid in future design of microbial systems for the next generation of bioprocesses.« less

[Epilepsy and videogame: which physiopathological mechanisms to expect?].

PubMed

Masnou, P; Nahum-Moscovoci, L

1999-04-01

Video games may induce epileptic seizures in some subjects. Most of them have photosensitive epilepsy. The triggering factors are multiple: characteristics of the softwares, effects of the electronic screen and interactivity. The wide diffusion of the video games explain the large number of descriptions of videogame induced seizures. Historical aspects and an analysis of the underlying mechanisms of videogame induced seizures are presented.

Multiple Identities, Negotiations, and Agency across Time and Space: A Narrative Inquiry of a Foreign Language Teacher Candidate

ERIC Educational Resources Information Center

Kayi-Aydar, Hayriye

2015-01-01

Drawing on the post-structural views and the literature on teacher identity and agency, and using narrative inquiry, this paper describes how one teacher candidate majoring in Spanish negotiated her identities across time and space and how her identity negotiations interacted with her agency. The recursive analysis of qualitative data sources…

Building the ECON extension: Functionality and lessons learned

Treesearch

Fred C. Martin

2008-01-01

The functionality of the ECON extension to FVS is described with emphasis on the ability to dynamically interact with all elements of the FVS simulation process. Like other extensions, ECON is fully integrated within FVS. This integration allows: (1) analysis of multiple alternative tree-removal actions within a single simulation without altering “normal” stand...

Implications of Interactions among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

ERIC Educational Resources Information Center

Deering, Pamela Rose

2014-01-01

This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…

Multivariate interactive digital analysis system /MIDAS/ - A new fast multispectral recognition system

NASA Technical Reports Server (NTRS)

Kriegler, F.; Marshall, R.; Lampert, S.; Gordon, M.; Cornell, C.; Kistler, R.

1973-01-01

The MIDAS system is a prototype, multiple-pipeline digital processor mechanizing the multivariate-Gaussian, maximum-likelihood decision algorithm operating at 200,000 pixels/second. It incorporates displays and film printer equipment under control of a general purpose midi-computer and possesses sufficient flexibility that operational versions of the equipment may be subsequently specified as subsets of the system.

A reproducible approach to high-throughput biological data acquisition and integration

PubMed Central

Rahnavard, Gholamali; Waldron, Levi; McIver, Lauren; Shafquat, Afrah; Franzosa, Eric A.; Miropolsky, Larissa; Sweeney, Christopher

2015-01-01

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. PMID:26157642

AIM: a comprehensive Arabidopsis interactome module database and related interologs in plants.

PubMed

Wang, Yi; Thilmony, Roger; Zhao, Yunjun; Chen, Guoping; Gu, Yong Q

2014-01-01

Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules that were generated using multiple analysis methods and integration of microarray expression data. All the modules in AIM are well annotated using multiple gene function knowledge databases. AIM provides a user-friendly interface for different types of searches and offers a powerful graphical viewer for displaying module networks linked to the enrichment annotation terms. Both interactive Venn diagram and power graph viewer are integrated into the database for easy comparison of modules. In addition, predicted interologs from other plant species (homologous proteins from different species that share a conserved interaction module) are available for each Arabidopsis module. AIM is a powerful systems biology platform for obtaining valuable insights into the function of proteins in Arabidopsis and other plants using the modules of the Arabidopsis interactome. Database URL:http://probes.pw.usda.gov/AIM Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

A Multilevel Multiset Time-Series Model for Describing Complex Developmental Processes

PubMed Central

Ma, Xin; Shen, Jianping

2017-01-01

The authors sought to develop an analytical platform where multiple sets of time series can be examined simultaneously. This multivariate platform capable of testing interaction effects among multiple sets of time series can be very useful in empirical research. The authors demonstrated that the multilevel framework can readily accommodate this analytical capacity. Given their intention to use the multilevel multiset time-series model to pursue complicated research purposes, their resulting model is relatively simple to specify, to run, and to interpret. These advantages make the adoption of their model relatively effortless as long as researchers have the basic knowledge and skills in working with multilevel growth modeling. With multiple potential extensions of their model, the establishment of this analytical platform for analysis of multiple sets of time series can inspire researchers to pursue far more advanced research designs to address complex developmental processes in reality. PMID:29881094

Unstart coupling mechanism analysis of multiple-modules hypersonic inlet.

PubMed

Hu, Jichao; Chang, Juntao; Wang, Lei; Cao, Shibin; Bao, Wen

2013-01-01

The combination of multiplemodules in parallel manner is an important way to achieve the much higher thrust of scramjet engine. For the multiple-modules scramjet engine, when inlet unstarted oscillatory flow appears in a single-module engine due to high backpressure, how to interact with each module by massflow spillage, and whether inlet unstart occurs in other modules are important issues. The unstarted flowfield and coupling characteristic for a three-module hypersonic inlet caused by center module II and side module III were, conducted respectively. The results indicate that the other two hypersonic inlets are forced into unstarted flow when unstarted phenomenon appears on a single-module hypersonic inlet due to high backpressure, and the reversed flow in the isolator dominates the formation, expansion, shrinkage, and disappearance of the vortexes, and thus, it is the major factor of unstart coupling of multiple-modules hypersonic inlet. The coupling effect among multiple modules makes hypersonic inlet be more likely unstarted.

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

imDEV: a graphical user interface to R multivariate analysis tools in Microsoft Excel.

PubMed

Grapov, Dmitry; Newman, John W

2012-09-01

Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R's multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010).

Mass Spec Studio for Integrative Structural Biology

PubMed Central

Rey, Martial; Sarpe, Vladimir; Burns, Kyle; Buse, Joshua; Baker, Charles A.H.; van Dijk, Marc; Wordeman, Linda; Bonvin, Alexandre M.J.J.; Schriemer, David C.

2015-01-01

SUMMARY The integration of biophysical data from multiple sources is critical for developing accurate structural models of large multiprotein systems and their regulators. Mass spectrometry (MS) can be used to measure the insertion location for a wide range of topographically sensitive chemical probes, and such insertion data provide a rich, but disparate set of modeling restraints. We have developed a software platform that integrates the analysis of label-based MS data with protein modeling activities (Mass Spec Studio). Analysis packages can mine any labeling data from any mass spectrometer in a proteomics-grade manner, and link labeling methods with data-directed protein interaction modeling using HADDOCK. Support is provided for hydrogen/ deuterium exchange (HX) and covalent labeling chemistries, including novel acquisition strategies such as targeted HX-tandem MS (MS2) and data-independent HX-MS2. The latter permits the modeling of highly complex systems, which we demonstrate by the analysis of microtubule interactions. PMID:25242457

Interparental Conflict and Parental Divorce: The Individual, Relative, and Interactive Effects on Adolescents across Four Years.

ERIC Educational Resources Information Center

Forehand, Rex; And Others

1994-01-01

Describes investigation examining individual, relative, and interactive influences of parental divorce and interparental conflict on adolescent functioning. Results demonstrate that multiple areas of functioning in multiple years were predicted by parental divorce, current interparental conflict, and interaction of both variables. (CRR)

Interactions among genetic variants in apoptosis pathway genes, reflux symptoms, body mass index, and smoking indicate two distinct etiologic patterns of esophageal adenocarcinoma.

PubMed

Zhai, Rihong; Chen, Feng; Liu, Geoffrey; Su, Li; Kulke, Matthew H; Asomaning, Kofi; Lin, Xihong; Heist, Rebecca S; Nishioka, Norman S; Sheu, Chau-Chyun; Wain, John C; Christiani, David C

2010-05-10

Apoptosis pathway, gastroesophageal reflux symptoms (reflux), higher body mass index (BMI), and tobacco smoking have been individually associated with esophageal adenocarcinoma (EA) development. However, how multiple factors jointly affect EA risk remains unclear. In total, 305 patients with EA and 339 age- and sex-matched controls were studied. High-order interactions among reflux, BMI, smoking, and functional polymorphisms in five apoptotic genes (FAS, FASL, IL1B, TP53BP, and BAT3) were investigated by entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional logistic regression (LR) models. In LR analysis, reflux, BMI, and smoking were significantly associated with EA risk, with reflux as the strongest individual factor. No individual single nucleotide polymorphism was associated with EA susceptibility. However, there was a two-way interaction between IL1B + 3954C>T and reflux (P = .008). In both CART and MDR analyses, reflux was also the strongest individual factor for EA risk. In individuals with reflux symptoms, CART analysis indicated that strongest interaction was among variant genotypes of IL1B + 3954C>T and BAT3S625P, higher BMI, and smoking (odds ratio [OR], 5.76; 95% CI, 2.48 to 13.38), a finding independently found using MDR analysis. In contrast, for participants without reflux symptoms, the strongest interaction was found between higher BMI and smoking (OR, 3.27; 95% CI, 1.88 to 5.68), also echoed by entropy-based MDR analysis. Although a history of reflux is an important risk for EA, multifactor interactions also play important roles in EA risk. Gene-environment interaction patterns differ between patients with and without reflux symptoms.

A rapid co-culture stamping device for studying intercellular communication.

PubMed

Hassanzadeh-Barforoushi, Amin; Shemesh, Jonathan; Farbehi, Nona; Asadnia, Mohsen; Yeoh, Guan Heng; Harvey, Richard P; Nordon, Robert E; Warkiani, Majid Ebrahimi

2016-10-18

Regulation of tissue development and repair depends on communication between neighbouring cells. Recent advances in cell micro-contact printing and microfluidics have facilitated the in-vitro study of homotypic and heterotypic cell-cell interaction. Nonetheless, these techniques are still complicated to perform and as a result, are seldom used by biologists. We report here development of a temporarily sealed microfluidic stamping device which utilizes a novel valve design for patterning two adherent cell lines with well-defined interlacing configurations to study cell-cell interactions. We demonstrate post-stamping cell viability of >95%, the stamping of multiple adherent cell types, and the ability to control the seeded cell density. We also show viability, proliferation and migration of cultured cells, enabling analysis of co-culture boundary conditions on cell fate. We also developed an in-vitro model of endothelial and cardiac stem cell interactions, which are thought to regulate coronary repair after myocardial injury. The stamp is fabricated using microfabrication techniques, is operated with a lab pipettor and uses very low reagent volumes of 20 μl with cell injection efficiency of >70%. This easy-to-use device provides a general strategy for micro-patterning of multiple cell types and will be important for studying cell-cell interactions in a multitude of applications.

