Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties

PubMed Central

Xiong, Guanglei; Figueroa, C. Alberto; Xiao, Nan; Taylor, Charles A.

2011-01-01

SUMMARY Simulation of blood flow using image-based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject-specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject-specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline-based and surface-based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject-specific vascular models with thoracic and cerebral aneurysms. PMID:21765984

Multipeak low-temperature behavior of specific heat capacity in frustrated magnetic systems: An exact theoretical analysis

NASA Astrophysics Data System (ADS)

Jurčišinová, E.; Jurčišin, M.

2018-05-01

We investigate in detail the process of formation of the multipeak low-temperature structure in the behavior of the specific heat capacity in frustrated magnetic systems in the framework of the exactly solvable antiferromagnetic spin-1 /2 Ising model with the multisite interaction in the presence of the external magnetic field on the kagome-like Husimi lattice. The behavior of the entropy of the model is studied and exact values of the residual entropies of all ground states are found. It is shown that the multipeak structure in the behavior of the specific heat capacity is related to the formation of the multilevel hierarchical ordering in the system of all ground states of the model. Direct relation between the maximal number of peaks in the specific heat capacity behavior and the number of independent interactions in studied frustrated magnetic system is identified. The mechanism of the formation of the multipeak structure in the specific heat capacity is described and studied in detail, and it is generalized to frustrated magnetic systems with arbitrary numbers of independent interactions.

Specificity of Intramembrane Protein–Lipid Interactions

PubMed Central

Contreras, Francesc-Xabier; Ernst, Andreas Max; Wieland, Felix; Brügger, Britta

2011-01-01

Our concept of biological membranes has markedly changed, from the fluid mosaic model to the current model that lipids and proteins have the ability to separate into microdomains, differing in their protein and lipid compositions. Since the breakthrough in crystallizing membrane proteins, the most powerful method to define lipid-binding sites on proteins has been X-ray and electron crystallography. More recently, chemical biology approaches have been developed to analyze protein–lipid interactions. Such methods have the advantage of providing highly specific cellular probes. With the advent of novel tools to study functions of individual lipid species in membranes together with structural analysis and simulations at the atomistic resolution, a growing number of specific protein–lipid complexes are defined and their functions explored. In the present article, we discuss the various modes of intramembrane protein–lipid interactions in cellular membranes, including examples for both annular and nonannular bound lipids. Furthermore, we will discuss possible functional roles of such specific protein–lipid interactions as well as roles of lipids as chaperones in protein folding and transport. PMID:21536707

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models

PubMed Central

Pires, Mathias M.; Cantor, Maurício; Guimarães, Paulo R.; de Aguiar, Marcus A. M.; dos Reis, Sérgio F.; Coltri, Patricia P.

2015-01-01

The network structure of biological systems provides information on the underlying processes shaping their organization and dynamics. Here we examined the structure of the network depicting protein interactions within the spliceosome, the macromolecular complex responsible for splicing in eukaryotic cells. We show the interactions of less connected spliceosome proteins are nested subsets of the connections of the highly connected proteins. At the same time, the network has a modular structure with groups of proteins sharing similar interaction patterns. We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs. This food-web model was as successful in reproducing the structure of protein interactions as it is in reproducing interactions among species. The good performance of the model suggests affinity and specificity, partially determined by protein size and the timing of association to the complex, may be determining network structure. Moreover, because network models allow building ensembles of realistic networks while encompassing uncertainty they can be useful to examine the dynamics and vulnerability of intracelullar processes. Unraveling the mechanisms organizing the spliceosome interactions is important to characterize the role of individual proteins on splicing catalysis and regulation. PMID:26443080

Using genome-wide measurements for computational prediction of SH2–peptide interactions

PubMed Central

Wunderlich, Zeba; Mirny, Leonid A.

2009-01-01

Peptide-recognition modules (PRMs) are used throughout biology to mediate protein–protein interactions, and many PRMs are members of large protein domain families. Recent genome-wide measurements describe networks of peptide–PRM interactions. In these networks, very similar PRMs recognize distinct sets of peptides, raising the question of how peptide-recognition specificity is achieved using similar protein domains. The analysis of individual protein complex structures often gives answers that are not easily applicable to other members of the same PRM family. Bioinformatics-based approaches, one the other hand, may be difficult to interpret physically. Here we integrate structural information with a large, quantitative data set of SH2 domain–peptide interactions to study the physical origin of domain–peptide specificity. We develop an energy model, inspired by protein folding, based on interactions between the amino-acid positions in the domain and peptide. We use this model to successfully predict which SH2 domains and peptides interact and uncover the positions in each that are important for specificity. The energy model is general enough that it can be applied to other members of the SH2 family or to new peptides, and the cross-validation results suggest that these energy calculations will be useful for predicting binding interactions. It can also be adapted to study other PRM families, predict optimal peptides for a given SH2 domain, or study other biological interactions, e.g. protein–DNA interactions. PMID:19502496

Correlation Imaging Reveals Specific Crowding Dynamics of Kinesin Motor Proteins

NASA Astrophysics Data System (ADS)

Miedema, Daniël M.; Kushwaha, Vandana S.; Denisov, Dmitry V.; Acar, Seyda; Nienhuis, Bernard; Peterman, Erwin J. G.; Schall, Peter

2017-10-01

Molecular motor proteins fulfill the critical function of transporting organelles and other building blocks along the biopolymer network of the cell's cytoskeleton, but crowding effects are believed to crucially affect this motor-driven transport due to motor interactions. Physical transport models, like the paradigmatic, totally asymmetric simple exclusion process (TASEP), have been used to predict these crowding effects based on simple exclusion interactions, but verifying them in experiments remains challenging. Here, we introduce a correlation imaging technique to precisely measure the motor density, velocity, and run length along filaments under crowding conditions, enabling us to elucidate the physical nature of crowding and test TASEP model predictions. Using the kinesin motor proteins kinesin-1 and OSM-3, we identify crowding effects in qualitative agreement with TASEP predictions, and we achieve excellent quantitative agreement by extending the model with motor-specific interaction ranges and crowding-dependent detachment probabilities. These results confirm the applicability of basic nonequilibrium models to the intracellular transport and highlight motor-specific strategies to deal with crowding.

A Feature-Based Approach to Modeling Protein–DNA Interactions

PubMed Central

Segal, Eran

2008-01-01

Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF–DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/. PMID:18725950

Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model.

PubMed

Brand, Matthias; Young, Kimberly S; Laier, Christian; Wölfling, Klaus; Potenza, Marc N

2016-12-01

Within the last two decades, many studies have addressed the clinical phenomenon of Internet-use disorders, with a particular focus on Internet-gaming disorder. Based on previous theoretical considerations and empirical findings, we suggest an Interaction of Person-Affect-Cognition-Execution (I-PACE) model of specific Internet-use disorders. The I-PACE model is a theoretical framework for the processes underlying the development and maintenance of an addictive use of certain Internet applications or sites promoting gaming, gambling, pornography viewing, shopping, or communication. The model is composed as a process model. Specific Internet-use disorders are considered to be the consequence of interactions between predisposing factors, such as neurobiological and psychological constitutions, moderators, such as coping styles and Internet-related cognitive biases, and mediators, such as affective and cognitive responses to situational triggers in combination with reduced executive functioning. Conditioning processes may strengthen these associations within an addiction process. Although the hypotheses regarding the mechanisms underlying the development and maintenance of specific Internet-use disorders, summarized in the I-PACE model, must be further tested empirically, implications for treatment interventions are suggested. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Catching fire? Social interactions, beliefs, and wildfire risk mitigation behaviors

Treesearch

Katherine Dickinson; Hannah Brenkert-Smith; Patricia Champ; Nicholas Flores

2015-01-01

Social interactions are widely recognized as a potential influence on risk-related behaviors. We present a mediation model in which social interactions (classified as formal/informal and generic-fire-specific) are associated with beliefs about wildfire risk and mitigation options, which in turn shape wildfire mitigation behaviors. We test this model using survey data...

Model lipid bilayers mimic non-specific interactions of gold nanoparticles with macrophage plasma membranes.

PubMed

Montis, Costanza; Generini, Viola; Boccalini, Giulia; Bergese, Paolo; Bani, Daniele; Berti, Debora

2018-04-15

Understanding the interaction between nanomaterials and biological interfaces is a key unmet goal that still hampers clinical translation of nanomedicine. Here we investigate and compare non-specific interaction of gold nanoparticles (AuNPs) with synthetic lipid and wild type macrophage membranes. A comprehensive data set was generated by systematically varying the structural and physicochemical properties of the AuNPs (size, shape, charge, surface functionalization) and of the synthetic membranes (composition, fluidity, bending properties and surface charge), which allowed to unveil the matching conditions for the interaction of the AuNPs with macrophage plasma membranes in vitro. This effort directly proved for the first time that synthetic bilayers can be set to mimic and predict with high fidelity key aspects of nanoparticle interaction with macrophage eukaryotic plasma membranes. It then allowed to model the experimental observations according to classical interface thermodynamics and in turn determine the paramount role played by non-specific contributions, primarily electrostatic, Van der Waals and bending energy, in driving nanoparticle-plasma membrane interactions. Copyright © 2018 Elsevier Inc. All rights reserved.

n-Dodecyl β-D-maltoside specifically competes with general anesthetics for anesthetic binding sites.

PubMed

Xu, Longhe; Matsunaga, Felipe; Xi, Jin; Li, Min; Ma, Jingyuan; Liu, Renyu

2014-01-01

We recently demonstrated that the anionic detergent sodium dodecyl sulfate (SDS) specifically interacts with the anesthetic binding site in horse spleen apoferritin, a soluble protein which models anesthetic binding sites in receptors. This raises the possibility of other detergents similarly interacting with and occluding such sites from anesthetics, thereby preventing the proper identification of novel anesthetic binding sites. n-Dodecyl β-D-maltoside (DDM) is a non-ionic detergent commonly used during protein-anesthetic studies because of its mild and non-denaturing properties. In this study, we demonstrate that SDS and DDM occupy anesthetic binding sites in the model proteins human serum albumin (HSA) and horse spleen apoferritin and thereby inhibit the binding of the general anesthetics propofol and isoflurane. DDM specifically interacts with HSA (Kd = 40 μM) with a lower affinity than SDS (Kd = 2 μM). DDM exerts all these effects while not perturbing the native structures of either model protein. Computational calculations corroborated the experimental results by demonstrating that the binding sites for DDM and both anesthetics on the model proteins overlapped. Collectively, our results indicate that DDM and SDS specifically interact with anesthetic binding sites and may thus prevent the identification of novel anesthetic sites. Special precaution should be taken when undertaking and interpreting results from protein-anesthetic investigations utilizing detergents like SDS and DDM.

Towards structural models of molecular recognition in olfactory receptors.

PubMed

Afshar, M; Hubbard, R E; Demaille, J

1998-02-01

The G protein coupled receptors (GPCR) are an important class of proteins that act as signal transducers through the cytoplasmic membrane. Understanding the structure and activation mechanism of these proteins is crucial for understanding many different aspects of cellular signalling. The olfactory receptors correspond to the largest family of GPCRs. Very little is known about how the structures of the receptors govern the specificity of interaction which enables identification of particular odorant molecules. In this paper, we review recent developments in two areas of molecular modelling: methods for modelling the configuration of trans-membrane helices and methods for automatic docking of ligands into receptor structures. We then show how a subset of these methods can be combined to construct a model of a rat odorant receptor interacting with lyral for which experimental data are available. This modelling can help us make progress towards elucidating the specificity of interactions between receptors and odorant molecules.

Assessing Spurious Interaction Effects in Structural Equation Modeling

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming

2015-01-01

Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…

Physiologically relevant organs on chips

PubMed Central

Yum, Kyungsuk; Hong, Soon Gweon; Lee, Luke P.

2015-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or organs on chips, that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue–tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. PMID:24357624

Molecular modeling of class I and II alleles of the major histocompatibility complex in Salmo salar.

PubMed

Cárdenas, Constanza; Bidon-Chanal, Axel; Conejeros, Pablo; Arenas, Gloria; Marshall, Sergio; Luque, F Javier

2010-12-01

Knowledge of the 3D structure of the binding groove of major histocompatibility (MHC) molecules, which play a central role in the immune response, is crucial to shed light into the details of peptide recognition and polymorphism. This work reports molecular modeling studies aimed at providing 3D models for two class I and two class II MHC alleles from Salmo salar (Sasa), as the lack of experimental structures of fish MHC molecules represents a serious limitation to understand the specific preferences for peptide binding. The reliability of the structural models built up using bioinformatic tools was explored by means of molecular dynamics simulations of their complexes with representative peptides, and the energetics of the MHC-peptide interaction was determined by combining molecular mechanics interaction energies and implicit continuum solvation calculations. The structural models revealed the occurrence of notable differences in the nature of residues at specific positions in the binding groove not only between human and Sasa MHC proteins, but also between different Sasa alleles. Those differences lead to distinct trends in the structural features that mediate the binding of peptides to both class I and II MHC molecules, which are qualitatively reflected in the relative binding affinities. Overall, the structural models presented here are a valuable starting point to explore the interactions between MHC receptors and pathogen-specific interactions and to design vaccines against viral pathogens.

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases*

PubMed Central

Tinti, Michele; Paoluzi, Serena; Santonico, Elena; Masch, Antonia; Schutkowski, Mike

2017-01-01

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level. PMID:28159843

Development of 3D browsing and interactive web system

NASA Astrophysics Data System (ADS)

Shi, Xiaonan; Fu, Jian; Jin, Chaolin

2017-09-01

In the current market, users need to download specific software or plug-ins to browse the 3D model, and browsing the system may be unstable, and it cannot be 3D model interaction issues In order to solve this problem, this paper presents a solution to the interactive browsing of the model in the server-side parsing model, and when the system is applied, the user only needs to input the system URL and upload the 3D model file to operate the browsing The server real-time parsing 3D model, the interactive response speed, these completely follows the user to walk the minimalist idea, and solves the current market block 3D content development question.

Course 1: Physics of Protein-DNA Interaction

NASA Astrophysics Data System (ADS)

Bruinsma, R. F.

1 Introduction 1.1 The central dogma and bacterial gene expression 1.2 Molecular structure 2 Thermodynamics and kinetics of repressor-DNA interaction 2.1 Thermodynamics and the lac repressor 2.2 Kinetics of repressor-DNA interaction 3 DNA deformability and protein-DNA interaction 3.1 Introduction 3.2 The worm-like chain 3.3 The RST model 4 Electrostatics in water and protein-DNA interaction 4.1 Macro-ions and aqueous electrostatics 4.2 The primitive model 4.3 Manning condensation 4.4 Counter-ion release and non-specific protein-DNA interaction

The influence of instructional interactions on students’ mental models about the quantization of physical observables: a modern physics course case

NASA Astrophysics Data System (ADS)

Didiş Körhasan, Nilüfer; Eryılmaz, Ali; Erkoç, Şakir

2016-01-01

Mental models are coherently organized knowledge structures used to explain phenomena. They interact with social environments and evolve with the interaction. Lacking daily experience with phenomena, the social interaction gains much more importance. In this part of our multiphase study, we investigate how instructional interactions influenced students’ mental models about the quantization of physical observables. Class observations and interviews were analysed by studying students’ mental models constructed in a modern physics course during an academic semester. The research revealed that students’ mental models were influenced by (1) the manner of teaching, including instructional methodologies and content specific techniques used by the instructor, (2) order of the topics and familiarity with concepts, and (3) peers.

Refining metabolic models and accounting for regulatory effects.

PubMed

Kim, Joonhoon; Reed, Jennifer L

2014-10-01

Advances in genome-scale metabolic modeling allow us to investigate and engineer metabolism at a systems level. Metabolic network reconstructions have been made for many organisms and computational approaches have been developed to convert these reconstructions into predictive models. However, due to incomplete knowledge these reconstructions often have missing or extraneous components and interactions, which can be identified by reconciling model predictions with experimental data. Recent studies have provided methods to further improve metabolic model predictions by incorporating transcriptional regulatory interactions and high-throughput omics data to yield context-specific metabolic models. Here we discuss recent approaches for resolving model-data discrepancies and building context-specific metabolic models. Once developed highly accurate metabolic models can be used in a variety of biotechnology applications. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

A Grammar-based Approach for Modeling User Interactions and Generating Suggestions During the Data Exploration Process.

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

Despite the recent popularity of visual analytics focusing on big data, little is known about how to support users that use visualization techniques to explore multi-dimensional datasets and accomplish specific tasks. Our lack of models that can assist end-users during the data exploration process has made it challenging to learn from the user's interactive and analytical process. The ability to model how a user interacts with a specific visualization technique and what difficulties they face are paramount in supporting individuals with discovering new patterns within their complex datasets. This paper introduces the notion of visualization systems understanding and modeling user interactions with the intent of guiding a user through a task thereby enhancing visual data exploration. The challenges faced and the necessary future steps to take are discussed; and to provide a working example, a grammar-based model is presented that can learn from user interactions, determine the common patterns among a number of subjects using a K-Reversible algorithm, build a set of rules, and apply those rules in the form of suggestions to new users with the goal of guiding them along their visual analytic process. A formal evaluation study with 300 subjects was performed showing that our grammar-based model is effective at capturing the interactive process followed by users and that further research in this area has the potential to positively impact how users interact with a visualization system.

The Drosophila melanogaster host model

PubMed Central

Igboin, Christina O.; Griffen, Ann L.; Leys, Eugene J.

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed. PMID:22368770

The Drosophila melanogaster host model.

PubMed

Igboin, Christina O; Griffen, Ann L; Leys, Eugene J

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen-host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial-host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis-host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed.

Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer.

PubMed

Degeling, Koen; Schivo, Stefano; Mehra, Niven; Koffijberg, Hendrik; Langerak, Rom; de Bono, Johann S; IJzerman, Maarten J

2017-12-01

With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required. To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions. An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed. Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure. Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A neural basis for category and modality specificity of semantic knowledge.

PubMed

Thompson-Schill, S L; Aguirre, G K; D'Esposito, M; Farah, M J

1999-06-01

Prevalent theories hold that semantic memory is organized by sensorimotor modality (e.g., visual knowledge, motor knowledge). While some neuroimaging studies support this idea, it cannot account for the category specific (e.g., living things) knowledge impairments seen in some brain damaged patients that cut across modalities. In this article we test an alternative model of how damage to interactive, modality-specific neural regions might give rise to these categorical impairments. Functional MRI was used to examine a cortical area with a known modality-specific function during the retrieval of visual and non-visual knowledge about living and non-living things. The specific predictions of our model regarding the signal observed in this area were confirmed, supporting the notion that semantic memory is functionally segregated into anatomically discrete, but highly interactive, modality-specific regions.

Genome-wide inference of transcription factor-DNA binding specificity in cell regeneration using a combination strategy.

PubMed

Wang, Xiaofeng; Zhang, Aiqun; Ren, Weizheng; Chen, Caiyu; Dong, Jiahong

2012-11-01

The cell growth, development, and regeneration of tissue and organ are associated with a large number of gene regulation events, which are mediated in part by transcription factors (TFs) binding to cis-regulatory elements involved in the genome. Predicting the binding affinity and inferring the binding specificity of TF-DNA interactions at the genomic level would be fundamentally helpful for our understanding of the molecular mechanism and biological implication underlying sequence-specific TF-DNA recognition. In this study, we report the development of a combination method to characterize the interaction behavior of a 11-mer oligonucleotide segment and its mutations with the Gcn4p protein, a homodimeric, basic leucine zipper TF, and to predict the binding affinity and specificity of potential Gcn4p binders in the genome-wide scale. In this procedure, a position-mutated energy matrix is created based on molecular modeling analysis of native and mutated Gcn4p-DNA complex structures to describe the position-independent interaction energy profile of Gcn4p with different nucleotide types at each position of the oligonucleotide, and the energy terms extracted from the matrix and their interactives are then correlated with experimentally measured affinities of 19268 distinct oligonucleotides using statistical modeling methodology. Subsequently, the best one of built regression models is successfully applied to screen those of potential high-affinity Gcn4p binders from the complete genome. The findings arising from this study are briefly listed below: (i) The 11 positions of oligonucleotides are highly interactive and non-additive in contribution to Gcn4p-DNA binding affinity; (ii) Indirect conformational effects upon nucleotide mutations as well as associated subtle changes in interfacial atomic contacts, but not the direct nonbonded interactions, are primarily responsible for the sequence-specific recognition; (iii) The intrinsic synergistic effects among the sequence positions of oligonucleotides determine Gcn4p-DNA binding affinity and specificity; (iv) Linear regression models in conjunction with variable selection seem to perform fairly well in capturing the internal dependences hidden in the Gcn4p-DNA system, albeit ignoring nonlinear factors may lead the models to systematically underestimate and overestimate high- and low-affinity samples, respectively. © 2012 John Wiley & Sons A/S.

The importance of understanding: Model space moderates goal specificity effects.

PubMed

Kistner, Saskia; Burns, Bruce D; Vollmeyer, Regina; Kortenkamp, Ulrich

2016-01-01

The three-space theory of problem solving predicts that the quality of a learner's model and the goal specificity of a task interact on knowledge acquisition. In Experiment 1 participants used a computer simulation of a lever system to learn about torques. They either had to test hypotheses (nonspecific goal), or to produce given values for variables (specific goal). In the good- but not in the poor-model condition they saw torque depicted as an area. Results revealed the predicted interaction. A nonspecific goal only resulted in better learning when a good model of torques was provided. In Experiment 2 participants learned to manipulate the inputs of a system to control its outputs. A nonspecific goal to explore the system helped performance when compared to a specific goal to reach certain values when participants were given a good model, but not when given a poor model that suggested the wrong hypothesis space. Our findings support the three-space theory. They emphasize the importance of understanding for problem solving and stress the need to study underlying processes.

The "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability.

PubMed

Derewenda, Zygmunt S; Godzik, Adam

2017-01-01

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e., crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure, and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular "sticky patch" model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer "sticky patches" which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the "sticky patch" model. We discuss state-of-the-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis.

Ferromagnetic interaction model of activity level in workplace communication

NASA Astrophysics Data System (ADS)

Akitomi, Tomoaki; Ara, Koji; Watanabe, Jun-ichiro; Yano, Kazuo

2013-03-01

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

Microbial Interactions within a Cheese Microbial Community▿ †

PubMed Central

Mounier, Jérôme; Monnet, Christophe; Vallaeys, Tatiana; Arditi, Roger; Sarthou, Anne-Sophie; Hélias, Arnaud; Irlinger, Françoise

2008-01-01

The interactions that occur during the ripening of smear cheeses are not well understood. Yeast-yeast interactions and yeast-bacterium interactions were investigated within a microbial community composed of three yeasts and six bacteria found in cheese. The growth dynamics of this community was precisely described during the ripening of a model cheese, and the Lotka-Volterra model was used to evaluate species interactions. Subsequently, the effects on ecosystem functioning of yeast omissions in the microbial community were evaluated. It was found both in the Lotka-Volterra model and in the omission study that negative interactions occurred between yeasts. Yarrowia lipolytica inhibited mycelial expansion of Geotrichum candidum, whereas Y. lipolytica and G. candidum inhibited Debaryomyces hansenii cell viability during the stationary phase. However, the mechanisms involved in these interactions remain unclear. It was also shown that yeast-bacterium interactions played a significant role in the establishment of this multispecies ecosystem on the cheese surface. Yeasts were key species in bacterial development, but their influences on the bacteria differed. It appeared that the growth of Arthrobacter arilaitensis or Hafnia alvei relied less on a specific yeast function because these species dominated the bacterial flora, regardless of which yeasts were present in the ecosystem. For other bacteria, such as Leucobacter sp. or Brevibacterium aurantiacum, growth relied on a specific yeast, i.e., G. candidum. Furthermore, B. aurantiacum, Corynebacterium casei, and Staphylococcus xylosus showed reduced colonization capacities in comparison with the other bacteria in this model cheese. Bacterium-bacterium interactions could not be clearly identified. PMID:17981942

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Exploring divergent trajectories: Disorder-specific moderators of the association between negative urgency and dysregulated eating.

PubMed

Racine, Sarah E; Martin, Shelby J

2016-08-01

Negative urgency (i.e., the tendency to act impulsively when experiencing negative emotions) is a well-established risk factor for dysregulated eating (e.g., binge eating, loss of control eating, emotional eating). However, negative urgency is transdiagnostic, in that it is associated with multiple forms of psychopathology. It is currently unclear why some individuals with high negative urgency develop dysregulated eating while others experience depressive symptoms or problematic alcohol use. Investigating disorder-specific moderators of the association between negative urgency and psychopathology may help elucidate these divergent trajectories. The current study examined interactions among negative urgency and eating disorder-specific risk factors specified in the well-established dual-pathway model of bulimic pathology (i.e., appearance pressures, thin-ideal internalization, body dissatisfaction, dietary restraint). We hypothesized that these interactions would predict dysregulated eating, but not depressive symptoms or problematic alcohol use. Latent moderated structural equation modeling was used to test this hypothesis in a large (N = 313) sample of female college students. Negative urgency was significantly associated with dysregulated eating, depressive symptoms, and problematic alcohol use. However, interactions among negative urgency and dual-pathway model variables were specific to dysregulated eating and accounted for an additional 3-5% of the variance beyond main effects. Findings suggest that eating disorder-specific risk factors may shape negative urgency into manifesting as dysregulated eating versus another form of psychopathology. Future research should use longitudinal designs to further test the impact of interactions among disorder-specific risk factors and negative urgency on divergent psychopathology trajectories. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comprehensive model of the railway wheelset-track interaction in curves

NASA Astrophysics Data System (ADS)

Martínez-Casas, José; Di Gialleonardo, Egidio; Bruni, Stefano; Baeza, Luis

2014-09-01

Train-track interaction has been extensively studied in the last 40 years at least, leading to modelling approaches that can deal satisfactorily with many dynamic problems arising at the wheel/rail interface. However, the available models are usually not considering specifically the running dynamics of the vehicle in a curve, whereas a number of train-track interaction phenomena are specific to curve negotiation. The aim of this paper is to define a model for a flexible wheelset running on a flexible curved track. The main novelty of this work is to combine a trajectory coordinate set with Eulerian modal coordinates; the former permits to consider curved tracks, and the latter models the small relative displacements between the trajectory frame and the solid. In order to reduce the computational complexity of the problem, one single flexible wheelset is considered instead of one complete bogie, and suitable forces are prescribed at the primary suspension seats so that the mean values of the creepages and contact forces are consistent with the low frequency curving dynamics of the complete vehicle. The wheelset model is coupled to a cyclic track model having constant curvature by means of a wheel/rail contact model which accounts for the actual geometry of the contacting profiles and for the nonlinear relationship between creepages and creep forces. The proposed model can be used to analyse a variety of dynamic problems for railway vehicles, including rail corrugation and wheel polygonalisation, squeal noise, numerical estimation of the wheelset service loads. In this paper, simulation results are presented for some selected running conditions to exemplify the application of the model to the study of realistic train-track interaction cases and to point out the importance of curve negotiation effects specifically addressed in the work.

The Semantic Environment: Heuristics for a Cross-Context Human-Information Interaction Model

NASA Astrophysics Data System (ADS)

Resmini, Andrea; Rosati, Luca

This chapter introduces a multidisciplinary holistic approach for the general design of successful bridge experiences as a cross-context human-information interaction model. Nowadays it is common to interact through a number of different domains in order to communicate successfully, complete a task, or elicit a desired response: Users visit a reseller’s web site to find a specific item, book it, then drive to the closest store to complete their purchase. As such, one of the crucial challenges user experience design will face in the near future is how to structure and provide bridge experiences seamlessly spanning multiple communication channels or media formats for a specific purpose.

In Silico, Experimental, Mechanistic Model for Extended-Release Felodipine Disposition Exhibiting Complex Absorption and a Highly Variable Food Interaction

PubMed Central

Kim, Sean H. J.; Jackson, Andre J.; Hunt, C. Anthony

2014-01-01

The objective of this study was to develop and explore new, in silico experimental methods for deciphering complex, highly variable absorption and food interaction pharmacokinetics observed for a modified-release drug product. Toward that aim, we constructed an executable software analog of study participants to whom product was administered orally. The analog is an object- and agent-oriented, discrete event system, which consists of grid spaces and event mechanisms that map abstractly to different physiological features and processes. Analog mechanisms were made sufficiently complicated to achieve prespecified similarity criteria. An equation-based gastrointestinal transit model with nonlinear mixed effects analysis provided a standard for comparison. Subject-specific parameterizations enabled each executed analog’s plasma profile to mimic features of the corresponding six individual pairs of subject plasma profiles. All achieved prespecified, quantitative similarity criteria, and outperformed the gastrointestinal transit model estimations. We observed important subject-specific interactions within the simulation and mechanistic differences between the two models. We hypothesize that mechanisms, events, and their causes occurring during simulations had counterparts within the food interaction study: they are working, evolvable, concrete theories of dynamic interactions occurring within individual subjects. The approach presented provides new, experimental strategies for unraveling the mechanistic basis of complex pharmacological interactions and observed variability. PMID:25268237

Degeneracy-Driven Self-Structuring Dynamics in Selective Repertoires

PubMed Central

Atamas, Sergei P.; Bell, Jonathan

2013-01-01

Numerous biological interactions, such as interactions between T cell receptors or antibodies with antigens, interactions between enzymes and substrates, or interactions between predators and prey are often not strictly specific. In such less specific, or “sloppy,” systems, referred to here as degenerate systems, a given unit of a diverse resource (antigens, enzymatic substrates, prey) is at risk of being recognized and consumed by multiple consumers (lymphocytes, enzymes, predators). In this study, we model generalized degenerate consumer-resource systems of Lotka–Volterra and Verhulst types. In the degenerate systems of Lotka–Volterra, there is a continuum of types of consumer and resource based on variation of a single trait (characteristic, or preference). The consumers experience competition for a continuum of resource types. This non-local interaction system is modeled with partial differential-integral equations and shows spontaneous self-structuring of the consumer population that depends on the degree of interaction degeneracy between resource and consumer, but does not mirror the distribution of resource. We also show that the classical Verhulst (i.e. logistic) single population model can be generalized to a degenerate model, which shows qualitative behavior similar to that in the degenerate Lotka–Volterra model. These results provide better insight into the dynamics of selective systems in biology, suggesting that adaptation of degenerate repertoires is not a simple “mirroring” of the environment by the “fittest” elements of population. PMID:19337776

Degeneracy-driven self-structuring dynamics in selective repertoires.

PubMed

Atamas, Sergei P; Bell, Jonathan

2009-08-01

Numerous biological interactions, such as interactions between T cell receptors or antibodies with antigens, interactions between enzymes and substrates, or interactions between predators and prey are often not strictly specific. In such less specific, or "sloppy," systems, referred to here as degenerate systems, a given unit of a diverse resource (antigens, enzymatic substrates, prey) is at risk of being recognized and consumed by multiple consumers (lymphocytes, enzymes, predators). In this study, we model generalized degenerate consumer-resource systems of Lotka-Volterra and Verhulst types. In the degenerate systems of Lotka-Volterra, there is a continuum of types of consumer and resource based on variation of a single trait (characteristic, or preference). The consumers experience competition for a continuum of resource types. This non-local interaction system is modeled with partial differential-integral equations and shows spontaneous self-structuring of the consumer population that depends on the degree of interaction degeneracy between resource and consumer, but does not mirror the distribution of resource. We also show that the classical Verhulst (i.e. logistic) single population model can be generalized to a degenerate model, which shows qualitative behavior similar to that in the degenerate Lotka-Volterra model. These results provide better insight into the dynamics of selective systems in biology, suggesting that adaptation of degenerate repertoires is not a simple "mirroring" of the environment by the "fittest" elements of population.

Physiologically relevant organs on chips.

PubMed

Yum, Kyungsuk; Hong, Soon Gweon; Healy, Kevin E; Lee, Luke P

2014-01-01

Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or also known as "ogans-on-chips", that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue-tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Pipeline for Constructing a Catalog of Multi-method Models of Interacting Galaxies

NASA Astrophysics Data System (ADS)

Holincheck, Anthony

Galaxies represent a fundamental unit of matter for describing the large-scale structure of the universe. One of the major processes affecting the formation and evolution of galaxies are mutual interactions. These interactions can including gravitational tidal distortion, mass transfer, and even mergers. In any hierarchical model, mergers are the key mechanism in galaxy formation and evolution. Computer simulations of interacting galaxies have evolved in the last four decades from simple restricted three-body algorithms to full n-body gravity models. These codes often included sophisticated physical mechanisms such as gas dynamics, supernova feedback, and central blackholes. As the level of complexity, and perhaps realism, increases so does the amount of computational resources needed. These advanced simulations are often used in parameter studies of interactions. They are usually only employed in an ad hoc fashion to recreate the dynamical history of specific sets of interacting galaxies. These specific models are often created with only a few dozen or at most few hundred sets of simulation parameters being attempted. This dissertation presents a prototype pipeline for modeling specific pairs of interacting galaxies in bulk. The process begins with a simple image of the current disturbed morphology and an estimate of distance to the system and mass of the galaxies. With the use of an updated restricted three-body simulation code and the help of Citizen Scientists, the pipeline is able to sample hundreds of thousands of points in parameter space for each system. Through the use of a convenient interface and innovative scoring algorithm, the pipeline aids researchers in identifying the best set of simulation parameters. This dissertation demonstrates a successful recreation of the disturbed morphologies of 62 pairs of interacting galaxies. The pipeline also provides for examining the level of convergence and uniqueness of the dynamical properties of each system. By creating a population of models for actual systems, the current research is able to compare simulation-based and observational values on a larger scale than previous efforts. Several potential relationships between star formation rate and dynamical time since closest approach are presented.

Modeling mechanical cardiopulmonary interactions for virtual environments.

PubMed

Kaye, J M

1997-01-01

We have developed a computer system for modeling mechanical cardiopulmonary behavior in an interactive, 3D virtual environment. The system consists of a compact, scalar description of cardiopulmonary mechanics, with an emphasis on respiratory mechanics, that drives deformable 3D anatomy to simulate mechanical behaviors of and interactions between physiological systems. Such an environment can be used to facilitate exploration of cardiopulmonary physiology, particularly in situations that are difficult to reproduce clinically. We integrate 3D deformable body dynamics with new, formal models of (scalar) cardiorespiratory physiology, associating the scalar physiological variables and parameters with corresponding 3D anatomy. Our approach is amenable to modeling patient-specific circumstances in two ways. First, using CT scan data, we apply semi-automatic methods for extracting and reconstructing the anatomy to use in our simulations. Second, our scalar models are defined in terms of clinically-measurable, patient-specific parameters. This paper describes our approach and presents a sample of results showing normal breathing and acute effects of pneumothoraces.

Exploring Relationships between Students' Interaction and Learning with a Haptic Virtual Biomolecular Model

ERIC Educational Resources Information Center

Schonborn, Konrad J.; Bivall, Petter; Tibell, Lena A. E.

2011-01-01

This study explores tertiary students' interaction with a haptic virtual model representing the specific binding of two biomolecules, a core concept in molecular life science education. Twenty students assigned to a "haptics" (experimental) or "no-haptics" (control) condition performed a "docking" task where users sought the most favourable…

Numerical implementation of a cold-ion, Boltzmann-electron model for nonplanar plasma-surface interactions

NASA Astrophysics Data System (ADS)

Holgate, J. T.; Coppins, M.

2018-04-01

Plasma-surface interactions are ubiquitous in the field of plasma science and technology. Much of the physics of these interactions can be captured with a simple model comprising a cold ion fluid and electrons which satisfy the Boltzmann relation. However, this model permits analytical solutions in a very limited number of cases. This paper presents a versatile and robust numerical implementation of the model for arbitrary surface geometries in cartesian and axisymmetric cylindrical coordinates. Specific examples of surfaces with sinusoidal corrugations, trenches, and hemi-ellipsoidal protrusions verify this numerical implementation. The application of the code to problems involving plasma-liquid interactions, plasma etching, and electron emission from the surface is discussed.

Study of a tri-trophic prey-dependent food chain model of interacting populations.

PubMed

Haque, Mainul; Ali, Nijamuddin; Chakravarty, Santabrata

2013-11-01

The current paper accounts for the influence of intra-specific competition among predators in a prey dependent tri-trophic food chain model of interacting populations. We offer a detailed mathematical analysis of the proposed food chain model to illustrate some of the significant results that has arisen from the interplay of deterministic ecological phenomena and processes. Biologically feasible equilibria of the system are observed and the behaviours of the system around each of them are described. In particular, persistence, stability (local and global) and bifurcation (saddle-node, transcritical, Hopf-Andronov) analysis of this model are obtained. Relevant results from previous well known food chain models are compared with the current findings. Global stability analysis is also carried out by constructing appropriate Lyapunov functions. Numerical simulations show that the present system is capable enough to produce chaotic dynamics when the rate of self-interaction is very low. On the other hand such chaotic behaviour disappears for a certain value of the rate of self interaction. In addition, numerical simulations with experimented parameters values confirm the analytical results and shows that intra-specific competitions bears a potential role in controlling the chaotic dynamics of the system; and thus the role of self interactions in food chain model is illustrated first time. Finally, a discussion of the ecological applications of the analytical and numerical findings concludes the paper. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

DOE PAGES

Melero, Cristina; Ollikainen, Noah; Harwood, Ian; ...