Investigating interactions between phospholipase B-Like 2 and antibodies during Protein A chromatography.

PubMed

Tran, Benjamin; Grosskopf, Vanessa; Wang, Xiangdan; Yang, Jihong; Walker, Don; Yu, Christopher; McDonald, Paul

2016-03-18

Purification processes for therapeutic antibodies typically exploit multiple and orthogonal chromatography steps in order to remove impurities, such as host-cell proteins. While the majority of host-cell proteins are cleared through purification processes, individual host-cell proteins such as Phospholipase B-like 2 (PLBL2) are more challenging to remove and can persist into the final purification pool even after multiple chromatography steps. With packed-bed chromatography runs using host-cell protein ELISAs and mass spectrometry analysis, we demonstrated that different therapeutic antibodies interact to varying degrees with host-cell proteins in general, and PLBL2 specifically. We then used a high-throughput Protein A chromatography method to further examine the interaction between our antibodies and PLBL2. Our results showed that the co-elution of PLBL2 during Protein A chromatography is highly dependent on the individual antibody and PLBL2 concentration in the chromatographic load. Process parameters such as antibody resin load density and pre-elution wash conditions also influence the levels of PLBL2 in the Protein A eluate. Furthermore, using surface plasmon resonance, we demonstrated that there is a preference for PLBL2 to interact with IgG4 subclass antibodies compared to IgG1 antibodies. Copyright © 2016 Elsevier B.V. All rights reserved.

A rapid co-culture stamping device for studying intercellular communication

NASA Astrophysics Data System (ADS)

Hassanzadeh-Barforoushi, Amin; Shemesh, Jonathan; Farbehi, Nona; Asadnia, Mohsen; Yeoh, Guan Heng; Harvey, Richard P.; Nordon, Robert E.; Warkiani, Majid Ebrahimi

2016-10-01

Regulation of tissue development and repair depends on communication between neighbouring cells. Recent advances in cell micro-contact printing and microfluidics have facilitated the in-vitro study of homotypic and heterotypic cell-cell interaction. Nonetheless, these techniques are still complicated to perform and as a result, are seldom used by biologists. We report here development of a temporarily sealed microfluidic stamping device which utilizes a novel valve design for patterning two adherent cell lines with well-defined interlacing configurations to study cell-cell interactions. We demonstrate post-stamping cell viability of >95%, the stamping of multiple adherent cell types, and the ability to control the seeded cell density. We also show viability, proliferation and migration of cultured cells, enabling analysis of co-culture boundary conditions on cell fate. We also developed an in-vitro model of endothelial and cardiac stem cell interactions, which are thought to regulate coronary repair after myocardial injury. The stamp is fabricated using microfabrication techniques, is operated with a lab pipettor and uses very low reagent volumes of 20 μl with cell injection efficiency of >70%. This easy-to-use device provides a general strategy for micro-patterning of multiple cell types and will be important for studying cell-cell interactions in a multitude of applications.

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

Son, Ora; Kim, Sunghan; Hur, Yoon-Sun

TOR (target of rapamycin) kinase signaling plays central role as a regulator of growth and proliferation in all eukaryotic cells and its key signaling components and effectors are also conserved in plants. Unlike the mammalian and yeast counterparts, however, we found through yeast two-hybrid analysis that multiple regions of the Arabidopsis Raptor (regulatory associated protein of TOR) are required for binding to its substrate. We also identified that a 44-amino acid region at the N-terminal end of Arabidopsis ribosomal S6 kinase 1 (AtS6K1) specifically interacted with AtRaptor1, indicating that this region may contain a functional equivalent of the TOS (TOR-Signaling)more » motif present in the mammalian TOR substrates. Transient over-expression of this 44-amino acid fragment in Arabidopsis protoplasts resulted in significant decrease in rDNA transcription, demonstrating a feasibility of developing a new plant-specific TOR signaling inhibitor based upon perturbation of the Raptor-substrate interaction. - Highlights: • Multiple regions on the Arabidopsis Raptor protein were found to be involved in substrate binding. • N-terminal end of the Arabidopsis ribosomal S6 kinase 1 (AtS6K1) was responsible for interacting with AtRaptor1. • The Raptor-interacting fragment of AtS6K1 could be utilized as an effective inhibitor of plant TOR signaling.« less

Study of cosmic ray events with high muon multiplicity using the ALICE detector at the CERN Large Hadron Collider

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

Collaboration: ALICE Collaboration

2016-01-01

ALICE is one of four large experiments at the CERN Large Hadron Collider near Geneva, specially designed to study particle production in ultra-relativistic heavy-ion collisions. Located 52 meters underground with 28 meters of overburden rock, it has also been used to detect muons produced by cosmic ray interactions in the upper atmosphere. In this paper, we present the multiplicity distribution of these atmospheric muons and its comparison with Monte Carlo simulations. This analysis exploits the large size and excellent tracking capability of the ALICE Time Projection Chamber. A special emphasis is given to the study of high multiplicity events containingmore » more than 100 reconstructed muons and corresponding to a muon areal density ρ{sub μ} > 5.9 m{sup −2}. Similar events have been studied in previous underground experiments such as ALEPH and DELPHI at LEP. While these experiments were able to reproduce the measured muon multiplicity distribution with Monte Carlo simulations at low and intermediate multiplicities, their simulations failed to describe the frequency of the highest multiplicity events. In this work we show that the high multiplicity events observed in ALICE stem from primary cosmic rays with energies above 10{sup 16} eV and that the frequency of these events can be successfully described by assuming a heavy mass composition of primary cosmic rays in this energy range. The development of the resulting air showers was simulated using the latest version of QGSJET to model hadronic interactions. This observation places significant constraints on alternative, more exotic, production mechanisms for these events.« less

TreeQ-VISTA: An Interactive Tree Visualization Tool withFunctional Annotation Query Capabilities

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

Gu, Shengyin; Anderson, Iain; Kunin, Victor

2007-05-07

Summary: We describe a general multiplatform exploratorytool called TreeQ-Vista, designed for presenting functional annotationsin a phylogenetic context. Traits, such as phenotypic and genomicproperties, are interactively queried from a relational database with auser-friendly interface which provides a set of tools for users with orwithout SQL knowledge. The query results are projected onto aphylogenetic tree and can be displayed in multiple color groups. A richset of browsing, grouping and query tools are provided to facilitatetrait exploration, comparison and analysis.Availability: The program,detailed tutorial and examples are available online athttp://genome-test.lbl.gov/vista/TreeQVista.

Rocket observations of the precipitation of electrons by ground VLF transmitters

NASA Technical Reports Server (NTRS)

Arnoldy, Roger L.; Kintner, Paul M.

1989-01-01

Recent results obtained with electric and magnetic receivers aboard a NASA sounding rocket launched on July 31, 1987 are presented which relate multiple electron spectral peaks observed in the bounce loss cone fluxes to the resonant interaction of electrons with VLF waves from ground transmitters. The correlation of transmitter signals passing through the ionosphere with the precipitated electrons was investigated. The analysis of these in situ wave and particle data addresses the propagation of waves through the ionosphere, and, through an application of the resonant theory, enables an estimation of the cold plasma density in the interaction region.

The Homeodomain of PDX-1 Mediates Multiple Protein-Protein Interactions in the Formation of a Transcriptional Activation Complex on the Insulin Promoter

PubMed Central

Ohneda, Kinuko; Mirmira, Raghavendra G.; Wang, Juehu; Johnson, Jeffrey D.; German, Michael S.

2000-01-01

Activation of insulin gene transcription specifically in the pancreatic β cells depends on multiple nuclear proteins that interact with each other and with sequences on the insulin gene promoter to build a transcriptional activation complex. The homeodomain protein PDX-1 exemplifies such interactions by binding to the A3/4 region of the rat insulin I promoter and activating insulin gene transcription by cooperating with the basic-helix-loop-helix (bHLH) protein E47/Pan1, which binds to the adjacent E2 site. The present study provides evidence that the homeodomain of PDX-1 acts as a protein-protein interaction domain to recruit multiple proteins, including E47/Pan1, BETA2/NeuroD1, and high-mobility group protein I(Y), to an activation complex on the E2A3/4 minienhancer. The transcriptional activity of this complex results from the clustering of multiple activation domains capable of interacting with coactivators and the basal transcriptional machinery. These interactions are not common to all homeodomain proteins: the LIM homeodomain protein Lmx1.1 can also activate the E2A3/4 minienhancer in cooperation with E47/Pan1 but does so through different interactions. Cooperation between Lmx1.1 and E47/Pan1 results not only in the aggregation of multiple activation domains but also in the unmasking of a potent activation domain on E47/Pan1 that is normally silent in non-β cells. While more than one activation complex may be capable of activating insulin gene transcription through the E2A3/4 minienhancer, each is dependent on multiple specific interactions among a unique set of nuclear proteins. PMID:10629047

Perspectives of Patients, Clinicians, and Health System Leaders on Changes Needed to Improve the Health Care and Outcomes of Older Adults With Multiple Chronic Conditions.

PubMed

Ferris, Rosie; Blaum, Caroline; Kiwak, Eliza; Austin, Janet; Esterson, Jessica; Harkless, Gene; Oftedahl, Gary; Parchman, Michael; Van Ness, Peter H; Tinetti, Mary E

2018-06-01

To ascertain perspectives of multiple stakeholders on contributors to inappropriate care for older adults with multiple chronic conditions. Perspectives of 36 purposively sampled patients, clinicians, health systems, and payers were elicited. Data analysis followed a constant comparative method. Structural factors triggering burden and fragmentation include disease-based quality metrics and need to interact with multiple clinicians. The key cultural barrier identified is the assumption that "physicians know best." Inappropriate decision making may result from inattention to trade-offs and adherence to multiple disease guidelines. Stakeholders recommended changes in culture, structure, and decision making. Care options and quality metrics should reflect a focus on patients' priorities. Clinician-patient partnerships should reflect patients knowing their health goals and clinicians knowing how to achieve them. Access to specialty expertise should not require visits. Stakeholders' recommendations suggest health care redesigns that incorporate patients' health priorities into care decisions and realign relationships across patients and clinicians.

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

DOE PAGES

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan; ...

2016-04-15

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction networkmore » between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.« less

A high-confidence interaction map identifies SIRT1 as a mediator of acetylation of USP22 and the SAGA coactivator complex.

PubMed

Armour, Sean M; Bennett, Eric J; Braun, Craig R; Zhang, Xiao-Yong; McMahon, Steven B; Gygi, Steven P; Harper, J Wade; Sinclair, David A

2013-04-01

Although many functions and targets have been attributed to the histone and protein deacetylase SIRT1, a comprehensive analysis of SIRT1 binding proteins yielding a high-confidence interaction map has not been established. Using a comparative statistical analysis of binding partners, we have assembled a high-confidence SIRT1 interactome. Employing this method, we identified the deubiquitinating enzyme ubiquitin-specific protease 22 (USP22), a component of the deubiquitinating module (DUBm) of the SAGA transcriptional coactivating complex, as a SIRT1-interacting partner. We found that this interaction is highly specific, requires the ZnF-UBP domain of USP22, and is disrupted by the inactivating H363Y mutation within SIRT1. Moreover, we show that USP22 is acetylated on multiple lysine residues and that alteration of a single lysine (K129) within the ZnF-UBP domain is sufficient to alter interaction of the DUBm with the core SAGA complex. Furthermore, USP22-mediated recruitment of SIRT1 activity promotes the deacetylation of individual SAGA complex components. Our results indicate an important role of SIRT1-mediated deacetylation in regulating the formation of DUBm subcomplexes within the larger SAGA complex.

Genetic variation in SLC7A2 interacts with calcium and magnesium intakes in modulating the risk of colorectal polyps.

PubMed

Sun, Pin; Zhu, Xiangzhu; Shrubsole, Martha J; Ness, Reid M; Hibler, Elizabeth A; Cai, Qiuyin; Long, Jirong; Chen, Zhi; Li, Guoliang; Hou, Lifang; Smalley, Walter E; Edwards, Todd L; Giovannucci, Edward; Zheng, Wei; Dai, Qi

2017-09-01

Solute carrier family 7, member 2 (SLC7A2) gene encodes a protein called cationic amino acid transporter 2, which mediates the transport of arginine, lysine and ornithine. l-Arginine is necessary for cancer development and progression, including an important role in colorectal cancer pathogenesis. Furthermore, previous studies found that both calcium and magnesium inhibit the transport of arginine. Thus, calcium, magnesium or calcium:magnesium intake ratio may interact with polymorphisms in the SLC7A2 gene in association with colorectal cancer. We conducted a two-phase case-control study within the Tennessee Colorectal Polyps Study. In the first phase, 23 tagging single-nucleotide polymorphisms in the SLC7A2 gene were included for 725 colorectal adenoma cases and 755 controls. In the second phase conducted in an independent set of 607 cases and 2113 controls, we replicated the significant findings in the first phase. We observed that rs2720574 significantly interacted with calcium:magnesium intake ratio in association with odds of adenoma, particularly multiple/advanced adenoma. In the combined analysis, among those with a calcium:magnesium intake ratio below 2.78, individuals who carried GC/CC genotypes demonstrated higher odds of adenoma [OR (95% CI):1.36 (1.11-1.68)] and multiple/advanced adenoma [OR (95% CI): 1.68 (1.28, 2.20)] than those who carried the GG genotype. The P values for interactions between calcium:magnesium intake ratio and rs2720574 were .002 for all adenomas and <.001 for multiple/advanced adenoma. Among those with the GG genotype, a high calcium:magnesium ratio was associated with increased odds of colorectal adenoma [OR (95% CI): 1.73 (1.27-2.36)] and advanced/multiple adenomas [1.62 (1.05-2.50)], whereas among those with the GC/CC genotypes, high calcium:magnesium ratio was related to reduced odds of colorectal adenoma [0.64 (0.42-0.99)] and advanced/multiple adenomas [0.55 (0.31-1.00)]. Copyright © 2017 Elsevier Inc. All rights reserved.

Income, housing, and fire injuries: a census tract analysis.

PubMed

Shai, Donna

2006-01-01

This study investigates the social and demographic correlates of nonfatal structural fire injury rates for the civilian population for Philadelphia census tracts during 1993-2001. The author analyzed 1,563 fire injuries by census tract using the 1990 census (STF 3) and unpublished data from the Office of the Fire Marshal of the Philadelphia Fire Department. Injury rates were calculated per 1,000 residents of a given census tract. Multiple regression was used to determine significant variables in predicting fire injuries in a given census tract over a nine-year period and interaction effects between two of these variables-age of housing and income. Multiple regression analysis indicates that older housing (prior to 1940), low income, the prevalence of vacant houses, and the ability to speak English have significant independent effects on fire injury rates in Philadelphia. In addition, the results show a significant interaction between older housing and low income. Given the finding of very high rates of fire injuries in census tracts that are both low income and have older housing, fire prevention units can take preventative measures. Fire protection devices, especially smoke alarms, should be distributed in the neighborhoods most at risk. Multiple occupancy dwellings should have sprinkler systems and fire extinguishers. Laws concerning the maintenance of older rental housing need to be strictly enforced. Vacant houses should be effectively boarded up or renovated for residential use. Fire prevention material should be distributed in a number of languages to meet local needs.

Lipid-associated oral delivery: Mechanisms and analysis of oral absorption enhancement.

PubMed

Rezhdo, Oljora; Speciner, Lauren; Carrier, Rebecca

2016-10-28

The majority of newly discovered oral drugs are poorly water soluble, and co-administration with lipids has proven effective in significantly enhancing bioavailability of some compounds with low aqueous solubility. Yet, lipid-based delivery technologies have not been widely employed in commercial oral products. Lipids can impact drug transport and fate in the gastrointestinal (GI) tract through multiple mechanisms including enhancement of solubility and dissolution kinetics, enhancement of permeation through the intestinal mucosa, and triggering drug precipitation upon lipid emulsion depletion (e.g., by digestion). The effect of lipids on drug absorption is currently not quantitatively predictable, in part due to the multiple complex dynamic processes that can be impacted by lipids. Quantitative mechanistic analysis of the processes significant to lipid system function and overall impact on drug absorption can aid in the understanding of drug-lipid interactions in the GI tract and exploitation of such interactions to achieve optimal lipid-based drug delivery. In this review, we discuss the impact of co-delivered lipids and lipid digestion on drug dissolution, partitioning, and absorption in the context of the experimental tools and associated kinetic expressions used to study and model these processes. The potential benefit of a systems-based consideration of the concurrent multiple dynamic processes occurring upon co-dosing lipids and drugs to predict the impact of lipids on drug absorption and enable rational design of lipid-based delivery systems is presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex.

PubMed

Yeo, B T Thomas; Krienen, Fenna M; Chee, Michael W L; Buckner, Randy L

2014-03-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. © 2013.

Estimates of Segregation and Overlap of Functional Connectivity Networks in the Human Cerebral Cortex

PubMed Central

Yeo, BT Thomas; Krienen, Fenna M; Chee, Michael WL; Buckner, Randy L

2014-01-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1,000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. PMID:24185018

Learning Effects of Interactive Whiteboard Pedagogy for Students in Taiwan from the Perspective of Multiple Intelligences

ERIC Educational Resources Information Center

Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan

2013-01-01

With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Possible Synergistic Interactions Among Multiple HPV Genotypes in Women Suffering from Genital Neoplasia

PubMed

Hajia, Massoud; Sohrabi, Amir

2018-03-27

Objective: Persistence of HPV infection is the true cause of cervical disorders. It is reported that competition may exist among HPV genotypes for colonization. This survey was designed to establish the multiple HPV genotype status in our community and the probability of multiple HPV infections involvement. Methods: All multiple HPV infections were selected for investigation in women suffering from genital infections referred to private laboratories in Tehran, Iran. A total of 160 multi HPV positive specimens from cervical scraping were identified by the HPV genotyping methods, "INNO-LiPA and Geno Array". Result: In present study, HPV 6 (LR), 16 (HR), 53 (pHR), 31 (HR) and 11 (LR) were included in 48.8% of detected infections as the most five dominant genotypes. HPV 16 was detected at the highest rate with genotypes 53, 31 and 52, while HPV 53 appeared linked with HPV 16, 51 and 56 in concurrent infections. It appears that HPV 16 and 53 may have significant tendencies to associate with each other rather than with other genotypes. Analysis of the data revealed there may be some synergistic interactions with a few particular genotypes such as "HPV 53". Conclusion: Multiple HPV genotypes appear more likely to be linked with development of cervical abnormalities especially in patients with genital infections. Since, there are various patterns of dominant HPV genotypes in different regions of world, more investigations of this type should be performed for careHPV programs in individual countries. Creative Commons Attribution License

Screening molecular associations with lipid membranes using natural abundance 13C cross-polarization magic-angle spinning NMR and principal component analysis.

PubMed

Middleton, David A; Hughes, Eleri; Madine, Jillian

2004-08-11

We describe an NMR approach for detecting the interactions between phospholipid membranes and proteins, peptides, or small molecules. First, 1H-13C dipolar coupling profiles are obtained from hydrated lipid samples at natural isotope abundance using cross-polarization magic-angle spinning NMR methods. Principal component analysis of dipolar coupling profiles for synthetic lipid membranes in the presence of a range of biologically active additives reveals clusters that relate to different modes of interaction of the additives with the lipid bilayer. Finally, by representing profiles from multiple samples in the form of contour plots, it is possible to reveal statistically significant changes in dipolar couplings, which reflect perturbations in the lipid molecules at the membrane surface or within the hydrophobic interior.