2014-10-13

Re-engineering protein–protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of “second-site suppressors,” where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein–protein interfaces. To extend this approach, it would be advantageous to be able to “transplant” existing engineered and experimentally validated specificity changes to other homologous protein–protein complexes. Here, we test thismore » strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain–peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein–protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein–protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.« less

Quantification of the transferability of a designed protein specificity switch reveals extensive epistasis in molecular recognition

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

Melero, Cristina; Ollikainen, Noah; Harwood, Ian

Re-engineering protein–protein recognition is an important route to dissecting and controlling complex interaction networks. Experimental approaches have used the strategy of “second-site suppressors,” where a functional interaction is inferred between two proteins if a mutation in one protein can be compensated by a mutation in the second. Mimicking this strategy, computational design has been applied successfully to change protein recognition specificity by predicting such sets of compensatory mutations in protein–protein interfaces. To extend this approach, it would be advantageous to be able to “transplant” existing engineered and experimentally validated specificity changes to other homologous protein–protein complexes. Here, we test thismore » strategy by designing a pair of mutations that modulates peptide recognition specificity in the Syntrophin PDZ domain, confirming the designed interaction biochemically and structurally, and then transplanting the mutations into the context of five related PDZ domain–peptide complexes. We find a wide range of energetic effects of identical mutations in structurally similar positions, revealing a dramatic context dependence (epistasis) of designed mutations in homologous protein–protein interactions. To better understand the structural basis of this context dependence, we apply a structure-based computational model that recapitulates these energetic effects and we use this model to make and validate forward predictions. The context dependence of these mutations is captured by computational predictions, our results both highlight the considerable difficulties in designing protein–protein interactions and provide challenging benchmark cases for the development of improved protein modeling and design methods that accurately account for the context.« less

Variable sound speed in interacting dark energy models

NASA Astrophysics Data System (ADS)

Linton, Mark S.; Pourtsidou, Alkistis; Crittenden, Robert; Maartens, Roy

2018-04-01

We consider a self-consistent and physical approach to interacting dark energy models described by a Lagrangian, and identify a new class of models with variable dark energy sound speed. We show that if the interaction between dark energy in the form of quintessence and cold dark matter is purely momentum exchange this generally leads to a dark energy sound speed that deviates from unity. Choosing a specific sub-case, we study its phenomenology by investigating the effects of the interaction on the cosmic microwave background and linear matter power spectrum. We also perform a global fitting of cosmological parameters using CMB data, and compare our findings to ΛCDM.

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

Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago

Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a modelmore » which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.« less

New Gravity Wave Treatments for GISS Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

2011-01-01

Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.

New Gravity Wave Treatments for GISS Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

2010-01-01

Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, we introduce a relatively simple and computationally efficient specification of unresolved orographic and non-orographic gravity waves and their interaction with the resolved flow. We show comparisons of the GISS model winds and temperatures with no gravity wave parametrization; with only orographic gravity wave parameterization; and with both orographic and non-orographic gravity wave parameterizations to illustrate how the zonal mean winds and temperatures converge toward observations. We also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. We then show results where the non-orographic gravity wave sources are specified to represent sources from convection in the Intertropical Convergence Zone and spontaneous emission from jet imbalances. Finally, we suggest a strategy to include these effects in a climate dependent manner.

The ‘Sticky Patch’ Model of Crystallization and Modification of Proteins for Enhanced Crystallizability

PubMed Central

Derewenda, Zygmunt S.; Godzik, Adam

2017-01-01

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e. crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular ‘sticky patch’ model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer ‘sticky patches’ which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the ‘sticky patch’ model. We discuss state-of-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design of variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis. PMID:28573570

An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization.

PubMed

Szałaj, Przemysław; Tang, Zhonghui; Michalski, Paul; Pietal, Michal J; Luo, Oscar J; Sadowski, Michał; Li, Xingwang; Radew, Kamen; Ruan, Yijun; Plewczynski, Dariusz

2016-12-01

ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures. © 2016 Szałaj et al.; Published by Cold Spring Harbor Laboratory Press.

Modeling Wood Encroachment in Abandoned Grasslands in the Eifel National Park – Model Description and Testing

PubMed Central

Hudjetz, Silvana; Lennartz, Gottfried; Krämer, Klara; Roß-Nickoll, Martina; Gergs, André; Preuss, Thomas G.

2014-01-01

The degradation of natural and semi-natural landscapes has become a matter of global concern. In Germany, semi-natural grasslands belong to the most species-rich habitat types but have suffered heavily from changes in land use. After abandonment, the course of succession at a specific site is often difficult to predict because many processes interact. In order to support decision making when managing semi-natural grasslands in the Eifel National Park, we built the WoodS-Model (Woodland Succession Model). A multimodeling approach was used to integrate vegetation dynamics in both the herbaceous and shrub/tree layer. The cover of grasses and herbs was simulated in a compartment model, whereas bushes and trees were modelled in an individual-based manner. Both models worked and interacted in a spatially explicit, raster-based landscape. We present here the model description, parameterization and testing. We show highly detailed projections of the succession of a semi-natural grassland including the influence of initial vegetation composition, neighborhood interactions and ungulate browsing. We carefully weighted the single processes against each other and their relevance for landscape development under different scenarios, while explicitly considering specific site conditions. Model evaluation revealed that the model is able to emulate successional patterns as observed in the field as well as plausible results for different population densities of red deer. Important neighborhood interactions such as seed dispersal, the protection of seedlings from browsing ungulates by thorny bushes, and the inhibition of wood encroachment by the herbaceous layer, have been successfully reproduced. Therefore, not only a detailed model but also detailed initialization turned out to be important for spatially explicit projections of a given site. The advantage of the WoodS-Model is that it integrates these many mutually interacting processes of succession. PMID:25494057

Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

ERIC Educational Resources Information Center

Zigic, Sasha; Lemckert, Charles J.

2007-01-01

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

Identifying Affordances of 3D Printed Tangible Models for Understanding Core Biological Concepts

ERIC Educational Resources Information Center

Davenport, Jodi L.; Silberglitt, Matt; Boxerman, Jonathan; Olson, Arthur

2014-01-01

3D models derived from actual molecular structures have the potential to transform student learning in biology. We share findings related to our research questions: 1) what types of interactions with a protein folding kit promote specific learning objectives?, and 2) what features of the instructional environment (e.g., peer interactions, teacher…

Specificity and mechanism of action of alpha-helical membrane-active peptides interacting with model and biological membranes by single-molecule force spectroscopy.

PubMed

Sun, Shiyu; Zhao, Guangxu; Huang, Yibing; Cai, Mingjun; Shan, Yuping; Wang, Hongda; Chen, Yuxin

2016-07-01

In this study, to systematically investigate the targeting specificity of membrane-active peptides on different types of cell membranes, we evaluated the effects of peptides on different large unilamellar vesicles mimicking prokaryotic, normal eukaryotic, and cancer cell membranes by single-molecule force spectroscopy and spectrum technology. We revealed that cationic membrane-active peptides can exclusively target negatively charged prokaryotic and cancer cell model membranes rather than normal eukaryotic cell model membranes. Using Acholeplasma laidlawii, 3T3-L1, and HeLa cells to represent prokaryotic cells, normal eukaryotic cells, and cancer cells in atomic force microscopy experiments, respectively, we further studied that the single-molecule targeting interaction between peptides and biological membranes. Antimicrobial and anticancer activities of peptides exhibited strong correlations with the interaction probability determined by single-molecule force spectroscopy, which illustrates strong correlations of peptide biological activities and peptide hydrophobicity and charge. Peptide specificity significantly depends on the lipid compositions of different cell membranes, which validates the de novo design of peptide therapeutics against bacteria and cancers.

Image-Based Patient-Specific Ventricle Models with Fluid-Structure Interaction for Cardiac Function Assessment and Surgical Design Optimization

PubMed Central

Tang, Dalin; Yang, Chun; Geva, Tal; del Nido, Pedro J.

2010-01-01

Recent advances in medical imaging technology and computational modeling techniques are making it possible that patient-specific computational ventricle models be constructed and used to test surgical hypotheses and replace empirical and often risky clinical experimentation to examine the efficiency and suitability of various reconstructive procedures in diseased hearts. In this paper, we provide a brief review on recent development in ventricle modeling and its potential application in surgical planning and management of tetralogy of Fallot (ToF) patients. Aspects of data acquisition, model selection and construction, tissue material properties, ventricle layer structure and tissue fiber orientations, pressure condition, model validation and virtual surgery procedures (changing patient-specific ventricle data and perform computer simulation) were reviewed. Results from a case study using patient-specific cardiac magnetic resonance (CMR) imaging and right/left ventricle and patch (RV/LV/Patch) combination model with fluid-structure interactions (FSI) were reported. The models were used to evaluate and optimize human pulmonary valve replacement/insertion (PVR) surgical procedure and patch design and test a surgical hypothesis that PVR with small patch and aggressive scar tissue trimming in PVR surgery may lead to improved recovery of RV function and reduced stress/strain conditions in the patch area. PMID:21344066

Sequence-Specific Model for Peptide Retention Time Prediction in Strong Cation Exchange Chromatography.

PubMed

Gussakovsky, Daniel; Neustaeter, Haley; Spicer, Victor; Krokhin, Oleg V

2017-11-07

The development of a peptide retention prediction model for strong cation exchange (SCX) separation on a Polysulfoethyl A column is reported. Off-line 2D LC-MS/MS analysis (SCX-RPLC) of S. cerevisiae whole cell lysate was used to generate a retention dataset of ∼30 000 peptides, sufficient for identifying the major sequence-specific features of peptide retention mechanisms in SCX. In contrast to RPLC/hydrophilic interaction liquid chromatography (HILIC) separation modes, where retention is driven by hydrophobic/hydrophilic contributions of all individual residues, SCX interactions depend mainly on peptide charge (number of basic residues at acidic pH) and size. An additive model (incorporating the contributions of all 20 residues into the peptide retention) combined with a peptide length correction produces a 0.976 R 2 value prediction accuracy, significantly higher than the additive models for either HILIC or RPLC. Position-dependent effects on peptide retention for different residues were driven by the spatial orientation of tryptic peptides upon interaction with the negatively charged surface functional groups. The positively charged N-termini serve as a primary point of interaction. For example, basic residues (Arg, His, Lys) increase peptide retention when located closer to the N-terminus. We also found that hydrophobic interactions, which could lead to a mixed-mode separation mechanism, are largely suppressed at 20-30% of acetonitrile in the eluent. The accuracy of the final Sequence-Specific Retention Calculator (SSRCalc) SCX model (∼0.99 R 2 value) exceeds all previously reported predictors for peptide LC separations. This also provides a solid platform for method development in 2D LC-MS protocols in proteomics and peptide retention prediction filtering of false positive identifications.

Evaluating differential effects using regression interactions and regression mixture models

PubMed Central

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

Factors affecting the formation of eutectic solid dispersions and their dissolution behavior.

PubMed

Vippagunta, Sudha R; Wang, Zeren; Hornung, Stefanie; Krill, Steven L

2007-02-01

The objective of this work was to obtain a fundamental understanding of the factors, specifically the properties of poorly water-soluble drugs and water-soluble carriers, which influence predominantly, the formation of eutectic or monotectic crystalline solid dispersion and their dissolution behavior. A theoretical model was applied on five poorly water-soluble drugs (fenofibrate, flurbiprofen, griseofulvin, naproxen, and ibuprofen) having diverse physicochemical properties and water-soluble carrier (polyethylene glycol (PEG) 8000) for the evaluation of these factors. Of these, two drugs, fenofibrate and flurbiprofen, and PEG of different molecular weights (3350, 8000, and 20000), were chosen as model drugs and carriers for further investigation. Experimental phase diagrams were constructed and dissolution testing was performed to assess the performance of the systems. The theoretical model predicted the formation of eutectic or monotectic solid dispersions of fenofibrate, griseofulvin, ibuprofen, and naproxen with PEG, holding the contribution of specific intermolecular interactions between compound and carrier to zero. In the case of the flurbiprofen-PEG eutectic system, intermolecular interactions between drug and polymer needed to be taken into consideration to predict the experimental phase diagram. The results of the current work suggest that the thermodynamic function of melting point and heat of fusion (as a measure of crystal energy of drug) plays a significant role in the formation of a eutectic system. Lipophilicity of the compound (as represented by cLog P) was also demonstrated to have an effect. Specific interactions between drug and carrier play a significant role in influencing the eutectic composition. Molar volume of the drug did not seem to have an impact on eutectic formation. The polymer molecular weight appeared to have an impact on the eutectic composition for flurbiprofen, which exhibits specific interactions with PEG, whereas no such impact of polymer molecular weight on eutectic composition was observed for fenofibrate, which does not exhibit specific interactions with PEG. The impact of polymer molecular weight on dissolution of systems where specific drug-polymer interactions are exhibited was also observed. The current work provides valuable insight into factors affecting formation and dissolution of eutectic systems, which can facilitate the rational selection of suitable water-soluble carriers. Copyright (c) 2006 Wiley-Liss, Inc.

Agent-based modeling: a new approach for theory building in social psychology.

PubMed

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.

Single-cell tracking of flavivirus RNA uncovers species-specific interactions with the immune system dictating disease outcome

PubMed Central

Douam, Florian; Hrebikova, Gabriela; Albrecht, Yentli E. Soto; Sellau, Julie; Sharon, Yael; Ding, Qiang; Ploss, Alexander

2017-01-01

Positive-sense RNA viruses pose increasing health and economic concerns worldwide. Our limited understanding of how these viruses interact with their host and how these processes lead to virulence and disease seriously hampers the development of anti-viral strategies. Here, we demonstrate the tracking of (+) and (−) sense viral RNA at single-cell resolution within complex subsets of the human and murine immune system in different mouse models. Our results provide insights into how a prototypic flavivirus, yellow fever virus (YFV-17D), differentially interacts with murine and human hematopoietic cells in these mouse models and how these dynamics influence distinct outcomes of infection. We detect (−) YFV-17D RNA in specific secondary lymphoid compartments and cell subsets not previously recognized as permissive for YFV replication, and we highlight potential virus–host interaction events that could be pivotal in regulating flavivirus virulence and attenuation. PMID:28290449

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold

PubMed Central

Huber, Roland G.; Bond, Peter J.

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners. PMID:29016650

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

PubMed

Ivanov, Stefan M; Cawley, Andrew; Huber, Roland G; Bond, Peter J; Warwicker, Jim

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

[Drosophila melanogaster as a model for studying the function of animal viral proteins].

PubMed

Omelianchuk, L V; Iudina, O S

2011-07-01

Studies in which Drosophila melanogaster individuals carrying transgenes of animal viruses were used to analyze the action of animal viral proteins on the cell are reviewed. The data presented suggest that host specificity of viruses is determined by their proteins responsible for the penetration of the virus into the cell, while viral proteins responsible for interactions with the host cell are much less host-specific. Due to this, the model of Drosophila with its developed system of searching for genetic interactions can be used to find intracellular targets for the action of viral proteins of the second group.

Simple analytical model reveals the functional role of embodied sensorimotor interaction in hexapod gaits

PubMed Central

Aoi, Shinya; Nachstedt, Timo; Manoonpong, Poramate; Wörgötter, Florentin; Matsuno, Fumitoshi

2018-01-01

Insects have various gaits with specific characteristics and can change their gaits smoothly in accordance with their speed. These gaits emerge from the embodied sensorimotor interactions that occur between the insect’s neural control and body dynamic systems through sensory feedback. Sensory feedback plays a critical role in coordinated movements such as locomotion, particularly in stick insects. While many previously developed insect models can generate different insect gaits, the functional role of embodied sensorimotor interactions in the interlimb coordination of insects remains unclear because of their complexity. In this study, we propose a simple physical model that is amenable to mathematical analysis to explain the functional role of these interactions clearly. We focus on a foot contact sensory feedback called phase resetting, which regulates leg retraction timing based on touchdown information. First, we used a hexapod robot to determine whether the distributed decoupled oscillators used for legs with the sensory feedback generate insect-like gaits through embodied sensorimotor interactions. The robot generated two different gaits and one had similar characteristics to insect gaits. Next, we proposed the simple model as a minimal model that allowed us to analyze and explain the gait mechanism through the embodied sensorimotor interactions. The simple model consists of a rigid body with massless springs acting as legs, where the legs are controlled using oscillator phases with phase resetting, and the governed equations are reduced such that they can be explained using only the oscillator phases with some approximations. This simplicity leads to analytical solutions for the hexapod gaits via perturbation analysis, despite the complexity of the embodied sensorimotor interactions. This is the first study to provide an analytical model for insect gaits under these interaction conditions. Our results clarified how this specific foot contact sensory feedback contributes to generation of insect-like ipsilateral interlimb coordination during hexapod locomotion. PMID:29489831

Weighting of topologically different interactions in a model of two-dimensional polymer collapse.

PubMed

Bedini, Andrea; Owczarek, Aleksander L; Prellberg, Thomas

2013-01-01

We study by computer simulation a recently introduced generalized model of self-interacting self-avoiding trails on the square lattice that distinguishes two topologically different types of self-interaction: namely, crossings where the trail passes across itself and collisions where the lattice path visits the same site without crossing. This model generalizes the canonical interacting self-avoiding trail model of polymer collapse, which has a strongly divergent specific heat at its transition point. We confirm the recent prediction that the asymmetry does not affect the universality class for a range of asymmetry. Certainly, where the weighting of collisions outweighs that of crossings this is well supported numerically. When crossings are weighted heavily relative to collisions, the collapse transition reverts to the canonical θ-point-like behavior found in interacting self-avoiding walks.

Substratum interfacial energetic effects on the attachment of marine bacteria

NASA Astrophysics Data System (ADS)

Ista, Linnea Kathryn

Biofilms represent an ancient, ubiquitous and influential form of life on earth. Biofilm formation is initiated by attachment of bacterial cells from an aqueous suspension onto a suitable attachment substratum. While in certain, well studied cases initial attachment and subsequent biofilm formation is mediated by specific ligand-receptor pairs on the bacteria and attachment substratum, in the open environment, including the ocean, it is assumed to be non-specific and mediated by processes similar to those that drive adsorption of colloids at the water-solid interface. Colloidal principles are studied to determine the molecular and physicochemical interactions involved in the attachment of the model marine bacterium, Cobetia marina to model self-assembled monolayer surfaces. In the simplest application of colloidal principles the wettability of attachment substrata, as measured by the advancing contact angle of water (theta AW) on the surface, is frequently used as an approximation for the surface tension. We demonstrate the applicability of this approach for attachment of C. marina and algal zoospores and extend it to the development of a means to control attachment and release of microorganisms by altering and tuning surface thetaAW. In many cases, however, thetaAW does not capture all the information necessary to model attachment of bacteria to attachment substrata; SAMs with similar thetaAW attach different number of bacteria. More advanced colloidal models of initial bacterial attachment have evolved over the last several decades, with the emergence of the model proposed by van Oss, Chaudhury and Good (VCG) as preeminent. The VCG model enables calculation of interfacial tensions by dividing these into two major interactions thought to be important at biointerfaces: apolar, Lifshitz-van der Waals and polar, Lewis acid-base (including hydrogen bonding) interactions. These interfacial tensions are combined to yield DeltaGadh, the free energy associated with attachment of bacteria to a substratum. We use VCG to model DeltaGadh and interfacial tensions as they relate to model bacterial attachment on SAMs that accumulate cells to different degrees. Even with the more complex interactions measured by VCG, surface energy of the attachment substratum alone was insufficient to predict attachment. VCG was then employed to model attachment of C. marina to a series of SAMs varying systematically in the number of ethylene glycol residues present in the molecule; an identical series has been previously shown to vary dramatically in the number of cells attached as a function of ethylene glycols present. Our results indicate that while VCG adequately models the interfacial tension between water and ethylene glycol SAMs in a manner that predicts bacterial attachment, DeltaGadh as calculated by VCG neither qualitatively nor quantitatively reflects the attachment data. The VCG model, thus, fails to capture specific information regarding the interactions between the attaching bacteria, water, and the SAM. We show that while hydrogen-bond accepting interactions are very well captured by this model, the ability for SAMs and bacteria to donate hydrogen bonds is not adequately described as the VCG model is currently applied. We also describe ways in which VCG fails to capture two specific biological aspects that may be important in bacterial attachment to surfaces:1.) specific interactions between molecules on the surface and bacteria and 2.) bacterial cell surface heterogeneities that may be important in differential attachment to different substrata.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Intercellular interaction mechanisms for the origination of blast crisis in chronic myeloid leukemia

PubMed Central

Sachs, Rainer; Johnsson, Kerstin; Hahnfeldt, Philip; Luo, Janet; Chen, Allen; Hlatky, Lynn

2011-01-01

Chronic myeloid leukemia (CML) is characterized by a specific chromosome translocation, and its pathobiology is considered comparatively well understood. Thus, quantitative analysis of CML and its progression to blast crisis may help elucidate general mechanisms of carcinogenesis and cancer progression. Hitherto it has been widely postulated that CML blast crisis originates mainly via cell-autonomous mechanisms such as secondary mutations or genomic instability, rather than by intercellular interactions. However, recent results suggest that intercellular interactions play an important role in carcinogenesis. In this study, we analyzed alternative mechanisms, including pairwise intercellular interactions, for CML blast crisis origination. A quantitative, mechanistic cell population dynamics model was employed. This model used recent data on imatinib-treated CML; it also used earlier clinical data, not previously incorporated into current mathematical CML/imatinib models. With the pre-imatinib data, which include results on many more blast crises, we obtained evidence that the driving mechanism for blast crisis origination is intercellular interaction between specific cell types. Assuming leukemic-normal interactions resulted in a statistically significant improvement over assuming either cell-autonomous mechanisms or interactions between leukemic cells. This conclusion was robust with regard to changes in the model’s adjustable parameters. Application of the results to patients treated with imatinib suggests that imatinib may act not only on malignant blast precursors, but also, to a limited degree, on the malignant blasts themselves. Major Findings A comprehensive mechanistic model gives evidence that the main driving mechanisms for CML blast crisis origination are interactions between leukemic and normal cells. PMID:21487044

Interspecific Tests of Allelism Reveal the Evolutionary Timing and Pattern of Accumulation of Reproductive Isolation Mutations

PubMed Central

Sherman, Natasha A.; Victorine, Anna; Wang, Richard J.; Moyle, Leonie C.

2014-01-01

Despite extensive theory, little is known about the empirical accumulation and evolutionary timing of mutations that contribute to speciation. Here we combined QTL (Quantitative Trait Loci) analyses of reproductive isolation, with information on species evolutionary relationships, to reconstruct the order and timing of mutations contributing to reproductive isolation between three plant (Solanum) species. To evaluate whether reproductive isolation QTL that appear to coincide in more than one species pair are homologous, we used cross-specific tests of allelism and found evidence for both homologous and lineage-specific (non-homologous) alleles at these co-localized loci. These data, along with isolation QTL unique to single species pairs, indicate that >85% of isolation-causing mutations arose later in the history of divergence between species. Phylogenetically explicit analyses of these data support non-linear models of accumulation of hybrid incompatibility, although the specific best-fit model differs between seed (pairwise interactions) and pollen (multi-locus interactions) sterility traits. Our findings corroborate theory that predicts an acceleration (‘snowballing’) in the accumulation of isolation loci as lineages progressively diverge, and suggest different underlying genetic bases for pollen versus seed sterility. Pollen sterility in particular appears to be due to complex genetic interactions, and we show this is consistent with a snowball model where later arising mutations are more likely to be involved in pairwise or multi-locus interactions that specifically involve ancestral alleles, compared to earlier arising mutations. PMID:25211473

Chlorophenol sorption on multi-walled carbon nanotubes: DFT modeling and structure-property relationship analysis.

PubMed

Watkins, Marquita; Sizochenko, Natalia; Moore, Quentarius; Golebiowski, Marek; Leszczynska, Danuta; Leszczynski, Jerzy

2017-02-01

The presence of chlorophenols in drinking water can be hazardous to human health. Understanding the mechanisms of adsorption under specific experimental conditions would be beneficial when developing methods to remove toxic substances from drinking water during water treatment in order to limit human exposure to these contaminants. In this study, we investigated the sorption of chlorophenols on multi-walled carbon nanotubes using a density functional theory (DFT) approach. This was applied to study selected interactions between six solvents, five types of nanotubes, and six chlorophenols. Experimental data were used to construct structure-adsorption relationship (SAR) models that describe the recovery process. Specific interactions between solvents and chlorophenols were taken into account in the calculations by using novel specific mixture descriptors.

Modeling of Complex Mixtures: JP-8 Toxicokinetics

DTIC Science & Technology

2008-10-01

generic tissue compartments in which we have combined diffusion limitation and deep tissue (global tissue model). We also applied a QSAR approach for...SUBJECT TERMS jet fuel, JP-8, PBPK modeling, complex mixtures, nonane, decane, naphthalene, QSAR , alternative fuels 16. SECURITY CLASSIFICATION OF...necessary, to apply to the interaction of specific compounds with specific tissues. We have also applied a QSAR approach for estimating blood and tissue

Full-Potential Modeling of Blade-Vortex Interactions. Degree awarded by George Washington Univ., Feb. 1987

NASA Technical Reports Server (NTRS)

Jones, Henry E.

1997-01-01

A study of the full-potential modeling of a blade-vortex interaction was made. A primary goal of this study was to investigate the effectiveness of the various methods of modeling the vortex. The model problem restricts the interaction to that of an infinite wing with an infinite line vortex moving parallel to its leading edge. This problem provides a convenient testing ground for the various methods of modeling the vortex while retaining the essential physics of the full three-dimensional interaction. A full-potential algorithm specifically tailored to solve the blade-vortex interaction (BVI) was developed to solve this problem. The basic algorithm was modified to include the effect of a vortex passing near the airfoil. Four different methods of modeling the vortex were used: (1) the angle-of-attack method, (2) the lifting-surface method, (3) the branch-cut method, and (4) the split-potential method. A side-by-side comparison of the four models was conducted. These comparisons included comparing generated velocity fields, a subcritical interaction, and a critical interaction. The subcritical and critical interactions are compared with experimentally generated results. The split-potential model was used to make a survey of some of the more critical parameters which affect the BVI.

Biophysical interactions with model lipid membranes: applications in drug discovery and drug delivery

PubMed Central

Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod

2009-01-01

The transport of drugs or drug delivery systems across the cell membrane is a complex biological process, often difficult to understand because of its dynamic nature. In this regard, model lipid membranes, which mimic many aspects of cell-membrane lipids, have been very useful in helping investigators to discern the roles of lipids in cellular interactions. One can use drug-lipid interactions to predict pharmacokinetic properties of drugs, such as their transport, biodistribution, accumulation, and hence efficacy. These interactions can also be used to study the mechanisms of transport, based on the structure and hydrophilicity/hydrophobicity of drug molecules. In recent years, model lipid membranes have also been explored to understand their mechanisms of interactions with peptides, polymers, and nanocarriers. These interaction studies can be used to design and develop efficient drug delivery systems. Changes in the lipid composition of cells and tissue in certain disease conditions may alter biophysical interactions, which could be explored to develop target-specific drugs and drug delivery systems. In this review, we discuss different model membranes, drug-lipid interactions and their significance, studies of model membrane interactions with nanocarriers, and how biophysical interaction studies with lipid model membranes could play an important role in drug discovery and drug delivery. PMID:19432455

Model for an RNA tertiary interaction from the structure of an intermolecular complex between a GAAA tetraloop and an RNA helix.

PubMed

Pley, H W; Flaherty, K M; McKay, D B

1994-11-03

In large structured RNAs, RNA hairpins in which the strands of the duplex stem are connected by a tetraloop of the consensus sequence 5'-GNRA (where N is any nucleotide, and R is either G or A) are unusually frequent. In group I introns there is a covariation in sequence between nucleotides in the third and fourth positions of the loop with specific distant base pairs in putative RNA duplex stems: GNAA loops correlate with successive 5'-C-C.G-C base pairs in stems, whereas GNGA loops correlate with 5'-C-U.G-A. This has led to the suggestion that GNRA tetraloops may be involved in specific long-range tertiary interactions, with each A in position 3 or 4 of the loop interacting with a C-G base pair in the duplex, and G in position 3 interacting with a U-A base pair. This idea is supported experimentally for the GAAA loop of the P5b extension of the group I intron of Tetrahymena thermophila and the L9 GUGA terminal loop of the td intron of bacteriophage T4 (ref. 4). NMR has revealed the overall structure of the tetraloop for 12-nucleotide hairpins with GCAA and GAAA loops and models have been proposed for the interaction of GNRA tetraloops with base pairs in the minor groove of A-form RNA. Here we describe the crystal structure of an intermolecular complex between a GAAA tetraloop and an RNA helix. The interactions we observe correlate with the specificity of GNRA tetraloops inferred from phylogenetic studies, suggesting that this complex is a legitimate model for intramolecular tertiary interactions mediated by GNRA tetraloops in large structured RNAs.

V and V of Lexical, Syntactic and Semantic Properties for Interactive Systems Through Model Checking of Formal Description of Dialog

NASA Technical Reports Server (NTRS)

Brat, Guillaume P.; Martinie, Celia; Palanque, Philippe

2013-01-01

During early phases of the development of an interactive system, future system properties are identified (through interaction with end users in the brainstorming and prototyping phase of the application, or by other stakehold-ers) imposing requirements on the final system. They can be specific to the application under development or generic to all applications such as usability principles. Instances of specific properties include visibility of the aircraft altitude, speed… in the cockpit and the continuous possibility of disengaging the autopilot in whatever state the aircraft is. Instances of generic properties include availability of undo (for undoable functions) and availability of a progression bar for functions lasting more than four seconds. While behavioral models of interactive systems using formal description techniques provide complete and unambiguous descriptions of states and state changes, it does not provide explicit representation of the absence or presence of properties. Assessing that the system that has been built is the right system remains a challenge usually met through extensive use and acceptance tests. By the explicit representation of properties and the availability of tools to support checking these properties, it becomes possible to provide developers with means for systematic exploration of the behavioral models and assessment of the presence or absence of these properties. This paper proposes the synergistic use two tools for checking both generic and specific properties of interactive applications: Petshop and Java PathFinder. Petshop is dedicated to the description of interactive system behavior. Java PathFinder is dedicated to the runtime verification of Java applications and as an extension dedicated to User Interfaces. This approach is exemplified on a safety critical application in the area of interactive cockpits for large civil aircrafts.

Object Oriented Modeling and Design

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

The Object Oriented Modeling and Design seminar is intended for software professionals and students, it covers the concepts and a language-independent graphical notation that can be used to analyze problem requirements, and design a solution to the problem. The seminar discusses the three kinds of object-oriented models class, state, and interaction. The class model represents the static structure of a system, the state model describes the aspects of a system that change over time as well as control behavior and the interaction model describes how objects collaborate to achieve overall results. Existing knowledge of object oriented programming may benefit the learning of modeling and good design. Specific expectations are: Create a class model, Read, recognize, and describe a class model, Describe association and link, Show abstract classes used with multiple inheritance, Explain metadata, reification and constraints, Group classes into a package, Read, recognize, and describe a state model, Explain states and transitions, Read, recognize, and describe interaction model, Explain Use cases and use case relationships, Show concurrency in activity diagram, Object interactions in sequence diagram.

Interacting dark energy: Dynamical system analysis

NASA Astrophysics Data System (ADS)

Golchin, Hanif; Jamali, Sara; Ebrahimi, Esmaeil

We investigate the impacts of interaction between dark matter (DM) and dark energy (DE) in the context of two DE models, holographic (HDE) and ghost dark energy (GDE). In fact, using the dynamical system analysis, we obtain the cosmological consequence of several interactions, considering all relevant component of universe, i.e. matter (dark and luminous), radiation and DE. Studying the phase space for all interactions in detail, we show the existence of unstable matter-dominated and stable DE-dominated phases. We also show that linear interactions suffer from the absence of standard radiation-dominated epoch. Interestingly, this failure resolved by adding the nonlinear interactions to the models. We find an upper bound for the value of the coupling constant of the interaction between DM and DE as b < 0.57in the case of holographic model, and b < 0.61 in the case of GDE model, to result in a cosmological viable matter-dominated epoch. More specifically, this bound is vital to satisfy instability and deceleration of matter-dominated epoch.

The Virtual Museum of Minerals and Molecules: Molecular Visualization in a Virtual Hands-On Museum

ERIC Educational Resources Information Center

Barak, Phillip; Nater, Edward A.

2005-01-01

The Virtual Museum of Minerals and Molecules (VMMM) is a web-based resource presenting interactive, 3-D, research-grade molecular models of more than 150 minerals and molecules of interest to chemical, earth, plant, and environmental sciences. User interactivity with the 3-D display allows models to be rotated, zoomed, and specific regions of…

RCCS bioreactor-based modelled microgravity induces significant changes on in vitro 3D neuroglial cell cultures.

PubMed

Morabito, Caterina; Steimberg, Nathalie; Mazzoleni, Giovanna; Guarnieri, Simone; Fanò-Illic, Giorgio; Mariggiò, Maria A

2015-01-01

We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions.

RCCS Bioreactor-Based Modelled Microgravity Induces Significant Changes on In Vitro 3D Neuroglial Cell Cultures

PubMed Central

Mazzoleni, Giovanna; Fanò-Illic, Giorgio; Mariggiò, Maria A.

2015-01-01

We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions. PMID:25654124

Host-to-host variation of ecological interactions in polymicrobial infections

NASA Astrophysics Data System (ADS)

Mukherjee, Sayak; Weimer, Kristin E.; Seok, Sang-Cheol; Ray, Will C.; Jayaprakash, C.; Vieland, Veronica J.; Swords, W. Edward; Das, Jayajit

2015-02-01

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

Vibrational Markovian modelling of footprints after the interaction of antibiotics with the packaging region of HIV type 1.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

The design of novel anti-HIV compounds has now become a crucial area for scientists working in numerous interrelated fields of science such as molecular biology, medicinal chemistry, mathematical biology, molecular modelling and bioinformatics. In this context, the development of simple but physically meaningful mathematical models to represent the interaction between anti-HIV drugs and their biological targets is of major interest. One such area currently under investigation involves the targets in the HIV-RNA-packaging region. In the work described here, we applied Markov chain theory in an attempt to describe the interaction between the antibiotic paromomycin and the packaging region of the RNA in Type-1 HIV. In this model, a nucleic acid squeezed graph is used. The vertices of the graph represent the nucleotides while the edges are the phosphodiester bonds. A stochastic (Markovian) matrix was subsequently defined on this graph, an operation that codifies the probabilities of interaction between specific nucleotides of HIV-RNA and the antibiotic. The strength of these local interactions can be calculated through an inelastic vibrational model. The successive power of this matrix codifies the probabilities with which the vibrations after drug-RNA interactions vanish along the polynucleotide main chain. The sums of self-return probabilities in the k-vicinity of each nucleotide represent physically meaningful descriptors. A linear discriminant function was developed and gave rise to excellent discrimination in 80.8% of interacting and footprinted nucleotides. The Jackknife method was employed to assess the stability and predictability of the model. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the antibiotic (R(2)=0.91, Q(2)=0.86). These kinds of models could play an important role either in the discovery of new anti-HIV compounds or the study of their mode of action.

Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model

PubMed Central

Seaman, Shaun R; White, Ian R; Carpenter, James R

2015-01-01

Missing covariate data commonly occur in epidemiological and clinical research, and are often dealt with using multiple imputation. Imputation of partially observed covariates is complicated if the substantive model is non-linear (e.g. Cox proportional hazards model), or contains non-linear (e.g. squared) or interaction terms, and standard software implementations of multiple imputation may impute covariates from models that are incompatible with such substantive models. We show how imputation by fully conditional specification, a popular approach for performing multiple imputation, can be modified so that covariates are imputed from models which are compatible with the substantive model. We investigate through simulation the performance of this proposal, and compare it with existing approaches. Simulation results suggest our proposal gives consistent estimates for a range of common substantive models, including models which contain non-linear covariate effects or interactions, provided data are missing at random and the assumed imputation models are correctly specified and mutually compatible. Stata software implementing the approach is freely available. PMID:24525487

Coarse-graining, Electrostatics and pH effects in phospholipid systems

NASA Astrophysics Data System (ADS)

Travesset, Alex; Vangaveti, Sweta

2010-03-01

We introduce a minimal free energy describing the interaction of charged groups and counterions including both classical electrostatic and specific interactions. The predictions of the model are compared against the standard model for describing ions next to charged interfaces, consisting of Poisson-Boltzmann theory with additional constants describing ion binding, which are specific to the counterion and the interfacial charge (``chemical binding''). It is shown that the ``chemical'' model can be appropriately described by an underlying ``physical'' model over several decades in concentration, but the extracted binding constants are not uniquely defined, as they differ depending on the particular observable quantity being studied. It is also shown that electrostatic correlations for divalent (or higher valence) ions enhance the surface charge by increasing deprotonation, an effect not properly accounted within chemical models. The model is applied to the charged phospholipids phosphatidylserine, Phosphatidc acid and Phosphoinositides and implications for different biological processes are discussed.

Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

PubMed Central

Brown, Patrick O.

2013-01-01

Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

Pharmacokinetic Modeling of JP-8 Jet Fuel Components: II. A Conceptual Framework

DTIC Science & Technology

2003-12-01

example, a single type of (simple) binary interaction between 300 components would require the specification of some 105 interaction coefficients . One...individual substances, via binary mechanisms, is enough to predict the interactions present in the mixture. Secondly, complex mixtures can often be...approximated as pseudo- binary systems, consisting of the compound of interest plus a single interacting complex vehicle with well-defined, composite

In silico modeling of the yeast protein and protein family interaction network

NASA Astrophysics Data System (ADS)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

PubMed

Cosic, Irena; Cosic, Drasko; Lazar, Katarina

2016-06-29

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

PubMed Central

Cosic, Irena; Cosic, Drasko; Lazar, Katarina

2016-01-01

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

Towards an interactive electromechanical model of the heart

PubMed Central

Talbot, Hugo; Marchesseau, Stéphanie; Duriez, Christian; Sermesant, Maxime; Cotin, Stéphane; Delingette, Hervé

2013-01-01

In this work, we develop an interactive framework for rehearsal of and training in cardiac catheter ablation, and for planning cardiac resynchronization therapy. To this end, an interactive and real-time electrophysiology model of the heart is developed to fit patient-specific data. The proposed interactive framework relies on two main contributions. First, an efficient implementation of cardiac electrophysiology is proposed, using the latest graphics processing unit computing techniques. Second, a mechanical simulation is then coupled to the electrophysiological signals to produce realistic motion of the heart. We demonstrate that pathological mechanical and electrophysiological behaviour can be simulated. PMID:24427533

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus

PubMed Central

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector’s life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis’ life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector–based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector. PMID:27159134

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

PubMed

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107

Gender-Specific Gene–Environment Interaction in Alcohol Dependence: The Impact of Daily Life Events and GABRA2

PubMed Central

Perry, Brea L.; Pescosolido, Bernice A.; Bucholz, Kathleen; Edenberg, Howard; Kramer, John; Kuperman, Samuel; Schuckit, Marc Alan; Nurnberger, John I.

2015-01-01

Gender-moderated gene–environment interactions are rarely explored, raising concerns about inaccurate specification of etiological models and inferential errors. The current study examined the influence of gender, negative and positive daily life events, and GABRA2 genotype (SNP rs279871) on alcohol dependence, testing two- and three-way interactions between these variables using multilevel regression models fit to data from 2,281 White participants in the Collaborative Study on the Genetics of Alcoholism. Significant direct effects of variables of interest were identified, as well as gender-specific moderation of genetic risk on this SNP by social experiences. Higher levels of positive life events were protective for men with the high-risk genotype, but not among men with the low-risk genotype or women, regardless of genotype. Our findings support the disinhibition theory of alcohol dependence, suggesting that gender differences in social norms, constraints and opportunities, and behavioral undercontrol may explain men and women’s distinct patterns of association. PMID:23974430

Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

De novo design of protein homo-oligomers with modular hydrogen bond network-mediated specificity

PubMed Central

Boyken, Scott E.; Chen, Zibo; Groves, Benjamin; Langan, Robert A.; Oberdorfer, Gustav; Ford, Alex; Gilmore, Jason; Xu, Chunfu; DiMaio, Frank; Pereira, Jose Henrique; Sankaran, Banumathi; Seelig, Georg; Zwart, Peter H.; Baker, David

2017-01-01

In nature, structural specificity in DNA and proteins is encoded quite differently: in DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen bond networks with atomic accuracy is a milestone for protein design and enables the programming of protein interaction specificity for a broad range of synthetic biology applications. PMID:27151862

Engineering High Assurance Distributed Cyber Physical Systems

DTIC Science & Technology

2015-01-15

decisions: number of interacting agents and co-dependent decisions made in real-time without causing interference . To engineer a high assurance DART...environment specification, architecture definition, domain-specific languages, design patterns, code - generation, analysis, test-generation, and simulation...include synchronization between the models and source code , debugging at the model level, expression of the design intent, and quality of service

Symbolic Interactionism and Social Action Theory

ERIC Educational Resources Information Center

Morrione, Thomas J.

1975-01-01

An explanation and elaboration of existing theory on interaction, this article describes a point of convergence between Parsons' Voluntaristic Theory of Action and Blumer's conceptualization of Symbolic Interactionism and develops specific problems of divergence in these normative and interpretive models of interaction. (JC)

Quantitative analysis of protein-ligand interactions by NMR.

PubMed

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used to analyze population-averaged NMR quantities. Essentially, to apply NMR successfully, both the type of experiment and equation to fit the data must be carefully and specifically chosen for the protein-ligand interaction under analysis. In this review, we first explain the exchange regimes and kinetic models of protein-ligand interactions, and then describe the NMR methods that quantitatively analyze these specific interactions. Copyright © 2016 Elsevier B.V. All rights reserved.

Birth/death process model

NASA Technical Reports Server (NTRS)

Solloway, C. B.; Wakeland, W.

1976-01-01

First-order Markov model developed on digital computer for population with specific characteristics. System is user interactive, self-documenting, and does not require user to have complete understanding of underlying model details. Contains thorough error-checking algorithms on input and default capabilities.

A test of an interactive model of binge eating among undergraduate men.

PubMed

Minnich, Allison M; Gordon, Kathryn H; Holm-Denoma, Jill M; Troop-Gordon, Wendy

2014-12-01

Past research has shown that a combination of high perfectionism, high body dissatisfaction, and low self-esteem is predictive of binge eating in college women (Bardone-Cone et al., 2006). In the current study, we examined whether this triple interaction model is applicable to men. Male undergraduate college students from a large Midwestern university (n=302) completed self-report measures online at two different time points, a minimum of eight weeks apart. Analyses revealed a significant interaction between the three risk factors, such that high perfectionism, high body dissatisfaction, and low self-esteem at Time 1 were associated with higher levels of Time 2 binge eating symptoms. The triple interaction model did not predict Time 2 anxiety or depressive symptoms, which suggests model specificity. These findings offer a greater understanding of the interactive nature of risk factors in predicting binge eating symptoms among men. Copyright © 2014 Elsevier Ltd. All rights reserved.

P-selectin- and heparanase-dependent antimetastatic activity of non-anticoagulant heparins.

PubMed

Hostettler, Nina; Naggi, Annamaria; Torri, Giangiacomo; Ishai-Michaeli, Riva; Casu, Benito; Vlodavsky, Israel; Borsig, Lubor

2007-11-01

Vascular cell adhesion molecules, P- and L-selectins, facilitate metastasis of cancer cells in mice by mediating interactions with platelets, endothelium, and leukocytes. Heparanase is an endoglycosidase that degrades heparan sulfate of extracellular matrix, thereby promoting tumor invasion and metastasis. Heparin is known to efficiently attenuate metastasis in different tumor models. Here we identified modified, nonanticoagulant species of heparin that specifically inhibit selectin-mediated cell-cell interactions, heparanase enzymatic activity, or both. We show that selective inhibition of selectin interactions or heparanase with specific heparin derivatives in mouse models of MC-38 colon carcinoma and B16-BL6 melanoma attenuates metastasis. Selectin-specific heparin derivatives attenuated metastasis of MC-38 carcinoma, but heparanase-specific derivatives had no effect, in accordance with the virtual absence of heparanase activity in these cells. Heparin derivatives had no further effect on metastasis in mice deficient in P- and L-selectin, indicating that selectins are the primary targets of heparin antimetastatic activity. Selectin-specific and heparanase-specific derivatives attenuated metastasis of B16-BL6 melanomas to a similar extent. When mice were injected with a derivative containing both heparanase and selectin inhibitory activity, no additional attenuation of metastasis could be observed. Thus, selectin-specific heparin derivatives efficiently attenuated metastasis of both tumor cell types whereas inhibition of heparanase led to reduction of metastasis only in tumor cells producing heparanase.

Evaluation and modeling of the eutectic composition of various drug-polyethylene glycol solid dispersions.

PubMed

Baird, Jared A; Taylor, Lynne S

2011-06-01

The purpose of this study was to gain a better understanding of which factors contribute to the eutectic composition of drug-polyethylene glycol (PEG) blends and to compare experimental values with predictions from the semi-empirical model developed by Lacoulonche et al. Eutectic compositions of various drug-PEG 3350 solid dispersions were predicted, assuming athermal mixing, and compared to experimentally determined eutectic points. The presence or absence of specific interactions between the drug and PEG 3350 were investigated using Fourier transform infrared (FT-IR) spectroscopy. The eutectic composition for haloperidol-PEG and loratadine-PEG solid dispersions was accurately predicted using the model, while predictions for aceclofenac-PEG and chlorpropamide-PEG were very different from those experimentally observed. Deviations in the model prediction from ideal behavior for the systems evaluated were confirmed to be due to the presence of specific interactions between the drug and polymer, as demonstrated by IR spectroscopy. Detailed analysis showed that the eutectic composition prediction from the model is interdependent on the crystal lattice energy of the drug compound (evaluated from the melting temperature and the heat of fusion) as well as the nature of the drug-polymer interactions. In conclusion, for compounds with melting points less than 200°C, the model is ideally suited for predicting the eutectic composition of systems where there is an absence of drug-polymer interactions.

The heparin-Ca(2+) interaction: the influence of the O-sulfation pattern on binding.

PubMed

Chevalier, Franck; Lucas, Ricardo; Angulo, Jesús; Martin-Lomas, Manuel; Nieto, Pedro M

2004-04-02

The specific binding of Ca(2+) to synthetic hexasaccharide models of modified heparin has been investigated by NMR and molecular modeling and compared with previous results on a model of regular heparin. These two models represent the regular region of heparin lacking one type of O-sulfate group, either at C-6 of glucosamine or at C-2 of iduronate. The NMR experiments show different responses to the presence of Ca(2+). In the case of the compound lacking O-sulfate groups at C-2, the results are indicative of specific binding similar to that observed for the regular heparin, while the model lacking sulfate groups in position 6 interacts more weakly with Ca(2+). In order to understand the basis of this difference, a molecular modeling study based on a rigid body docking approach of the interaction of these carbohydrates with Ca(2+) and Na(+) was performed. We have found that the results are strongly dependent on the starting orientation of the lateral side chains of the charged groups of the carbohydrate, and that the best agreement with the experimental results is obtained when the starting conformations are taken from previous simulations in the presence of Ca(2+).

Introducing a model of pairing based on base pair specific interactions between identical DNA sequences

NASA Astrophysics Data System (ADS)

(O' Lee, Dominic J.

2018-02-01

At present, there have been suggested two types of physical mechanism that may facilitate preferential pairing between DNA molecules, with identical or similar base pair texts, without separation of base pairs. One mechanism solely relies on base pair specific patterns of helix distortion being the same on the two molecules, discussed extensively in the past. The other mechanism proposes that there are preferential interactions between base pairs of the same composition. We introduce a model, built on this second mechanism, where both thermal stretching and twisting fluctuations are included, as well as the base pair specific helix distortions. Firstly, we consider an approximation for weak pairing interactions, or short molecules. This yields a dependence of the energy on the square root of the molecular length, which could explain recent experimental data. However, analysis suggests that this approximation is no longer valid at large DNA lengths. In a second approximation, for long molecules, we define two adaptation lengths for twisting and stretching, over which the pairing interaction can limit the accumulation of helix disorder. When the pairing interaction is sufficiently strong, both adaptation lengths are finite; however, as we reduce pairing strength, the stretching adaptation length remains finite but the torsional one becomes infinite. This second state persists to arbitrarily weak values of the pairing strength; suggesting that, if the molecules are long enough, the pairing energy scales as length. To probe differences between the two pairing mechanisms, we also construct a model of similar form. However, now, pairing between identical sequences solely relies on the intrinsic helix distortion patterns. Between the two models, we see interesting qualitative differences. We discuss our findings, and suggest new work to distinguish between the two mechanisms.

Diversity and specificity in the interaction between Caenorhabditis elegans and the pathogen Serratia marcescens.

PubMed

Schulenburg, Hinrich; Ewbank, Jonathan J

2004-11-22

Co-evolutionary arms races between parasites and hosts are considered to be of immense importance in the evolution of living organisms, potentially leading to highly dynamic life-history changes. The outcome of such arms races is in many cases thought to be determined by frequency dependent selection, which relies on genetic variation in host susceptibility and parasite virulence, and also genotype-specific interactions between host and parasite. Empirical evidence for these two prerequisites is scarce, however, especially for invertebrate hosts. We addressed this topic by analysing the interaction between natural isolates of the soil nematode Caenorhabditis elegans and the pathogenic soil bacterium Serratia marcescens. Our analysis reveals the presence of i) significant variation in host susceptibility, ii) significant variation in pathogen virulence, and iii) significant strain- and genotype-specific interactions between the two species. The results obtained support the previous notion that highly specific interactions between parasites and animal hosts are generally widespread. At least for C. elegans, the high specificity is observed among isolates from the same population, such that it may provide a basis for and/or represent the outcome of co-evolutionary adaptations under natural conditions. Since both C. elegans and S. marcescens permit comprehensive molecular analyses, these two species provide a promising model system for inference of the molecular basis of such highly specific interactions, which are as yet unexplored in invertebrate hosts.

Diversity and specificity in the interaction between Caenorhabditis elegans and the pathogen Serratia marcescens

PubMed Central

Schulenburg, Hinrich; Ewbank, Jonathan J

2004-01-01

Background Co-evolutionary arms races between parasites and hosts are considered to be of immense importance in the evolution of living organisms, potentially leading to highly dynamic life-history changes. The outcome of such arms races is in many cases thought to be determined by frequency dependent selection, which relies on genetic variation in host susceptibility and parasite virulence, and also genotype-specific interactions between host and parasite. Empirical evidence for these two prerequisites is scarce, however, especially for invertebrate hosts. We addressed this topic by analysing the interaction between natural isolates of the soil nematode Caenorhabditis elegans and the pathogenic soil bacterium Serratia marcescens. Results Our analysis reveals the presence of i) significant variation in host susceptibility, ii) significant variation in pathogen virulence, and iii) significant strain- and genotype-specific interactions between the two species. Conclusions The results obtained support the previous notion that highly specific interactions between parasites and animal hosts are generally widespread. At least for C. elegans, the high specificity is observed among isolates from the same population, such that it may provide a basis for and/or represent the outcome of co-evolutionary adaptations under natural conditions. Since both C. elegans and S. marcescens permit comprehensive molecular analyses, these two species provide a promising model system for inference of the molecular basis of such highly specific interactions, which are as yet unexplored in invertebrate hosts. PMID:15555070

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

Getting off the Straight and Narrow: Exploiting Non-Linear, Interactive Narrative Structures in Digital Stories for Language Teaching

ERIC Educational Resources Information Center

Prosser, Andrew

2014-01-01

Digital storytelling is already used extensively in language education. Web documentaries, particularly in terms of design and narrative structure, provide an extension of the digital storytelling concept, specifically in terms of increased interactivity. Using a model of interactive, non-linear storytelling, originally derived from computer game…

Component Models for Semantic Web Languages

NASA Astrophysics Data System (ADS)

Henriksson, Jakob; Aßmann, Uwe

Intelligent applications and agents on the Semantic Web typically need to be specified with, or interact with specifications written in, many different kinds of formal languages. Such languages include ontology languages, data and metadata query languages, as well as transformation languages. As learnt from years of experience in development of complex software systems, languages need to support some form of component-based development. Components enable higher software quality, better understanding and reusability of already developed artifacts. Any component approach contains an underlying component model, a description detailing what valid components are and how components can interact. With the multitude of languages developed for the Semantic Web, what are their underlying component models? Do we need to develop one for each language, or is a more general and reusable approach achievable? We present a language-driven component model specification approach. This means that a component model can be (automatically) generated from a given base language (actually, its specification, e.g. its grammar). As a consequence, we can provide components for different languages and simplify the development of software artifacts used on the Semantic Web.

Recent developments of NASTRAN pre- amd post-processors: Response spectrum analysis (RESPAN) and interactive graphics (GIFTS)

NASA Technical Reports Server (NTRS)

Hirt, E. F.; Fox, G. L.

1982-01-01

Two specific NASTRAN preprocessors and postprocessors are examined. A postprocessor for dynamic analysis and a graphical interactive package for model generation and review of resuls are presented. A computer program that provides response spectrum analysis capability based on data from NASTRAN finite element model is described and the GIFTS system, a graphic processor to augment NASTRAN is introduced.

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.

PubMed

Acosta-Pech, Rocío; Crossa, José; de Los Campos, Gustavo; Teyssèdre, Simon; Claustres, Bruno; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino

2017-07-01

A new genomic model that incorporates genotype × environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype × environment interaction (G × E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G × E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G × E in the prediction of untested maize hybrids increases the accuracy of genomic models.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Analysis of Adsorbate-Adsorbate and Adsorbate-Adsorbent Interactions to Decode Isosteric Heats of Gas Adsorption.

PubMed

Madani, S Hadi; Sedghi, Saeid; Biggs, Mark J; Pendleton, Phillip

2015-12-21

A qualitative interpretation is proposed to interpret isosteric heats of adsorption by considering contributions from three general classes of interaction energy: fluid-fluid heat, fluid-solid heat, and fluid-high-energy site (HES) heat. Multiple temperature adsorption isotherms are defined for nitrogen, T=(75, 77, 79) K, argon at T=(85, 87, 89) K, and for water and methanol at T=(278, 288, 298) K on a well-characterized polymer-based, activated carbon. Nitrogen and argon are subjected to isosteric heat analyses; their zero filling isosteric heats of adsorption are consistent with slit-pore, adsorption energy enhancement modelling. Water adsorbs entirely via specific interactions, offering decreasing isosteric heat at low pore filling followed by a constant heat slightly in excess of water condensation enthalpy, demonstrating the effects of micropores. Methanol offers both specific adsorption via the alcohol group and non-specific interactions via its methyl group; the isosteric heat increases at low pore filling, indicating the predominance of non-specific interactions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Context-specific target definition in influenza a virus hemagglutinin-glycan receptor interactions.

PubMed

Shriver, Zachary; Raman, Rahul; Viswanathan, Karthik; Sasisekharan, Ram

2009-08-28

Protein-glycan interactions are important regulators of a variety of biological processes, ranging from immune recognition to anticoagulation. An important area of active research is directed toward understanding the role of host cell surface glycans as recognition sites for pathogen protein receptors. Recognition of cell surface glycans is a widely employed strategy for a variety of pathogens, including bacteria, parasites, and viruses. We present here a representative example of such an interaction: the binding of influenza A hemagglutinin (HA) to specific sialylated glycans on the cell surface of human upper airway epithelial cells, which initiates the infection cycle. We detail a generalizable strategy to understand the nature of protein-glycan interactions both structurally and biochemically, using HA as a model system. This strategy combines a top-down approach using available structural information to define important contacts between glycans and HA, with a bottom-up approach using data-mining and informatics approaches to identify the common motifs that distinguish glycan binders from nonbinders. By probing protein-glycan interactions simultaneously through top-down and bottom-up approaches, we can scientifically validate a series of observations. This in turn provides additional confidence and surmounts known challenges in the study of protein-glycan interactions, such as accounting for multivalency, and thus truly defines concepts such as specificity, affinity, and avidity. With the advent of new technologies for glycomics-including glycan arrays, data-mining solutions, and robust algorithms to model protein-glycan interactions-we anticipate that such combination approaches will become tractable for a wide variety of protein-glycan interactions.

Computational Psychotherapy Research: Scaling up the evaluation of patient-provider interactions

PubMed Central

Imel, Zac E.; Steyvers, Mark; Atkins, David C.

2014-01-01

In psychotherapy, the patient-provider interaction contains the treatment’s active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required in order to “scale up” to larger evaluation tasks and “drill down” into the raw linguistic data of patient-therapist interactions. In the current paper we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, content, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time, and we conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. PMID:24866972

Computational psychotherapy research: scaling up the evaluation of patient-provider interactions.

PubMed

Imel, Zac E; Steyvers, Mark; Atkins, David C

2015-03-01

In psychotherapy, the patient-provider interaction contains the treatment's active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required to "scale up" to larger evaluation tasks and "drill down" into the raw linguistic data of patient-therapist interactions. In the current article, we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, relational, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment-related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive-behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model-derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time. We conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Aggregation of polyglutamine-expanded ataxin-3 sequesters its specific interacting partners into inclusions: Implication in a loss-of-function pathology

PubMed Central

Yang, Hui; Li, Jing-Jing; Liu, Shuai; Zhao, Jian; Jiang, Ya-Jun; Song, Ai-Xin; Hu, Hong-Yu

2014-01-01

Expansion of polyglutamine (polyQ) tract may cause protein misfolding and aggregation that lead to cytotoxicity and neurodegeneration, but the underlying mechanism remains to be elucidated. We applied ataxin-3 (Atx3), a polyQ tract-containing protein, as a model to study sequestration of normal cellular proteins. We found that the aggregates formed by polyQ-expanded Atx3 sequester its interacting partners, such as P97/VCP and ubiquitin conjugates, into the protein inclusions through specific interactions both in vitro and in cells. Moreover, this specific sequestration impairs the normal cellular function of P97 in down-regulating neddylation. However, expansion of polyQ tract in Atx3 does not alter the conformation of its surrounding regions and the interaction affinities with the interacting partners, although it indeed facilitates misfolding and aggregation of the Atx3 protein. Thus, we propose a loss-of-function pathology for polyQ diseases that sequestration of the cellular essential proteins via specific interactions into inclusions by the polyQ aggregates causes dysfunction of the corresponding proteins, and consequently leads to neurodegeneration. PMID:25231079

Intermolecular orbital interaction in π systems

NASA Astrophysics Data System (ADS)

Zhao, Rundong; Zhang, Rui-Qin

2018-04-01

Intermolecular interactions, in regard to which people tend to emphasise the noncovalent van der Waals (vdW) forces when conducting investigations throughout chemistry, can influence the structure, stability and function of molecules and materials. Despite the ubiquitous nature of vdW interactions, a simplified electrostatic model has been popularly adopted to explain common intermolecular interactions, especially those existing in π-involved systems. However, this classical model has come under fire in revealing specific issues such as substituent effects, due to its roughness; and it has been followed in past decades by sundry explanations which sometimes bring in nebulous descriptions. In this account, we try to summarise and present a unified model for describing and analysing the binding mechanism of such systems from the viewpoint of energy decomposition. We also emphasise a commonly ignored factor - orbital interaction, pointing out that the noncovalent intermolecular orbital interactions actually exhibit similar bonding and antibonding phenomena as those in covalent bonds.

Staging scientific controversies: a gallery test on science museums' interactivity.

PubMed

Yaneva, Albena; Rabesandratana, Tania Mara; Greiner, Birgit

2009-01-01

The "transfer" model in science communication has been addressed critically from different perspectives, while the advantages of the interactive model have been continuously praised. Yet, little is done to account for the specific role of the interactive model in communicating "unfinished science." The traditional interactive methods in museums are not sufficient to keep pace with rapid scientific developments. Interactive exchanges between laypeople and experts are thought mainly through the lens of a dialogue that is facilitated and framed by the traditional "conference room" architecture. Drawing on the results of a small-scale experiment in a gallery space, we argue for the need for a new "architecture of interaction" in museum settings based on art installation and simulation techniques, which will enhance the communication potentials of science museums and will provide conditions for a fruitful even-handed exchange of expert and lay knowledge.

Neural network modeling of emotion

NASA Astrophysics Data System (ADS)

Levine, Daniel S.

2007-03-01

This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

The Application of Humanized Mouse Models for the Study of Human Exclusive Viruses.

PubMed

Vahedi, Fatemeh; Giles, Elizabeth C; Ashkar, Ali A

2017-01-01

The symbiosis between humans and viruses has allowed human tropic pathogens to evolve intricate means of modulating the human immune response to ensure its survival among the human population. In doing so, these viruses have developed profound mechanisms that mesh closely with our human biology. The establishment of this intimate relationship has created a species-specific barrier to infection, restricting the virus-associated pathologies to humans. This specificity diminishes the utility of traditional animal models. Humanized mice offer a model unique to all other means of study, providing an in vivo platform for the careful examination of human tropic viruses and their interaction with human cells and tissues. These types of animal models have provided a reliable medium for the study of human-virus interactions, a relationship that could otherwise not be investigated without questionable relevance to humans.

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection.

PubMed

Mwanza, Jean-Claude; Warren, Joshua L; Hochberg, Jessica T; Budenz, Donald L; Chang, Robert T; Ramulu, Pradeep Y

2015-01-01

To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. One hundred ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike's information criterion (AIC), and prediction confidence interval lengths. For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDx-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT×NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single-variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAP-FDT, and interaction GDx-TSNIT×NAP-FDT consistently provided better discriminating abilities for detecting early, moderate, and severe glaucoma than the best single-variable models. The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDx-TSNIT×NAP-FDT provides the best glaucoma prediction compared with all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared with using GDx or FDT alone.

North Atlantic Ocean OSSE system development: Nature Run evaluation and application to hurricane interaction with the Gulf Stream

NASA Astrophysics Data System (ADS)

Kourafalou, Vassiliki H.; Androulidakis, Yannis S.; Halliwell, George R.; Kang, HeeSook; Mehari, Michael M.; Le Hénaff, Matthieu; Atlas, Robert; Lumpkin, Rick

2016-11-01

A high resolution, free-running model has been developed for the hurricane region of the North Atlantic Ocean. The model is evaluated with a variety of observations to ensure that it adequately represents both the ocean climatology and variability over this region, with a focus on processes relevant to hurricane-ocean interactions. As such, it can be used as the "Nature Run" (NR) model within the framework of Observing System Simulation Experiments (OSSEs), designed specifically to improve the ocean component of coupled ocean-atmosphere hurricane forecast models. The OSSE methodology provides quantitative assessment of the impact of specific observations on the skill of forecast models and enables the comprehensive design of future observational platforms and the optimization of existing ones. Ocean OSSEs require a state-of-the-art, high-resolution free-running model simulation that represents the true ocean (the NR). This study concentrates on the development and data based evaluation of the NR model component, which leads to a reliable model simulation that has a dual purpose: (a) to provide the basis for future hurricane related OSSEs; (b) to explore process oriented studies of hurricane-ocean interactions. A specific example is presented, where the impact of Hurricane Bill (2009) on the eastward extension and transport of the Gulf Stream is analyzed. The hurricane induced cold wake is shown in both NR simulation and observations. Interaction of storm-forced currents with the Gulf Stream produced a temporary large reduction in eastward transport downstream from Cape Hatteras and had a marked influence on frontal displacement in the upper ocean. The kinetic energy due to ageostrophic currents showed a significant increase as the storm passed, and then decreased to pre-storm levels within 8 days after the hurricane advanced further north. This is a unique result of direct hurricane impact on a western boundary current, with possible implications on the ocean feedback on hurricane evolution.

Radiative model of neutrino mass with neutrino interacting MeV dark matter

DOE PAGES

Arhrib, Abdesslam; Bohm, Celine; Ma, Ernest; ...

2016-04-26

We consider the radiative generation of neutrino mass through the interactions of neutrinos with MeV dark matter. We construct a realistic renormalizable model with one scalar doublet (in additional to the standard model doublet) and one complex singlet together with three light singlet Majorana fermions, all transforming under a dark U(1)(D) symmetry which breaks softly to Z(2). We study in detail the scalar sector which supports this specific scenario and its rich phenomenology.

A coarse grain model for protein-surface interactions

NASA Astrophysics Data System (ADS)

Wei, Shuai; Knotts, Thomas A.

2013-09-01

The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

PubMed Central

de Croon, E M; Blonk, R; de Zwart, B C H; Frings-Dresen, M; Broersen, J

2002-01-01

Objectives: Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. Methods: From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. Results: The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Conclusions: Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work. PMID:12040108

Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control.

PubMed

de Croon, E M; Blonk, R W B; de Zwart, B C H; Frings-Dresen, M H W; Broersen, J P J

2002-06-01

Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work.

Combined collapse by bridging and self-adhesion in a prototypical polymer model inspired by the bacterial nucleoid

NASA Astrophysics Data System (ADS)

Scolari, Vittore F.; Cosentino Lagomarsino, Marco

Recent experimental results suggest that the E. coli chromosome feels a self-attracting interaction of osmotic origin, and is condensed in foci by bridging interactions. Motivated by these findings, we explore a generic modeling framework combining solely these two ingredients, in order to characterize their joint effects. Specifically, we study a simple polymer physics computational model with weak ubiquitous short-ranged self attraction and stronger sparse bridging interactions. Combining theoretical arguments and simulations, we study the general phenomenology of polymer collapse induced by these dual contributions, in the case of regularly-spaced bridging. Our results distinguish a regime of classical Flory-like coil-globule collapse dictated by the interplay of excluded volume and attractive energy and a switch-like collapse where bridging interaction compete with entropy loss terms from the looped arms of a star-like rosette. Additionally, we show that bridging can induce stable compartmentalized domains. In these configurations, different "cores" of bridging proteins are kept separated by star-like polymer loops in an entropically favorable multi-domain configuration, with a mechanism that parallels micellar polysoaps. Such compartmentalized domains are stable, and do not need any intra-specific interactions driving their segregation. Domains can be stable also in presence of uniform attraction, as long as the uniform collapse is above its theta point.

Design, synthesis and DNA interactions of a chimera between a platinum complex and an IHF mimicking peptide.

PubMed

Rao, Harita; Damian, Mariana S; Alshiekh, Alak; Elmroth, Sofi K C; Diederichsen, Ulf

2015-12-28

Conjugation of metal complexes with peptide scaffolds possessing high DNA binding affinity has shown to modulate their biological activities and to enhance their interaction with DNA. In this work, a platinum complex/peptide chimera was synthesized based on a model of the Integration Host Factor (IHF), an architectural protein possessing sequence specific DNA binding and bending abilities through its interaction with a minor groove. The model peptide consists of a cyclic unit resembling the minor grove binding subdomain of IHF, a positively charged lysine dendrimer for electrostatic interactions with the DNA phosphate backbone and a flexible glycine linker tethering the two units. A norvaline derived artificial amino acid was designed to contain a dimethylethylenediamine as a bidentate platinum chelating unit, and introduced into the IHF mimicking peptides. The interaction of the chimeric peptides with various DNA sequences was studied by utilizing the following experiments: thermal melting studies, agarose gel electrophoresis for plasmid DNA unwinding experiments, and native and denaturing gel electrophoresis to visualize non-covalent and covalent peptide-DNA adducts, respectively. By incorporation of the platinum metal center within the model peptide mimicking IHF we have attempted to improve its specificity and DNA targeting ability, particularly towards those sequences containing adjacent guanine residues.

The Interaction between Dietary Fiber and Fat and Risk of Colorectal Cancer in the Women's Health Initiative.

PubMed

Navarro, Sandi L; Neuhouser, Marian L; Cheng, Ting-Yuan David; Tinker, Lesley F; Shikany, James M; Snetselaar, Linda; Martinez, Jessica A; Kato, Ikuko; Beresford, Shirley A A; Chapkin, Robert S; Lampe, Johanna W

2016-11-30

Combined intakes of specific dietary fiber and fat subtypes protect against colon cancer in animal models. We evaluated associations between self-reported individual and combinations of fiber (insoluble, soluble, and pectins, specifically) and fat (omega-6, omega-3, and docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), specifically) and colorectal cancer (CRC) risk in the Women's Health Initiative prospective cohort ( n = 134,017). During a mean 11.7 years (1993-2010), 1952 incident CRC cases were identified. Cox regression models computed multivariate adjusted hazard ratios to estimate the association between dietary factors and CRC risk. Assessing fiber and fat individually, there was a modest trend for lower CRC risk with increasing intakes of total and insoluble fiber ( p-trend 0.09 and 0.08). An interaction ( p = 0.01) was observed between soluble fiber and DHA + EPA, with protective effects of DHA + EPA with lower intakes of soluble fiber and an attenuation at higher intakes, however this association was no longer significant after correction for multiple testing. These results suggest a modest protective effect of higher fiber intake on CRC risk, but not in combination with dietary fat subtypes. Given the robust results in preclinical models and mixed results in observational studies, controlled dietary interventions with standardized intakes are needed to better understand the interaction of specific fat and fiber subtypes on colon biology and ultimately CRC susceptibility in humans.

On modelling the interaction between two rotating bodies with statistically distributed features: an application to dressing of grinding wheels

NASA Astrophysics Data System (ADS)

Spampinato, A.; Axinte, D. A.

2017-12-01

The mechanisms of interaction between bodies with statistically arranged features present characteristics common to different abrasive processes, such as dressing of abrasive tools. In contrast with the current empirical approach used to estimate the results of operations based on attritive interactions, the method we present in this paper allows us to predict the output forces and the topography of a simulated grinding wheel for a set of specific operational parameters (speed ratio and radial feed-rate), providing a thorough understanding of the complex mechanisms regulating these processes. In modelling the dressing mechanisms, the abrasive characteristics of both bodies (grain size, geometry, inter-space and protrusion) are first simulated; thus, their interaction is simulated in terms of grain collisions. Exploiting a specifically designed contact/impact evaluation algorithm, the model simulates the collisional effects of the dresser abrasives on the grinding wheel topography (grain fracture/break-out). The method has been tested for the case of a diamond rotary dresser, predicting output forces within less than 10% error and obtaining experimentally validated grinding wheel topographies. The study provides a fundamental understanding of the dressing operation, enabling the improvement of its performance in an industrial scenario, while being of general interest in modelling collision-based processes involving statistically distributed elements.

Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs.

PubMed

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems. The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug-nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting/non-interacting sites. More specifically, the model classified 36/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews' regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews' coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action. On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com).

Model Communities Hint at Promiscuous Metabolic Linkages between Ubiquitous Free-Living Freshwater Bacteria

PubMed Central

Buck, Moritz; Hamilton, Joshua J.; Wurzbacher, Christian; Grossart, Hans-Peter; Eiler, Alexander

2018-01-01

ABSTRACT Genome streamlining is frequently observed in free-living aquatic microorganisms and results in physiological dependencies between microorganisms. However, we know little about the specificity of these microbial associations. In order to examine the specificity and extent of these associations, we established mixed cultures from three different freshwater environments and analyzed the cooccurrence of organisms using a metagenomic time series. Free-living microorganisms with streamlined genomes lacking multiple biosynthetic pathways showed no clear recurring pattern in their interaction partners. Free-living freshwater bacteria form promiscuous cooperative associations. This notion contrasts with the well-documented high specificities of interaction partners in host-associated bacteria. Considering all data together, we suggest that highly abundant free-living bacterial lineages are functionally versatile in their interactions despite their distinct streamlining tendencies at the single-cell level. This metabolic versatility facilitates interactions with a variable set of community members. PMID:29848762

The role of the cell wall in fungal pathogenesis

PubMed Central

Arana, David M.; Prieto, Daniel; Román, Elvira; Nombela, César; Alonso‐Monge, Rebeca; Pla, Jesús

2009-01-01

Summary Fungal infections are a serious health problem. In recent years, basic research is focusing on the identification of fungal virulence factors as promising targets for the development of novel antifungals. The wall, as the most external cellular component, plays a crucial role in the interaction with host cells mediating processes such as adhesion or phagocytosis that are essential during infection. Specific components of the cell wall (called PAMPs) interact with specific receptors in the immune cell (called PRRs), triggering responses whose molecular mechanisms are being elucidated. We review here the main structural carbohydrate components of the fungal wall (glucan, mannan and chitin), how their biogenesis takes place in fungi and the specific receptors that they interact with. Different model fungal pathogens are chosen to illustrate the functional consequences of this interaction. Finally, the identification of the key components will have important consequences in the future and will allow better approaches to treat fungal infections. PMID:21261926

Spin-labelling study of interactions of ovalbumin with multilamellar liposomes and specific anti-ovalbumin antibodies.

PubMed

Brgles, Marija; Mirosavljević, Krunoslav; Noethig-Laslo, Vesna; Frkanec, Ruza; Tomasić, Jelka

2007-03-10

Ovalbumin (OVA) has been used continuously as the model antigen in numerous studies of immune reactions and antigen processing, very often encapsulated into liposomes. The purpose of this work was to study the possible interactions of spin-labelled OVA and lipids in liposomal membranes using electron spin resonance (ESR) spectroscopy. OVA was covalently spin-labelled with 4-maleimido-2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO-maleimide), characterized and encapsulated into multilamellar, negatively charged liposomes. ESR spectra of this liposomal preparation gave evidence for the interaction of OVA with the lipid bilayers. Such an interaction was also evidenced by the ESR spectra of liposomal preparation containing OVA, where liposomes were spin-labelled with n-doxyl stearic acids. The spin-labelled OVA retains its property to bind specific anti-OVA antibodies, as shown by ESR spectroscopy, but also in ELISA for specific anti-OVA IgG.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

PubMed

Ghosh, Sourav K; Ostanin, Victor P; Johnson, Christian L; Lowe, Christopher R; Seshia, Ashwin A

2011-11-15

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks. Copyright © 2011 Elsevier B.V. All rights reserved.