Fully-coupled analysis of jet mixing problems. Part 1. Shock-capturing model, SCIPVIS

NASA Technical Reports Server (NTRS)

Dash, S. M.; Wolf, D. E.

1984-01-01

A computational model, SCIPVIS, is described which predicts the multiple cell shock structure in imperfectly expanded, turbulent, axisymmetric jets. The model spatially integrates the parabolized Navier-Stokes jet mixing equations using a shock-capturing approach in supersonic flow regions and a pressure-split approximation in subsonic flow regions. The regions are coupled using a viscous-characteristic procedure. Turbulence processes are represented via the solution of compressibility-corrected two-equation turbulence models. The formation of Mach discs in the jet and the interactive analysis of the wake-like mixing process occurring behind Mach discs is handled in a rigorous manner. Calculations are presented exhibiting the fundamental interactive processes occurring in supersonic jets and the model is assessed via comparisons with detailed laboratory data for a variety of under- and overexpanded jets.

Combining ecosystem service relationships and DPSIR framework to manage multiple ecosystem services.

PubMed

Xue, Hui; Li, Shiyu; Chang, Jie

2015-03-01

Ecosystem service (ES) relationship occurs due to two types of mechanisms: (1) interact directly or (2) interact through the impact of a shared factor. Identifying such mechanisms behind ES relationship within a single land-use/land-cover category and combining it with a system thinking framework is especially necessary for effective decision-making to manage multiple ESs generated by this land-use/land-cover. In this study, we use tea plantations in China to investigate mechanisms behind ES relationships. We find that tea production is positively correlated with four regulating services (i.e., carbon sequestration, soil N protection, soil P protection, and water conservation). Several regulating services, such as carbon sequestration and soil N, P, and K protection, have positive correlations with each other. Tea production, carbon sequestration, and soil retention are significantly correlated with local annual mean temperature and precipitation. We then establish driver-pressure-state-impact-response (DPSIR) framework for tea plantations, which has been widely used for environmental management issues. Integrating our findings of ES relationship into DPSIR framework, we can estimate how ES change is responding to two types of responses: response to control drivers and response to maintain or restore state. Scenario analysis showed that the responses to control drivers have a larger impact on ES. We discuss that DPSIR would favor managing multiple ES because it enables a more precise understanding of how ES interacts through the effects of factors from various hierarchies. Finally, we suggest integrating ES direct interaction into DPSIR framework. We think such integration could improve the ability of DPSIR framework to support decision-making in multiple ES management, specifically in at least three aspects: (1) favor to identify all possible response alternatives, (2) enable us to evaluate ES which cannot be assessed if without such combining, and (3) help to identify ecological leverage points where small management investment can yield substantial benefits.

Pediatric Disaster Triage: Multiple Simulation Curriculum Improves Prehospital Care Providers' Assessment Skills.

PubMed

Cicero, Mark Xavier; Whitfill, Travis; Overly, Frank; Baird, Janette; Walsh, Barbara; Yarzebski, Jorge; Riera, Antonio; Adelgais, Kathleen; Meckler, Garth D; Baum, Carl; Cone, David Christopher; Auerbach, Marc

2017-01-01

Paramedics and emergency medical technicians (EMTs) triage pediatric disaster victims infrequently. The objective of this study was to measure the effect of a multiple-patient, multiple-simulation curriculum on accuracy of pediatric disaster triage (PDT). Paramedics, paramedic students, and EMTs from three sites were enrolled. Triage accuracy was measured three times (Time 0, Time 1 [two weeks later], and Time 2 [6 months later]) during a disaster simulation, in which high and low fidelity manikins and actors portrayed 10 victims. Accuracy was determined by participant triage decision concordance with predetermined expected triage level (RED [Immediate], YELLOW [Delayed], GREEN [Ambulatory], BLACK [Deceased]) for each victim. Between Time 0 and Time 1, participants completed an interactive online module, and after each simulation there was an individual debriefing. Associations between participant level of training, years of experience, and enrollment site were determined, as were instances of the most dangerous mistriage, when RED and YELLOW victims were triaged BLACK. The study enrolled 331 participants, and the analysis included 261 (78.9%) participants who completed the study, 123 from the Connecticut site, 83 from Rhode Island, and 55 from Massachusetts. Triage accuracy improved significantly from Time 0 to Time 1, after the educational interventions (first simulation with debriefing, and an interactive online module), with a median 10% overall improvement (p < 0.001). Subgroup analyses showed between Time 0 and Time 1, paramedics and paramedic students improved more than EMTs (p = 0.002). Analysis of triage accuracy showed greatest improvement in overall accuracy for YELLOW triage patients (Time 0 50% accurate, Time1 100%), followed by RED patients (Time 0 80%, Time 1 100%). There was no significant difference in accuracy between Time 1 and Time 2 (p = 0.073). This study shows that the multiple-victim, multiple-simulation curriculum yields a durable 10% improvement in simulated triage accuracy. Future iterations of the curriculum can target greater improvements in EMT triage accuracy.

Analysis of multiple instructional techniques on the understanding and retention of select mechanical topics

NASA Astrophysics Data System (ADS)

Fetsco, Sara Elizabeth

There are several topics that introductory physics students typically have difficulty understanding. The purpose of this thesis is to investigate if multiple instructional techniques will help students to better understand and retain the material. The three units analyzed in this study are graphing motion, projectile motion, and conservation of momentum. For each unit students were taught using new or altered instructional methods including online laboratory simulations, inquiry labs, and interactive demonstrations. Additionally, traditional instructional methods such as lecture and problem sets were retained. Effectiveness was measured through pre- and post-tests and student opinion surveys. Results suggest that incorporating multiple instructional techniques into teaching will improve student understanding and retention. Students stated that they learned well from all of the instructional methods used except the online simulations.

Using Infrared Thermography to Assess Emotional Responses to Infants.

PubMed

Esposito, Gianluca; Nakazawa, Jun; Ogawa, Shota; Stival, Rita; Putnick, Diane L; Bornstein, Marc H

2015-01-01

Adult-infant interactions operate simultaneously across multiple domains and at multiple levels - from physiology to behavior. Unpackaging and understanding them, therefore, involves analysis of multiple data streams. In this study, we tested physiological responses and cognitive preferences for infant and adult faces in adult females and males. Infrared thermography was used to assess facial temperature changes as a measure of emotional valence, and we used a behavioral rating system to assess adults' expressed preferences. We found greater physiological activation in response to infant stimuli in females than males. As for cognitive preferences, we found greater responses to adult stimuli than to infant stimuli, both in males and females. The results are discuss in light of the Life History Theory. Finally, we discuss the importance of integrating the two data streams on our conclusions.

Hydrophilic interaction chromatography-multiple reaction monitoring mass spectrometry method for basic building block analysis of low molecular weight heparins prepared through nitrous acid depolymerization.

PubMed

Sun, Xiaojun; Guo, Zhimou; Yu, Mengqi; Lin, Chao; Sheng, Anran; Wang, Zhiyu; Linhardt, Robert J; Chi, Lianli

2017-01-06

Low molecular weight heparins (LMWHs) are important anticoagulant drugs that are prepared through depolymerization of unfractionated heparin. Based on the types of processing reactions and the structures of the products, LMWHs can be divided into different classifications. Enoxaparin is prepared by benzyl esterification and alkaline depolymerization, while dalteparin and nadroparin are prepared through nitrous acid depolymerization followed by borohydride reduction. Compositional analysis of their basic building blocks is an effective way to provide structural information on heparin and LMWHs. However, most current compositional analysis methods have been limited to heparin and enoxaparin. A sensitive and comprehensive approach is needed for detailed investigation of the structure of LMWHs prepared through nitrous acid depolymerization, especially their characteristic saturated non-reducing end (NRE) and 2,5-anhydro-d-mannitol reducing end (RE). A maltose modified hydrophilic interaction column offers improved separation of complicated mixtures of acidic disaccharides and oligosaccharides. A total of 36 basic building blocks were unambiguously identified by high-resolution tandem mass spectrometry (MS). Multiple reaction monitoring (MRM) MS/MS quantification was developed and validated in the analysis of dalteparin and nadroparin samples. Each group of building blocks revealed different aspects of the properties of LMWHs, such as functional motifs required for anticoagulant activity, the structure of heparin starting materials, cleavage sites in the depolymerization reaction, and undesired structural modifications resulting from side reactions. Copyright © 2016 Elsevier B.V. All rights reserved.

Long lifetimes of ultrahot particles in interacting Fermi systems

NASA Astrophysics Data System (ADS)

Bard, M.; Protopopov, I. V.; Mirlin, A. D.

2018-05-01

The energy dependence of the relaxation rate of hot electrons due to interaction with the Fermi sea is studied. We consider 2D and 3D systems, quasi-1D quantum wires with multiple transverse bands, as well as single-channel 1D wires. Our analysis includes both spinful and spin-polarized setups, with short-range and Coulomb interactions. We show that, quite generally, the relaxation rate is a nonmonotonic function of the electron energy and decays as a power law at high energies. In other words, ultrahot electrons regain their coherence with increasing energy. Such a behavior was observed in a recent experiment on multiband quantum wires, J. Reiner et al., Phys. Rev. X 7, 021016 (2017)., 10.1103/PhysRevX.7.021016

Preliminary disposal limits, plume interaction factors, and final disposal limits

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

Flach, G.

In the 2008 E-Area Performance Assessment (PA), each final disposal limit was constructed as the product of a preliminary disposal limit and a plume interaction factor. The following mathematical development demonstrates that performance objectives are generally expected to be satisfied with high confidence under practical PA scenarios using this method. However, radionuclides that experience significant decay between a disposal unit and the 100-meter boundary, such as H-3 and Sr-90, can challenge performance objectives, depending on the disposed-of waste composition, facility geometry, and the significance of the plume interaction factor. Pros and cons of analyzing single disposal units or multiple disposalmore » units as a group in the preliminary disposal limits analysis are also identified.« less

Archaea in symbioses.