Mapping substrate interactions of the human membrane-associated neuraminidase, NEU3, using STD NMR.

PubMed

Albohy, Amgad; Richards, Michele R; Cairo, Christopher W

2015-03-01

Saturation transfer difference (STD) nuclear magnetic resonance (NMR) is a powerful technique which can be used to investigate interactions between proteins and their substrates. The method identifies specific sites of interaction found on a small molecule ligand when in complex with a protein. The ability of STD NMR to provide specific insight into binding interactions in the absence of other structural data is an attractive feature for its use with membrane proteins. We chose to employ STD NMR in our ongoing investigations of the human membrane-associated neuraminidase NEU3 and its interaction with glycolipid substrates (e.g., GM3). In order to identify critical substrate-enzyme interactions, we performed STD NMR with a catalytically inactive form of the enzyme, NEU3(Y370F), containing an N-terminal maltose-binding protein (MBP)-affinity tag. In the absence of crystallographic data on the enzyme, these data represent a critical experimental test of proposed homology models, as well as valuable new structural data. To aid interpretation of the STD NMR data, we compared the results with molecular dynamics (MD) simulations of the enzyme-substrate complexes. We find that the homology model is able to predict essential features of the experimental data, including close contact of the hydrophobic aglycone and the Neu5Ac residue with the enzyme. Additionally, the model and STD NMR data agree on the facial recognition of the galactose and glucose residues of the GM3-analog studied. We conclude that the homology model of NEU3 can be used to predict substrate recognition, but our data indicate that unstructured portions of the NEU3 model may require further refinement. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Fibroblasts Influence Survival and Therapeutic Response in a 3D Co-Culture Model

PubMed Central

Majety, Meher; Pradel, Leon P.; Gies, Manuela; Ries, Carola H.

2015-01-01

In recent years, evidence has indicated that the tumor microenvironment (TME) plays a significant role in tumor progression. Fibroblasts represent an abundant cell population in the TME and produce several growth factors and cytokines. Fibroblasts generate a suitable niche for tumor cell survival and metastasis under the influence of interactions between fibroblasts and tumor cells. Investigating these interactions requires suitable experimental systems to understand the cross-talk involved. Most in vitro experimental systems use 2D cell culture and trans-well assays to study these interactions even though these paradigms poorly represent the tumor, in which direct cell-cell contacts in 3D spaces naturally occur. Investigating these interactions in vivo is of limited value due to problems regarding the challenges caused by the species-specificity of many molecules. Thus, it is essential to use in vitro models in which human fibroblasts are co-cultured with tumor cells to understand their interactions. Here, we developed a 3D co-culture model that enables direct cell-cell contacts between pancreatic, breast and or lung tumor cells and human fibroblasts/ or tumor-associated fibroblasts (TAFs). We found that co-culturing with fibroblasts/TAFs increases the proliferation in of several types of cancer cells. We also observed that co-culture induces differential expression of soluble factors in a cancer type-specific manner. Treatment with blocking antibodies against selected factors or their receptors resulted in the inhibition of cancer cell proliferation in the co-cultures. Using our co-culture model, we further revealed that TAFs can influence the response to therapeutic agents in vitro. We suggest that this model can be reliably used as a tool to investigate the interactions between a tumor and the TME. PMID:26053043

A study of social interaction and teamwork in reformed physics laboratories

NASA Astrophysics Data System (ADS)

Gresser, Paul W.

It is widely accepted that, for many students, learning can be accomplished most effectively through social interaction with peers, and there have been many successes in using the group environment to improve learning in a variety of classroom settings. What is not well understood, however, are the dynamics of student groups, specifically how the students collectively apprehend the subject matter and share the mental workload. This research examines recent developments of theoretical tools for describing the cognitive states of individual students: associational patterns such as epistemic games and cultural structures such as epistemological framing. Observing small group interaction in authentic classroom situations (labs, tutorials, problem solving) suggests that these tools could be effective in describing these interactions. Though conventional wisdom tells us that groups may succeed where individuals fail, there are many reasons why group work may also run into difficulties, such as a lack or imbalance of knowledge, an inappropriate mix of learning styles, or a destructive power arrangement. This research explores whether or not inconsistent epistemological framing among group members can also be a cause of group failure. Case studies of group interaction in the laboratory reveal evidence of successful groups employing common framing, and unsuccessful groups failing from lack of a shared frame. This study was conducted in a large introductory algebra-based physics course at the University of Maryland, College Park, in a laboratory designed specifically to foster increased student interaction and cooperation. Videotape studies of this environment reveal that productive lab groups coordinate their efforts through a number of locally coherent knowledge-building activities, which are described through the framework of epistemic games. The existence of these epistemic games makes it possible for many students to participate in cognitive activities without a complete shared understanding of the specific activity's goal. Also examined is the role that social interaction plays in initiating, negotiating, and carrying out these epistemic games. This behavior is illustrated through the model of distributed cognition. An attempt is made to analyze this group activity using Tuckman's stage model, which is a prominent description of group development within educational psychology. However, the shortcomings of this model in dealing with specific cognitive tasks lead us to seek another explanation. The model used in this research seeks to expand existing cognitive tools into the realm of social interaction. In doing so, we can see that successful groups approach tasks in the lab by negotiating a shared frame of understanding. Using the findings from these case studies, recommendations are made concerning the teaching of introductory physics laboratory courses.

Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review

PubMed Central

Misra, Sarthak; Ramesh, K. T.; Okamura, Allison M.

2009-01-01

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the interaction between surgical instruments and organs has been recognized as a key requirement in the development of high-fidelity surgical simulators. Researchers have attempted to model tool-tissue interactions in a wide variety of ways, which can be broadly classified as (1) linear elasticity-based, (2) nonlinear (hyperelastic) elasticity-based finite element (FE) methods, and (3) other techniques that not based on FE methods or continuum mechanics. Realistic modeling of organ deformation requires populating the model with real tissue data (which are difficult to acquire in vivo) and simulating organ response in real time (which is computationally expensive). Further, it is challenging to account for connective tissue supporting the organ, friction, and topological changes resulting from tool-tissue interactions during invasive surgical procedures. Overcoming such obstacles will not only help us to model tool-tissue interactions in real time, but also enable realistic force feedback to the user during surgical simulation. This review paper classifies the existing research on tool-tissue interactions for surgical simulators specifically based on the modeling techniques employed and the kind of surgical operation being simulated, in order to inform and motivate future research on improved tool-tissue interaction models. PMID:20119508

Probing the target search of DNA-binding proteins in mammalian cells using TetR as model searcher

NASA Astrophysics Data System (ADS)

Normanno, Davide; Boudarène, Lydia; Dugast-Darzacq, Claire; Chen, Jiji; Richter, Christian; Proux, Florence; Bénichou, Olivier; Voituriez, Raphaël; Darzacq, Xavier; Dahan, Maxime

2015-07-01

Many cellular functions rely on DNA-binding proteins finding and associating to specific sites in the genome. Yet the mechanisms underlying the target search remain poorly understood, especially in the case of the highly organized mammalian cell nucleus. Using as a model Tet repressors (TetRs) searching for a multi-array locus, we quantitatively analyse the search process in human cells with single-molecule tracking and single-cell protein-DNA association measurements. We find that TetRs explore the nucleus and reach their target by 3D diffusion interspersed with transient interactions with non-cognate sites, consistent with the facilitated diffusion model. Remarkably, nonspecific binding times are broadly distributed, underlining a lack of clear delimitation between specific and nonspecific interactions. However, the search kinetics is not determined by diffusive transport but by the low association rate to nonspecific sites. Altogether, our results provide a comprehensive view of the recruitment dynamics of proteins at specific loci in mammalian cells.

Ontogenetic ritualization of primate gesture as a case study in dyadic brain modeling.

PubMed

Gasser, Brad; Cartmill, Erica A; Arbib, Michael A

2014-01-01

This paper introduces dyadic brain modeling - the simultaneous, computational modeling of the brains of two interacting agents - to explore ways in which our understanding of macaque brain circuitry can ground new models of brain mechanisms involved in ape interaction. Specifically, we assess a range of data on gestural communication of great apes as the basis for developing an account of the interactions of two primates engaged in ontogenetic ritualization, a proposed learning mechanism through which a functional action may become a communicative gesture over repeated interactions between two individuals (the 'dyad'). The integration of behavioral, neural, and computational data in dyadic (or, more generally, social) brain modeling has broad application to comparative and evolutionary questions, particularly for the evolutionary origins of cognition and language in the human lineage. We relate this work to the neuroinformatics challenges of integrating and sharing data to support collaboration between primatologists, neuroscientists and modelers that will help speed the emergence of what may be called comparative neuro-primatology.

Field theories and fluids for an interacting dark sector

NASA Astrophysics Data System (ADS)

Carrillo González, Mariana; Trodden, Mark

2018-02-01

We consider the relationship between fluid models of an interacting dark sector and the field theoretical models that underlie such descriptions. This question is particularly important in light of suggestions that such interactions may help alleviate a number of current tensions between different cosmological datasets. We construct consistent field theory models for an interacting dark sector that behave exactly like the coupled fluid ones, even at the level of linear perturbations, and can be trusted deep in the nonlinear regime. As a specific example, we focus on the case of a Dirac, Born-Infeld (DBI) field conformally coupled to a quintessence field. We show that the fluid linear regime breaks before the field gradients become large; this means that the field theory is valid inside a large region of the fluid nonlinear regime.

The BioGRID interaction database: 2017 update

PubMed Central

Chatr-aryamontri, Andrew; Oughtred, Rose; Boucher, Lorrie; Rust, Jennifer; Chang, Christie; Kolas, Nadine K.; O'Donnell, Lara; Oster, Sara; Theesfeld, Chandra; Sellam, Adnane; Stark, Chris; Breitkreutz, Bobby-Joe; Dolinski, Kara; Tyers, Mike

2017-01-01

The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases. PMID:27980099

Passing Messages between Biological Networks to Refine Predicted Interactions

PubMed Central

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402

A Computational Model of Active Vision for Visual Search in Human-Computer Interaction

DTIC Science & Technology

2010-08-01

processors that interact with the production rules to produce behavior, and (c) parameters that constrain the behavior of the model (e.g., the...velocity of a saccadic eye movement). While the parameters can be task-specific, the majority of the parameters are usually fixed across a wide variety...previously estimated durations. Hooge and Erkelens (1996) review these four explanations of fixation duration control. A variety of research

A Unified Approach to Modeling Multidisciplinary Interactions

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Bhatia, Kumar G.

2000-01-01

There are a number of existing methods to transfer information among various disciplines. For a multidisciplinary application with n disciplines, the traditional methods may be required to model (n(exp 2) - n) interactions. This paper presents a unified three-dimensional approach that reduces the number of interactions from (n(exp 2) - n) to 2n by using a computer-aided design model. The proposed modeling approach unifies the interactions among various disciplines. The approach is independent of specific discipline implementation, and a number of existing methods can be reformulated in the context of the proposed unified approach. This paper provides an overview of the proposed unified approach and reformulations for two existing methods. The unified approach is specially tailored for application environments where the geometry is created and managed through a computer-aided design system. Results are presented for a blended-wing body and a high-speed civil transport.

A systems model for immune cell interactions unravels the mechanism of inflammation in human skin.

PubMed

Valeyev, Najl V; Hundhausen, Christian; Umezawa, Yoshinori; Kotov, Nikolay V; Williams, Gareth; Clop, Alex; Ainali, Crysanthi; Ouzounis, Christos; Tsoka, Sophia; Nestle, Frank O

2010-12-02

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.

A unified approach to computer analysis and modeling of spacecraft environmental interactions

NASA Technical Reports Server (NTRS)

Katz, I.; Mandell, M. J.; Cassidy, J. J.

1986-01-01

A new, coordinated, unified approach to the development of spacecraft plasma interaction models is proposed. The objective is to eliminate the unnecessary duplicative work in order to allow researchers to concentrate on the scientific aspects. By streamlining the developmental process, the interchange between theories and experimentalists is enhanced, and the transfer of technology to the spacecraft engineering community is faster. This approach is called the UNIfied Spacecraft Interaction Model (UNISIM). UNISIM is a coordinated system of software, hardware, and specifications. It is a tool for modeling and analyzing spacecraft interactions. It will be used to design experiments, to interpret results of experiments, and to aid in future spacecraft design. It breaks a Spacecraft Ineraction analysis into several modules. Each module will perform an analysis for some physical process, using phenomenology and algorithms which are well documented and have been subject to review. This system and its characteristics are discussed.

Site specific interaction between ZnO nanoparticles and tyrosine: A density functional theory study

NASA Astrophysics Data System (ADS)

Singh, Satvinder; Singh, Janpreet; Singh, Baljinder; Singh, Gurinder; Kaura, Aman; Tripathi, S. K.

2018-05-01

First Principles Calculations have been performed on ZnO/Tyrosine atomic complex to study site specific interaction of Tyrosine and ZnO nanoparticles. Calculated results shows that -COOH group present in Tyrosine is energetically more favorable than -NH2 group. Interactions show ionic bonding between ZnO and Tyrosine. All the calculations have been performed under the Density Functional Theory (DFT) framework. Structural and electronic properties of (ZnO)3/Tyrosine complex have been studied. Gaussian basis set approach has been adopted for the calculations. A ring type most stable (ZnO)3 atomic cluster has been modeled, analyzed and used for the calculations.

Spatial interactions between urban areas and cause-specific mortality differentials in France.

PubMed

Ghosn, Walid; Kassie, Daouda; Jougla, Eric; Rican, Stéphane; Rey, Grégoire

2013-11-01

Spatial interactions constitute a challenging but promising approach for investigation of spatial mortality inequalities. Among spatial interactions measures, between-spatial unit migration differentials are a marker of socioeconomic imbalance, but also reflect discrepancies due to other factors. Specifically, this paper asks whether population exchange intensities measure differentials or similarities that are not captured by usual socioeconomic indicators. Urban areas were grouped pairwise by the intensity of connection estimated from a gravity model. The mortality differences for several causes of death were observed to be significantly smaller for strongly connected pairs than for weakly connected pairs even after adjustment on deprivation. © 2013 Published by Elsevier Ltd.

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms. PMID:28095400

Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2017-01-01

Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.

Generalized Structured Component Analysis with Latent Interactions

ERIC Educational Resources Information Center

Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

2010-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

Elements of Engagement: A Model of Teacher Interactions via Professional Learning Networks

ERIC Educational Resources Information Center

Krutka, Daniel G.; Carpenter, Jeffrey P.; Trust, Torrey

2016-01-01

In recent years, many educators have turned to participatory online affinity spaces for professional growth with peers who are more accessible because of reduced temporal and spatial constraints. Specifically, professional learning networks (PLNs) are "uniquely personalized, complex systems of interactions consisting of people, resources, and…

A Single-Boundary Accumulator Model of Response Times in an Addition Verification Task

PubMed Central

Faulkenberry, Thomas J.

2017-01-01

Current theories of mathematical cognition offer competing accounts of the interplay between encoding and calculation in mental arithmetic. Additive models propose that manipulations of problem format do not interact with the cognitive processes used in calculation. Alternatively, interactive models suppose that format manipulations have a direct effect on calculation processes. In the present study, we tested these competing models by fitting participants' RT distributions in an arithmetic verification task with a single-boundary accumulator model (the shifted Wald distribution). We found that in addition to providing a more complete description of RT distributions, the accumulator model afforded a potentially more sensitive test of format effects. Specifically, we found that format affected drift rate, which implies that problem format has a direct impact on calculation processes. These data give further support for an interactive model of mental arithmetic. PMID:28769853

Use of Network Inference to Elucidate Common and Chemical-specific Effects on Steoidogenesis

EPA Science Inventory

Microarray data is a key source for modeling gene regulatory interactions. Regulatory network models based on multiple datasets are potentially more robust and can provide greater confidence. In this study, we used network modeling on microarray data generated by exposing the fat...

Combining Frequency Doubling Technology Perimetry and Scanning Laser Polarimetry for Glaucoma Detection

PubMed Central

Mwanza, Jean-Claude; Warren, Joshua L.; Hochberg, Jessica T.; Budenz, Donald L.; Chang, Robert T.; Ramulu, Pradeep Y.

2014-01-01

Purpose To determine the ability of frequency doubling technology (FDT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) to detect glaucoma when used individually and in combination. Methods One hundred and ten normal and 114 glaucomatous subjects were tested with FDT C-20-5 screening protocol and the GDx-VCC. The discriminating ability was tested for each device individually and for both devices combined using GDx-NFI, GDx-TSNIT, number of missed points of FDT, and normal or abnormal FDT. Measures of discrimination included sensitivity, specificity, area under the curve (AUC), Akaike’s information criterion (AIC), and prediction confidence interval lengths (PIL). Results For detecting glaucoma regardless of severity, the multivariable model resulting from the combination of GDX-TSNIT, number of abnormal points on FDT (NAP-FDT), and the interaction GDx-TSNIT * NAP-FDT (AIC: 88.28, AUC: 0.959, sensitivity: 94.6%, specificity: 89.5%) outperformed the best single variable model provided by GDx-NFI (AIC: 120.88, AUC: 0.914, sensitivity: 87.8%, specificity: 84.2%). The multivariable model combining GDx-TSNIT, NAPFDT, and interaction GDx-TSNIT*NAP-FDT consistently provided better discriminating abilities for detecting early, moderate and severe glaucoma than the best single variable models. Conclusions The multivariable model including GDx-TSNIT, NAP-FDT, and the interaction GDX-TSNIT * NAP-FDT provides the best glaucoma prediction compared to all other multivariable and univariable models. Combining the FDT C-20-5 screening protocol and GDx-VCC improves glaucoma detection compared to using GDx or FDT alone. PMID:24777046

Patient-Specific Computational Modeling of Human Phonation

NASA Astrophysics Data System (ADS)

Xue, Qian; Zheng, Xudong; University of Maine Team

2013-11-01

Phonation is a common biological process resulted from the complex nonlinear coupling between glottal aerodynamics and vocal fold vibrations. In the past, the simplified symmetric straight geometric models were commonly employed for experimental and computational studies. The shape of larynx lumen and vocal folds are highly three-dimensional indeed and the complex realistic geometry produces profound impacts on both glottal flow and vocal fold vibrations. To elucidate the effect of geometric complexity on voice production and improve the fundamental understanding of human phonation, a full flow-structure interaction simulation is carried out on a patient-specific larynx model. To the best of our knowledge, this is the first patient-specific flow-structure interaction study of human phonation. The simulation results are well compared to the established human data. The effects of realistic geometry on glottal flow and vocal fold dynamics are investigated. It is found that both glottal flow and vocal fold dynamics present a high level of difference from the previous simplified model. This study also paved the important step toward the development of computer model for voice disease diagnosis and surgical planning. The project described was supported by Grant Number ROlDC007125 from the National Institute on Deafness and Other Communication Disorders (NIDCD).

Defect sink characteristics of specific grain boundary types in 304 stainless steels under high dose neutron environments

DOE PAGES

Field, Kevin G.; Yang, Ying; Busby, Jeremy T.; ...

2015-03-09

Radiation induced segregation (RIS) is a well-studied phenomena which occurs in many structurally relevant nuclear materials including austenitic stainless steels. RIS occurs due to solute atoms preferentially coupling to mobile point defect fluxes that migrate and interact with defect sinks. Here, a 304 stainless steel was neutron irradiated up to 47.1 dpa at 320 °C. Investigations into the RIS response at specific grain boundary types were utilized to determine the sink characteristics of different boundary types as a function of irradiation dose. A rate theory model built on the foundation of the modified inverse Kirkendall (MIK) model is proposed andmore » benchmarked to the experimental results. This model, termed the GiMIK model, includes alterations in the boundary conditions based on grain boundary structure and includes expressions for interstitial binding. This investigation, through experiment and modeling, found specific grain boundary structures exhibit unique defect sink characteristics depending on their local structure. Furthermore, such interactions were found to be consistent across all doses investigated and had larger global implications including precipitation of Ni-Si clusters near different grain boundary types.« less

Use of polyclonal and monoclonal antibodies to study hCG-receptor interactions

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

Milius, R.P.

1985-01-01

Although the glycoprotein hormones lutropin (LH), follitropin (FSH), and thyrotropin (TSH) bind to different receptors, each contains an identical alpha subunit. Specificity is somehow endowed by theta subunits which are distinct for each hormone. Human choriogonadotropin (hCG) is a natural LH analog that contains a beta subunit nearly identical to that of LH. The roles of these subunits in the recognition and high affinity binding of hCG to receptor was examined. Polyclonal and monoclonal antibodies specific for the individual subunits of hCG were used to probe the hormone-receptor interaction. Conformation-specific and sequence-specific antibodies were examined for their abilities to bindmore » Triton X-100-solubilized /sup 125/I-hCG-receptor complex and to inhibit hormone binding to crude rat ovarian membranes containing receptor. Even though the immunoreactive sites are not located on the receptor binding surface of the beta subunit, most, but not all, of these polyclonal and monoclonal antibodies were able to inhibit /sup 125/I-hCG binding to receptor. Although the inhibition of binding may be due to steric interference due to the size of the antibody molecules, a two-step model for hCG binding to receptor is presented that also explains these results. In this model, the beta subunit initially binds with the receptor with a highly specific but low affinity interaction. This activates a site for the high affinity binding of the alpha subunit and stabilization of the complex. This is an attractive model as it may be applied to other glycoprotein hormones sharing an alpha subunit.« less

Predictive Bcl-2 Family Binding Models Rooted in Experiment or Structure

PubMed Central

DeBartolo, Joe; Dutta, Sanjib; Reich, Lothar; Keating, Amy E.

2013-01-01

Proteins of the Bcl-2 family either enhance or suppress programmed cell death and are centrally involved in cancer development and resistance to chemotherapy. BH3 (Bcl-2 homology 3)-only Bcl-2 proteins promote cell death by docking an α-helix into a hydrophobic groove on the surface of one or more of five pro-survival Bcl-2 receptor proteins. There is high structural homology within the pro-death and pro-survival families, yet a high degree of interaction specificity is nevertheless encoded, posing an interesting and important molecular recognition problem. Understanding protein features that dictate Bcl-2 interaction specificity is critical for designing peptide-based cancer therapeutics and diagnostics. In this study, we present peptide SPOT arrays and deep sequencing data from yeast display screening experiments that significantly expand the BH3 sequence space that has been experimentally tested for interaction with five human anti-apoptotic receptors. These data provide rich information about the determinants of Bcl-2 family specificity. To interpret and use the information, we constructed two simple data-based models that can predict affinity and specificity when evaluated on independent data sets within a limited sequence space. We also constructed a novel structure-based statistical potential, called STATIUM, which is remarkably good at predicting Bcl-2 affinity and specificity, especially considering it is not trained on experimental data. We compare the performance of our three models to each other and to alternative structure-based methods and discuss how such tools can guide prediction and design of new Bcl-2 family complexes. PMID:22617328

A study on the application of voice interaction in automotive human machine interface experience design

NASA Astrophysics Data System (ADS)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

Heat transfer modelling of pulsed laser-tissue interaction

NASA Astrophysics Data System (ADS)

Urzova, J.; Jelinek, M.

2018-03-01

Due to their attributes, the application of medical lasers is on the rise in numerous medical fields. From a biomedical point of view, the most interesting applications are the thermal interactions and the photoablative interactions, which effectively remove tissue without excessive heat damage to the remaining tissue. The objective of this work is to create a theoretical model for heat transfer in the tissue following its interaction with the laser beam to predict heat transfer during medical laser surgery procedures. The dimensions of the ablated crater (shape and ablation depth) were determined by computed tomography imaging. COMSOL Multiphysics software was used for temperature modelling. The parameters of tissue and blood, such as density, specific heat capacity, thermal conductivity and diffusivity, were calculated from the chemical ratio. The parameters of laser-tissue interaction, such as absorption and reflection coefficients, were experimentally determined. The parameters of the laser beam were power density, repetition frequency, pulse length and spot dimensions. Heat spreading after laser interaction with tissue was captured using a Fluke thermal camera. The model was verified for adipose tissue, skeletal muscle tissue and heart muscle tissue.

Rational redesign of inhibitors of furin/kexin processing proteases by electrostatic mutations.

PubMed

Cai, Xiao-hui; Zhang, Qing; Ding, Da-fu

2004-12-01

To model the three-dimensional structure and investigate the interaction mechanism of the proprotein convertase furin/kexin and their inhibitors (eglin c mutants). The three-dimensional complex structures of furin/kexin with its inhibitors, eglin c mutants, were generated by modeller program using the newly published X-ray crystallographical structures of mouse furin and yeast kexin as templates. The electrostatic interaction energy of each complex was calculated and the results were compared with the experimentally determined inhibition constants to find the correlation between them. High quality models of furin/kexin-eglin c mutants were obtained and used for calculation of the electrostatic interaction energies between the proteases and their inhibitors. The calculated electrostatic energies of interaction showed a linear correlation to the experimental inhibition constants. The modeled structures give good explanations of the specificity of eglin c mutants to furin/kexin. The electrostatic interactions play important roles in inhibitory activity of eglin c mutants to furin/kexin. The results presented here provided quantitative structural and functional information concerning the role of the charge-charge interactions in the binding of furin/kexin and their inhibitors.

A GIS-Enabled, Michigan-Specific, Hierarchical Groundwater Modeling and Visualization System

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, S.; Mandle, R.; Simard, A.; Fisher, B.; Brown, E.; Ross, S.

2005-12-01

Efficient management of groundwater resources relies on a comprehensive database that represents the characteristics of the natural groundwater system as well as analysis and modeling tools to describe the impacts of decision alternatives. Many agencies in Michigan have spent several years compiling expensive and comprehensive surface water and groundwater inventories and other related spatial data that describe their respective areas of responsibility. However, most often this wealth of descriptive data has only been utilized for basic mapping purposes. The benefits from analyzing these data, using GIS analysis functions or externally developed analysis models or programs, has yet to be systematically realized. In this talk, we present a comprehensive software environment that allows Michigan groundwater resources managers and frontline professionals to make more effective use of the available data and improve their ability to manage and protect groundwater resources, address potential conflicts, design cleanup schemes, and prioritize investigation activities. In particular, we take advantage of the Interactive Ground Water (IGW) modeling system and convert it to a customized software environment specifically for analyzing, modeling, and visualizing the Michigan statewide groundwater database. The resulting Michigan IGW modeling system (IGW-M) is completely window-based, fully interactive, and seamlessly integrated with a GIS mapping engine. The system operates in real-time (on the fly) providing dynamic, hierarchical mapping, modeling, spatial analysis, and visualization. Specifically, IGW-M allows water resources and environmental professionals in Michigan to: * Access and utilize the extensive data from the statewide groundwater database, interactively manipulate GIS objects, and display and query the associated data and attributes; * Analyze and model the statewide groundwater database, interactively convert GIS objects into numerical model features, automatically extract data and attributes, and simulate unsteady groundwater flow and contaminant transport in response to water and land management decisions; * Visualize and map model simulations and predictions with data from the statewide groundwater database in a seamless interactive environment. IGW-M has the potential to significantly improve the productivity of Michigan groundwater management investigations. It changes the role of engineers and scientists in modeling and analyzing the statewide groundwater database from heavily physical to cognitive problem-solving and decision-making tasks. The seamless real-time integration, real-time visual interaction, and real-time processing capability allows a user to focus on critical management issues, conflicts, and constraints, to quickly and iteratively examine conceptual approximations, management and planning scenarios, and site characterization assumptions, to identify dominant processes, to evaluate data worth and sensitivity, and to guide further data-collection activities. We illustrate the power and effectiveness of the M-IGW modeling and visualization system with a real case study and a real-time, live demonstration.

Comparison of analytical models for zonal flow generation in ion-temperature-gradient mode turbulence

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

Anderson, J.; Miki, K.; Uzawa, K.

2006-11-30

During the past years the understanding of the multi scale interaction problems have increased significantly. However, at present there exists a flora of different analytical models for investigating multi scale interactions and hardly any specific comparisons have been performed among these models. In this work two different models for the generation of zonal flows from ion-temperature-gradient (ITG) background turbulence are discussed and compared. The methods used are the coherent mode coupling model and the wave kinetic equation model (WKE). It is shown that the two models give qualitatively the same results even though the assumption on the spectral difference ismore » used in the (WKE) approach.« less

Interaction of transient radiation in nongray gaseous systems

NASA Technical Reports Server (NTRS)

Tiwari, S. N.; Singh, D. J.

1987-01-01

A general formulation is presented to investigate the transient radiative interaction in nongray absorbing-emitting species between two parallel plates. Depending on the desired sophistication and accuracy, any nongray absorption model from line-by-line models to the wide band model correlations can be employed in the formulation to investigate the radiative interaction. Special attention is directed to investigate the radiative interaction in a system initially at a uniform reference temperature and suddenly the temperature of the bottom plate is reduced to a lower but constant temperature. The interaction is considered for the case of radiative equilibrium as well as for combined radiation and conduction. General as well as limiting forms of the governing equations are presented and solutions are obtained numerically by employing the method of variation of parameters. Specific results are obtained for CO, CO2, H2O, and OH. The information on species H2O and OH is of special interest for the proposed scramjet engine application. The results demonstrate the relative ability of different species for radiative interactions.

Modeling interactions between political parties and electors

NASA Astrophysics Data System (ADS)

Bagarello, F.; Gargano, F.

2017-09-01

In this paper we extend some recent results on an operatorial approach to the description of alliances between political parties interacting among themselves and with a basin of electors. In particular, we propose and compare three different models, deducing the dynamics of their related decision functions, i.e. the attitude of each party to form or not an alliance. In the first model the interactions between each party and their electors are considered. We show that these interactions drive the decision functions toward certain asymptotic values depending on the electors only: this is the perfect party, which behaves following the electors' suggestions. The second model is an extension of the first one in which we include a rule which modifies the status of the electors, and of the decision functions as a consequence, at some specific time step. In the third model we neglect the interactions with the electors while we consider cubic and quartic interactions between the parties and we show that we get (slightly oscillating) asymptotic values for the decision functions, close to their initial values. This is the real party, which does not listen to the electors. Several explicit situations are considered in details and numerical results are also shown.

Gender-specific interactions between education and income in relation to obesity: a cross-sectional analysis of the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V)

PubMed Central

Chung, Woojin; Lim, Seung-ji; Lee, Sunmi; Kim, Roeul; Kim, Jaeyeun

2017-01-01

Objectives To identify gender-specific associations between education and income in relation to obesity in developed countries by considering both the interaction-effect terms of the independent variables and their main-effect terms. Design A cross-sectional study. Education and income levels were chosen as socioeconomic status indicators. Sociodemographics, lifestyles and medical conditions were used as covariates in multivariable logistic regression models. Adjusted ORs and predicted probabilities of being obese were computed and adjusted for a complex survey design. Setting Data were obtained from the Fifth Korea National Health and Nutrition Examination Survey (2010–2012). Participants The sample included 7337 male and 9908 female participants aged ≥19 years. Outcome measure Obesity was defined as body mass index of ≥25, according to a guideline for Asians. Results In models with no interaction-effect terms of independent variables, education was significantly associated with obesity in both men and women, but income was significant only in women. However, in models with the interaction-effect terms, education was significant only in women, but income was significant only in men. The interaction effect between income and education was significant in men but not in women. Participants having the highest predicted probability of being obese over educational and income levels differed between the two types of models, and between men and women. A prediction using the models with the interaction-effect terms demonstrated that for all men, the highest level of formal education was associated with an increase in their probability of being obese by as much as 26%. Conclusions The well-known, negative association between socioeconomic status and obesity in developed countries may not be valid when interaction effects are included. Ignoring these effects and their gender differences may result in the targeting of wrong populations for reducing obesity prevalence and its resultant socioeconomic gradients. PMID:29288171

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model.

PubMed

Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair

2013-08-01

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.

Specification and Verification of Web Applications in Rewriting Logic

NASA Astrophysics Data System (ADS)

Alpuente, María; Ballis, Demis; Romero, Daniel

This paper presents a Rewriting Logic framework that formalizes the interactions between Web servers and Web browsers through a communicating protocol abstracting HTTP. The proposed framework includes a scripting language that is powerful enough to model the dynamics of complex Web applications by encompassing the main features of the most popular Web scripting languages (e.g. PHP, ASP, Java Servlets). We also provide a detailed characterization of browser actions (e.g. forward/backward navigation, page refresh, and new window/tab openings) via rewrite rules, and show how our models can be naturally model-checked by using the Linear Temporal Logic of Rewriting (LTLR), which is a Linear Temporal Logic specifically designed for model-checking rewrite theories. Our formalization is particularly suitable for verification purposes, since it allows one to perform in-depth analyses of many subtle aspects related to Web interaction. Finally, the framework has been completely implemented in Maude, and we report on some successful experiments that we conducted by using the Maude LTLR model-checker.

RACER a Coarse-Grained RNA Model for Capturing Folding Free Energy in Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Cheng, Sara; Bell, David; Ren, Pengyu

RACER is a coarse-grained RNA model that can be used in molecular dynamics simulations to predict native structures and sequence-specific variation of free energy of various RNA structures. RACER is capable of accurate prediction of native structures of duplexes and hairpins (average RMSD of 4.15 angstroms), and RACER can capture sequence-specific variation of free energy in excellent agreement with experimentally measured stabilities (r-squared =0.98). The RACER model implements a new effective non-bonded potential and re-parameterization of hydrogen bond and Debye-Huckel potentials. Insights from the RACER model include the importance of treating pairing and stacking interactions separately in order to distinguish folded an unfolded states and identification of hydrogen-bonding, base stacking, and electrostatic interactions as essential driving forces for RNA folding. Future applications of the RACER model include predicting free energy landscapes of more complex RNA structures and use of RACER for multiscale simulations.

Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

NASA Astrophysics Data System (ADS)

Bertazzon, Stefania

The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new directions for further work in the field of spatial analysis, in conjunction with the development of specific software.

Can the vector space model be used to identify biological entity activities?

PubMed Central

2011-01-01

Background Biological systems are commonly described as networks of entity interactions. Some interactions are already known and integrate the current knowledge in life sciences. Others remain unknown for long periods of time and are frequently discovered by chance. In this work we present a model to predict these unknown interactions from a textual collection using the vector space model (VSM), a well known and established information retrieval model. We have extended the VSM ability to retrieve information using a transitive closure approach. Our objective is to use the VSM to identify the known interactions from the literature and construct a network. Based on interactions established in the network our model applies the transitive closure in order to predict and rank new interactions. Results We have tested and validated our model using a collection of patent claims issued from 1976 to 2005. From 266,528 possible interactions in our network, the model identified 1,027 known interactions and predicted 3,195 new interactions. Iterating the model according to patent issue dates, interactions found in a given past year were often confirmed by patent claims not in the collection and issued in more recent years. Most confirmation patent claims were found at the top 100 new interactions obtained from each subnetwork. We have also found papers on the Web which confirm new inferred interactions. For instance, the best new interaction inferred by our model relates the interaction between the adrenaline neurotransmitter and the androgen receptor gene. We have found a paper that reports the partial dependence of the antiapoptotic effect of adrenaline on androgen receptor. Conclusions The VSM extended with a transitive closure approach provides a good way to identify biological interactions from textual collections. Specifically for the context of literature-based discovery, the extended VSM contributes to identify and rank relevant new interactions even if these interactions occcur in only a few documents in the collection. Consequently, we have developed an efficient method for extracting and restricting the best potential results to consider as new advances in life sciences, even when indications of these results are not easily observed from a mass of documents. PMID:22369514

Career Area Rotation Model: User's Manual.

ERIC Educational Resources Information Center

Williams, Richard B.; And Others

The Career Area Rotation Model (CAROM) was developed as a result of the need for a computer based model describing the rotation of airmen within a specific career area (occupational specialty) through various categories of tour duty, accommodating all policies and interactions which are relevant for evaluation purposes. CAROM is an entity…

3D multicellular model of shock wave-cell interaction.