PubMed

Wrede, Christoph; Dreier, Anne; Kokoschka, Sebastian; Hoppert, Michael

2012-01-01

During the last few years, the analysis of microbial diversity in various habitats greatly increased our knowledge on the kingdom Archaea. At the same time, we became aware of the multiple ways in which Archaea may interact with each other and with organisms of other kingdoms. The large group of euryarchaeal methanogens and their methane oxidizing relatives, in particular, take part in essential steps of the global methane cycle. Both of these processes, which are in reverse to each other, are partially conducted in a symbiotic interaction with different partners, either ciliates and xylophagous animals or sulfate reducing bacteria. Other symbiotic interactions are mostly of unknown ecological significance but depend on highly specific mechanisms. This paper will give an overview on interactions between Archaea and other organisms and will point out the ecological relevance of these symbiotic processes, as long as these have been already recognized.

Archaea in Symbioses

PubMed Central

Wrede, Christoph; Dreier, Anne; Kokoschka, Sebastian; Hoppert, Michael

2012-01-01

During the last few years, the analysis of microbial diversity in various habitats greatly increased our knowledge on the kingdom Archaea. At the same time, we became aware of the multiple ways in which Archaea may interact with each other and with organisms of other kingdoms. The large group of euryarchaeal methanogens and their methane oxidizing relatives, in particular, take part in essential steps of the global methane cycle. Both of these processes, which are in reverse to each other, are partially conducted in a symbiotic interaction with different partners, either ciliates and xylophagous animals or sulfate reducing bacteria. Other symbiotic interactions are mostly of unknown ecological significance but depend on highly specific mechanisms. This paper will give an overview on interactions between Archaea and other organisms and will point out the ecological relevance of these symbiotic processes, as long as these have been already recognized. PMID:23326206

Towards Inter- and Intra- Cellular Protein Interaction Analysis: Applying the Betweenness Centrality Graph Measure for Node Importance

NASA Astrophysics Data System (ADS)

Barton, Alan J.; Haqqani, Arsalan S.

2011-11-01

Three public biological network data sets (KEGG, GeneRIF and Reactome) are collected and described. Two problems are investigated (inter- and intra- cellular interactions) via augmentation of the collected networks to the problem specific data. Results include an estimate of the importance of proteins for the interaction of inflammatory cells with the blood-brain barrier via the computation of Betweenness Centrality. Subsequently, the interactions may be validated from a number of differing perspectives; including comparison with (i) existing biological results, (ii) the literature, and (iii) new hypothesis driven biological experiments. Novel therapeutic and diagnostic targets for inhibiting inflammation at the blood-brain barrier in a number of brain diseases including Alzheimer's disease, stroke and multiple sclerosis are possible. In addition, this methodology may also be applicable towards investigating the breast cancer tumour microenvironment.

An Updated Meta-Analysis of Risk of Multiple Sclerosis following Infectious Mononucleosis

PubMed Central

Handel, Adam E.; Williamson, Alexander J.; Disanto, Giulio; Handunnetthi, Lahiru; Giovannoni, Gavin; Ramagopalan, Sreeram V.

2010-01-01

Background Multiple sclerosis (MS) appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV) infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM) has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published. Methods/Principal Findings We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR) 2.17; 95% confidence interval 1.97–2.39; p<10−54). Discussion Our results establish firmly that a history of infectious mononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors. PMID:20824132

Genome-wide analysis of protein disorder in Arabidopsis thaliana: implications for plant environmental adaptation.

PubMed

Pietrosemoli, Natalia; García-Martín, Juan A; Solano, Roberto; Pazos, Florencio

2013-01-01

Intrinsically disordered proteins/regions (IDPs/IDRs) are currently recognized as a widespread phenomenon having key cellular functions. Still, many aspects of the function of these proteins need to be unveiled. IDPs conformational flexibility allows them to recognize and interact with multiple partners, and confers them larger interaction surfaces that may increase interaction speed. For this reason, molecular interactions mediated by IDPs/IDRs are particularly abundant in certain types of protein interactions, such as those of signaling and cell cycle control. We present the first large-scale study of IDPs in Arabidopsis thaliana, the most widely used model organism in plant biology, in order to get insight into the biological roles of these proteins in plants. The work includes a comparative analysis with the human proteome to highlight the differential use of disorder in both species. Results show that while human proteins are in general more disordered, certain functional classes, mainly related to environmental response, are significantly more enriched in disorder in Arabidopsis. We propose that because plants cannot escape from environmental conditions as animals do, they use disorder as a simple and fast mechanism, independent of transcriptional control, for introducing versatility in the interaction networks underlying these biological processes so that they can quickly adapt and respond to challenging environmental conditions.

Bilinearization of the generalized coupled nonlinear Schrödinger equation with variable coefficients and gain and dark-bright pair soliton solutions.

PubMed

Chakraborty, Sushmita; Nandy, Sudipta; Barthakur, Abhijit

2015-02-01

We investigate coupled nonlinear Schrödinger equations (NLSEs) with variable coefficients and gain. The coupled NLSE is a model equation for optical soliton propagation and their interaction in a multimode fiber medium or in a fiber array. By using Hirota's bilinear method, we obtain the bright-bright, dark-bright combinations of a one-soliton solution (1SS) and two-soliton solutions (2SS) for an n-coupled NLSE with variable coefficients and gain. Crucial properties of two-soliton (dark-bright pair) interactions, such as elastic and inelastic interactions and the dynamics of soliton bound states, are studied using asymptotic analysis and graphical analysis. We show that a bright 2-soliton, in addition to elastic interactions, also exhibits multiple inelastic interactions. A dark 2-soliton, on the other hand, exhibits only elastic interactions. We also observe a breatherlike structure of a bright 2-soliton, a feature that become prominent with gain and disappears as the amplitude acquires a minimum value, and after that the solitons remain parallel. The dark 2-soliton, however, remains parallel irrespective of the gain. The results found by us might be useful for applications in soliton control, a fiber amplifier, all optical switching, and optical computing.

Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms.

PubMed

Roetker, Nicholas S; Page, C David; Yonker, James A; Chang, Vicky; Roan, Carol L; Herd, Pamela; Hauser, Taissa S; Hauser, Robert M; Atwood, Craig S

2013-10-01

We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

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

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Multiple intelligences and alternative teaching strategies: The effects on student academic achievement, conceptual understanding, and attitude

NASA Astrophysics Data System (ADS)

Baragona, Michelle

The purpose of this study was to investigate the interactions between multiple intelligence strengths and alternative teaching methods on student academic achievement, conceptual understanding and attitudes. The design was a quasi-experimental study, in which students enrolled in Principles of Anatomy and Physiology, a developmental biology course, received lecture only, problem-based learning with lecture, or peer teaching with lecture. These students completed the Multiple Intelligence Inventory to determine their intelligence strengths, the Students' Motivation Toward Science Learning questionnaire to determine student attitudes towards learning in science, multiple choice tests to determine academic achievement, and open-ended questions to determine conceptual understanding. Effects of intelligence types and teaching methods on academic achievement and conceptual understanding were determined statistically by repeated measures ANOVAs. No significance occurred in academic achievement scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in logical-mathematical, interpersonal, kinesthetic, and intrapersonal intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by problem-based learning (PBL) as compared to peer teaching (PT). No significance occurred in conceptual understanding scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in musical, kinesthetic, intrapersonal, and spatial intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by lecture as compared to PBL. Students with strengths in intrapersonal intelligence and enrolled in Group One scored significantly lower when taught by lecture as compared to PBL. Results of a repeated measures ANOVA for student attitudes showed significant increases in positive student attitudes toward science learning for all three types of teaching method between pretest and posttest; but there were no significant differences in posttest attitude scores by type of teaching method.

Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

NASA Astrophysics Data System (ADS)

Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

2016-11-01

Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

Sex ratio in multiple sclerosis mortality over 65 years; an age-period-cohort analysis in Norway.

PubMed

Nakken, Ola; Lindstrøm, Jonas Christoffer; Holmøy, Trygve

2018-06-01

Increasing female: male ratio in multiple sclerosis (MS) has been assigned to cohort effects, with females in more recent birth cohorts possibly being more exposed or vulnerable to environmental risk factors than males. We collected MS mortality data in Norway from 1951 to 2015 from The Norwegian Cause of Death registry. Age-Period-Cohort analysis was conducted using log-linear Poisson models, including sex interaction terms. MS was registered as the underlying, contributing or direct cause in 6060 deaths. MS associated mortality remained stable with a slight preponderance among males until after 1980, and have since increased preferentially among females. Throughout the study period the mean annual increase was 1.25% for females and 0.3% for males (p < 0.0001). Age-period-cohort analysis revealed limited evidence of cohort effects for the gender differences; the best fitting model only included gender-age and gender-period interaction terms. The period effect evened out for males in the last three decades but increased for females, especially among the oldest age-groups. In conclusion, the increased female: male mortality ratio in MS associated mortality is driven mainly by increased mortality among females in the three last decades, particularly in the older age groups. It is best explained by disproportional period effects, providing evidence of time-varying external factors including improved access to diagnosis among females.

Whole-of-society approach for public health policymaking: a case study of polycentric governance from Quebec, Canada.

PubMed

Addy, Nii A; Poirier, Alain; Blouin, Chantal; Drager, Nick; Dubé, Laurette

2014-12-01

In adopting a whole-of-society (WoS) approach that engages multiple stakeholders in public health policies across contexts, the authors propose that effective governance presents a challenge. The purpose of this paper is to highlight a case for how polycentric governance underlying the WoS approach is already functioning, while outlining an agenda to enable adaptive learning for improving such governance processes. Drawing upon a case study from Quebec, Canada, we employ empirically developed concepts from extensive, decades-long work of the 2009 Nobel laureate Elinor Ostrom in the governance of policy in nonhealth domains to analyze early efforts at polycentric governance in policies around overnutrition, highlighting interactions between international, domestic, state and nonstate actors and processes. Using information from primary and secondary sources, we analyze the emergence of the broader policy context of Quebec's public health system in the 20th century. We present a microsituational analysis of the WoS approach for Quebec's 21st century policies on healthy lifestyles, emphasizing the role of governance at the community level. We argue for rethinking prescriptive policy analysis of the 20th century, proposing an agenda for diagnostic policy analysis, which explicates the multiple sets of actors and interacting variables shaping polycentric governance for operationalizing the WoS approach to policymaking in specific contexts. © 2014 New York Academy of Sciences.

Laplace Transform Based Radiative Transfer Studies

NASA Astrophysics Data System (ADS)

Hu, Y.; Lin, B.; Ng, T.; Yang, P.; Wiscombe, W.; Herath, J.; Duffy, D.

2006-12-01

Multiple scattering is the major uncertainty for data analysis of space-based lidar measurements. Until now, accurate quantitative lidar data analysis has been limited to very thin objects that are dominated by single scattering, where photons from the laser beam only scatter a single time with particles in the atmosphere before reaching the receiver, and simple linear relationship between physical property and lidar signal exists. In reality, multiple scattering is always a factor in space-based lidar measurement and it dominates space- based lidar returns from clouds, dust aerosols, vegetation canopy and phytoplankton. While multiple scattering are clear signals, the lack of a fast-enough lidar multiple scattering computation tool forces us to treat the signal as unwanted "noise" and use simple multiple scattering correction scheme to remove them. Such multiple scattering treatments waste the multiple scattering signals and may cause orders of magnitude errors in retrieved physical properties. Thus the lack of fast and accurate time-dependent radiative transfer tools significantly limits lidar remote sensing capabilities. Analyzing lidar multiple scattering signals requires fast and accurate time-dependent radiative transfer computations. Currently, multiple scattering is done with Monte Carlo simulations. Monte Carlo simulations take minutes to hours and are too slow for interactive satellite data analysis processes and can only be used to help system / algorithm design and error assessment. We present an innovative physics approach to solve the time-dependent radiative transfer problem. The technique utilizes FPGA based reconfigurable computing hardware. The approach is as following, 1. Physics solution: Perform Laplace transform on the time and spatial dimensions and Fourier transform on the viewing azimuth dimension, and convert the radiative transfer differential equation solving into a fast matrix inversion problem. The majority of the radiative transfer computation goes to matrix inversion processes, FFT and inverse Laplace transforms. 2. Hardware solutions: Perform the well-defined matrix inversion, FFT and Laplace transforms on highly parallel, reconfigurable computing hardware. This physics-based computational tool leads to accurate quantitative analysis of space-based lidar signals and improves data quality of current lidar mission such as CALIPSO. This presentation will introduce the basic idea of this approach, preliminary results based on SRC's FPGA-based Mapstation, and how we may apply it to CALIPSO data analysis.

Automated Track Recognition and Event Reconstruction in Nuclear Emulsion

NASA Technical Reports Server (NTRS)

Deines-Jones, P.; Cherry, M. L.; Dabrowska, A.; Holynski, R.; Jones, W. V.; Kolganova, E. D.; Kudzia, D.; Nilsen, B. S.; Olszewski, A.; Pozharova, E. A.;

Solomon design analysis of multiple-choice Rorschach animal content.

PubMed

Feigenbaum, D; Costello, R M

1975-10-01

The Solomon four-group design was used to study the effects of a persuasive message on a selected multiple-choice Rorschach index--animal content. The independent variable elicited behavior in a predictable manner. Pretesting as a main effect was not significant, but as an interactional effect obviated the effect of the persuasive message. Although knowledge of test rationale can elicit behavior that conforms to experimental demand characteristics, some subjects nonetheless acted in defiance of such information. A condition for defiance in this experimental arrangement, however, was pretesting. Other possibilities regarding the study of compliance behavior and the use of pathognomonic indicators were suggested. Ethical issues were raised.

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

2010-01-01

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

Effects of Multiple Simulation Presentation among Students of Different Anxiety Levels in the Learning of Probability

ERIC Educational Resources Information Center

Fong, Soon Fook; Por, Fei Ping; Tang, Ai Ling

2012-01-01

The purpose of this study was to investigate the effects of multiple simulation presentation in interactive multimedia are on the achievement of students with different levels of anxiety in the learning of Probability. The interactive multimedia courseware was developed in two different modes, which were Multiple Simulation Presentation (MSP) and…

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

Characterizing the effect of Bortezomib on Rift Valley Fever Virus multiplication.

PubMed

Keck, Forrest; Amaya, Moushimi; Kehn-Hall, Kylene; Roberts, Brian; Bailey, Charles; Narayanan, Aarthi

2015-08-01

Rift Valley Fever Virus (RVFV) belongs to the family Bunyaviridae and is a known cause of epizootics and epidemics in Africa and the Middle East. With no FDA approved therapeutics available to treat RVFV infection, understanding the interactions between the virus and the infected host is crucial to developing novel therapeutic strategies. Here, we investigated the requirement of the ubiquitin-proteasome system (UPS) for the establishment of a productive RVFV infection. It was previously shown that the UPS plays a central role in RVFV multiplication involving degradation of PKR and p62 subunit of TFIIH. Using the FDA-approved proteasome inhibitor Bortezomib, we observed robust inhibition of intracellular and extracellular viral loads. Bortezomib treatment did not affect the nuclear/cytoplasmic distribution of the non-structural S-segment protein (NSs); however, the ability of NSs to form nuclear filaments was abolished as a result of Bortezomib treatment. In silico ubiquitination prediction analysis predicted that known NSs interactors (SAP30, YY1, and mSin3A) have multiple putative ubiquitination sites, while NSs itself was not predicted to be ubiquitinated. Immunoprecipitation studies indicated a decrease in interaction between SAP30 - NSs, and mSin3A - NSs in the context of Bortezomib treatment. This decrease in association between SAP30 - NSs also correlated with a decrease in the ubiquitination status of SAP30 with Bortezomib treatment. Bortezomib treatment, however, resulted in increased ubiquitination of mSin3A, suggesting that Bortezomib dynamically affects the ubiquitination status of host proteins that interact with NSs. Finally, we observed that expression of interferon beta (IFN-β) was increased in Bortezomib treated cells which indicated that the cellular antiviral mechanism was revived as a result of treatment and may contribute to control of viral multiplication. Copyright © 2015 Elsevier B.V. All rights reserved.

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

Interactive visualization and analysis of multimodal datasets for surgical applications.

PubMed

Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

2012-12-01

Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

Helicobacter pylori Persistence: an Overview of Interactions between H. pylori and Host Immune Defenses

PubMed Central

Algood, Holly M. Scott; Cover, Timothy L.

2006-01-01

Helicobacter pylori is a gram-negative bacterium that persistently colonizes more than half of the global human population. In order to successfully colonize the human stomach, H. pylori must initially overcome multiple innate host defenses. Remarkably, H. pylori can persistently colonize the stomach for decades or an entire lifetime despite development of an acquired immune response. This review focuses on the immune response to H. pylori and the mechanisms by which H. pylori resists immune clearance. Three main sections of the review are devoted to (i) analysis of the immune response to H. pylori in humans, (ii) analysis of interactions of H. pylori with host immune defenses in animal models, and (iii) interactions of H. pylori with immune cells in vitro. The topics addressed in this review are important for understanding how H. pylori resists immune clearance and also are relevant for understanding the pathogenesis of diseases caused by H. pylori (peptic ulcer disease, gastric adenocarcinoma, and gastric lymphoma). PMID:17041136

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

More Results from the Opera Experiment at the Gran Sasso Underground Lab

NASA Astrophysics Data System (ADS)

Kamiscioglu, Mustafa

The OPERA experiment reached its main goal by proving the appearance of ντ in the CNGS νμ beam. Five ντ candidates fulfilling the analysis defined in the proposal were detected with a S/B ratio of about ten allowing to reject the null hypothesis at 5.1σ. The search has been extended by loosening the selection criteria in order to obtain a statistically enhanced, lower purity, signal sample. One such interesting neutrino interaction with a double vertex topology having a high probability of being a ντ interaction with charm production is reported. Based on the enlarged data sample the estimation of Δm232 in appearance mode is presented. The search for νe interactions has been extended over the full data set with a more than twofold increase in statistics with respect to published data. The analysis of the νμ → νe channel is updated and the implications of the electron neutrino sample in the framework of the 3+1 neutrino model is discussed. An analysis of νμ → ντ interactions in the framework of the sterile neutrino model has also been performed. Finally, the results of the study of charged hadron multiplicity distributions is presented.

Meta-analysis confirms the LCE3C_LCE3B deletion as a risk factor for psoriasis in several ethnic groups and finds interaction with HLA-Cw6

PubMed Central

Riveira-Munoz, Eva; He, Su-Min; Escaramís, Georgia; Stuart, Philip E; Hüffmeier, Ulrike; Lee, Catherine; Kirby, Brian; Oka, Akira; Giardina, Emiliano; Liao, Wilson; Bergboer, Judith; Kainu, Kati; de Cid, Rafael; Munkhbat, Batmunkh; Zeeuwen, Patrick L J M; Armour, John A L; Poon, Annie; Mabuchi, Tomotaka; Ozawa, Akira; Zawirska, Agnieszka; Burden, David A; Barker, Jonathan N; Capon, Francesca; Traupe, Heiko; Sun, Liang-Dan; Cui, Yong; Yin, Xian-Yong; Chen, Gang; Lim, Henry; Nair, Rajan; Voorhess, John; Tejasvi, Trilokraj; Pujol, Ramón; Munkhtuvshin, Namid; Fischer, Judith; Kere, Juha; Schalkwijk, Joost; Bowcock, Anne; Kwok, Pui-Yan; Novelli, Giuseppe; Inoko, Hidetoshi; Ryan, Anthony W; Trembath, Richard C; Reis, André; Zhang, Xue-Jun; Elder, James T; Estivill, Xavier

2012-01-01

A multicenter meta-analysis including data from 9389 psoriasis patients and 9477 control subjects was performed to investigate the contribution of the deletion of genes LCE3C and LCE3B, involved in skin barrier defense, to psoriasis susceptibility in different populations. The study confirms that the deletion of LCE3C and LCE3B is a common genetic factor for susceptibility to psoriasis in European populations [OROverall = 1.21 (1.15–1.27)], and for the first time directly demonstrated the deletion's association with psoriasis in [Chinese OR = 1.27 (1.16–1.34); Mongolian OR = 2.08 (1.44–2.99)] populations. The analysis of the HLA-Cw6 locus showed significant differences in the epistatic interaction with the LCE3C and LCE3B deletion in at least some European populations, indicating epistatic effects between these two major genetic contributors to psoriasis. The study highlights the value of examining genetic risk factors in multiple populations to identify genetic interactions, and indicates the need of further studies to understand the interaction of the skin barrier and the immune system in susceptibility to psoriasis. PMID:21107349

Comparative 4f-4f absorption spectral study for the interactions of Nd(III) with some amino acids: Preliminary thermodynamics and kinetic studies of interaction of Nd(III):glycine with Ca(II)

NASA Astrophysics Data System (ADS)

Moaienla, T.; Bendangsenla, N.; David Singh, Th.; Sumitra, Ch.; Rajmuhon Singh, N.; Indira Devi, M.