PubMed

Li, Dongli; Hallack, Andre; Cleveland, Robin O; Jérusalem, Antoine

2018-05-01

Understanding the interaction between shock waves and tissue is critical for ad- vancing the use of shock waves for medical applications, such as cancer therapy. This work aims to study shock wave-cell interaction in a more realistic environment, relevant to in vitro and in vivo studies, by using 3D computational models of healthy and cancerous cells. The results indicate that for a single cell embedded in an extracellular environment, the cellular geometry does not influence significantly the membrane strain but does influence the von Mises stress. On the contrary, the presence of neighbouring cells has a strong effect on the cell response, by increasing fourfold both quantities. The membrane strain response of a cell converges with more than three neighbouring cell layers, indicating that a cluster of four layers of cells is sufficient to model the membrane strain in a large domain of tissue. However, a full 3D tissue model is needed if the stress evaluation is of main interest. A tumour mimicking multicellular spheroid model is also proposed to study mutual interaction between healthy and cancer cells and shows that cancer cells can be specifically targeted in an early stage tumour-mimicking environment. This work presents 3D computational models of shock-wave/cell interaction in a biophysically realistic environment using real cell morphology in tissue-mimicking phantom and multicellular spheroid. Results show that cell morphology does not strongly influence the membrane strain but influences the von Mises stress. While the presence of neighbouring cells significantly increases the cell response, four cell layers are enough to capture the membrane strain change in tissue. However, a full tissue model is necessary if accurate stress analysis is needed. The work also shows that cancer cells can be specifically targetted in early stage tumourmimicking environment. This work is a step towards realistic modelling of shock-wave/cell interactions in tissues and provides insight on the use of 3D models for different scenarios. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Inflamed site-specific drug delivery system based on the interaction of human serum albumin nanoparticles with myeloperoxidase in a murine model of experimental colitis.

PubMed

Iwao, Yasunori; Tomiguchi, Izumi; Domura, Ayaka; Mantaira, Yusuke; Minami, Akira; Suzuki, Takashi; Ikawa, Takashi; Kimura, Shin-Ichiro; Itai, Shigeru

2018-04-01

To develop a new strategy for inflamed site-specific drug delivery in the colon for the treatment of ulcerative colitis (UC), we leveraged on the interaction between myeloperoxidase (MPO) and human serum albumin (HSA) and prepared nanoparticles (HSA NPs) conjugated with 5-aminosalicylic acid (5-ASA). The 5-ASA-HSA NPs (nine molecules of 5-ASA per HSA molecule) were uniform particles with an average particle size of 190 nm, a zeta potential of --11.8 mV, and a polydispersity index of 0.35. This was considered a suitable particle characteristic to pass through the mucus layer and accumulate into the mucosa. The specific interaction between the 5-ASA-HSA NPs and MPO was observed using quartz crystal microbalance analysis in vitro. In addition, the 5-ASA-HSA NPs group containing one thousandth of the dose of the 5-ASA (75 μg/kg) showed significantly lower disease activity index values and colon weight/length ratios in UC model mice as similar to large amount of neat 5-ASA group (75 mg/kg), indicating that the therapeutic effect of the 5-ASA-HSA NP formulation was confirmed in vivo. Microscopic images of tissue sections of colon extracted from UC model mice demonstrated that HSA NPs and MPO were both localized in the colon, and this specific interaction between HSA NPs and MPO would be involved the in the therapeutic effect in vivo. Furthermore, in the 5-ASA and 5-ASA-HSA NPs groups, some inflammatory damage was observed in the colon, but the degree of damage was mild compared with the control and HSA NPs groups, suggesting mucosal repair and replacement with fibrous granulation tissue had occurred. Therefore, these data demonstrated that an HSA NP formulation has the potential to specifically deliver 5-ASA to an inflamed site where MPO is highly expressed. Copyright © 2018 Elsevier B.V. All rights reserved.

Data-driven modelling of social forces and collective behaviour in zebrafish.

PubMed

Zienkiewicz, Adam K; Ladu, Fabrizio; Barton, David A W; Porfiri, Maurizio; Bernardo, Mario Di

2018-04-14

Zebrafish are rapidly emerging as a powerful model organism in hypothesis-driven studies targeting a number of functional and dysfunctional processes. Mathematical models of zebrafish behaviour can inform the design of experiments, through the unprecedented ability to perform pilot trials on a computer. At the same time, in-silico experiments could help refining the analysis of real data, by enabling the systematic investigation of key neurobehavioural factors. Here, we establish a data-driven model of zebrafish social interaction. Specifically, we derive a set of interaction rules to capture the primary response mechanisms which have been observed experimentally. Contrary to previous studies, we include dynamic speed regulation in addition to turning responses, which together provide attractive, repulsive and alignment interactions between individuals. The resulting multi-agent model provides a novel, bottom-up framework to describe both the spontaneous motion and individual-level interaction dynamics of zebrafish, inferred directly from experimental observations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation of a computerized aid for creating human behavioral representations of human-computer interaction.

PubMed

Williams, Kent E; Voigt, Jeffrey R

2004-01-01

The research reported herein presents the results of an empirical evaluation that focused on the accuracy and reliability of cognitive models created using a computerized tool: the cognitive analysis tool for human-computer interaction (CAT-HCI). A sample of participants, expert in interacting with a newly developed tactical display for the U.S. Army's Bradley Fighting Vehicle, individually modeled their knowledge of 4 specific tasks employing the CAT-HCI tool. Measures of the accuracy and consistency of task models created by these task domain experts using the tool were compared with task models created by a double expert. The findings indicated a high degree of consistency and accuracy between the different "single experts" in the task domain in terms of the resultant models generated using the tool. Actual or potential applications of this research include assessing human-computer interaction complexity, determining the productivity of human-computer interfaces, and analyzing an interface design to determine whether methods can be automated.

Towards a bulk approach to local interactions of hydrometeors

NASA Astrophysics Data System (ADS)

Baumgartner, Manuel; Spichtinger, Peter

2018-02-01

The growth of small cloud droplets and ice crystals is dominated by the diffusion of water vapor. Usually, Maxwell's approach to growth for isolated particles is used in describing this process. However, recent investigations show that local interactions between particles can change diffusion properties of cloud particles. In this study we develop an approach for including these local interactions into a bulk model approach. For this purpose, a simplified framework of local interaction is proposed and governing equations are derived from this setup. The new model is tested against direct simulations and incorporated into a parcel model framework. Using the parcel model, possible implications of the new model approach for clouds are investigated. The results indicate that for specific scenarios the lifetime of cloud droplets in subsaturated air may be longer (e.g., for an initially water supersaturated air parcel within a downdraft). These effects might have an impact on mixed-phase clouds, for example in terms of riming efficiencies.

Simulating human behavior for national security human interactions.

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

Bernard, Michael Lewis; Hart, Dereck H.; Verzi, Stephen J.

2007-01-01

This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the ''Simulating Human Behavior for National Security Human Interactions'' project was to demonstrate initial simulated human modeling capability that realistically represents intra- and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humansmore » were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra{reg_sign} simulation framework.« less

The Interaction between Dietary Fiber and Fat and Risk of Colorectal Cancer in the Women’s Health Initiative

PubMed Central

Navarro, Sandi L.; Neuhouser, Marian L.; Cheng, Ting-Yuan David; Tinker, Lesley F.; Shikany, James M.; Snetselaar, Linda; Martinez, Jessica A.; Kato, Ikuko; Beresford, Shirley A. A.; Chapkin, Robert S.; Lampe, Johanna W.

2016-01-01

Combined intakes of specific dietary fiber and fat subtypes protect against colon cancer in animal models. We evaluated associations between self-reported individual and combinations of fiber (insoluble, soluble, and pectins, specifically) and fat (omega-6, omega-3, and docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), specifically) and colorectal cancer (CRC) risk in the Women’s Health Initiative prospective cohort (n = 134,017). During a mean 11.7 years (1993–2010), 1952 incident CRC cases were identified. Cox regression models computed multivariate adjusted hazard ratios to estimate the association between dietary factors and CRC risk. Assessing fiber and fat individually, there was a modest trend for lower CRC risk with increasing intakes of total and insoluble fiber (p-trend 0.09 and 0.08). An interaction (p = 0.01) was observed between soluble fiber and DHA + EPA, with protective effects of DHA + EPA with lower intakes of soluble fiber and an attenuation at higher intakes, however this association was no longer significant after correction for multiple testing. These results suggest a modest protective effect of higher fiber intake on CRC risk, but not in combination with dietary fat subtypes. Given the robust results in preclinical models and mixed results in observational studies, controlled dietary interventions with standardized intakes are needed to better understand the interaction of specific fat and fiber subtypes on colon biology and ultimately CRC susceptibility in humans. PMID:27916893

Host–parasite fluctuating selection in the absence of specificity

PubMed Central

Ashby, Ben; White, Andy; Bowers, Roger; Buckling, Angus; Koskella, Britt

2017-01-01

Fluctuating selection driven by coevolution between hosts and parasites is important for the generation of host and parasite diversity across space and time. Theory has focused primarily on infection genetics, with highly specific ‘matching-allele’ frameworks more likely to generate fluctuating selection dynamics (FSD) than ‘gene-for-gene’ (generalist–specialist) frameworks. However, the environment, ecological feedbacks and life-history characteristics may all play a role in determining when FSD occurs. Here, we develop eco-evolutionary models with explicit ecological dynamics to explore the ecological, epidemiological and host life-history drivers of FSD. Our key result is to demonstrate for the first time, to our knowledge, that specificity between hosts and parasites is not required to generate FSD. Furthermore, highly specific host–parasite interactions produce unstable, less robust stochastic fluctuations in contrast to interactions that lack specificity altogether or those that vary from generalist to specialist, which produce predictable limit cycles. Given the ubiquity of ecological feedbacks and the variation in the nature of specificity in host–parasite interactions, our work emphasizes the underestimated potential for host–parasite coevolution to generate fluctuating selection. PMID:29093222

Ames interactive molecular model building system - A 3-D computer modelling system applied to the study of the origin of life

NASA Technical Reports Server (NTRS)

Coeckelenbergh, Y.; Macelroy, R. D.; Rein, R.

1978-01-01

The investigation of specific interactions among biological molecules must take into consideration the stereochemistry of the structures. Thus, models of the molecules are essential for describing the spatial organization of potentially interacting groups, and estimations of conformation are required for a description of spatial organization. Both the function of visualizing molecules, and that of estimating conformation through calculations of energy, are part of the molecular modeling system described in the present paper. The potential uses of the system in investigating some aspects of the origin of life rest on the assumption that translation of conformation from genetic elements to catalytic elements would have been required for the development of the first replicating systems subject to the process of biological evolution.

Honoring children, making relatives: the cultural translation of parent-child interaction therapy for American Indian and Alaska Native families.

PubMed

Bigfoot, Dolores Subia; Funderburk, Beverly W

2011-01-01

The Indian Country Child Trauma Center, as part of the National Child Traumatic Stress Network, designed a series of American Indian and Alaska Native transformations of evidence-based treatment models. Parent-Child Interaction Therapy (PCIT) was culturally adapted/translated to provide an effective treatment model for parents who have difficulty with appropriate parenting skills or for their children who have problematic behavior. The model, Honoring Children-Making Relatives, embeds the basic tenets and procedures of PCIT in a framework that supports American Indian and Alaska Native traditional beliefs and parenting practices that regard children as being the center of the Circle. This article provides an overview of the Honoring Children-Making Relatives model, reviews cultural considerations incorporated into ICCTC's model transformation process, and discusses specific applications for Parent-Child Interaction Therapy within the model.

Economic dynamics with financial fragility and mean-field interaction: A model

NASA Astrophysics Data System (ADS)

Di Guilmi, C.; Gallegati, M.; Landini, S.

2008-06-01

Following Aoki’s statistical mechanics methodology [Masanao Aoki, New Approaches to Macroeconomic Modeling, Cambridge University Press, 1996; Masanao Aoki, Modeling Aggregate Behaviour and Fluctuations in Economics, Cambridge University Press, 2002; Masanao Aoki, and Hiroshi Yoshikawa, Reconstructing Macroeconomics, Cambridge University Press, 2006], we provide some insights into the well-known works of [Bruce Greenwald, Joseph Stiglitz, Macroeconomic models with equity and credit rationing, in: R. Hubbard (Ed.), Information, Capital Markets and Investment, Chicago University Press, Chicago, 1990; Bruce Greenwald, Joseph Stiglitz, Financial markets imperfections and business cycles, Quarterly journal of Economics (1993)]. Specifically, we reach analytically a closed form solution of their models overcoming the aggregation problem. The key idea is to represent the economy as an evolving complex system, composed by heterogeneous interacting agents, that can be partitioned into a space of macroscopic states. This meso level of aggregation permits to adopt mean-field interaction modeling and master equation techniques.

Instability in interacting dark sector: an appropriate holographic Ricci dark energy model

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

Herrera, Ramón; Hipólito-Ricaldi, W.S.; Videla, Nelson, E-mail: ramon.herrera@pucv.cl, E-mail: wiliam.ricaldi@ufes.br, E-mail: nelson.videla@ing.uchile.cl

In this paper we investigate the consequences of phantom crossing considering the perturbative dynamics in models with interaction in their dark sector. By mean of a general study of gauge-invariant variables in comoving gauge, we relate the sources of instabilities in the structure formation process with the phantom crossing. In order to illustrate these relations and its consequences in more detail, we consider a specific case of an holographic dark energy interacting with dark matter. We find that in spite of the model is in excellent agreement with observational data at background level, however it is plagued of instabilities inmore » its perturbative dynamics. We reconstruct the model in order to avoid these undesirable instabilities, and we show that this implies a modification of the concordance model at background. Also we find drastic changes on the parameters space in our model when instabilities are avoided.« less

Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

Angarica, Vladimir Espinosa; Pérez, Abel González; Vasconcelos, Ana T; Collado-Vides, Julio; Contreras-Moreira, Bruno

2008-01-01

Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition. PMID:18922190

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

Virtual Tissues and Developmental Systems Biology (book chapter)

EPA Science Inventory

Virtual tissue (VT) models provide an in silico environment to simulate cross-scale properties in specific tissues or organs based on knowledge of the underlying biological networks. These integrative models capture the fundamental interactions in a biological system and enable ...

Modeling Group Interactions via Open Data Sources

DTIC Science & Technology

2011-08-30

data. The state-of-art search engines are designed to help general query-specific search and not suitable for finding disconnected online groups. The...groups, (2) developing innovative mathematical and statistical models and efficient algorithms that leverage existing search engines and employ

On BC1 RNA and the fragile X mental retardation protein

PubMed Central

Iacoangeli, Anna; Rozhdestvensky, Timofey S.; Dolzhanskaya, Natalia; Tournier, Barthélémy; Schütt, Janin; Brosius, Jürgen; Denman, Robert B.; Khandjian, Edouard W.; Kindler, Stefan; Tiedge, Henri

2008-01-01

The fragile X mental retardation protein (FMRP), the functional absence of which causes fragile X syndrome, is an RNA-binding protein that has been implicated in the regulation of local protein synthesis at the synapse. The mechanism of FMRP's interaction with its target mRNAs, however, has remained controversial. In one model, it has been proposed that BC1 RNA, a small non-protein-coding RNA that localizes to synaptodendritic domains, operates as a requisite adaptor by specifically binding to both FMRP and, via direct base-pairing, to FMRP target mRNAs. Other models posit that FMRP interacts with its target mRNAs directly, i.e., in a BC1-independent manner. Here five laboratories independently set out to test the BC1–FMRP model. We report that specific BC1–FMRP interactions could be documented neither in vitro nor in vivo. Interactions between BC1 RNA and FMRP target mRNAs were determined to be of a nonspecific nature. Significantly, the association of FMRP with bona fide target mRNAs was independent of the presence of BC1 RNA in vivo. The combined experimental evidence is discordant with a proposed scenario in which BC1 RNA acts as a bridge between FMRP and its target mRNAs and rather supports a model in which BC1 RNA and FMRP are translational repressors that operate independently. PMID:18184799

Frontal–Occipital Connectivity During Visual Search

PubMed Central

Pantazatos, Spiro P.; Yanagihara, Ted K.; Zhang, Xian; Meitzler, Thomas

2012-01-01

Abstract Although expectation- and attention-related interactions between ventral and medial prefrontal cortex and stimulus category-selective visual regions have been identified during visual detection and discrimination, it is not known if similar neural mechanisms apply to other tasks such as visual search. The current work tested the hypothesis that high-level frontal regions, previously implicated in expectation and visual imagery of object categories, interact with visual regions associated with object recognition during visual search. Using functional magnetic resonance imaging, subjects searched for a specific object that varied in size and location within a complex natural scene. A model-free, spatial-independent component analysis isolated multiple task-related components, one of which included visual cortex, as well as a cluster within ventromedial prefrontal cortex (vmPFC), consistent with the engagement of both top-down and bottom-up processes. Analyses of psychophysiological interactions showed increased functional connectivity between vmPFC and object-sensitive lateral occipital cortex (LOC), and results from dynamic causal modeling and Bayesian Model Selection suggested bidirectional connections between vmPFC and LOC that were positively modulated by the task. Using image-guided diffusion-tensor imaging, functionally seeded, probabilistic white-matter tracts between vmPFC and LOC, which presumably underlie this effective interconnectivity, were also observed. These connectivity findings extend previous models of visual search processes to include specific frontal–occipital neuronal interactions during a natural and complex search task. PMID:22708993

Role of 0D peripheral vasculature model in fluid-structure interaction modeling of aneurysms

NASA Astrophysics Data System (ADS)

Torii, Ryo; Oshima, Marie; Kobayashi, Toshio; Takagi, Kiyoshi; Tezduyar, Tayfun E.

2010-06-01

Patient-specific simulations based on medical images such as CT and MRI offer information on the hemodynamic and wall tissue stress in patient-specific aneurysm configurations. These are considered important in predicting the rupture risk for individual aneurysms but are not possible to measure directly. In this paper, fluid-structure interaction (FSI) analyses of a cerebral aneurysm at the middle cerebral artery (MCA) bifurcation are presented. A 0D structural recursive tree model of the peripheral vasculature is incorporated and its impedance is coupled with the 3D FSI model to compute the outflow through the two branches accurately. The results are compared with FSI simulation with prescribed pressure variation at the outlets. The comparison shows that the pressure at the two outlets are nearly identical even with the peripheral vasculature model and the flow division to the two branches is nearly the same as what we see in the simulation without the peripheral vasculature model. This suggests that the role of the peripheral vasculature in FSI modeling of the MCA aneurysm is not significant.

A three-dimensional virtual environment for modeling mechanical cardiopulmonary interactions.

PubMed

Kaye, J M; Primiano, F P; Metaxas, D N

1998-06-01

We have developed a real-time computer system for modeling mechanical physiological behavior in an interactive, 3-D virtual environment. Such an environment can be used to facilitate exploration of cardiopulmonary physiology, particularly in situations that are difficult to reproduce clinically. We integrate 3-D deformable body dynamics with new, formal models of (scalar) cardiorespiratory physiology, associating the scalar physiological variables and parameters with the corresponding 3-D anatomy. Our framework enables us to drive a high-dimensional system (the 3-D anatomical models) from one with fewer parameters (the scalar physiological models) because of the nature of the domain and our intended application. Our approach is amenable to modeling patient-specific circumstances in two ways. First, using CT scan data, we apply semi-automatic methods for extracting and reconstructing the anatomy to use in our simulations. Second, our scalar physiological models are defined in terms of clinically measurable, patient-specific parameters. This paper describes our approach, problems we have encountered and a sample of results showing normal breathing and acute effects of pneumothoraces.

A theoretical model for the Gla-TSR-EGF-1 region of the anticoagulant cofactor protein S: From biostructural pathology to specie

NASA Astrophysics Data System (ADS)

Villoutreix, Bruno O.; Teleman, Olle; Dahlbäck, Björn

1997-05-01

Protein S (PS), which functions as a species-specific anticoagulant cofactor to activated protein C (APC), is a mosaic protein that interacts with the phospholipid membrane via its γ-carboxyglutamate-rich (Gla) module. This module is followed by the thrombin-sensitive region (TSR), sensitive to thrombin cleavage, four epidermal growth factor (EGF)-like modules and a last region referred to as the sex hormone binding globulin (SHBG) domain. Of these, the TSR and the first EGF-like regions have been shown to be important for the species-specific interaction with APC. Difficulties in crystallising PS have so far hindered its study at the atomic level. Here, we report theoretical models for the Gla and EGF-1 modules of human PS constructed using prothrombin and factor X experimental structures. The TSR was built interactively. Analysis of the model linked with the large body of biochemical literature on PS and related proteins leads to suggestions that (i) the TSR stabilises the calcium-loaded Gla module through hydrophobic and ionic interactions and its conformation depends on the presence of the Gla module; (ii) the TSR does not form a calcium binding site but is protected from thrombin cleavage in the calcium-loaded form owing to short secondary structure elements and close contact with the Gla module; (iii) the PS missense mutations in this region are consistent with the structural data, except in one case which needs further investigation; and (iv) the two PS `faces' involving regions of residues Arg49-Gln52-Lys97 (TSR-EGF-1) and Thr103-Pro106 (EGF-1) may be involved in species-specific interactions with APC as they are richer in nonconservative substitution when comparing human and bovine protein S. This preliminary model helps to plan future experiments and the resulting data will be used to further validate and optimise the present structure.

SU-F-BRF-01: A GPU Framework for Developing Interactive High-Resolution Patient-Specific Biomechanical Models

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

Neylon, J; Qi, S; Sheng, K

2014-06-15

Purpose: To develop a GPU-based framework that can generate highresolution and patient-specific biomechanical models from a given simulation CT and contoured structures, optimized to run at interactive speeds, for addressing adaptive radiotherapy objectives. Method: A Massspring-damping (MSD) model was generated from a given simulation CT. The model's mass elements were generated for every voxel of anatomy, and positioned in a deformation space in the GPU memory. MSD connections were established between neighboring mass elements in a dense distribution. Contoured internal structures allowed control over elastic material properties of different tissues. Once the model was initialized in GPU memory, skeletal anatomymore » was actuated using rigid-body transformations, while soft tissues were governed by elastic corrective forces and constraints, which included tensile forces, shear forces, and spring damping forces. The model was validated by applying a known load to a soft tissue block and comparing the observed deformation to ground truth calculations from established elastic mechanics. Results: Our analyses showed that both local and global load experiments yielded results with a correlation coefficient R{sup 2} > 0.98 compared to ground truth. Models were generated for several anatomical regions. Head and neck models accurately simulated posture changes by rotating the skeletal anatomy in three dimensions. Pelvic models were developed for realistic deformations for changes in bladder volume. Thoracic models demonstrated breast deformation due to gravity when changing treatment position from supine to prone. The GPU framework performed at greater than 30 iterations per second for over 1 million mass elements with up to 26 MSD connections each. Conclusions: Realistic simulations of site-specific, complex posture and physiological changes were simulated at interactive speeds using patient data. Incorporating such a model with live patient tracking would facilitate real time assessment of variations of the actual anatomy and delivered dose for adaptive intervention and re-planning.« less

Declarative language design for interactive visualization.

PubMed

Heer, Jeffrey; Bostock, Michael

2010-01-01

We investigate the design of declarative, domain-specific languages for constructing interactive visualizations. By separating specification from execution, declarative languages can simplify development, enable unobtrusive optimization, and support retargeting across platforms. We describe the design of the Protovis specification language and its implementation within an object-oriented, statically-typed programming language (Java). We demonstrate how to support rich visualizations without requiring a toolkit-specific data model and extend Protovis to enable declarative specification of animated transitions. To support cross-platform deployment, we introduce rendering and event-handling infrastructures decoupled from the runtime platform, letting designers retarget visualization specifications (e.g., from desktop to mobile phone) with reduced effort. We also explore optimizations such as runtime compilation of visualization specifications, parallelized execution, and hardware-accelerated rendering. We present benchmark studies measuring the performance gains provided by these optimizations and compare performance to existing Java-based visualization tools, demonstrating scalability improvements exceeding an order of magnitude.

Family nonuniversal Z' models with protected flavor-changing interactions

NASA Astrophysics Data System (ADS)

Celis, Alejandro; Fuentes-Martín, Javier; Jung, Martin; Serôdio, Hugo

2015-07-01

We define a new class of Z' models with neutral flavor-changing interactions at tree level in the down-quark sector. They are related in an exact way to elements of the quark mixing matrix due to an underlying flavored U(1)' gauge symmetry, rendering these models particularly predictive. The same symmetry implies lepton-flavor nonuniversal couplings, fully determined by the gauge structure of the model. Our models allow us to address presently observed deviations from the standard model and specific correlations among the new physics contributions to the Wilson coefficients C9,10' ℓ can be tested in b →s ℓ+ℓ- transitions. We furthermore predict lepton-universality violations in Z' decays, testable at the LHC.

Interactions between human osteoblasts and prostate cancer cells in a novel 3D in vitro model

PubMed Central

Sieh, Shirly; Lubik, Amy A; Clements, Judith A; Nelson, Colleen C

2010-01-01

Cell-cell and cell-matrix interactions play a major role in tumor morphogenesis and cancer metastasis. Therefore, it is crucial to create a model with a biomimetic microenvironment that allows such interactions to fully represent the pathophysiology of a disease for an in vitro study. This is achievable by using three-dimensional (3D) models instead of conventional two-dimensional (2D) cultures with the aid of tissue engineering technology. We are now able to better address the complex intercellular interactions underlying prostate cancer (CaP) bone metastasis through such models. In this study, we assessed the interaction of CaP cells and human osteoblasts (hOBs) within a tissue engineered bone (TEB) construct. Consistent with other in vivo studies, our findings show that intercellular and CaP cell-bone matrix interactions lead to elevated levels of matrix metalloproteinases, steroidogenic enzymes and the CaP biomarker, prostate specific antigen (PSA); all associated with CaP metastasis. Hence, it highlights the physiological relevance of this model. We believe that this model will provide new insights for understanding of the previously poorly understood molecular mechanisms of bone metastasis, which will foster further translational studies, and ultimately offer a potential tool for drug screening. PMID:21197221

The Interaction of Functional and Dysfunctional Emotions during Balance Beam Performance

ERIC Educational Resources Information Center

Cottyn, Jorge; De Clercq, Dirk; Crombez, Geert; Lenoir, Matthieu

2012-01-01

The interaction between functional and dysfunctional emotions, as one of the major tenets of the Individual Zones of Optimal Functioning (IZOF) model (Hanin, 2000), was studied in a sport specific setting. Fourteen female gymnasts performed three attempts of a compulsory balance beam routine at three different heights. Heart rate and self-report…

Students' Self-Regulation for Interaction with Others in Online Learning Environments

ERIC Educational Resources Information Center

Cho, Moon-Heum; Kim, B. Joon

2013-01-01

The purpose of this study was to explore variables explaining students' self-regulation (SR) for interaction with others, specifically peers and instructors, in online learning environments. A total of 407 students participated in the study. With hierarchical regression model (HRM), several variables were regressed on students' SR for interaction…

Stochastic analog neutron transport with TRIPOLI-4 and FREYA: Bayesian uncertainty quantification for neutron multiplicity counting

DOE PAGES

Verbeke, J. M.; Petit, O.

2016-06-01

From nuclear safeguards to homeland security applications, the need for the better modeling of nuclear interactions has grown over the past decades. Current Monte Carlo radiation transport codes compute average quantities with great accuracy and performance; however, performance and averaging come at the price of limited interaction-by-interaction modeling. These codes often lack the capability of modeling interactions exactly: for a given collision, energy is not conserved, energies of emitted particles are uncorrelated, and multiplicities of prompt fission neutrons and photons are uncorrelated. Many modern applications require more exclusive quantities than averages, such as the fluctuations in certain observables (e.g., themore » neutron multiplicity) and correlations between neutrons and photons. In an effort to meet this need, the radiation transport Monte Carlo code TRIPOLI-4® was modified to provide a specific mode that models nuclear interactions in a full analog way, replicating as much as possible the underlying physical process. Furthermore, the computational model FREYA (Fission Reaction Event Yield Algorithm) was coupled with TRIPOLI-4 to model complete fission events. As a result, FREYA automatically includes fluctuations as well as correlations resulting from conservation of energy and momentum.« less

Three-dimensional reconstructions come to life--interactive 3D PDF animations in functional morphology.

PubMed

van de Kamp, Thomas; dos Santos Rolo, Tomy; Vagovič, Patrik; Baumbach, Tilo; Riedel, Alexander

2014-01-01

Digital surface mesh models based on segmented datasets have become an integral part of studies on animal anatomy and functional morphology; usually, they are published as static images, movies or as interactive PDF files. We demonstrate the use of animated 3D models embedded in PDF documents, which combine the advantages of both movie and interactivity, based on the example of preserved Trigonopterus weevils. The method is particularly suitable to simulate joints with largely deterministic movements due to precise form closure. We illustrate the function of an individual screw-and-nut type hip joint and proceed to the complex movements of the entire insect attaining a defence position. This posture is achieved by a specific cascade of movements: Head and legs interlock mutually and with specific features of thorax and the first abdominal ventrite, presumably to increase the mechanical stability of the beetle and to maintain the defence position with minimal muscle activity. The deterministic interaction of accurately fitting body parts follows a defined sequence, which resembles a piece of engineering.

Three-Dimensional Reconstructions Come to Life – Interactive 3D PDF Animations in Functional Morphology

PubMed Central

van de Kamp, Thomas; dos Santos Rolo, Tomy; Vagovič, Patrik; Baumbach, Tilo; Riedel, Alexander

2014-01-01

Digital surface mesh models based on segmented datasets have become an integral part of studies on animal anatomy and functional morphology; usually, they are published as static images, movies or as interactive PDF files. We demonstrate the use of animated 3D models embedded in PDF documents, which combine the advantages of both movie and interactivity, based on the example of preserved Trigonopterus weevils. The method is particularly suitable to simulate joints with largely deterministic movements due to precise form closure. We illustrate the function of an individual screw-and-nut type hip joint and proceed to the complex movements of the entire insect attaining a defence position. This posture is achieved by a specific cascade of movements: Head and legs interlock mutually and with specific features of thorax and the first abdominal ventrite, presumably to increase the mechanical stability of the beetle and to maintain the defence position with minimal muscle activity. The deterministic interaction of accurately fitting body parts follows a defined sequence, which resembles a piece of engineering. PMID:25029366

Protein–Mineral Interactions: Molecular Dynamics Simulations Capture Importance of Variations in Mineral Surface Composition and Structure

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

Andersen, Amity; Reardon, Patrick N.; Chacon, Stephany S.

Molecular dynamics simulations, conventional and metadynamics, were performed to determine the interaction of model protein Gb1 over kaolinite (001), Na+-montmorillonite (001), Ca2+-montmorillonite (001), goethite (100), and Na+-birnessite (001) mineral surfaces. Gb1, a small (56 residue) protein with a well-characterized solution-state nuclear magnetic resonance (NMR) structure and having α-helix, four-fold β-sheet, and hydrophobic core features, is used as a model protein to study protein soil mineral interactions and gain insights on structural changes and potential degradation of protein. From our simulations, we observe little change to the hydrated Gb1 structure over the kaolinite, montmorillonite, and goethite surfaces relative to its solvatedmore » structure without these mineral surfaces present. Over the Na+-birnessite basal surface, however, the Gb1 structure is highly disturbed as a result of interaction with this birnessite surface. Unraveling of the Gb1 β-sheet at specific turns and a partial unraveling of the α-helix is observed over birnessite, which suggests specific vulnerable residue sites for oxidation or hydrolysis possibly leading to fragmentation.« less

A history of studies that examine the interactions of Toxoplasma with its host cell: Emphasis on in vitro models.

PubMed

Boyle, Jon P; Radke, Jay R

2009-07-01

This review is a historical look at work carried out over the past 50 years examining interactions of Toxoplasma with the host cell and attempts to focus on some of the seminal experiments in the field. This early work formed the foundation for more recent studies aimed at identifying the host and parasite factors mediating key Toxoplasma-host cell interactions. We focus especially on those studies that were performed in vitro and provide discussions of the following general areas: (i) establishment of the parasitophorous vacuole, (ii) the requirement of specific host cell molecules for parasite replication, (iii) the scenarios under which the host cell can resist parasite replication and/or persistence, (iv) host species-specific and host strain-specific responses to Toxoplasma infection, and (v) Toxoplasma-induced immune modulation.

Interactions Between Convective Storms and Their Environment

NASA Technical Reports Server (NTRS)

Maddox, R. A.; Hoxit, L. R.; Chappell, C. F.

1979-01-01

The ways in which intense convective storms interact with their environment are considered for a number of specific severe storm situations. A physical model of subcloud wind fields and vertical wind profiles was developed to explain the often observed intensification of convective storms that move along or across thermal boundaries. A number of special, unusually dense, data sets were used to substantiate features of the model. GOES imagery was used in conjunction with objectively analyzed surface wind data to develop a nowcast technique that might be used to identify specific storm cells likely to become tornadic. It was shown that circulations associated with organized meso-alpha and meso-beta scale storm complexes may, on occasion, strongly modify tropospheric thermodynamic patterns and flow fields.

Predicting rates of interspecific interaction from phylogenetic trees.

PubMed

Nuismer, Scott L; Harmon, Luke J

2015-01-01

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction. © 2014 John Wiley & Sons Ltd/CNRS.

CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription.

PubMed

Tang, Zhonghui; Luo, Oscar Junhong; Li, Xingwang; Zheng, Meizhen; Zhu, Jacqueline Jufen; Szalaj, Przemyslaw; Trzaskoma, Pawel; Magalska, Adriana; Wlodarczyk, Jakub; Ruszczycki, Blazej; Michalski, Paul; Piecuch, Emaly; Wang, Ping; Wang, Danjuan; Tian, Simon Zhongyuan; Penrad-Mobayed, May; Sachs, Laurent M; Ruan, Xiaoan; Wei, Chia-Lin; Liu, Edison T; Wilczynski, Grzegorz M; Plewczynski, Dariusz; Li, Guoliang; Ruan, Yijun

2015-12-17

Spatial genome organization and its effect on transcription remains a fundamental question. We applied an advanced chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) strategy to comprehensively map higher-order chromosome folding and specific chromatin interactions mediated by CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) with haplotype specificity and nucleotide resolution in different human cell lineages. We find that CTCF/cohesin-mediated interaction anchors serve as structural foci for spatial organization of constitutive genes concordant with CTCF-motif orientation, whereas RNAPII interacts within these structures by selectively drawing cell-type-specific genes toward CTCF foci for coordinated transcription. Furthermore, we show that haplotype variants and allelic interactions have differential effects on chromosome configuration, influencing gene expression, and may provide mechanistic insights into functions associated with disease susceptibility. 3D genome simulation suggests a model of chromatin folding around chromosomal axes, where CTCF is involved in defining the interface between condensed and open compartments for structural regulation. Our 3D genome strategy thus provides unique insights in the topological mechanism of human variations and diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Retroviral Gag protein-RNA interactions: Implications for specific genomic RNA packaging and virion assembly.

PubMed

Olson, Erik D; Musier-Forsyth, Karin

2018-03-31

Retroviral Gag proteins are responsible for coordinating many aspects of virion assembly. Gag possesses two distinct nucleic acid binding domains, matrix (MA) and nucleocapsid (NC). One of the critical functions of Gag is to specifically recognize, bind, and package the retroviral genomic RNA (gRNA) into assembling virions. Gag interactions with cellular RNAs have also been shown to regulate aspects of assembly. Recent results have shed light on the role of MA and NC domain interactions with nucleic acids, and how they jointly function to ensure packaging of the retroviral gRNA. Here, we will review the literature regarding RNA interactions with NC, MA, as well as overall mechanisms employed by Gag to interact with RNA. The discussion focuses on human immunodeficiency virus type-1, but other retroviruses will also be discussed. A model is presented combining all of the available data summarizing the various factors and layers of selection Gag employs to ensure specific gRNA packaging and correct virion assembly. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

Symmetric Anderson impurity model: Magnetic susceptibility, specific heat and Wilson ratio

NASA Astrophysics Data System (ADS)

Zalom, Peter; Pokorný, Vladislav; Janiš, Václav

2018-05-01

We extend the spin-polarized effective-interaction approximation of the parquet renormalization scheme from Refs. [1,2] applied on the symmetric Anderson model by adding the low-temperature asymptotics of the total energy and the specific heat. We calculate numerically the Wilson ratio and determine analytically its asymptotic value in the strong-coupling limit. We demonstrate in this way that the exponentially small Kondo scale from the strong-coupling regime emerges in qualitatively the same way in the spectral function, magnetic susceptibility and the specific heat.

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

Pyruvate formate-lyase interacts directly with the formate channel FocA to regulate formate translocation.

PubMed

Doberenz, Claudia; Zorn, Michael; Falke, Dörte; Nannemann, David; Hunger, Doreen; Beyer, Lydia; Ihling, Christian H; Meiler, Jens; Sinz, Andrea; Sawers, R Gary

2014-07-29

The FNT (formate-nitrite transporters) form a superfamily of pentameric membrane channels that translocate monovalent anions across biological membranes. FocA (formate channel A) translocates formate bidirectionally but the mechanism underlying how translocation of formate is controlled and what governs substrate specificity remains unclear. Here we demonstrate that the normally soluble dimeric enzyme pyruvate formate-lyase (PflB), which is responsible for intracellular formate generation in enterobacteria and other microbes, interacts specifically with FocA. Association of PflB with the cytoplasmic membrane was shown to be FocA dependent and purified, Strep-tagged FocA specifically retrieved PflB from Escherichia coli crude extracts. Using a bacterial two-hybrid system, it could be shown that the N-terminus of FocA and the central domain of PflB were involved in the interaction. This finding was confirmed by chemical cross-linking experiments. Using constraints imposed by the amino acid residues identified in the cross-linking study, we provide for the first time a model for the FocA-PflB complex. The model suggests that the N-terminus of FocA is important for interaction with PflB. An in vivo assay developed to monitor changes in formate levels in the cytoplasm revealed the importance of the interaction with PflB for optimal translocation of formate by FocA. This system represents a paradigm for the control of activity of FNT channel proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

An enhanced Oct-tree data structure and operations for solid modeling

NASA Technical Reports Server (NTRS)

Fujimura, K.; Toriya, H.; Yamaguchi, K.; Kunii, T. L.