2012-02-01

Spectral analysis of Nd(III) complexes with some amino acids viz.; glycine, L-alanine, L-phenylalanine and L-aspartic acid in the presence and absence of Ca 2+ was carried out in some organic solvents; CH 3OH, CH 3CN, DMF and dioxane using comparative absorption spectra of 4f-4f transitions. The study was carried out by evaluating various energy interaction parameters like Slator-Condon ( Fk), Lande factor ( ξ4f), nephelauxetic ratio ( β), bonding parameter ( b1/2), percent-covalency ( δ) by applying partial and multiple regression analysis. The values of oscillator strength ( Pobs) and Judd-Ofelt electric dipole intensity parameter Tλ ( λ = 2, 4, 6) for different 4f-4f transitions have been calculated. On analysis of the variation of the various energy interaction parameters as well as the changes in the oscillator strength ( Pobs) and Tλ values, reveal the mode of binding with the different ligands. Kinetic studies for the complexation of Nd(III):glycine:Ca(II) have also been discussed at different temperatures in DMF medium and from it the values of activation energy ( Ea) and thermodynamic parameters like Δ H°, Δ S° and Δ G° for the complexation are evaluated.

Integrating Conjoint Analysis with TOPSIS Algorithm to the Visual Effect of Icon Design Based on Multiple Users' Image Perceptions

ERIC Educational Resources Information Center

Tung, Ting-Chun; Chen, Hung-Yuan

2017-01-01

With the advance of mobile computing and wireless technology, a user's intent to interact with the interface of a mobile device is motivated not only by its intuitional operation, but also by the emotional perception induced by its aesthetic appeal. A graphical interface employing icons with suitable visual effect based on the users' emotional…

Repeating Patterns and Multiplicative Thinking: Analysis of Classroom Interactions with 9-Year-Old Students that Support the Transition from the Known to the Novel

ERIC Educational Resources Information Center

Warren, Elizabeth; Cooper, Tom

2007-01-01

In early years' (primary grade) classrooms in Australia repeated patterns are commonly explored as an early introductory activity to mathematics. Most young students have an extensive knowledge of and exhibit success in copying, continuing, creating and transferring patterns into other media. By contrast, research indicates one of the most…

Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-02-01

Spatial reciprocity is generally regarded as a positive rule facilitating the evolution of cooperation. However, a few recent studies show that, in the snowdrift game, spatial structure still could be detrimental to cooperation. Here we propose a model of multiple interactive dynamics, where each individual can cooperate and defect simultaneously against different neighbors. We realize individuals' multiple interactions simply by endowing them with strategies relevant to probabilities, and every one decides to cooperate or defect with a probability. With multiple interactive dynamics, the cooperation level in square lattices is higher than that in the well-mixed case for a wide range of cost-to-benefit ratio r, implying that spatial structure favors cooperative behavior in the snowdrift game. Moreover, in square lattices, the most favorable strategy follows a simple relation of r, which confers theoretically the average evolutionary frequency of cooperative behavior. We further extend our study to various homogeneous and heterogeneous networks, which demonstrates the robustness of our results. Here multiple interactive dynamics stabilizes the positive role of spatial structure on the evolution of cooperation and individuals' distinct reactions to different neighbors can be a new line in understanding the emergence of cooperation.

Scaling in cognitive performance reflects multiplicative multifractal cascade dynamics

PubMed Central

Stephen, Damian G.; Anastas, Jason R.; Dixon, James A.

2012-01-01

Self-organized criticality purports to build multi-scaled structures out of local interactions. Evidence of scaling in various domains of biology may be more generally understood to reflect multiplicative interactions weaving together many disparate scales. The self-similarity of power-law scaling entails homogeneity: fluctuations distribute themselves similarly across many spatial and temporal scales. However, this apparent homogeneity can be misleading, especially as it spans more scales. Reducing biological processes to one power-law relationship neglects rich cascade dynamics. We review recent research into multifractality in executive-function cognitive tasks and propose that scaling reflects not criticality but instead interactions across multiple scales and among fluctuations of multiple sizes. PMID:22529819

[Potential interaction effect on attention-deficit/hyperactivity disorder between mother's educational level and preschoolers' dietary pattern].

PubMed

Yan, S Q; Cao, H; Gu, C L; Gao, G P; Ni, L L; Tao, H H; Shao, T; Xu, Y Q; Tao, F B

2018-04-10

Objective: To explore the interaction effect between mother's educational level and preschoolers' dietary pattern on attention-deficit/hyperactivity disorder (ADHD). Methods: In 2014, there were 16 439 children aged 3-6 years old from 91 kindergartens in Ma'anshan municipality of China. A semi-quantitative food frequency questionnaire and the 10-item Chinese version of the Conners' Abbreviated Symptom Questionnaire (C-ASQ) were administered to assess the usual dietary intake and symptoms on ADHD. Social-demographic information was collected through questionnaires. Unconditional logistic regression was used to analyze the multiplication interaction effect between mother's educational level and preschoolers' dietary pattern on ADHD. Excel software was used to analyze the additive interaction effect of mother's educational level and preschoolers'dietary pattern on ADHD. Results: Results showed that factors as: mother's low educational level[a OR =1.31 (1.13-1.52)], scores related to preschoolers in the top quintile of "food processing" [a OR =1.31 (1.16-1.48)] and "snack" [a OR =1.45 (1.29-1.63)]patterns showed greater odds while preschoolers in the top quintile of "vegetarian" [a OR =0.80 (0.71-0.90)]showed less odds for having ADHD symptoms. Both multiplication and additive interactions were observed between mothers with less education. The processed dietary patterns ( OR =1.17, 95% CI : 1.11-1.25), relative excess risk of interaction ( RERI ), attributable proportion ( AP ) and the interaction index ( SI ) appeared as 0.21, 0.13 and 1.47, respectively. Multiplication interaction was observed between levels of mother's low education and the snack dietary pattern ( OR =1.21, 95% CI : 1.14-1.29), with RERI , AP and SI as 0.49, 0.26 and 2.36, respectively. However, neither multiplication interaction or additive interaction was noticed between levels of mother's low education and the vegetarian dietary pattern ( OR =0.97, 95% CI : 0.92-1.03), with RERI , AP and SI as 0.09, 0.05 and 1.15, respectively. Conclusions: Levels of mother's low education presented a risk factor for ADHD symptoms in preschool children. Both multiplication interaction and additive interaction were observed between mother's low education levels and the processed dietary pattern. Multiplication interaction was noticed between mother's education levels and the snack dietary pattern but not with the vegetarian dietary pattern.

Visual Analysis of MOOC Forums with iForum.

PubMed

Fu, Siwei; Zhao, Jian; Cui, Weiwei; Qu, Huamin

2017-01-01

Discussion forums of Massive Open Online Courses (MOOC) provide great opportunities for students to interact with instructional staff as well as other students. Exploration of MOOC forum data can offer valuable insights for these staff to enhance the course and prepare the next release. However, it is challenging due to the large, complicated, and heterogeneous nature of relevant datasets, which contain multiple dynamically interacting objects such as users, posts, and threads, each one including multiple attributes. In this paper, we present a design study for developing an interactive visual analytics system, called iForum, that allows for effectively discovering and understanding temporal patterns in MOOC forums. The design study was conducted with three domain experts in an iterative manner over one year, including a MOOC instructor and two official teaching assistants. iForum offers a set of novel visualization designs for presenting the three interleaving aspects of MOOC forums (i.e., posts, users, and threads) at three different scales. To demonstrate the effectiveness and usefulness of iForum, we describe a case study involving field experts, in which they use iForum to investigate real MOOC forum data for a course on JAVA programming.

BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa–Function Relationships in Microbiome Data

PubMed Central

McNally, Colin P.; Eng, Alexander; Noecker, Cecilia; Gagne-Maynard, William C.; Borenstein, Elhanan

2018-01-01

The abundance of both taxonomic groups and gene categories in microbiome samples can now be easily assayed via various sequencing technologies, and visualized using a variety of software tools. However, the assemblage of taxa in the microbiome and its gene content are clearly linked, and tools for visualizing the relationship between these two facets of microbiome composition and for facilitating exploratory analysis of their co-variation are lacking. Here we introduce BURRITO, a web tool for interactive visualization of microbiome multi-omic data with paired taxonomic and functional information. BURRITO simultaneously visualizes the taxonomic and functional compositions of multiple samples and dynamically highlights relationships between taxa and functions to capture the underlying structure of these data. Users can browse for taxa and functions of interest and interactively explore the share of each function attributed to each taxon across samples. BURRITO supports multiple input formats for taxonomic and metagenomic data, allows adjustment of data granularity, and can export generated visualizations as static publication-ready formatted figures. In this paper, we describe the functionality of BURRITO, and provide illustrative examples of its utility for visualizing various trends in the relationship between the composition of taxa and functions in complex microbiomes. PMID:29545787

Interaction and influence of two creeks on Escherichia coli concentrations of nearby beaches: Exploration of predictability and mechanisms

USGS Publications Warehouse

Nevers, M.B.; Whitman, R.L.; Frick, W.E.; Ge, Z.