1984-01-01

Oct-trees are enhanced to increase the processing efficiency of geometric operations for interactive CAD use. Further enhancement is made to combine them with surface models for more precise boundary specification as needed by tool path generation in CAM applications.

Water's Interfacial Hydrogen Bonding Structure Reveals the Effective Strength of Surface-Water Interactions.

PubMed

Shin, Sucheol; Willard, Adam P

2018-06-05

We combine all-atom molecular dynamics simulations with a mean field model of interfacial hydrogen bonding to analyze the effect of surface-water interactions on the structural and energetic properties of the liquid water interface. We show that the molecular structure of water at a weakly interacting ( i.e., hydrophobic) surface is resistant to change unless the strength of surface-water interactions are above a certain threshold. We find that below this threshold water's interfacial structure is homogeneous and insensitive to the details of the disordered surface, however, above this threshold water's interfacial structure is heterogeneous. Despite this heterogeneity, we demonstrate that the equilibrium distribution of molecular orientations can be used to quantify the energetic component of the surface-water interactions that contribute specifically to modifying the interfacial hydrogen bonding network. We identify this specific energetic component as a new measure of hydrophilicity, which we refer to as the intrinsic hydropathy.

A Framework for the Specification of the Semantics and the Dynamics of Instructional Applications

ERIC Educational Resources Information Center

Buendia-Garcia, Felix; Diaz, Paloma

2003-01-01

An instructional application consists of a set of resources and activities to implement interacting, interrelated, and structured experiences oriented towards achieving specific educational objectives. The development of computer-based instructional applications has to follow a well defined process, so models for computer-based instructional…

A model-based approach to monitor complex road-vehicle interactions through first principles

NASA Astrophysics Data System (ADS)

Chakravarty, T.; Srinivasarengan, K.; Roy, S.; Bilal, S.; Balamuralidhar, P.

2013-02-01

The increasing availability of portable computing devices and their interaction with physical systems ask for designing compact models and simulations to understand and characterize such interactions. For instance, monitoring a road's grade using accelerometer stationed inside a moving ground vehicle is an emerging trend in city administration. Typically the focus has largely been to develop algorithms to articulate meaning from that. But, the experimentation cannot provide with an exhaustive analysis of all scenarios and the characteristics of them. We propose an approach of modeling these interactions of physical systems with gadgets through first principles, in a compact manner to focus on limited number of interactions. We derive an approach to model the vehicle interaction with a pothole on a road, a specific case, but allowing for selectable car parameters like natural damped frequency, tire size etc, thus generalizing it. Different road profiles are also created to represent rough road with sharp irregularities. These act as excitation to the moving vehicle and the interaction is computed to determine the vertical/ lateral vibration of the system i.e vehicle with sensors using joint time-frequency signal analysis methods. The simulation is compared with experimental data for validation. We show some directions as to how simulation of such models can reveal different characteristics of the interaction through analysis of their frequency spectrum. It is envisioned that the proposed models will get enriched further as and when large data set of real life data is captured and appropriate sensitivity analysis is done.

Background | Office of Cancer Clinical Proteomics Research

Cancer.gov

The term "proteomics" refers to a large-scale comprehensive study of a specific proteome resulting from its genome, including abundances of proteins, their variations and modifications, and interacting partners and networks in order to understand cellular processes involved.  Similarly, “Cancer proteomics” refers to comprehensive analyses of proteins and their derivatives translated from a specific cancer genome using a human biospecimen or a preclinical model (e.g., cultured cell or animal model).

Using an agent-based model to analyze the dynamic communication network of the immune response

PubMed Central

2011-01-01

Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win) versus persistent infection (loss), due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the loss outcomes. Conclusions An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies. PMID:21247471

Disentangling the Role of Domain-Specific Knowledge in Student Modeling

NASA Astrophysics Data System (ADS)

Ruppert, John; Duncan, Ravit Golan; Chinn, Clark A.

2017-08-01

This study explores the role of domain-specific knowledge in students' modeling practice and how this knowledge interacts with two domain-general modeling strategies: use of evidence and developing a causal mechanism. We analyzed models made by middle school students who had a year of intensive model-based instruction. These models were made to explain a familiar but unstudied biological phenomenon: late onset muscle pain. Students were provided with three pieces of evidence related to this phenomenon and asked to construct a model to account for this evidence. Findings indicate that domain-specific resources play a significant role in the extent to which the models accounted for provided evidence. On the other hand, familiarity with the situation appeared to contribute to the mechanistic character of models. Our results indicate that modeling strategies alone are insufficient for the development of a mechanistic model that accounts for provided evidence and that, while learners can develop a tentative model with a basic familiarity of the situation, scaffolding certain domain-specific knowledge is necessary to assist students with incorporating evidence in modeling tasks.

Protein modeling and molecular dynamics simulation of the two novel surfactant proteins SP-G and SP-H.

PubMed

Rausch, Felix; Schicht, Martin; Bräuer, Lars; Paulsen, Friedrich; Brandt, Wolfgang

2014-11-01

Surfactant proteins are well known from the human lung where they are responsible for the stability and flexibility of the pulmonary surfactant system. They are able to influence the surface tension of the gas-liquid interface specifically by directly interacting with single lipids. This work describes the generation of reliable protein structure models to support the experimental characterization of two novel putative surfactant proteins called SP-G and SP-H. The obtained protein models were complemented by predicted posttranslational modifications and placed in a lipid model system mimicking the pulmonary surface. Molecular dynamics simulations of these protein-lipid systems showed the stability of the protein models and the formation of interactions between protein surface and lipid head groups on an atomic scale. Thereby, interaction interface and strength seem to be dependent on orientation and posttranslational modification of the protein. The here presented modeling was fundamental for experimental localization studies and the simulations showed that SP-G and SP-H are theoretically able to interact with lipid systems and thus are members of the surfactant protein family.

A mathematical model of the effect of a predator on species diversity

NASA Technical Reports Server (NTRS)

Weston, C. R.; Yang, J. N.

1970-01-01

Mathematical model determines reaction between new predator and microbe competitor when the competitor is the predator's sole nutrient resource. The model utilizes differential equations to describe the interactions with the specific growth rates, and analyzes these growth rates as they are affected by population density and nutrient concentration.

Electrostatic correlations at the Stern layer: Physics or chemistry?

NASA Astrophysics Data System (ADS)

Travesset, A.; Vangaveti, S.

2009-11-01

We introduce a minimal free energy describing the interaction of charged groups and counterions including both classical electrostatic and specific interactions. The predictions of the model are compared against the standard model for describing ions next to charged interfaces, consisting of Poisson-Boltzmann theory with additional constants describing ion binding, which are specific to the counterion and the interfacial charge ("chemical binding"). It is shown that the "chemical" model can be appropriately described by an underlying "physical" model over several decades in concentration, but the extracted binding constants are not uniquely defined, as they differ depending on the particular observable quantity being studied. It is also shown that electrostatic correlations for divalent (or higher valence) ions enhance the surface charge by increasing deprotonation, an effect not properly accounted within chemical models. The charged phospholipid phosphatidylserine is analyzed as a concrete example with good agreement with experimental results. We conclude with a detailed discussion on the limitations of chemical or physical models for describing the rich phenomenology of charged interfaces in aqueous media and its relevance to different systems with a particular emphasis on phospholipids.

A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package.

PubMed

Lan, Hongzhi; Updegrove, Adam; Wilson, Nathan M; Maher, Gabriel D; Shadden, Shawn C; Marsden, Alison L

2018-02-01

Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid-structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.

Spectroscopic studies of interactions between dyes and model molecules of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Elhaddaoui, A.; Delacourte, A.; Turrell, S.

1993-06-01

Raman, FTIR, fluorescence, and UV-visible spectra are used to study interactions between amuloid-labelling dyes and poly-L-lysine and bovine insulin, two proteins which play the role of models of (beta) amyloid of Alzheimers disease. It is found that though the (beta) conformation of the peptide is not essential, it helps to encourage binding which appears to be stable and specific in nature, involving SO3- groups of the dyes and NH2 groups of the proteins.

Two-component Gaussian core model: Strong-coupling limit, Bjerrum pairs, and gas-liquid phase transition.

PubMed

Frydel, Derek; Levin, Yan

2018-01-14

In the present work, we investigate a gas-liquid transition in a two-component Gaussian core model, where particles of the same species repel and those of different species attract. Unlike a similar transition in a one-component system with particles having attractive interactions at long separations and repulsive interactions at short separations, a transition in the two-component system is not driven solely by interactions but by a specific feature of the interactions, the correlations. This leads to extremely low critical temperature, as correlations are dominant in the strong-coupling limit. By carrying out various approximations based on standard liquid-state methods, we show that a gas-liquid transition of the two-component system poses a challenging theoretical problem.

Two-component Gaussian core model: Strong-coupling limit, Bjerrum pairs, and gas-liquid phase transition

NASA Astrophysics Data System (ADS)

Frydel, Derek; Levin, Yan

2018-01-01

In the present work, we investigate a gas-liquid transition in a two-component Gaussian core model, where particles of the same species repel and those of different species attract. Unlike a similar transition in a one-component system with particles having attractive interactions at long separations and repulsive interactions at short separations, a transition in the two-component system is not driven solely by interactions but by a specific feature of the interactions, the correlations. This leads to extremely low critical temperature, as correlations are dominant in the strong-coupling limit. By carrying out various approximations based on standard liquid-state methods, we show that a gas-liquid transition of the two-component system poses a challenging theoretical problem.

Fighting detection using interaction energy force

NASA Astrophysics Data System (ADS)

Wateosot, Chonthisa; Suvonvorn, Nikom

2017-02-01

Fighting detection is an important issue in security aimed to prevent criminal or undesirable events in public places. Many researches on computer vision techniques have studied to detect the specific event in crowded scenes. In this paper we focus on fighting detection using social-based Interaction Energy Force (IEF). The method uses low level features without object extraction and tracking. The interaction force is modeled using the magnitude and direction of optical flows. A fighting factor is developed under this model to detect fighting events using thresholding method. An energy map of interaction force is also presented to identify the corresponding events. The evaluation is performed using NUSHGA and BEHAVE datasets. The results show the efficiency with high accuracy regardless of various conditions.

A time domain frequency-selective multivariate Granger causality approach.

PubMed

Leistritz, Lutz; Witte, Herbert

2016-08-01

The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

A Generalized Form of Context-Dependent Psychophysiological Interactions (gPPI): A Comparison to Standard Approaches

PubMed Central

McLaren, Donald G.; Ries, Michele L.; Xu, Guofan; Johnson, Sterling C.

2012-01-01

Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike Information Criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings. PMID:22484411

Integrating place-specific livelihood and equity outcomes into global assessments of bioenergy deployment

NASA Astrophysics Data System (ADS)

Creutzig, Felix; Corbera, Esteve; Bolwig, Simon; Hunsberger, Carol

2013-09-01

Integrated assessment models suggest that the large-scale deployment of bioenergy could contribute to ambitious climate change mitigation efforts. However, such a shift would intensify the global competition for land, with possible consequences for 1.5 billion smallholder livelihoods that these models do not consider. Maintaining and enhancing robust livelihoods upon bioenergy deployment is an equally important sustainability goal that warrants greater attention. The social implications of biofuel production are complex, varied and place-specific, difficult to model, operationalize and quantify. However, a rapidly developing body of social science literature is advancing the understanding of these interactions. In this letter we link human geography research on the interaction between biofuel crops and livelihoods in developing countries to integrated assessments on biofuels. We review case-study research focused on first-generation biofuel crops to demonstrate that food, income, land and other assets such as health are key livelihood dimensions that can be impacted by such crops and we highlight how place-specific and global dynamics influence both aggregate and distributional outcomes across these livelihood dimensions. We argue that place-specific production models and land tenure regimes mediate livelihood outcomes, which are also in turn affected by global and regional markets and their resulting equilibrium dynamics. The place-specific perspective suggests that distributional consequences are a crucial complement to aggregate outcomes; this has not been given enough weight in comprehensive assessments to date. By narrowing the gap between place-specific case studies and global models, our discussion offers a route towards integrating livelihood and equity considerations into scenarios of future bioenergy deployment, thus contributing to a key challenge in sustainability sciences.

Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.

PubMed

Lin, Xiaotong; Liu, Mei; Chen, Xue-wen

2009-04-29

Protein-protein interactions play vital roles in nearly all cellular processes and are involved in the construction of biological pathways such as metabolic and signal transduction pathways. Although large-scale experiments have enabled the discovery of thousands of previously unknown linkages among proteins in many organisms, the high-throughput interaction data is often associated with high error rates. Since protein interaction networks have been utilized in numerous biological inferences, the inclusive experimental errors inevitably affect the quality of such prediction. Thus, it is essential to assess the quality of the protein interaction data. In this paper, a novel Bayesian network-based integrative framework is proposed to assess the reliability of protein-protein interactions. We develop a cross-species in silico model that assigns likelihood scores to individual protein pairs based on the information entirely extracted from model organisms. Our proposed approach integrates multiple microarray datasets and novel features derived from gene ontology. Furthermore, the confidence scores for cross-species protein mappings are explicitly incorporated into our model. Applying our model to predict protein interactions in the human genome, we are able to achieve 80% in sensitivity and 70% in specificity. Finally, we assess the overall quality of the experimentally determined yeast protein-protein interaction dataset. We observe that the more high-throughput experiments confirming an interaction, the higher the likelihood score, which confirms the effectiveness of our approach. This study demonstrates that model organisms certainly provide important information for protein-protein interaction inference and assessment. The proposed method is able to assess not only the overall quality of an interaction dataset, but also the quality of individual protein-protein interactions. We expect the method to continually improve as more high quality interaction data from more model organisms becomes available and is readily scalable to a genome-wide application.

Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

PubMed Central

Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

2011-01-01

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots. PMID:21980274

Smart swarms of bacteria-inspired agents with performance adaptable interactions.

PubMed

Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

2011-09-01

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

Molecular interaction networks in the analyses of sequence variation and proteomics data.

PubMed

Stelzl, Ulrich

2013-12-01

Protein-protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cation specific binding with protein surface charges

PubMed Central

Hess, Berk; van der Vegt, Nico F. A.

2009-01-01

Biological organization depends on a sensitive balance of noncovalent interactions, in particular also those involving interactions between ions. Ion-pairing is qualitatively described by the law of “matching water affinities.” This law predicts that cations and anions (with equal valence) form stable contact ion pairs if their sizes match. We show that this simple physical model fails to describe the interaction of cations with (molecular) anions of weak carboxylic acids, which are present on the surfaces of many intra- and extracellular proteins. We performed molecular simulations with quantitatively accurate models and observed that the order K+ < Na+ < Li+ of increasing binding affinity with carboxylate ions is caused by a stronger preference for forming weak solvent-shared ion pairs. The relative insignificance of contact pair interactions with protein surfaces indicates that thermodynamic stability and interactions between proteins in alkali salt solutions is governed by interactions mediated through hydration water molecules. PMID:19666545

More than a meal: integrating non-feeding interactions into food webs

USGS Publications Warehouse

Kéfi, Sonia; Berlow, Eric L.; Wieters, Evie A.; Navarrete, Sergio A.; Petchey, Owen L.; Wood, Spencer A.; Boit, Alice; Joppa, Lucas N.; Lafferty, Kevin D.; Williams, Richard J.; Martinez, Neo D.; Menge, Bruce A.; Blanchette, Carol A.; Iles, Alison C.; Brose, Ulrich

2012-01-01

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Romantic Relationship Satisfaction and Ambulatory Blood Pressure During Social Interactions: Specificity or Spillover Effects?

PubMed

Cornelius, Talea; Birk, Jeffrey L; Edmondson, Donald; Schwartz, Joseph E

2018-05-08

People in high-quality romantic relationships tend to have lower blood pressure (BP). People may experience lower BP specifically when interacting with romantic partners. This study parsed the effects of different types of social interactions on ambulatory BP (ABP) and tested whether romantic relationship satisfaction moderated these effects during interactions with partners in particular (specificity) or with others (spillover; e.g., friends, co-workers). Partnered participants (N = 594) were drawn from a larger study on BP and cardiovascular health (age = 46.5 ± 9.3; 57.4% female). Participants reported on romantic relationship satisfaction and completed 24-hr ABP monitoring. At each reading, participants reported whether they had a social interaction and with whom. Multilevel models accounted for nesting of data over time. Romantic relationship satisfaction significantly modified the effects of some social interactions on systolic and diastolic BP (SBP, DBP). Participants with high (+1 SD) relationship satisfaction had significantly lower SBP (-0.77 mmHg, p = .02) during partner interactions compared with no social interaction; low-satisfaction (-1 SD) participants had a nonsignificant 0.59 mmHg increase (p = .14). A similar pattern emerged for DBP. Relationship satisfaction also modified SBP response during friend interactions (elevated SBP for low-satisfaction participants) and DBP response during "other" interactions (elevated DBP for high-satisfaction participants). Participants with high levels of romantic relationship satisfaction experienced significantly lower BP during social interactions with their partner compared with situations without social interaction. Although there was some evidence for spillover to other types of relationships, effects were largely restricted to partner interactions.

Recent progress in tidal modeling

NASA Technical Reports Server (NTRS)

Vial, F.; Forbes, J. M.

1989-01-01

Recent contributions to tidal theory during the last five years are reviewed. Specific areas where recent progress has occurred include: the action of mean wind and dissipation on tides, interactions of other waves with tides, the use of TGCM in tidal studies. Furthermore, attention is put on the nonlinear interaction between semidiurnal and diurnal tides. Finally, more realistic thermal excitation and background wind and temperature models have been developed in the past few years. This has led to new month-to-month numerical simulations of the semidiurnal tide. Some results using these models are presented and compared with ATMAP tidal climatologies.

Radiative interactions in chemically reacting supersonic internal flows

NASA Technical Reports Server (NTRS)

Tiwari, S. N.; Chandrasekhar, R.

1991-01-01

The two-dimensional, elliptic Navier-Stokes equations are used to investigate supersonic flows with finite-rate chemistry and radiation for hydrogen-air systems. The chemistry source terms in the species equation is treated implicitly to alleviate the stiffness associated with fast reactions. The explicit, unsplit MacCormack finite-difference scheme is used to advance the governing equations in time, until convergence is achieved. The specific problem considered is the premixed flow in a channel with a ten-degree compression ramp. Three different chemistry models are used, accounting for increasing number of reactions and participating species. Two chemistry models assure nitrogen as inert, while the third model accounts for nitrogen reactions and NO(x) formation. The tangent slab approximation is used in the radiative flux formulation. A pseudo-gray model is used to represent the absorption-emission characteristics of the participating species. Results obtained for specific conditions indicate that the radiative interactions vary substantially, depending on reactions involving HO2 and NO species and that this can have a significant influence on the flowfield.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.

PubMed

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-11-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.

Phase relations in a forced turbulent boundary layer: implications for modelling of high Reynolds number wall turbulence

PubMed Central

2017-01-01

Phase relations between specific scales in a turbulent boundary layer are studied here by highlighting the associated nonlinear scale interactions in the flow. This is achieved through an experimental technique that allows for targeted forcing of the flow through the use of a dynamic wall perturbation. Two distinct large-scale modes with well-defined spatial and temporal wavenumbers were simultaneously forced in the boundary layer, and the resulting nonlinear response from their direct interactions was isolated from the turbulence signal for the study. This approach advances the traditional studies of large- and small-scale interactions in wall turbulence by focusing on the direct interactions between scales with triadic wavenumber consistency. The results are discussed in the context of modelling high Reynolds number wall turbulence. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’. PMID:28167576

Examining the mechanisms of overgeneral autobiographical memory: capture and rumination, and impaired executive control.

PubMed

Sumner, Jennifer A; Griffith, James W; Mineka, Susan

2011-02-01

Overgeneral autobiographical memory (OGM) is an important cognitive phenomenon in depression, but questions remain regarding the underlying mechanisms. The CaR-FA-X model (Williams et al., 2007) proposes three mechanisms that may contribute to OGM, but little work has examined the possible additive and/or interactive effects among them. We examined two mechanisms of CaR-FA-X: capture and rumination, and impaired executive control. We analysed data from undergraduates (N=109) scoring high or low on rumination who were presented with cues of high and low self-relevance on the Autobiographical Memory Test (AMT). Executive control was operationalised as performance on both the Stroop Colour-Word Task and the Controlled Oral Word Association Test (COWAT). Hierarchical generalised linear modelling was used to predict whether participants would generate a specific memory on a trial of the AMT. Higher COWAT scores, lower rumination, and greater cue self-relevance predicted a higher probability of a specific memory. There was also a rumination×cue self-relevance interaction: Higher (vs lower) rumination was associated with a lower probability of a specific memory primarily for low self-relevant cues. We found no evidence of interactions between these mechanisms. Findings are interpreted with respect to current autobiographical memory models. Future directions for OGM mechanism research are discussed. © 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

Tissue-Specific Chromatin Modifications at a Multigene Locus Generate Asymmetric Transcriptional Interactions

PubMed Central

Yoo, Eung Jae; Cajiao, Isabela; Kim, Jeong-Seon; Kimura, Atsushi P.; Zhang, Aiwen; Cooke, Nancy E.; Liebhaber, Stephen A.

2006-01-01

Random assortment within mammalian genomes juxtaposes genes with distinct expression profiles. This organization, along with the prevalence of long-range regulatory controls, generates a potential for aberrant transcriptional interactions. The human CD79b/GH locus contains six tightly linked genes with three mutually exclusive tissue specificities and interdigitated control elements. One consequence of this compact organization is that the pituitarycell-specific transcriptional events that activate hGH-N also trigger ectopic activation of CD79b. However, the B-cell-specific events that activate CD79b do not trigger reciprocal activation of hGH-N. Here we utilized DNase I hypersensitive site mapping, chromatin immunoprecipitation, and transgenic models to explore the basis for this asymmetric relationship. The results reveal tissue-specific patterns of chromatin structures and transcriptional controls at the CD79b/GH locus in B cells distinct from those in the pituitary gland and placenta. These three unique transcriptional environments suggest a set of corresponding gene expression pathways and transcriptional interactions that are likely to be found juxtaposed at multiple sites within the eukaryotic genome. PMID:16847312

Decorin Core Protein (Decoron) Shape Complements Collagen Fibril Surface Structure and Mediates Its Binding

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

Orgel, Joseph P.R.O.; Eid, Aya; Antipova, Olga

Decorin is the archetypal small leucine rich repeat proteoglycan of the vertebrate extracellular matrix (ECM). With its glycosaminoglycuronan chain, it is responsible for stabilizing inter-fibrillar organization. Type I collagen is the predominant member of the fibrillar collagen family, fulfilling both organizational and structural roles in animal ECMs. In this study, interactions between decoron (the decorin core protein) and binding sites in the d and e1 bands of the type I collagen fibril were investigated through molecular modeling of their respective X-ray diffraction structures. Previously, it was proposed that a model-based, highly curved concave decoron interacts with a single collagen molecule,more » which would form extensive van der Waals contacts and give rise to strong non-specific binding. However, the large well-ordered aggregate that is the collagen fibril places significant restraints on modes of ligand binding and necessitates multi-collagen molecular contacts. We present here a relatively high-resolution model of the decoron-fibril collagen complex. We find that the respective crystal structures complement each other well, although it is the monomeric form of decoron that shows the most appropriate shape complementarity with the fibril surface and favorable calculated energies of interaction. One molecule of decoron interacts with four to six collagen molecules, and the binding specificity relies on a large number of hydrogen bonds and electrostatic interactions, primarily with the collagen motifs KXGDRGE and AKGDRGE (d and e{sub 1} bands). This work helps us to understand collagen-decorin interactions and the molecular architecture of the fibrillar ECM in health and disease.« less

RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.

PubMed

Wang, Lei; You, Zhu-Hong; Chen, Xing; Yan, Xin; Liu, Gang; Zhang, Wei

2018-01-01

Identification of interaction between drugs and target proteins plays an important role in discovering new drug candidates. However, through the experimental method to identify the drug-target interactions remain to be extremely time-consuming, expensive and challenging even nowadays. Therefore, it is urgent to develop new computational methods to predict potential drugtarget interactions (DTI). In this article, a novel computational model is developed for predicting potential drug-target interactions under the theory that each drug-target interaction pair can be represented by the structural properties from drugs and evolutionary information derived from proteins. Specifically, the protein sequences are encoded as Position-Specific Scoring Matrix (PSSM) descriptor which contains information of biological evolutionary and the drug molecules are encoded as fingerprint feature vector which represents the existence of certain functional groups or fragments. Four benchmark datasets involving enzymes, ion channels, GPCRs and nuclear receptors, are independently used for establishing predictive models with Rotation Forest (RF) model. The proposed method achieved the prediction accuracy of 91.3%, 89.1%, 84.1% and 71.1% for four datasets respectively. In order to make our method more persuasive, we compared our classifier with the state-of-theart Support Vector Machine (SVM) classifier. We also compared the proposed method with other excellent methods. Experimental results demonstrate that the proposed method is effective in the prediction of DTI, and can provide assistance for new drug research and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Decorin core protein (decoron) shape complements collagen fibril surface structure and mediates its binding.

PubMed

Orgel, Joseph P R O; Eid, Aya; Antipova, Olga; Bella, Jordi; Scott, John E

2009-09-15

Decorin is the archetypal small leucine rich repeat proteoglycan of the vertebrate extracellular matrix (ECM). With its glycosaminoglycuronan chain, it is responsible for stabilizing inter-fibrillar organization. Type I collagen is the predominant member of the fibrillar collagen family, fulfilling both organizational and structural roles in animal ECMs. In this study, interactions between decoron (the decorin core protein) and binding sites in the d and e(1) bands of the type I collagen fibril were investigated through molecular modeling of their respective X-ray diffraction structures. Previously, it was proposed that a model-based, highly curved concave decoron interacts with a single collagen molecule, which would form extensive van der Waals contacts and give rise to strong non-specific binding. However, the large well-ordered aggregate that is the collagen fibril places significant restraints on modes of ligand binding and necessitates multi-collagen molecular contacts. We present here a relatively high-resolution model of the decoron-fibril collagen complex. We find that the respective crystal structures complement each other well, although it is the monomeric form of decoron that shows the most appropriate shape complementarity with the fibril surface and favorable calculated energies of interaction. One molecule of decoron interacts with four to six collagen molecules, and the binding specificity relies on a large number of hydrogen bonds and electrostatic interactions, primarily with the collagen motifs KXGDRGE and AKGDRGE (d and e(1) bands). This work helps us to understand collagen-decorin interactions and the molecular architecture of the fibrillar ECM in health and disease.

Monodisperse self-assembly in a model with protein-like interactions

NASA Astrophysics Data System (ADS)

Wilber, Alex W.; Doye, Jonathan P. K.; Louis, Ard A.; Lewis, Anna C. F.

2009-11-01

We study the self-assembly behavior of patchy particles with "proteinlike" interactions that can be considered as a minimal model for the assembly of viral capsids and other shell-like protein complexes. We thoroughly explore the thermodynamics and dynamics of self-assembly as a function of the parameters of the model and find robust assembly of all target structures considered. Optimal assembly occurs in the region of parameter space where a free energy barrier regulates the rate of nucleation, thus preventing the premature exhaustion of the supply of monomers that can lead to the formation of incomplete shells. The interactions also need to be specific enough to prevent the assembly of malformed shells, but while maintaining kinetic accessibility. Free energy landscapes computed for our model have a funnel-like topography guiding the system to form the target structure and show that the torsional component of the interparticle interactions prevents the formation of disordered aggregates that would otherwise act as kinetic traps.

A genome-wide survey of transgenerational genetic effects in autism.

PubMed

Tsang, Kathryn M; Croen, Lisa A; Torres, Anthony R; Kharrazi, Martin; Delorenze, Gerald N; Windham, Gayle C; Yoshida, Cathleen K; Zerbo, Ousseny; Weiss, Lauren A

2013-01-01

Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10(-4)) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.

Political Skill as Moderator of Personality--Job Performance Relationships in Socioanalytic Theory: Test of the Getting Ahead Motive in Automobile Sales

ERIC Educational Resources Information Center

Blickle, Gerhard; Wendel, Stephanie; Ferris, Gerald R.

2010-01-01

Based on the socioanalytic perspective of performance prediction ([Hogan, 1991] and [Hogan and Shelton, 1998]), this study tests whether the motive to get ahead produces greater performance when interactively combined with social effectiveness. Specifically, we investigated whether interactions of the five-factor model constructs of extraversion…

An overview to networks and its applications

NASA Astrophysics Data System (ADS)

Huerta-Quintanilla, Rodrigo; Sanabria M., Christian H.

2010-07-01

We present an introduction to the basics on networks and their application to econo-physics. In particular we study a model in which agents interact through a network chosen in a very specific way and the exchange they make of a given asset. We study different types of exchange interactions and also the effect of the network on the dynamics.

INTERACTION ANALYSES OF BINARY MIXTURES OF CARCINOGENIC PAHS USING MORPHOLOGICAL CELL TRANSFORMATION OF C3H1OT1/2CL8 MOUSE EMBRYO FIBROBLASTS IN CULTURE.

EPA Science Inventory

Studies of defined mixtures of carcinogenic polycyclic aromatic hydrocarbons (PAH) have shown three major categories of interactions: antagonism, synergism, and additivity depending on the biological model, tissue, route of exposure, and specific PAH. To understand the bases of t...

How Do Pre-Service Teachers Picture Various Electromagnetic Phenomenon? A Qualitative Study of Pre-Service Teachers' Conceptual Understanding of Fundamental Electromagnetic Interaction

ERIC Educational Resources Information Center

Beer, Christopher P.

2010-01-01

This study analyzes the nature of pre-service teachers' conceptual models of various electromagnetic phenomena, specifically electrical current, electrical resistance, and light/matter interactions. This is achieved through the students answering the three questions on electromagnetism using a free response approach including both verbal and…

A Guide to Analyzing Message-Response Sequences and Group Interaction Patterns in Computer-Mediated Communication

ERIC Educational Resources Information Center

Jeong, Allan

2005-01-01

This paper proposes a set of methods and a framework for evaluating, modeling, and predicting group interactions in computer-mediated communication. The method of sequential analysis is described along with specific software tools and techniques to facilitate the analysis of message-response sequences. In addition, the Dialogic Theory and its…

Interaction Effects of Gender and Motivational Beliefs on Self-Regulated Learning: A Study at ICT- Integrated Schools

ERIC Educational Resources Information Center

Abdullah, Melissa Ng Lee Yen

2016-01-01

Purpose: This study aimed to examine the interaction effects of gender and motivational beliefs on students' self-regulated learning. Specifically, three types of motivational beliefs under the Expectancy-Value Model were examined, namely self-efficacy, control beliefs and anxiety. Methodology: A quantitative correlational research design was used…

The Influence of Social Experience in the Classroom on Cognitive Development.

ERIC Educational Resources Information Center

Silverman, Paul S.

This study is an attempt to identify social interactions which fit into a Piagetian model for cognitive change, and specifically to examine the degree to which the frequency of those interactions predicts the rate of cognitive development. The subjects were 74 elementary school children enrolled in 19 K-4 classrooms. These children were in the…

Learning Gene Expression through Modelling and Argumentation: A Case Study Exploring the Connections between the Worlds of Knowledge

ERIC Educational Resources Information Center

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-01-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is…

Towards A Complete Model Of Photopic Visual Threshold Performance

NASA Astrophysics Data System (ADS)

Overington, I.

1982-02-01

Based on a wide variety of fragmentary evidence taken from psycho-physics, neurophysiology and electron microscopy, it has been possible to put together a very widely applicable conceptual model of photopic visual threshold performance. Such a model is so complex that a single comprehensive mathematical version is excessively cumbersome. It is, however, possible to set up a suite of related mathematical models, each of limited application but strictly known envelope of usage. Such models may be used for assessment of a variety of facets of visual performance when using display imagery, including effects and interactions of image quality, random and discrete display noise, viewing distance, image motion, etc., both for foveal interrogation tasks and for visual search tasks. The specific model may be selected from the suite according to the assessment task in hand. The paper discusses in some depth the major facets of preperceptual visual processing and their interaction with instrumental image quality and noise. It then highlights the statistical nature of visual performance before going on to consider a number of specific mathematical models of partial visual function. Where appropriate, these are compared with widely popular empirical models of visual function.

Some dynamics of signaling games.

PubMed

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-07-22

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions.

Some dynamics of signaling games

PubMed Central

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-01-01

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions. PMID:25024209

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

PubMed Central

Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results. PMID:26457077

Molecular mechanisms of floral organ specification by MADS domain proteins.

PubMed

Yan, Wenhao; Chen, Dijun; Kaufmann, Kerstin

2016-02-01

Flower development is a model system to understand organ specification in plants. The identities of different types of floral organs are specified by homeotic MADS transcription factors that interact in a combinatorial fashion. Systematic identification of DNA-binding sites and target genes of these key regulators show that they have shared and unique sets of target genes. DNA binding by MADS proteins is not based on 'simple' recognition of a specific DNA sequence, but depends on DNA structure and combinatorial interactions. Homeotic MADS proteins regulate gene expression via alternative mechanisms, one of which may be to modulate chromatin structure and accessibility in their target gene promoters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy Landscape and Transition State of Protein-Protein Association

NASA Astrophysics Data System (ADS)

Alsallaq, Ramzi; Zhou, Huan-Xiang

2006-11-01

Formation of a stereospecific protein complex is favored by specific interactions between two proteins but disfavored by the loss of translational and rotational freedom. Echoing the protein folding process, we have previously proposed a transition state for protein-protein association. Here we clarify the specification of the transition state by working with two toy models for protein association. The models demonstrate that a sharp transition between the bound state with numerous short-range interactions but restricted translation and rotational freedom and the unbound state with at most a small number of interactions but expanded configurational freedom. This transition sets the outer boundary of the bound state as well as the transition state for association. The energy landscape is funnel-like, with the deep well of the bound state surrounded by a broad shallow basin. This formalism of protein-protein association is applied to four protein-protein complexes, and is found to give accurate predictions for the effects of charge mutations and ionic strength on the association rates.

Ion specific effects: decoupling ion-ion and ion-water interactions

PubMed Central

Song, Jinsuk; Kang, Tae Hui; Kim, Mahn Won; Han, Songi

2015-01-01

Ion-specific effects in aqueous solution, known as the Hofmeister effect is prevalent in diverse systems ranging from pure ionic to complex protein solutions. The objective of this paper is to explicitly demonstrate how complex ion-ion and ion-water interactions manifest themselves in the Hofmeister effects, based on a series of recent experimental observation. These effects are not considered in the classical description of ion effects, such as the Deryaguin-Landau-Verwey-Overbeek (DLVO) theory that, likely for that reason, fail to describe the origin of the phenomenological Hofmeister effect. However, given that models considering the basic forces of electrostatic and van der Waals interactions can offer rationalization for the core experimental observations, a universal interaction model stands a chance to be developed. In this perspective, we separately derive the contribution from ion-ion electrostatic interaction and ion-water interaction from second harmonic generation (SHG) data at the air-ion solution interface, which yields an estimate of ion-water interactions in solution. Hofmeister ion effects observed on biological solutes in solution should be similarly influenced by contributions from ion-ion and ion-water interactions, where the same ion-water interaction parameters derived from SHG data at the air-ion solution interface could be applicable. A key experimental data set available from solution systems to probe ion-water interaction is the modulation of water diffusion dynamics near ions in bulk ion solution, as well as near biological liposome surfaces. It is obtained from Overhauser dynamic nuclear polarization (ODNP), a nuclear magnetic resonance (NMR) relaxometry technique. The surface water diffusivity is influenced by the contribution from ion-water interactions, both from localized surface charges and adsorbed ions, although the relative contribution of the former is larger on liposome surfaces. In this perspective, ion-water interaction energy values derived from experimental data for various ions are compared with theoretical values in the literature. Ultimately, quantifying ion-induced changes in surface energy for the purpose of developing valid theoretical models for ion-water interaction, will be critical to rationalizing the Hofmeister effect. PMID:25761273

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Attachment of Salmonella strains to a plant cell wall model is modulated by surface characteristics and not by specific carbohydrate interactions.

PubMed

Tan, Michelle Sze-Fan; Moore, Sean C; Tabor, Rico F; Fegan, Narelle; Rahman, Sadequr; Dykes, Gary A

2016-09-15

Processing of fresh produce exposes cut surfaces of plant cell walls that then become vulnerable to human foodborne pathogen attachment and contamination, particularly by Salmonella enterica. Plant cell walls are mainly composed of the polysaccharides cellulose, pectin and hemicelluloses (predominantly xyloglucan). Our previous work used bacterial cellulose-based plant cell wall models to study the interaction between Salmonella and the various plant cell wall components. We demonstrated that Salmonella attachment was favoured in the presence of pectin while xyloglucan had no effect on its attachment. Xyloglucan significantly increased the attachment of Salmonella cells to the plant cell wall model only when it was in association with pectin. In this study, we investigate whether the plant cell wall polysaccharides mediate Salmonella attachment to the bacterial cellulose-based plant cell wall models through specific carbohydrate interactions or through the effects of carbohydrates on the physical characteristics of the attachment surface. We found that none of the monosaccharides that make up the plant cell wall polysaccharides specifically inhibit Salmonella attachment to the bacterial cellulose-based plant cell wall models. Confocal laser scanning microscopy showed that Salmonella cells can penetrate and attach within the tightly arranged bacterial cellulose network. Analysis of images obtained from atomic force microscopy revealed that the bacterial cellulose-pectin-xyloglucan composite with 0.3 % (w/v) xyloglucan, previously shown to have the highest number of Salmonella cells attached to it, had significantly thicker cellulose fibrils compared to other composites. Scanning electron microscopy images also showed that the bacterial cellulose and bacterial cellulose-xyloglucan composites were more porous when compared to the other composites containing pectin. Our study found that the attachment of Salmonella cells to cut plant cell walls was not mediated by specific carbohydrate interactions. This suggests that the attachment of Salmonella strains to the plant cell wall models were more dependent on the structural characteristics of the attachment surface. Pectin reduces the porosity and space between cellulose fibrils, which then forms a matrix that is able to retain Salmonella cells within the bacterial cellulose network. When present with pectin, xyloglucan provides a greater surface for Salmonella cells to attach through the thickening of cellulose fibrils.

A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis: targeting a human-like model.

PubMed

Terai, Asuka; Nakagawa, Masanori

2007-08-01

The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

Time and dose-dependent risk of pneumococcal pneumonia following influenza: a model for within-host interaction between influenza and Streptococcus pneumoniae

PubMed Central

Shrestha, Sourya; Foxman, Betsy; Dawid, Suzanne; Aiello, Allison E.; Davis, Brian M.; Berus, Joshua; Rohani, Pejman

2013-01-01

A significant fraction of seasonal and in particular pandemic influenza deaths are attributed to secondary bacterial infections. In animal models, influenza virus predisposes hosts to severe infection with both Streptococcus pneumoniae and Staphylococcus aureus. Despite its importance, the mechanistic nature of the interaction between influenza and pneumococci, its dependence on the timing and sequence of infections as well as the clinical and epidemiological consequences remain unclear. We explore an immune-mediated model of the viral–bacterial interaction that quantifies the timing and the intensity of the interaction. Taking advantage of the wealth of knowledge gained from animal models, and the quantitative understanding of the kinetics of pathogen-specific immunological dynamics, we formulate a mathematical model for immune-mediated interaction between influenza virus and S. pneumoniae in the lungs. We use the model to examine the pathogenic effect of inoculum size and timing of pneumococcal invasion relative to influenza infection, as well as the efficacy of antivirals in preventing severe pneumococcal disease. We find that our model is able to capture the key features of the interaction observed in animal experiments. The model predicts that introduction of pneumococcal bacteria during a 4–6 day window following influenza infection results in invasive pneumonia at significantly lower inoculum size than in hosts not infected with influenza. Furthermore, we find that antiviral treatment administered later than 4 days after influenza infection was not able to prevent invasive pneumococcal disease. This work provides a quantitative framework to study interactions between influenza and pneumococci and has the potential to accurately quantify the interactions. Such quantitative understanding can form a basis for effective clinical care, public health policies and pandemic preparedness. PMID:23825111

Are Anion/π Interactions Actually a Case of Simple Charge–Dipole Interactions?†

PubMed Central

Wheeler, Steven E.; Houk, K. N.

2011-01-01

Substituent effects in Cl− ••• C6H6−nXn complexes, models for anion/π interactions, have been examined using density functional theory and robust ab initio methods paired with large basis sets. Predicted interaction energies for 83 model Cl− ••• C6H6−nXn complexes span almost 40 kcal mol−1 and show an excellent correlation (r = 0.99) with computed electrostatic potentials. In contrast to prevailing models of anion/π interactions, which rely on substituent-induced changes in the aryl π-system, it is shown that substituent effects in these systems are due mostly to direct interactions between the anion and the substituents. Specifically, interaction energies for Cl− ••• C6H6−nXn complexes are recovered using a model system in which the substituents are isolated from the aromatic ring and π-resonance effects are impossible. Additionally, accurate potential energy curves for Cl− interacting with prototypical anion-binding arenes can be qualitatively reproduced by adding a classical charge–dipole interaction to the Cl− ••• C6H6 interaction potential. In substituted benzenes, binding of anions arises primarily from interactions of the anion with the local dipoles induced by the substituents, not changes in the interaction with the aromatic ring itself. When designing anion-binding motifs, phenyl rings should be viewed as a scaffold upon which appropriate substituents can be placed, because there are no attractive interactions between anions and the aryl π-system of substituted benzenes. PMID:20433187

Multidisciplinary model-based-engineering for laser weapon systems: recent progress

NASA Astrophysics Data System (ADS)

Coy, Steve; Panthaki, Malcolm

2013-09-01

We are working to develop a comprehensive, integrated software framework and toolset to support model-based engineering (MBE) of laser weapons systems. MBE has been identified by the Office of the Director, Defense Science and Engineering as one of four potentially "game-changing" technologies that could bring about revolutionary advances across the entire DoD research and development and procurement cycle. To be effective, however, MBE requires robust underlying modeling and simulation technologies capable of modeling all the pertinent systems, subsystems, components, effects, and interactions at any level of fidelity that may be required in order to support crucial design decisions at any point in the system development lifecycle. Very often the greatest technical challenges are posed by systems involving interactions that cut across two or more distinct scientific or engineering domains; even in cases where there are excellent tools available for modeling each individual domain, generally none of these domain-specific tools can be used to model the cross-domain interactions. In the case of laser weapons systems R&D these tools need to be able to support modeling of systems involving combined interactions among structures, thermal, and optical effects, including both ray optics and wave optics, controls, atmospheric effects, target interaction, computational fluid dynamics, and spatiotemporal interactions between lasing light and the laser gain medium. To address this problem we are working to extend Comet™, to add the addition modeling and simulation capabilities required for this particular application area. In this paper we will describe our progress to date.

Intramolecular interactions regulate SAP97 binding to GKAP

PubMed Central

Wu, Hongju; Reissner, Carsten; Kuhlendahl, Sven; Coblentz, Blake; Reuver, Susanne; Kindler, Stefan; Gundelfinger, Eckart D.; Garner, Craig C.

2000-01-01

Membrane-associated guanylate kinase homologs (MAGUKs) are multidomain proteins found to be central organizers of cellular junctions. In this study, we examined the molecular mechanisms that regulate the interaction of the MAGUK SAP97 with its GUK domain binding partner GKAP (GUK-associated protein). The GKAP–GUK interaction is regulated by a series of intramolecular interactions. Specifically, the association of the Src homology 3 (SH3) domain and sequences situated between the SH3 and GUK domains with the GUK domain was found to interfere with GKAP binding. In contrast, N-terminal sequences that precede the first PDZ domain in SAP97, facilitated GKAP binding via its association with the SH3 domain. Utilizing crystal structure data available for PDZ, SH3 and GUK domains, molecular models of SAP97 were generated. These models revealed that SAP97 can exist in a compact U-shaped conformation in which the N-terminal domain folds back and interacts with the SH3 and GUK domains. These models support the biochemical data and provide new insights into how intramolecular interactions may regulate the association of SAP97 with its binding partners. PMID:11060025

Wetting behavior of nonpolar nanotubes in simple dipolar liquids for varying nanotube diameter and solute-solvent interactions

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

Rana, Malay Kumar; Chandra, Amalendu, E-mail: amalen@iitk.ac.in

2015-01-21

Atomistic simulations of model nonpolar nanotubes in a Stockmayer liquid are carried out for varying nanotube diameter and nanotube-solvent interactions to investigate solvophobic interactions in generic dipolar solvents. We have considered model armchair type single-walled nonpolar nanotubes with increasing radii from (5,5) to (12,12). The interactions between solute and solvent molecules are modeled by the well-known Lennard-Jones and repulsive Weeks-Chandler-Andersen potentials. We have investigated the density profiles and microscopic arrangement of Stockmayer molecules, orientational profiles of their dipole vectors, time dependence of their occupation, and also the translational and rotational motion of solvent molecules in confined environments of the cylindricalmore » nanopores and also in their external peripheral regions. The present results of structural and dynamical properties of Stockmayer molecules inside and near atomistically rough nonpolar surfaces including their wetting and dewetting behavior for varying interactions provide a more generic picture of solvophobic effects experienced by simple dipolar liquids without any specific interactions such as hydrogen bonds.« less

Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors.

PubMed

Raveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, Ora

2011-04-29

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions. © 2011 Raveh et al.

Rosetta FlexPepDock ab-initio: Simultaneous Folding, Docking and Refinement of Peptides onto Their Receptors

PubMed Central

Raveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, Ora

2011-01-01

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions. PMID:21572516

Emotion attribution to a non-humanoid robot in different social situations.

PubMed

Lakatos, Gabriella; Gácsi, Márta; Konok, Veronika; Brúder, Ildikó; Bereczky, Boróka; Korondi, Péter; Miklósi, Ádám

2014-01-01

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human-animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour ("happiness" and "fear"), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot's greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot.

Emotion Attribution to a Non-Humanoid Robot in Different Social Situations

PubMed Central

Lakatos, Gabriella; Gácsi, Márta; Konok, Veronika; Brúder, Ildikó; Bereczky, Boróka; Korondi, Péter; Miklósi, Ádám

2014-01-01

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (“happiness” and “fear”), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot's greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot. PMID:25551218

Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity

PubMed Central

Lumpkin, Will; Hurtado, Paul J.; Dyer, Lee A.

2018-01-01

Most of earth’s biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change. PMID:29579077

Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity.

PubMed

Pardikes, Nicholas A; Lumpkin, Will; Hurtado, Paul J; Dyer, Lee A

2018-01-01

Most of earth's biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change.

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

Functional Coupling of Human Microphysiology Systems: Intestine, Liver, Kidney Proximal Tubule, Blood-Brain Barrier and Skeletal Muscle

PubMed Central

Vernetti, Lawrence; Gough, Albert; Baetz, Nicholas; Blutt, Sarah; Broughman, James R.; Brown, Jacquelyn A.; Foulke-Abel, Jennifer; Hasan, Nesrin; In, Julie; Kelly, Edward; Kovbasnjuk, Olga; Repper, Jonathan; Senutovitch, Nina; Stabb, Janet; Yeung, Catherine; Zachos, Nick C.; Donowitz, Mark; Estes, Mary; Himmelfarb, Jonathan; Truskey, George; Wikswo, John P.; Taylor, D. Lansing

2017-01-01

Organ interactions resulting from drug, metabolite or xenobiotic transport between organs are key components of human metabolism that impact therapeutic action and toxic side effects. Preclinical animal testing often fails to predict adverse outcomes arising from sequential, multi-organ metabolism of drugs and xenobiotics. Human microphysiological systems (MPS) can model these interactions and are predicted to dramatically improve the efficiency of the drug development process. In this study, five human MPS models were evaluated for functional coupling, defined as the determination of organ interactions via an in vivo-like sequential, organ-to-organ transfer of media. MPS models representing the major absorption, metabolism and clearance organs (the jejunum, liver and kidney) were evaluated, along with skeletal muscle and neurovascular models. Three compounds were evaluated for organ-specific processing: terfenadine for pharmacokinetics (PK) and toxicity; trimethylamine (TMA) as a potentially toxic microbiome metabolite; and vitamin D3. We show that the organ-specific processing of these compounds was consistent with clinical data, and discovered that trimethylamine-N-oxide (TMAO) crosses the blood-brain barrier. These studies demonstrate the potential of human MPS for multi-organ toxicity and absorption, distribution, metabolism and excretion (ADME), provide guidance for physically coupling MPS, and offer an approach to coupling MPS with distinct media and perfusion requirements. PMID:28176881

Implications for neurobiological research of cognitive models of psychosis: a theoretical paper.

PubMed

Garety, Philippa A; Bebbington, Paul; Fowler, David; Freeman, Daniel; Kuipers, Elizabeth

2007-10-01

Cognitive models of the positive symptoms of psychosis specify the cognitive, social and emotional processes hypothesized to contribute to their occurrence and persistence, and propose that vulnerable individuals make characteristic appraisals that result in specific positive symptoms. We describe cognitive models of positive psychotic symptoms and use this as the basis of discussing recent relevant empirical investigations and reviews that integrate cognitive approaches into neurobiological frameworks. Evidence increasingly supports a number of the hypotheses proposed by cognitive models. These are that: psychosis is on a continuum; specific cognitive processes are risk factors for the transition from subclinical experiences to clinical disorder; social adversity and trauma are associated with psychosis and with negative emotional processes; and these emotional processes contribute to the occurrence and persistence of psychotic symptoms. There is also evidence that reasoning biases contribute to the occurrence of delusions. The benefits of incorporating cognitive processes into neurobiological research include more sophisticated, bidirectional and interactive causal models, the amplification of phenotypes in neurobiological investigations by including emotional processes, and the adoption of more specific clinical phenotypes. For example, there is potential value in studying gene x environment x cognition/emotion interactions. Cognitive models and their derived phenotypes constitute the missing link in the chain between genetic or acquired biological vulnerability, the social environment and the expression of individual positive symptoms.

Fluid-structure Interaction Modeling of Aneurysmal Conditions with High and Normal Blood Pressures

NASA Astrophysics Data System (ADS)

Torii, Ryo; Oshima, Marie; Kobayashi, Toshio; Takagi, Kiyoshi; Tezduyar, Tayfun E.

2006-09-01

Hemodynamic factors like the wall shear stress play an important role in cardiovascular diseases. To investigate the influence of hemodynamic factors in blood vessels, the authors have developed a numerical fluid-structure interaction (FSI) analysis technique. The objective is to use numerical simulation as an effective tool to predict phenomena in a living human body. We applied the technique to a patient-specific arterial model, and with that we showed the effect of wall deformation on the WSS distribution. In this paper, we compute the interaction between the blood flow and the arterial wall for a patient-specific cerebral aneurysm with various hemodynamic conditions, such as hypertension. We particularly focus on the effects of hypertensive blood pressure on the interaction and the WSS, because hypertension is reported to be a risk factor in rupture of aneurysms. We also aim to show the possibility of FSI computations with hemodynamic conditions representing those risk factors in cardiovascular disease. The simulations show that the transient behavior of the interaction under hypertensive blood pressure is significantly different from the interaction under normal blood pressure. The transient behavior of the blood-flow velocity, and the resulting WSS and the mechanical stress in the aneurysmal wall, are significantly affected by hypertension. The results imply that hypertension affects the growth of an aneurysm and the damage in arterial tissues.

HiTEC: a connectionist model of the interaction between perception and action planning.

PubMed

Haazebroek, Pascal; Raffone, Antonino; Hommel, Bernhard

2017-11-01

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

Characterizing interactions in online social networks during exceptional events

NASA Astrophysics Data System (ADS)

Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

2015-08-01

Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

The role of nonbonded interactions in the conformational dynamics of organophosphorous hydrolase adsorbed onto functionalized mesoporous silica surfaces.

PubMed

Gomes, Diego E B; Lins, Roberto D; Pascutti, Pedro G; Lei, Chenghong; Soares, Thereza A

2010-01-14

The enzyme organophosphorous hydrolase (OPH) catalyzes the hydrolysis of a wide variety of organophosphorous compounds with high catalytic efficiency and broad substrate specificity. The immobilization of OPH in functionalized mesoporous silica (FMS) surfaces increases significantly its catalytic specific activity, as compared to the enzyme in solution, with important applications for the detection and decontamination of insecticides and chemical warfare agents. Experimental measurements of immobilization efficiency as a function of the charge and coverage percentage of different functional groups have been interpreted as electrostatic forces being the predominant interactions underlying the adsorption of OPH onto FMS surfaces. Explicit solvent molecular dynamics simulations have been performed for OPH in bulk solution and adsorbed onto two distinct interaction potential models of the FMS functional groups to investigate the relative contributions of nonbonded interactions to the conformational dynamics and adsorption of the protein. Our results support the conclusion that electrostatic interactions are responsible for the binding of OPH to the FMS surface. However, these results also show that van der Waals forces are detrimental for interfacial adhesion. In addition, it is found that OPH adsorption onto the FMS models favors a protein conformation whose active site is fully accessible to the substrate, in contrast to the unconfined protein.

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

Field, Kevin G.; Yang, Ying; Busby, Jeremy T.

Radiation induced segregation (RIS) is a well-studied phenomena which occurs in many structurally relevant nuclear materials including austenitic stainless steels. RIS occurs due to solute atoms preferentially coupling to mobile point defect fluxes that migrate and interact with defect sinks. Here, a 304 stainless steel was neutron irradiated up to 47.1 dpa at 320 °C. Investigations into the RIS response at specific grain boundary types were utilized to determine the sink characteristics of different boundary types as a function of irradiation dose. A rate theory model built on the foundation of the modified inverse Kirkendall (MIK) model is proposed andmore » benchmarked to the experimental results. This model, termed the GiMIK model, includes alterations in the boundary conditions based on grain boundary structure and includes expressions for interstitial binding. This investigation, through experiment and modeling, found specific grain boundary structures exhibit unique defect sink characteristics depending on their local structure. Furthermore, such interactions were found to be consistent across all doses investigated and had larger global implications including precipitation of Ni-Si clusters near different grain boundary types.« less

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

Field, Kevin G.; Yang, Ying; Allen, Todd R.

Radiation induced segregation (RIS) is a well-studied phenomena which occurs in many structurally relevant nuclear materials including austenitic stainless steels. RIS occurs due to solute atoms preferentially coupling to mobile point defect fluxes that migrate and interact with defect sinks. Here, a 304 stainless steel was neutron irradiated up to 47.1 dpa at 320 °C. Investigations into the RIS response at specific grain boundary types were utilized to determine the sink characteristics of different boundary types as a function of irradiation dose. A rate theory model built on the foundation of the modified inverse Kirkendall (MIK) model is proposed andmore » benchmarked to the experimental results. This model, termed the GiMIK model, includes alterations in the boundary conditions based on grain boundary structure and includes expressions for interstitial binding. This investigation, through experiment and modeling, found specific grain boundary structures exhibit unique defect sink characteristics depending on their local structure. Such interactions were found to be consistent across all doses investigated and had larger global implications including precipitation of Ni-Si clusters near different grain boundary types.« less

Gaussian Processes for Data-Efficient Learning in Robotics and Control.

PubMed

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

Model-based Utility Functions

NASA Astrophysics Data System (ADS)

Hibbard, Bill

2012-05-01

Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.

Computational Model for DNA Organization Mediated by Protein Interaction in Prokaryotes

NASA Astrophysics Data System (ADS)

Garimella, Karthik; Kharel, Savan

2016-03-01

In Escherichia Coli, there are several mechanisms that drive chromosomal organization. We know through experiments that the E. Coli chromosome is condensed into highly structured regions known as macrodomains (MDs). One of the regions known as the Terminus undergoes DNA-bridging condensation that form loops between distant DNA sites and it is known to be mediated by a Terminus specific protein, which binds to specific markers within the Terminus region. In the absence of Terminus specific protein, however, the Terminus region is known to not condense nearly as much, which will likely impede several biological processes including DNA replication. In order to understand the molecular basis of protein mediation in vivo several models of Terminus specific segregation have been constructed in silico which model DNA as polymer chains.

Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations.

PubMed

Hayes, Andrew F; Matthes, Jörg

2009-08-01

Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Fluid-Structure Interaction and Structural Analyses using a Comprehensive Mitral Valve Model with 3D Chordal Structure

PubMed Central

Toma, Milan; Einstein, Daniel R.; Bloodworth, Charles H.; Cochran, Richard P.; Yoganathan, Ajit P.; Kunzelman, Karyn S.

2016-01-01

Over the years, three-dimensional models of the mitral valve have generally been organized around a simplified anatomy. Leaflets have been typically modeled as membranes, tethered to discrete chordae typically modeled as one-dimensional, non-linear cables. Yet, recent, high-resolution medical images have revealed that there is no clear boundary between the chordae and the leaflets. In fact, the mitral valve has been revealed to be more of a webbed structure whose architecture is continuous with the chordae and their extensions into the leaflets. Such detailed images can serve as the basis of anatomically accurate, subject-specific models, wherein the entire valve is modeled with solid elements that more faithfully represent the chordae, the leaflets, and the transition between the two. These models have the potential to enhance our understanding of mitral valve mechanics, and to re-examine the role of the mitral valve chordae, which heretofore have been considered to be “invisible” to the fluid and to be of secondary importance to the leaflets. However, these new models also require a rethinking of modeling assumptions. In this study, we examine the conventional practice of loading the leaflets only and not the chordae in order to study the structural response of the mitral valve apparatus. Specifically, we demonstrate that fully resolved 3D models of the mitral valve require a fluid-structure interaction analysis to correctly load the valve even in the case of quasi-static mechanics. While a fluid-structure interaction mode is still more computationally expensive than a structural-only model, we also show that advances in GPU computing have made such models tractable. PMID:27342229

Fluid-structure interaction and structural analyses using a comprehensive mitral valve model with 3D chordal structure.

PubMed

Toma, Milan; Einstein, Daniel R; Bloodworth, Charles H; Cochran, Richard P; Yoganathan, Ajit P; Kunzelman, Karyn S

2017-04-01

Over the years, three-dimensional models of the mitral valve have generally been organized around a simplified anatomy. Leaflets have been typically modeled as membranes, tethered to discrete chordae typically modeled as one-dimensional, non-linear cables. Yet, recent, high-resolution medical images have revealed that there is no clear boundary between the chordae and the leaflets. In fact, the mitral valve has been revealed to be more of a webbed structure whose architecture is continuous with the chordae and their extensions into the leaflets. Such detailed images can serve as the basis of anatomically accurate, subject-specific models, wherein the entire valve is modeled with solid elements that more faithfully represent the chordae, the leaflets, and the transition between the two. These models have the potential to enhance our understanding of mitral valve mechanics and to re-examine the role of the mitral valve chordae, which heretofore have been considered to be 'invisible' to the fluid and to be of secondary importance to the leaflets. However, these new models also require a rethinking of modeling assumptions. In this study, we examine the conventional practice of loading the leaflets only and not the chordae in order to study the structural response of the mitral valve apparatus. Specifically, we demonstrate that fully resolved 3D models of the mitral valve require a fluid-structure interaction analysis to correctly load the valve even in the case of quasi-static mechanics. While a fluid-structure interaction mode is still more computationally expensive than a structural-only model, we also show that advances in GPU computing have made such models tractable. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Identification of SNPs associated with variola virus virulence.

PubMed

Hoen, Anne Gatewood; Gardner, Shea N; Moore, Jason H

2013-02-14

Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity.

Identification of SNPs associated with variola virus virulence

PubMed Central

2013-01-01

Background Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Findings Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. Conclusions We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity. PMID:23410064

Interaction studies reveal specific recognition of an anti-inflammatory polyphosphorhydrazone dendrimer by human monocytes.

PubMed

Ledall, Jérémy; Fruchon, Séverine; Garzoni, Matteo; Pavan, Giovanni M; Caminade, Anne-Marie; Turrin, Cédric-Olivier; Blanzat, Muriel; Poupot, Rémy

2015-11-14

Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes.

Micropatterned cell-cell interactions enable functional encapsulation of primary hepatocytes in hydrogel microtissues.

PubMed

Li, Cheri Y; Stevens, Kelly R; Schwartz, Robert E; Alejandro, Brian S; Huang, Joanne H; Bhatia, Sangeeta N

2014-08-01

Drug-induced liver injury is a major cause of drug development failures and postmarket withdrawals. In vitro models that incorporate primary hepatocytes have been shown to be more predictive than model systems which rely on liver microsomes or hepatocellular carcinoma cell lines. Methods to phenotypically stabilize primary hepatocytes ex vivo often rely on mimicry of hepatic microenvironmental cues such as cell-cell interactions and cell-matrix interactions. In this work, we sought to incorporate phenotypically stable hepatocytes into three-dimensional (3D) microtissues, which, in turn, could be deployed in drug-screening platforms such as multiwell plates and diverse organ-on-a-chip devices. We first utilize micropatterning on collagen I to specify cell-cell interactions in two-dimensions, followed by collagenase digestion to produce well-controlled aggregates for 3D encapsulation in polyethylene glycol (PEG) diacrylate. Using this approach, we examined the influence of homotypic hepatocyte interactions and composition of the encapsulating hydrogel, and achieved the maintenance of liver-specific function for over 50 days. Optimally preaggregated structures were subsequently encapsulated using a microfluidic droplet-generator to produce 3D microtissues. Interactions of engineered hepatic microtissues with drugs was characterized by flow cytometry, and yielded both induction of P450 enzymes in response to prototypic small molecules and drug-drug interactions that give rise to hepatotoxicity. Collectively, this study establishes a pipeline for the manufacturing of 3D hepatic microtissues that exhibit stabilized liver-specific functions and can be incorporated into a wide array of emerging drug development platforms.

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

NASA Technical Reports Server (NTRS)

Schimel, David S.

1992-01-01

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides.

PubMed

Panwar, Bharat; Raghava, Gajendra P S

2015-04-01

The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redundant dataset and are evaluated using five-fold cross validation technique. A web-server called RNApin has been developed for the scientific community (http://crdd.osdd.net/raghava/rnapin/). Copyright © 2015 Elsevier Inc. All rights reserved.

Volatiles in Inter-Specific Bacterial Interactions

PubMed Central

Tyc, Olaf; Zweers, Hans; de Boer, Wietse; Garbeva, Paolina

2015-01-01

The importance of volatile organic compounds for functioning of microbes is receiving increased research attention. However, to date very little is known on how inter-specific bacterial interactions effect volatiles production as most studies have been focused on volatiles produced by monocultures of well-described bacterial genera. In this study we aimed to understand how inter-specific bacterial interactions affect the composition, production and activity of volatiles. Four phylogenetically different bacterial species namely: Chryseobacterium, Dyella, Janthinobacterium, and Tsukamurella were selected. Earlier results had shown that pairwise combinations of these bacteria induced antimicrobial activity in agar media whereas this was not the case for monocultures. In the current study, we examined if these observations were also reflected by the production of antimicrobial volatiles. Thus, the identity and antimicrobial activity of volatiles produced by the bacteria were determined in monoculture as well in pairwise combinations. Antimicrobial activity of the volatiles was assessed against fungal, oomycetal, and bacterial model organisms. Our results revealed that inter-specific bacterial interactions affected volatiles blend composition. Fungi and oomycetes showed high sensitivity to bacterial volatiles whereas the effect of volatiles on bacteria varied between no effects, growth inhibition to growth promotion depending on the volatile blend composition. In total 35 volatile compounds were detected most of which were sulfur-containing compounds. Two commonly produced sulfur-containing volatile compounds (dimethyl disulfide and dimethyl trisulfide) were tested for their effect on three target bacteria. Here, we display the importance of inter-specific interactions on bacterial volatiles production and their antimicrobial activities. PMID:26733959

A Sequence in the loop domain of hepatitis C virus E2 protein identified in silico as crucial for the selective binding to human CD81

PubMed Central

Chang, Chun-Chun; Hsu, Hao-Jen; Yen, Jui-Hung; Lo, Shih-Yen

2017-01-01

Hepatitis C virus (HCV) is a species-specific pathogenic virus that infects only humans and chimpanzees. Previous studies have indicated that interactions between the HCV E2 protein and CD81 on host cells are required for HCV infection. To determine the crucial factors for species-specific interactions at the molecular level, this study employed in silico molecular docking involving molecular dynamic simulations of the binding of HCV E2 onto human and rat CD81s. In vitro experiments including surface plasmon resonance measurements and cellular binding assays were applied for simple validations of the in silico results. The in silico studies identified two binding regions on the HCV E2 loop domain, namely E2-site1 and E2-site2, as being crucial for the interactions with CD81s, with the E2-site2 as the determinant factor for human-specific binding. Free energy calculations indicated that the E2/CD81 binding process might follow a two-step model involving (i) the electrostatic interaction-driven initial binding of human-specific E2-site2, followed by (ii) changes in the E2 orientation to facilitate the hydrophobic and van der Waals interaction-driven binding of E2-site1. The sequence of the human-specific, stronger-binding E2-site2 could serve as a candidate template for the future development of HCV-inhibiting peptide drugs. PMID:28481946

Three-dimensional structure-activity relationship modeling of cocaine binding to two monoclonal antibodies by comparative molecular field analysis.

PubMed

Paula, Stefan; Tabet, Michael R; Keenan, Susan M; Welsh, William J; Ball, W James

2003-01-17

Successful immunotherapy of cocaine addiction and overdoses requires cocaine-binding antibodies with specific properties, such as high affinity and selectivity for cocaine. We have determined the affinities of two cocaine-binding murine monoclonal antibodies (mAb: clones 3P1A6 and MM0240PA) for cocaine and its metabolites by [3H]-radioligand binding assays. mAb 3P1A6 (K(d) = 0.22 nM) displayed a 50-fold higher affinity for cocaine than mAb MM0240PA (K(d) = 11 nM) and also had a greater specificity for cocaine. For the systematic exploration of both antibodies' binding specificities, we used a set of approximately 35 cocaine analogues as structural probes by determining their relative binding affinities (RBAs) using an enzyme-linked immunosorbent competition assay. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models on the basis of comparative molecular field analysis (CoMFA) techniques correlated the binding data with structural features of the ligands. The analysis indicated that despite the mAbs' differing specificities for cocaine, the relative contributions of the steric (approximately 80%) and electrostatic (approximately 20%) field interactions to ligand-binding were similar. Generated three-dimensional CoMFA contour plots then located the specific regions about cocaine where the ligand/receptor interactions occurred. While the overall binding patterns of the two mAbs had many features in common, distinct differences were observed about the phenyl ring and the methylester group of cocaine. Furthermore, using previously published data, a 3D-QSAR model was developed for cocaine binding to the dopamine reuptake transporter (DAT) that was compared to the mAb models. Although the relative steric and electrostatic field contributions were similar to those of the mAbs, the DAT cocaine-binding site showed a preference for negatively charged ligands. Besides establishing molecular level insight into the interactions that govern cocaine binding specificity by biopolymers, the three-dimensional images obtained reflect the properties of the mAbs binding pockets and provide the initial information needed for the possible design of novel antibodies with properties optimized for immunotherapy. Copyright 2003 Elsevier Science Ltd.

Site-specific Interaction Mapping of Phosphorylated Ubiquitin to Uncover Parkin Activation*♦

PubMed Central

Yamano, Koji; Queliconi, Bruno B.; Koyano, Fumika; Saeki, Yasushi; Hirokawa, Takatsugu; Tanaka, Keiji; Matsuda, Noriyuki

2015-01-01

Damaged mitochondria are eliminated through autophagy machinery. A cytosolic E3 ubiquitin ligase Parkin, a gene product mutated in familial Parkinsonism, is essential for this pathway. Recent progress has revealed that phosphorylation of both Parkin and ubiquitin at Ser65 by PINK1 are crucial for activation and recruitment of Parkin to the damaged mitochondria. However, the mechanism by which phosphorylated ubiquitin associates with and activates phosphorylated Parkin E3 ligase activity remains largely unknown. Here, we analyze interactions between phosphorylated forms of both Parkin and ubiquitin at a spatial resolution of the amino acid residue by site-specific photo-crosslinking. We reveal that the in-between-RING (IBR) domain along with RING1 domain of Parkin preferentially binds to ubiquitin in a phosphorylation-dependent manner. Furthermore, another approach, the Fluoppi (fluorescent-based technology detecting protein-protein interaction) assay, also showed that pathogenic mutations in these domains blocked interactions with phosphomimetic ubiquitin in mammalian cells. Molecular modeling based on the site-specific photo-crosslinking interaction map combined with mass spectrometry strongly suggests that a novel binding mechanism between Parkin and ubiquitin leads to a Parkin conformational change with subsequent activation of Parkin E3 ligase activity. PMID:26260794

The structure of the Tiam1 PDZ domain/ phospho-syndecan1 complex reveals a ligand conformation that modulates protein dynamics.

PubMed

Liu, Xu; Shepherd, Tyson R; Murray, Ann M; Xu, Zhen; Fuentes, Ernesto J

2013-03-05

PDZ (PSD-95/Dlg/ZO-1) domains are protein-protein interaction modules often regulated by ligand phosphorylation. Here, we investigated the specificity, structure, and dynamics of Tiam1 PDZ domain/ligand interactions. We show that the PDZ domain specifically binds syndecan1 (SDC1), phosphorylated SDC1 (pSDC1), and SDC3 but not other syndecan isoforms. The crystal structure of the PDZ/SDC1 complex indicates that syndecan affinity is derived from amino acids beyond the four C-terminal residues. Remarkably, the crystal structure of the PDZ/pSDC1 complex reveals a binding pocket that accommodates the phosphoryl group. Methyl relaxation experiments of PDZ/SCD1 and PDZ/pSDC1 complexes reveal that PDZ-phosphoryl interactions dampen dynamic motions in a distal region of the PDZ domain by decoupling them from the ligand-binding site. Our data are consistent with a selection model by which specificity and phosphorylation regulate PDZ/syndecan interactions and signaling events. Importantly, our relaxation data demonstrate that PDZ/phospho-ligand interactions regulate protein dynamics and their coupling to distal sites. Copyright © 2013 Elsevier Ltd. All rights reserved.

Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

PubMed

Dettmer, Jan; Dosso, Stan E

2012-10-01

This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

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.

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.

AgRISTARS: Yield model development/soil moisture. Interface control document

NASA Technical Reports Server (NTRS)

1980-01-01

The interactions and support functions required between the crop Yield Model Development (YMD) Project and Soil Moisture (SM) Project are defined. The requirements for YMD support of SM and vice-versa are outlined. Specific tasks in support of these interfaces are defined for development of support functions.

Foundations of reusable and interoperable facet models using category theory

PubMed Central

2016-01-01

Faceted browsing has become ubiquitous with modern digital libraries and online search engines, yet the process is still difficult to abstractly model in a manner that supports the development of interoperable and reusable interfaces. We propose category theory as a theoretical foundation for faceted browsing and demonstrate how the interactive process can be mathematically abstracted. Existing efforts in facet modeling are based upon set theory, formal concept analysis, and light-weight ontologies, but in many regards, they are implementations of faceted browsing rather than a specification of the basic, underlying structures and interactions. We will demonstrate that category theory allows us to specify faceted objects and study the relationships and interactions within a faceted browsing system. Resulting implementations can then be constructed through a category-theoretic lens using these models, allowing abstract comparison and communication that naturally support interoperability and reuse. PMID:27942248

The GISS global climate-middle atmosphere model. II - Model variability due to interactions between planetary waves, the mean circulation and gravity wave drag

NASA Technical Reports Server (NTRS)

Rind, D.; Suozzo, R.; Balachandran, N. K.

1988-01-01

The variability which arises in the GISS Global Climate-Middle Atmosphere Model on two time scales is reviewed: interannual standard deviations, derived from the five-year control run, and intraseasonal variability as exemplified by statospheric warnings. The model's extratropical variability for both mean fields and eddy statistics appears reasonable when compared with observations, while the tropical wind variability near the stratopause may be excessive possibly, due to inertial oscillations. Both wave 1 and wave 2 warmings develop, with connections to tropospheric forcing. Variability on both time scales results from a complex set of interactions among planetary waves, the mean circulation, and gravity wave drag. Specific examples of these interactions are presented, which imply that variability in gravity wave forcing and drag may be an important component of the variability of the middle atmosphere.

The Interaction Between Child Behavioral Inhibition and Parenting Behaviors: Effects on Internalizing and Externalizing Symptomology.

PubMed

Ryan, Sarah M; Ollendick, Thomas H

2018-02-20

Both child temperament and parenting have been extensively researched as predictors of child outcomes. However, theoretical models suggest that specific combinations of temperament styles and parenting behaviors are better predictors of certain child outcomes such as internalizing and externalizing symptoms than either temperament or parenting alone. The current qualitative review examines the interaction between one childhood temperamental characteristic (child behavioral inhibition) and parenting behaviors, and their subsequent impact on child psychopathology. Specifically, the moderating role of parenting on the relationship between child behavioral inhibition and both internalizing and externalizing psychopathology is examined, and the methodological variations which may contribute to inconsistent findings are explored. Additionally, support for the bidirectional relations between behavioral inhibition and parenting behaviors, as well as for the moderating role of temperament on the relationships between parenting and child outcomes, is briefly discussed. Finally, the clinical applicability of this overall conceptual model, specifically in regard to future research directions and potential clinical interventions, is considered.