2007-01-01

The impact of river outfalls on beach water quality depends on numerous interacting factors. The delivery of contaminants by multiple creeks greatly complicates understanding of the source contributions, especially when pollution might originate up- or down-coast of beaches. We studied two beaches along Lake Michigan that are located between two creek outfalls to determine the hydrometeorologic factors influencing near-shore microbiologic water quality and the relative impact of the creeks. The creeks continuously delivered water with high concentrations of Escherichia coli to Lake Michigan, and the direction of transport of these bacteria was affected by current direction. Current direction reversals were associated with elevated E. coli concentrations at Central Avenue beach. Rainfall, barometric pressure, wave height, wave period, and creek specific conductance were significantly related to E. coli concentration at the beaches and were the parameters used in predictive models that best described E. coli variation at the two beaches. Multiple inputs to numerous beaches complicates the analysis and understanding of the relative relationship of sources but affords opportunities for showing how these complex creek inputs might interact to yield collective or individual effects on beach water quality.

Material property analytical relations for the case of an AFM probe tapping a viscoelastic surface containing multiple characteristic times

PubMed Central

López-Guerra, Enrique A

2017-01-01

We explore the contact problem of a flat-end indenter penetrating intermittently a generalized viscoelastic surface, containing multiple characteristic times. This problem is especially relevant for nanoprobing of viscoelastic surfaces with the highly popular tapping-mode AFM imaging technique. By focusing on the material perspective and employing a rigorous rheological approach, we deliver analytical closed-form solutions that provide physical insight into the viscoelastic sources of repulsive forces, tip–sample dissipation and virial of the interaction. We also offer a systematic comparison to the well-established standard harmonic excitation, which is the case relevant for dynamic mechanical analysis (DMA) and for AFM techniques where tip–sample sinusoidal interaction is permanent. This comparison highlights the substantial complexity added by the intermittent-contact nature of the interaction, which precludes the derivation of straightforward equations as is the case for the well-known harmonic excitations. The derivations offered have been thoroughly validated through numerical simulations. Despite the complexities inherent to the intermittent-contact nature of the technique, the analytical findings highlight the potential feasibility of extracting meaningful viscoelastic properties with this imaging method. PMID:29114450

Interactions within the MHC contribute to the genetic architecture of celiac disease.

PubMed

Goudey, Benjamin; Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda; Kowalczyk, Adam; Inouye, Michael

2017-01-01

Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

[Pickled food, fish, seafood intakes and oral squamous cell carcinoma: a case-control study].

PubMed

Huang, J F; Qiu, Y; Cai, L; Liu, F P; Chen, F; Yan, L J; Wu, J F; Bao, X D; Liu, F Q; Zheng, X Y; Lin, L S; He, B C

2017-08-06

Objective: To investigate the effects between fish, seafood and pickled food intakes on oral squamous cell carcinoma (OSCC). Methods: A case-control study was carried out in Fujian area during September 2010 to December 2016, in which 604 newly diagnosed primary OSCC cases confirmed by pathological diagnosis were collected from hospital and 1 343 control subjects were enrolled from community and healthy hospital population. Demographic data, history of smoking drinking and tea drinking, oral hygiene status and dietary behaviors (fish, seafood and pickled food intakes) were collected by in-person interviews using a standard questionnaire.Using unconditional logistic regression to estimate adjusted odds ratios ( ORs ) and corresponding 95% confidence intervals ( CIs ) to assess the effects of fish, seafood and pickled food intakes on OSCC. Analysis stratified by smoking, alcohol drinking and bad prosthesis to explore the possible difference in association between subgroups. Multiplicative interactions and additive interactions between fish and bad prosthesis, seafood and alcohol drinking, pickled food and bad prosthesis were assessed by unconditional logistic regression, relative excess risk due to interaction ( RERI ), attributable proportion due to interaction ( AP ) and synergy index (S). Results: The average age of case group and control group were separately (58.69±13.92) years old and (59.27±11.37) years old (χ(2)=4.75, P= 0.191). The people whose fish and seafood intakes ≥3 times/week had the lower risk of OSCC, the adjusted OR (95 %CI ) values were 0.63 (0.52-0.77) and 0.51 (0.41-0.64); The stratified analysis indicated that the people having bad prosthesis had the lower risk of OSCC if they eating fish ≥3 times/week, and the adjusted OR (95 %CI ) values was 0.53 (0.39-0.71); the people having bad prosthesis had the higher risk of OSCC if they eating pickled food ≥3 times/week, the adjusted OR (95 %CI ) values was 1.37 (1.02-1.88). Regularly eating seafood can decrease the risk of OSCC for non-smokers, smokers, non-drinkers, drinkers, people without bad prosthesis and had bad prosthesis, the adjusted OR (95 %CI ) values were 0.49 (0.36-0.68), 0.52 (0.37-0.73), 0.41 (0.31-0.55), 0.77 (0.51-0.96), 0.49 (0.36-0.67), 0.59 (0.42-0.83). Crossover analysis showed fish and bad prosthesis exist multiplication interaction relationship (adjusted OR= 0.66, 95 %CI: 0.44-0.97) and additional interaction relationship ( RERI =-0.81, 95 %CI: -1.43--0.19; AP= -0.76, 95 %CI: -1.35--0.17; S =0.08, 95 %CI: 0.01-0.98); pickled food and bad prosthesis exist multiplication interaction relationship (adjusted OR= 1.63, 95 %CI: 1.06-2.51) and addition interaction relationship ( RERI =0.65, 95 %CI: 0.08-1.22; AP= 0.36, 95 %CI: 0.10-0.62; S =5.19, 95 %CI: 1.32-54.49). Conclusion: Reducing the consumption of pickled food, quitting smoking and limiting alcohol consumption, and regularly eating fish and seafood can prevent the occurrence of OSCC.

Attentional Processes in Interactions between People with Profound Intellectual and Multiple Disabilities and Direct Support Staff

ERIC Educational Resources Information Center

Ine, Hostyn; Heleen, Neerinckx; Bea, Maes

2011-01-01

Few studies have examined joint attention in interactions with persons with profound intellectual and multiple disabilities (PIMD), despite its important role in high-quality interaction. The purpose of this study is to describe the attention-directing behaviours of persons with PIMD and their direct support staff and the attention episodes…

Additive effects prevail: The response of biota to multiple stressors in an intensively monitored watershed.

PubMed

Gieswein, Alexander; Hering, Daniel; Feld, Christian K

2017-09-01

Freshwater ecosystems are impacted by a range of stressors arising from diverse human-caused land and water uses. Identifying the relative importance of single stressors and understanding how multiple stressors interact and jointly affect biology is crucial for River Basin Management. This study addressed multiple human-induced stressors and their effects on the aquatic flora and fauna based on data from standard WFD monitoring schemes. For altogether 1095 sites within a mountainous catchment, we used 12 stressor variables covering three different stressor groups: riparian land use, physical habitat quality and nutrient enrichment. Twenty-one biological metrics calculated from taxa lists of three organism groups (fish, benthic invertebrates and aquatic macrophytes) served as response variables. Stressor and response variables were subjected to Boosted Regression Tree (BRT) analysis to identify stressor hierarchy and stressor interactions and subsequently to Generalised Linear Regression Modelling (GLM) to quantify the stressors standardised effect size. Our results show that riverine habitat degradation was the dominant stressor group for the river fauna, notably the bed physical habitat structure. Overall, the explained variation in benthic invertebrate metrics was higher than it was in fish and macrophyte metrics. In particular, general integrative (aggregate) metrics such as % Ephemeroptera, Plecoptera and Trichoptera (EPT) taxa performed better than ecological traits (e.g. % feeding types). Overall, additive stressor effects dominated, while significant and meaningful stressor interactions were generally rare and weak. We concluded that given the type of stressor and ecological response variables addressed in this study, river basin managers do not need to bother much about complex stressor interactions, but can focus on the prevailing stressors according to the hierarchy identified. Copyright © 2017 Elsevier B.V. All rights reserved.

Compartmentalization and Functionality of Nuclear Disorder: Intrinsic Disorder and Protein-Protein Interactions in Intra-Nuclear Compartments

PubMed Central

Meng, Fanchi; Na, Insung; Kurgan, Lukasz; Uversky, Vladimir N.

2015-01-01

The cell nucleus contains a number of membrane-less organelles or intra-nuclear compartments. These compartments are dynamic structures representing liquid-droplet phases which are only slightly denser than the bulk intra-nuclear fluid. They possess different functions, have diverse morphologies, and are typically composed of RNA (or, in some cases, DNA) and proteins. We analyzed 3005 mouse proteins localized in specific intra-nuclear organelles, such as nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinuclear compartment and compared them with ~29,863 non-nuclear proteins from mouse proteome. Our analysis revealed that intrinsic disorder is enriched in the majority of intra-nuclear compartments, except for the nuclear pore and lamina. These compartments are depleted in proteins that lack disordered domains and enriched in proteins that have multiple disordered domains. Moonlighting proteins found in multiple intra-nuclear compartments are more likely to have multiple disordered domains. Protein-protein interaction networks in the intra-nuclear compartments are denser and include more hubs compared to the non-nuclear proteins. Hubs in the intra-nuclear compartments (except for the nuclear pore) are enriched in disorder compared with non-nuclear hubs and non-nuclear proteins. Therefore, our work provides support to the idea of the functional importance of intrinsic disorder in the cell nucleus and shows that many proteins associated with sub-nuclear organelles in nuclei of mouse cells are enriched in disorder. This high level of disorder in the mouse nuclear proteins defines their ability to serve as very promiscuous binders, possessing both large quantities of potential disorder-based interaction sites and the ability of a single such site to be involved in a large number of interactions. PMID:26712748