Specific Cx43 phosphorylation events regulate gap junction turnover in vivo

PubMed Central

Solan, Joell L.; Lampe, Paul D.

2014-01-01

Gap junctions, composed of proteins from the connexin gene family, are highly dynamic structures that are regulated by kinase-mediated signaling pathways and interactions with other proteins. Phosphorylation of Connexin43 (Cx43) at different sites controls gap junction assembly, gap junction size and gap junction turnover. Here we present a model describing how Akt, mitogen activated protein kinase (MAPK) and src kinase coordinate to regulate rapid turnover of gap junctions. Specifically, Akt phosphorylates Cx43 at S373 eliminating interaction with zona occludens-1 (ZO-1) allowing gap junctions to enlarge. Then MAPK and src phosphorylate Cx43 to initiate turnover. We integrate published data with new data to test and refine this model. Finally, we propose that differential coordination of kinase activation and Cx43 phosphorylation controls the specific routes of disassembly, e.g., annular junction formation or gap junctions can potentially “unzip” and be internalized/endocytosed into the cell that produced each connexin. PMID:24508467

Interaction of 5-HTTLPR and Idiographic Stressors Predicts Prospective Depressive Symptoms Specifically among Youth in a Multiwave Design

ERIC Educational Resources Information Center

Hankin, Benjamin L.; Jenness, Jessica; Abela, John R. Z.; Smolen, Andrew

2011-01-01

5-HTTLPR, episodic stressors, depressive and anxious symptoms were assessed prospectively (child and parent report) every 3 months over 1 year (5 waves of data) among community youth ages 9 to 15 (n = 220). Lagged hierarchical linear modeling analyses showed 5-HTTLPR interacted with idiographic stressors (increases relative to the child's own…

The Exosome Associates Cotranscriptionally with the Nascent Pre-mRNP through Interactions with Heterogeneous Nuclear Ribonucleoproteins

PubMed Central

Hessle, Viktoria; Björk, Petra; Sokolowski, Marcus; de Valdivia, Ernesto González; Silverstein, Rebecca; Artemenko, Konstantin; Tyagi, Anu; Maddalo, Gianluca; Ilag, Leopold; Helbig, Roger; Zubarev, Roman A.

2009-01-01

Eukaryotic cells have evolved quality control mechanisms to degrade aberrant mRNA molecules and prevent the synthesis of defective proteins that could be deleterious for the cell. The exosome, a protein complex with ribonuclease activity, is a key player in quality control. An early quality checkpoint takes place cotranscriptionally but little is known about the molecular mechanisms by which the exosome is recruited to the transcribed genes. Here we study the core exosome subunit Rrp4 in two insect model systems, Chironomus and Drosophila. We show that a significant fraction of Rrp4 is associated with the nascent pre-mRNPs and that a specific mRNA-binding protein, Hrp59/hnRNP M, interacts in vivo with multiple exosome subunits. Depletion of Hrp59 by RNA interference reduces the levels of Rrp4 at transcription sites, which suggests that Hrp59 is needed for the exosome to stably interact with nascent pre-mRNPs. Our results lead to a revised mechanistic model for cotranscriptional quality control in which the exosome is constantly recruited to newly synthesized RNAs through direct interactions with specific hnRNP proteins. PMID:19494042

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; van Riel, Piet L C M; Coenen, Marieke J H; Scorza, Raffaella

2010-08-06

Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. http://sourceforge.net/projects/sdrproject/.

In live interaction, does familiarity promote attraction or contempt? Reply to Norton, Frost, and Ariely (2011).

PubMed

Reis, Harry T; Maniaci, Michael R; Caprariello, Peter A; Eastwick, Paul W; Finkel, Eli J

2011-09-01

In this reply, we address and refute each of Norton, Frost, and Ariely's (see record 2011-18560-001) specific objections to the conclusion that, ceteris paribus, familiarity breeds liking in live interaction. In particular, we reiterate the importance of studying live interaction rather than decontextualized processes. These rebuttals notwithstanding, we concur with Norton et al.'s call for an integrative model that encompasses both Norton, Frost, and Ariely's (see record 2006-23056-008) results and ours (see record 2011-04644-001), and we point readers toward a description of a possible model presented in our original article. PsycINFO Database Record (c) 2011 APA, all rights reserved.

How intergenerational interaction affects attitude-behavior inconsistency.

PubMed

Sekiguchi, Takuya; Nakamaru, Mayuko

2014-04-07

Social norms play an important role in maintaining social order, but at the same time, they can act as a constraint that compels people to take specific actions which run contrary to their attitudes. This paper treats the latter case: we investigate conditions in which attitude-behavior inconsistency persists, constructing mathematical models combining evolutionary games and cultural transmissions. In particular, we focus on the effect of intergenerational interactions. Our models show that both information about others' attitude (e.g., through social surveys) and the combination of intra- and inter-generational interactions are key factors to generate the situation where all people adopt the same behavior but different people have different attitudes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Physics-based interactive volume manipulation for sharing surgical process.

PubMed

Nakao, Megumi; Minato, Kotaro

2010-05-01

This paper presents a new set of techniques by which surgeons can interactively manipulate patient-specific volumetric models for sharing surgical process. To handle physical interaction between the surgical tools and organs, we propose a simple surface-constraint-based manipulation algorithm to consistently simulate common surgical manipulations such as grasping, holding and retraction. Our computation model is capable of simulating soft-tissue deformation and incision in real time. We also present visualization techniques in order to rapidly visualize time-varying, volumetric information on the deformed image. This paper demonstrates the success of the proposed methods in enabling the simulation of surgical processes, and the ways in which this simulation facilitates preoperative planning and rehearsal.

Conceptual model of iCAL4LA: Proposing the components using comparative analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Zulaiha; Mutalib, Ariffin Abdul

2016-08-01

This paper discusses an on-going study that initiates an initial process in determining the common components for a conceptual model of interactive computer-assisted learning that is specifically designed for low achieving children. This group of children needs a specific learning support that can be used as an alternative learning material in their learning environment. In order to develop the conceptual model, this study extracts the common components from 15 strongly justified computer assisted learning studies. A comparative analysis has been conducted to determine the most appropriate components by using a set of specific indication classification to prioritize the applicability. The results of the extraction process reveal 17 common components for consideration. Later, based on scientific justifications, 16 of them were selected as the proposed components for the model.

The association between major depression prevalence and sex becomes weaker with age.

PubMed

Patten, Scott B; Williams, Jeanne V A; Lavorato, Dina H; Wang, Jian Li; Bulloch, Andrew G M; Sajobi, Tolulope

2016-02-01

Women have a higher prevalence of major depressive episodes (MDE) than men, and the annual prevalence of MDE declines with age. Age by sex interactions may occur (a weakening of the sex effect with age), but are easily overlooked since individual studies lack statistical power to detect interactions. The objective of this study was to evaluate age by sex interactions in MDE prevalence. In Canada, a series of 10 national surveys conducted between 1996 and 2013 assessed MDE prevalence in respondents over the age of 14. Treating age as a continuous variable, binomial and linear regression was used to model age by sex interactions in each survey. To increase power, the survey-specific interaction coefficients were then pooled using meta-analytic methods. The estimated interaction terms were homogeneous. In the binomial regression model I (2) was 31.2 % and was not statistically significant (Q statistic = 13.1, df = 9, p = 0.159). The pooled estimate (-0.004) was significant (z = 3.13, p = 0.002), indicating that the effect of sex became weaker with increasing age. This resulted in near disappearance of the sex difference in the 75+ age group. This finding was also supported by an examination of age- and sex-specific estimates pooled across the surveys. The association of MDE prevalence with sex becomes weaker with age. The interaction may reflect biological effect modification. Investigators should test for, and consider inclusion of age by sex interactions in epidemiological analyses of MDE prevalence.

Organic Ion Transporters and Statin Drug Interactions.

PubMed

Kellick, Kenneth

2017-11-25

Statin drug-drug interactions (DDIs) are both troublesome to patients as well as costly to medical resources. The ability to predict and avoid these events could lead to improved outcomes as well as patient satisfaction. This review will explore efforts to better understand and predict these interactions specifically related to one drug transport system, the organic anion-transporting polypeptides (OATPs) specifically OATP1B1 and OATP1B3. Since the publication of the discovery of OATPs, there have been various pharmacokinetic models that have been proposed to explain the variation in pharmacokinetic and clinical effects related to the OATPs. The effects in transport activity appear to be partially related to the individual polymorphisms studied. Drug-drug interactions can occur when other drugs compete for the metabolic site on the OATPs. Various medications are identified as substrates and/or inhibitors of the OATPs, thereby complicating the ability to fully predict the impact on levels and effects. All of the models reviewed claim successes but show limited clinical utility. There are specific populations that have been identified, predominately various Asian descendants that require lower doses of statins to avoid adverse events. The concept of attributing these actions to the OATPs has been explored, but current models cannot accurately predict statin blood levels or elimination constants. The current research only points to the differences in the human genome and the single-nucleotide polymorphisms that exist between us. Based upon the currently available studies, there is beginning to be a glimmer in the understanding how different populations respond to statin transport and elimination. Additionally and unfortunately, there are other enzymes to be studied to better predict patient differences. Clearly, there has been much work completed, yet many more questions require answering to better understand these transport proteins.

A latent modeling approach to genotype-phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype.

PubMed

McGrath, L M; Mustanski, B; Metzger, A; Pine, D S; Kistner-Griffin, E; Cook, E; Wakschlag, L S

2012-08-01

This study illustrates the application of a latent modeling approach to genotype-phenotype relationships and gene × environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the monoamine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N = 192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA × physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA.

Multiscale Asymptotics for the Skeleton of the Madden-Julian Oscillation and Tropical-Extratropical Interactions (Open Access)

DTIC Science & Technology

2015-11-30

equatorial baroclinic dynamics, and (iii) the interactive effects of moisture and convection. More specifically, the model integrates the dry...interactions 5 Par. Derivation Dim. val. Description β 2.3× 10−11 m−1s−1 Variation of Coriolis parameter with latitude θ0 300 K Potential temperature...tropical Coriolis force, and x and y denote the zonal and meridional coordinates. Without the moisture q and convection envelope a, system (1) is the two

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Modelling the development and arrangement of the primary vascular structure in plants.

PubMed

Cartenì, Fabrizio; Giannino, Francesco; Schweingruber, Fritz Hans; Mazzoleni, Stefano

2014-09-01

The process of vascular development in plants results in the formation of a specific array of bundles that run throughout the plant in a characteristic spatial arrangement. Although much is known about the genes involved in the specification of procambium, phloem and xylem, the dynamic processes and interactions that define the development of the radial arrangement of such tissues remain elusive. This study presents a spatially explicit reaction-diffusion model defining a set of logical and functional rules to simulate the differentiation of procambium, phloem and xylem and their spatial patterns, starting from a homogeneous group of undifferentiated cells. Simulation results showed that the model is capable of reproducing most vascular patterns observed in plants, from primitive and simple structures made up of a single strand of vascular bundles (protostele), to more complex and evolved structures, with separated vascular bundles arranged in an ordered pattern within the plant section (e.g. eustele). The results presented demonstrate, as a proof of concept, that a common genetic-molecular machinery can be the basis of different spatial patterns of plant vascular development. Moreover, the model has the potential to become a useful tool to test different hypotheses of genetic and molecular interactions involved in the specification of vascular tissues.

Mixed infections reveal virulence differences between host-specific bee pathogens.

PubMed

Klinger, Ellen G; Vojvodic, Svjetlana; DeGrandi-Hoffman, Gloria; Welker, Dennis L; James, Rosalind R

2015-07-01

Dynamics of host-pathogen interactions are complex, often influencing the ecology, evolution and behavior of both the host and pathogen. In the natural world, infections with multiple pathogens are common, yet due to their complexity, interactions can be difficult to predict and study. Mathematical models help facilitate our understanding of these evolutionary processes, but empirical data are needed to test model assumptions and predictions. We used two common theoretical models regarding mixed infections (superinfection and co-infection) to determine which model assumptions best described a group of fungal pathogens closely associated with bees. We tested three fungal species, Ascosphaera apis, Ascosphaera aggregata and Ascosphaera larvis, in two bee hosts (Apis mellifera and Megachile rotundata). Bee survival was not significantly different in mixed infections vs. solo infections with the most virulent pathogen for either host, but fungal growth within the host was significantly altered by mixed infections. In the host A. mellifera, only the most virulent pathogen was present in the host post-infection (indicating superinfective properties). In M. rotundata, the most virulent pathogen co-existed with the lesser-virulent one (indicating co-infective properties). We demonstrated that the competitive outcomes of mixed infections were host-specific, indicating strong host specificity among these fungal bee pathogens. Published by Elsevier Inc.

Simulation of Interaction of Strong Shocks with Gas Bubbles using the Direct Simulation Monte Carlo Method

NASA Astrophysics Data System (ADS)

Puranik, Bhalchandra; Watvisave, Deepak; Bhandarkar, Upendra

2016-11-01

The interaction of a shock with a density interface is observed in several technological applications such as supersonic combustion, inertial confinement fusion, and shock-induced fragmentation of kidney and gall-stones. The central physical process in this interaction is the mechanism of the Richtmyer-Meshkov Instability (RMI). The specific situation where the density interface is initially an isolated spherical or cylindrical gas bubble presents a relatively simple geometry that exhibits all the essential RMI processes such as reflected and refracted shocks, secondary instabilities, turbulence and mixing of the species. If the incident shocks are strong, the calorically imperfect nature needs to be modelled. In the present work, we have carried out simulations of the shock-bubble interaction using the DSMC method for such situations. Specifically, an investigation of the shock-bubble interaction with diatomic gases involving rotational and vibrational excitations at high temperatures is performed, and the effects of such high temperature phenomena will be presented.

Protein-surface interactions on stimuli-responsive polymeric biomaterials.

PubMed

Cross, Michael C; Toomey, Ryan G; Gallant, Nathan D

2016-03-04

Responsive surfaces: a review of the dependence of protein adsorption on the reversible volume phase transition in stimuli-responsive polymers. Specifically addressed are a widely studied subset: thermoresponsive polymers. Findings are also generalizable to other materials which undergo a similarly reversible volume phase transition. As of 2015, over 100,000 articles have been published on stimuli-responsive polymers and many more on protein-biomaterial interactions. Significantly, fewer than 100 of these have focused specifically on protein interactions with stimuli-responsive polymers. These report a clear trend of increased protein adsorption in the collapsed state compared to the swollen state. This control over protein interactions makes stimuli-responsive polymers highly useful in biomedical applications such as wound repair scaffolds, on-demand drug delivery, and antifouling surfaces. Outstanding questions are whether the protein adsorption is reversible with the volume phase transition and whether there is a time-dependence. A clear understanding of protein interactions with stimuli-responsive polymers will advance theoretical models, experimental results, and biomedical applications.

Temperature-dependent body size effects determine population responses to climate warming.

PubMed

Lindmark, Max; Huss, Magnus; Ohlberger, Jan; Gårdmark, Anna

2018-02-01

Current understanding of animal population responses to rising temperatures is based on the assumption that biological rates such as metabolism, which governs fundamental ecological processes, scale independently with body size and temperature, despite empirical evidence for interactive effects. Here, we investigate the consequences of interactive temperature- and size scaling of vital rates for the dynamics of populations experiencing warming using a stage-structured consumer-resource model. We show that interactive scaling alters population and stage-specific responses to rising temperatures, such that warming can induce shifts in population regulation and stage-structure, influence community structure and govern population responses to mortality. Analysing experimental data for 20 fish species, we found size-temperature interactions in intraspecific scaling of metabolic rate to be common. Given the evidence for size-temperature interactions and the ubiquity of size structure in animal populations, we argue that accounting for size-specific temperature effects is pivotal for understanding how warming affects animal populations and communities. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Three-Nucleon Forces and Triplet Pairing in Neutron Matter

NASA Astrophysics Data System (ADS)

Papakonstantinou, P.; Clark, J. W.

2017-12-01

The existence of superfluidity of the neutron component in the core of a neutron star, associated specifically with triplet P-wave pairing, is currently an open question that is central to interpretation of the observed cooling curves and other neutron-star observables. Ab initio theoretical calculations aimed at resolving this issue face unique challenges in the relevant high-density domain, which reaches beyond the saturation density of symmetrical nuclear matter. These issues include uncertainties in the three-nucleon (3N) interaction and in the effects of strong short-range correlations—and more generally of in-medium modification of nucleonic self-energies and interactions. A survey of existing solutions of the gap equations in the triplet channel demonstrates that the net impact on the gap magnitude of 3N forces, coupled channels, and mass renormalization shows extreme variation dependent on specific theoretical inputs, in some cases even pointing to the absence of a triplet gap, thus motivating a detailed analysis of competing effects within a well-controlled model. In the present study, we track the effects of the 3N force and in-medium modifications in the representative case of the ^3P_2 channel, based on the Argonne v_{18} two-nucleon (2N) interaction supplemented by 3N interactions of the Urbana IX family. Sensitivity of the results to the input interaction is clearly demonstrated. We point out consistency issues with respect to the simultaneous treatment of 3N forces and in-medium effects, which warrant further investigation. We consider this pilot study as the first step toward a systematic and comprehensive exploration of coupled-channel ^3P F_2 pairing using a broad range of 2N and 3N interactions from the current generation of refined semi-phenomenological models and models derived from chiral effective field theory.

Knowing and acting in the clinical workplace: trainees' perspectives on modelling and feedback.

PubMed

Stegeman, J H; Schoten, E J; Terpstra, O T

2013-10-01

In this article we discuss clinical workplace learning using a dual approach: a theoretical one and an empirical one. Drawing on the philosophical work of Aristotle, Polanyi and Schön we posit that the 'knowing and acting' underpinning day-to-day medical practice is personal and embraces by nature a tacit dimension. Consequently, imparting and acquiring this knowledge type necessitates personal interaction between trainer and trainee. The tacit dimension particularly influences modelling and feedback. In our empirical exploration we explore these educational routes in two disparate disciplines: surgery and paediatrics. We use a longitudinal design with in-depth interviewing. Our conclusion on modelling is: modelling is a dynamic and fragmented process reflecting discipline bound characteristics and working styles. On feedback it is: 'feedback' serves as vehicle for three distinctive forms of commenting on performance, each holding a specific power of expression for learning. We propose to view clinical workplace learning as: an interactive master-apprenticeship model encompassing modelling and feedback as natural educational routes. We conceptualise modelling and feedback as 'function' of interaction (developing grounded theory). Modelling function and feedback function may serve to study these routes as didactical components of ongoing interaction between trainer and trainee rather than an educator-driven series of unrelated events.

NOXclass: prediction of protein-protein interaction types.

PubMed

Zhu, Hongbo; Domingues, Francisco S; Sommer, Ingolf; Lengauer, Thomas

2006-01-19

Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at http://noxclass.bioinf.mpi-inf.mpg.de/.

Mean-field behavior in coupled oscillators with attractive and repulsive interactions.

PubMed

Hong, Hyunsuk; Strogatz, Steven H

2012-05-01

We consider a variant of the Kuramoto model of coupled oscillators in which both attractive and repulsive pairwise interactions are allowed. The sign of the coupling is assumed to be a characteristic of a given oscillator. Specifically, some oscillators repel all the others, thus favoring an antiphase relationship with them. Other oscillators attract all the others, thus favoring an in-phase relationship. The Ott-Antonsen ansatz is used to derive the exact low-dimensional dynamics governing the system's long-term macroscopic behavior. The resulting analytical predictions agree with simulations of the full system. We explore the effects of changing various parameters, such as the width of the distribution of natural frequencies and the relative strengths and proportions of the positive and negative interactions. For the particular model studied here we find, unexpectedly, that the mixed interactions produce no new effects. The system exhibits conventional mean-field behavior and displays a second-order phase transition like that found in the original Kuramoto model. In contrast to our recent study of a different model with mixed interactions [Phys. Rev. Lett. 106, 054102 (2011)], the π state and traveling-wave state do not appear for the coupling type considered here.

The Poisson-Helmholtz-Boltzmann model.

PubMed

Bohinc, K; Shrestha, A; May, S

2011-10-01

We present a mean-field model of a one-component electrolyte solution where the mobile ions interact not only via Coulomb interactions but also through a repulsive non-electrostatic Yukawa potential. Our choice of the Yukawa potential represents a simple model for solvent-mediated interactions between ions. We employ a local formulation of the mean-field free energy through the use of two auxiliary potentials, an electrostatic and a non-electrostatic potential. Functional minimization of the mean-field free energy leads to two coupled local differential equations, the Poisson-Boltzmann equation and the Helmholtz-Boltzmann equation. Their boundary conditions account for the sources of both the electrostatic and non-electrostatic interactions on the surface of all macroions that reside in the solution. We analyze a specific example, two like-charged planar surfaces with their mobile counterions forming the electrolyte solution. For this system we calculate the pressure between the two surfaces, and we analyze its dependence on the strength of the Yukawa potential and on the non-electrostatic interactions of the mobile ions with the planar macroion surfaces. In addition, we demonstrate that our mean-field model is consistent with the contact theorem, and we outline its generalization to arbitrary interaction potentials through the use of a Laplace transformation. © EDP Sciences / Società Italiana di Fisica / Springer-Verlag 2011

A proposal for a new multiaxial model of psychiatric diagnosis. A continuum-based patient model derived from evolutionary developmental gene-environment interaction.

PubMed

Leigh, Hoyle

2009-01-01

To review recent genetic and neuroscientific research on psychiatric syndromes based on the current diagnostic scheme, and develop a better-fitting multiaxial patient-oriented diagnostic model. DSM I, published in 1952, considered psychiatric illnesses as reactions or extremes of adaptations of the patient's personality to stressful environmental demands. Personality itself was determined by constitution and psychodynamic development. In 1980, this continuum model gave way to an atheoretical categorical diagnostic scheme (DSM III), based on research diagnostic criteria for obtaining 'pure cultures' of patients for biological research. Subsequent research using the 'pure cultures' suggests that psychiatric syndromes represent a phenotypic continuum determined by genes, childhood traumas, and recent stress, mitigated by childhood nurturance, education, and current social support. Specific gene x childhood abuse x recent stress interactions have been discovered, which may serve as a model of how interacting vulnerability genes may or may not result in a psychiatric syndrome, depending on the individual's developmental history and current stress. A continuum model is proposed, with genes interacting with early experiences of stress or nurturance resulting in brain states that may evince minor but persistent symptoms (neurosis) or maladaptive patterns of behavior (personality disorder). The addition of recent or current stress may precipitate a major psychiatric syndrome. While a severe genetic predisposition, such as a mutation, may be sufficient to cause a major syndrome, major psychiatric syndromes are best conceptualized as dysregulation of evolutionarily adaptive brain functions, such as anxiety and vigilance. A new multiaxial model of psychiatric diagnosis is proposed based on this model: axis I for phenomenological diagnoses that include major psychiatric syndromes (e.g. depressive syndrome, psychosis), neuroses, personality disorders, and isolated symptoms; axis II for geno-neuroscience diagnoses, some of which may represent biological conditions associated with axis I, i.e. genes, specific brain morphology, and the functional state of specific brain areas based on laboratory and imaging studies; axis III for medical diseases and conditions; axis IV for stress (childhood, recent, and current); axis V for psychosocial assets (intelligence, education, school/work, social support, and global assessment of functioning) over past 5 years and current. (c) 2008 S. Karger AG, Basel.

Options and Consequences: Water Banking/Leasing Issues Explored for the Rio Grande in Southern New Mexico

NASA Astrophysics Data System (ADS)

Brookshire, D. S.; Coursey, D.; Dimint, A.; Tidwell, V.

2004-12-01

Since 1950, the demand for water has more than doubled in the United States. Historically, growing demands have been met by increasing reservoir capacity and through groundwater mining, often at the expense of environmental and cultural concerns. The future is expected to hold much the same. Demand for water will continue to increase particularly in response to the expanding urban sector, while growing concerns over the environment are prompting interest in allocating more water for in-stream uses. So, where will this water come from? Virtually all water supplies are allocated. Providing for new uses requires a reduction in the amount of water dedicated to existing uses. The water banking/leasing model is formulated within a system dynamics context using the object oriented commercial software package, Powersimä Studio 2003. System dynamics provides a unique mathematical framework for integrating the natural and social processes important to managing natural resources and can provide an interactive interface for engaging the public in the decision process. These system level models focus on capturing the broad structure of the system, specifically the feedback and time delays between interacting subsystems. The spatially aggregated models are computationally efficient allowing simulations to be conducted on a PC in a matter of seconds to minutes. By employing interactive interfaces, these models can be taken directly to the public or decision maker. To demonstrate the water banking/leasing model, application has been made to potential markets on the Rio Grande. Specifically, the model spans the reach between Elephant Butte Reservoir (central New Mexico) and the New Mexico/Texas state line. Primary sectors in the model include climate, surface and groundwater, riparian and aquatic habitat, watershed processes, water quality, water demand (residential, commercial, industrial, institution, and agricultural), economics, policy, and legal institutions. Within the model the basin is divided into four distinct but interacting reaches and a monthly time-step is employed. River operations and water demand trends have been calibrated to historical data.

Changes in flexibility upon binding: Application of the self-consistent pair contact probability method to protein-protein interactions

NASA Astrophysics Data System (ADS)

Canino, Lawrence S.; Shen, Tongye; McCammon, J. Andrew

2002-12-01

We extend the self-consistent pair contact probability method to the evaluation of the partition function for a protein complex at thermodynamic equilibrium. Specifically, we adapt the method for multichain models and introduce a parametrization for amino acid-specific pairwise interactions. This method is similar to the Gaussian network model but allows for the adjusting of the strengths of native state contacts. The method is first validated on a high resolution x-ray crystal structure of bovine Pancreatic Phospholipase A2 by comparing calculated B-factors with reported values. We then examine binding-induced changes in flexibility in protein-protein complexes, comparing computed results with those obtained from x-ray crystal structures and molecular dynamics simulations. In particular, we focus on the mouse acetylcholinesterase:fasciculin II and the human α-thrombin:thrombomodulin complexes.

Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity.

PubMed

Zander, Thorsten O; Krol, Laurens R; Birbaumer, Niels P; Gramann, Klaus

2016-12-27

The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator's mindset. Neuroadaptive technology significantly widens the communication bottleneck and has the potential to fundamentally change the way we interact with technology.

Recognition, survival and persistence of Staphylococcus aureus in the model host Tenebrio molitor.

PubMed

Dorling, Jack; Moraes, Caroline; Rolff, Jens

2015-02-01

The degree of specificity of any given immune response to a parasite is governed by the complexity and variation of interactions between host and pathogen derived molecules. Here, we assess the extent to which recognition and immuno-resistance of cell wall mutants of the pathogen Staphylococcus aureus may contribute to establishment and maintenance of persistent infection in the model insect host, Tenebrio molitor. The cell surface of S. aureus is decorated with various molecules, including glycopolymers such as wall teichoic acid (WTA). WTA is covalently bound to peptidoglycan (PGN) and its absence has been associated with increased recognition of PGN by host receptors (PGRPs). WTA is also further modified by other molecules such as D-alanine (D-alanylation). Both the level of WTA expression and its D-alanylation were found to be important in the mediation of the host-parasite interaction in this model system. Specifically, WTA itself was seen to influence immune recognition, while D-alanylation of WTA was found to increase immuno-resistance and was associated with prolonged persistence of S. aureus in T. molitor. These results implicate WTA and its D-alanylation as important factors in the establishment and maintenance of persistent infection, affecting different critical junctions in the immune response; through potential evasion of recognition by PGRPs and resistance to humoral immune effectors during prolonged exposure to the immune system. This highlights a mechanism by which specificity in this host-parasite interaction may arise. Copyright © 2014 Elsevier Ltd. All rights reserved.

A male-specific QTL for social interaction behavior in mice mapped with automated pattern detection by a hidden Markov model incorporated into newly developed freeware.

PubMed

Arakawa, Toshiya; Tanave, Akira; Ikeuchi, Shiho; Takahashi, Aki; Kakihara, Satoshi; Kimura, Shingo; Sugimoto, Hiroki; Asada, Nobuhiko; Shiroishi, Toshihiko; Tomihara, Kazuya; Tsuchiya, Takashi; Koide, Tsuyoshi

2014-08-30

Owing to their complex nature, social interaction tests normally require the observation of video data by a human researcher, and thus are difficult to use in large-scale studies. We previously established a statistical method, a hidden Markov model (HMM), which enables the differentiation of two social states ("interaction" and "indifference"), and three social states ("sniffing", "following", and "indifference"), automatically in silico. Here, we developed freeware called DuoMouse for the rapid evaluation of social interaction behavior. This software incorporates five steps: (1) settings, (2) video recording, (3) tracking from the video data, (4) HMM analysis, and (5) visualization of the results. Using DuoMouse, we mapped a genetic locus related to social interaction. We previously reported that a consomic strain, B6-Chr6C(MSM), with its chromosome 6 substituted for one from MSM/Ms, showed more social interaction than C57BL/6 (B6). We made four subconsomic strains, C3, C5, C6, and C7, each of which has a shorter segment of chromosome 6 derived from B6-Chr6C, and conducted social interaction tests on these strains. DuoMouse indicated that C6, but not C3, C5, and C7, showed higher interaction, sniffing, and following than B6, specifically in males. The data obtained by human observation showed high concordance to those from DuoMouse. The results indicated that the MSM-derived chromosomal region present in C6-but not in C3, C5, and C7-associated with increased social behavior. This method to analyze social interaction will aid primary screening for difference in social behavior in mice. Copyright © 2014 Elsevier B.V. All rights reserved.

Treating personality-relationship transactions with respect: narrow facets, advanced models, and extended time frames.

PubMed

Mund, Marcus; Neyer, Franz J

2014-08-01

Contrary to premises of dynamic transactionism, most studies investigating personality-relationship transaction only found personality effects on relationships but failed to find effects of relationship experiences on personality development. The current study reconsiders this issue in 3 ways. First, alongside the broad Big Five characteristics (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness), specific personality facets were considered to make comparisons with relationships more symmetric. Second, a recent extension of latent change modeling was applied allowing for a theoretically more appropriate model that compensates for the shortcomings of traditionally used cross-lagged panel or growth curve models. Third, personality-relationship transaction was studied from young adulthood to midlife using a 15-year longitudinal study with 654 German adults. Results showed patterns of personality-relationship transaction with the romantic partner, friends, kin, and other interaction partners. Specifically, the development of Neuroticism, Agreeableness, and Conscientiousness and their facets was closely interacting with partner and friend relationships, underlining the importance of these relationships for personality maturation during the adult years. We conclude that relationship effects have often been underestimated in previous studies. They are not bound to specific developmental periods, such as emerging adulthood, but their detection depends on the modeling approach and the analysis level (broad dimensions vs. facets). Relationship effects are most likely to occur in relationships that reflect self-selected life styles and circumstances.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

Biodiversity in models of cyclic dominance is preserved by heterogeneity in site-specific invasion rates.

PubMed

Szolnoki, Attila; Perc, Matjaž

2016-12-05

Global, population-wide oscillations in models of cyclic dominance may result in the collapse of biodiversity due to the accidental extinction of one species in the loop. Previous research has shown that such oscillations can emerge if the interaction network has small-world properties, and more generally, because of long-range interactions among individuals or because of mobility. But although these features are all common in nature, global oscillations are rarely observed in actual biological systems. This begets the question what is the missing ingredient that would prevent local oscillations to synchronize across the population to form global oscillations. Here we show that, although heterogeneous species-specific invasion rates fail to have a noticeable impact on species coexistence, randomness in site-specific invasion rates successfully hinders the emergence of global oscillations and thus preserves biodiversity. Our model takes into account that the environment is often not uniform but rather spatially heterogeneous, which may influence the success of microscopic dynamics locally. This prevents the synchronization of locally emerging oscillations, and ultimately results in a phenomenon where one type of randomness is used to mitigate the adverse effects of other types of randomness in the system.

Biodiversity in models of cyclic dominance is preserved by heterogeneity in site-specific invasion rates

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2016-12-01

Global, population-wide oscillations in models of cyclic dominance may result in the collapse of biodiversity due to the accidental extinction of one species in the loop. Previous research has shown that such oscillations can emerge if the interaction network has small-world properties, and more generally, because of long-range interactions among individuals or because of mobility. But although these features are all common in nature, global oscillations are rarely observed in actual biological systems. This begets the question what is the missing ingredient that would prevent local oscillations to synchronize across the population to form global oscillations. Here we show that, although heterogeneous species-specific invasion rates fail to have a noticeable impact on species coexistence, randomness in site-specific invasion rates successfully hinders the emergence of global oscillations and thus preserves biodiversity. Our model takes into account that the environment is often not uniform but rather spatially heterogeneous, which may influence the success of microscopic dynamics locally. This prevents the synchronization of locally emerging oscillations, and ultimately results in a phenomenon where one type of randomness is used to mitigate the adverse effects of other types of randomness in the system.

Electrostatically Accelerated Coupled Binding and Folding of Intrinsically Disordered Proteins

PubMed Central

Ganguly, Debabani; Otieno, Steve; Waddell, Brett; Iconaru, Luigi; Kriwacki, Richard W.; Chen, Jianhan

2012-01-01

Intrinsically disordered proteins (IDPs) are now recognized to be prevalent in biology, and many potential functional benefits have been discussed. However, the frequent requirement of peptide folding in specific interactions of IDPs could impose a kinetic bottleneck, which could be overcome only by efficient folding upon encounter. Intriguingly, existing kinetic data suggest that specific binding of IDPs is generally no slower than that of globular proteins. Here, we exploited the cell cycle regulator p27Kip1 (p27) as a model system to understand how IDPs might achieve efficient folding upon encounter for facile recognition. Combining experiments and coarse-grained modeling, we demonstrate that long-range electrostatic interactions between enriched charges on p27 and near its binding site on cyclin A not only enhance the encounter rate (i.e., electrostatic steering), but also promote folding-competent topologies in the encounter complexes, allowing rapid subsequent formation of short-range native interactions en route to the specific complex. In contrast, nonspecific hydrophobic interactions, while hardly affecting the encounter rate, can significantly reduce the efficiency of folding upon encounter and lead to slower binding kinetics. Further analysis of charge distributions in a set of known IDP complexes reveals that, although IDP binding sites tend to be more hydrophobic compared to the rest of the target surface, their vicinities are frequently enriched with charges to complement those on IDPs. This observation suggests that electrostatically accelerated encounter and induced folding might represent a prevalent mechanism for promoting facile IDP recognition. PMID:22721951

Automatic programming of simulation models

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, Shou X.; Dwan, Wen S.

1990-01-01

The concepts of software engineering were used to improve the simulation modeling environment. Emphasis was placed on the application of an element of rapid prototyping, or automatic programming, to assist the modeler define the problem specification. Then, once the problem specification has been defined, an automatic code generator is used to write the simulation code. The following two domains were selected for evaluating the concepts of software engineering for discrete event simulation: manufacturing domain and a spacecraft countdown network sequence. The specific tasks were to: (1) define the software requirements for a graphical user interface to the Automatic Manufacturing Programming System (AMPS) system; (2) develop a graphical user interface for AMPS; and (3) compare the AMPS graphical interface with the AMPS interactive user interface.

Computational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis.

PubMed

Amor, N; Geris, L; Vander Sloten, J; Van Oosterwyck, H

2011-02-01

Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet-biomaterial interactions and/or interaction with (pre-)osteoblast cells. We have developed a computational model of implant endosseous healing that takes into account these interactions. We hypothesized that the initial attachment and growth factor release from activated platelets is crucial in achieving contact osteogenesis. In order to investigate this, a computational model was applied to an animal experiment [7] that looked at the effect of surface microroughness on endosseous healing. Surface-specific model parameters were implemented based on in vitro data (Lincks et al. Biomaterials 1998;19:2219-32). The predicted spatio-temporal patterns of bone formation correlated with the histological data. It was found that contact osteogenesis could not be predicted if only the osteogenic response of cells was up-regulated by surface microroughness. This could only be achieved if platelet-biomaterial interactions were sufficiently up-regulated as well. These results confirmed our hypothesis and demonstrate the added value of the computational model to study the importance of surface-mediated events for peri-implant endosseous healing. Copyright © 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Interaction strength combinations and the overfishing of a marine food web.

PubMed

Bascompte, Jordi; Melián, Carlos J; Sala, Enric

2005-04-12

The stability of ecological communities largely depends on the strength of interactions between predators and their prey. Here we show that these interaction strengths are structured nonrandomly in a large Caribbean marine food web. Specifically, the cooccurrence of strong interactions on two consecutive levels of food chains occurs less frequently than expected by chance. Even when they occur, these strongly interacting chains are accompanied by strong omnivory more often than expected by chance. By using a food web model, we show that these interaction strength combinations reduce the likelihood of trophic cascades after the overfishing of top predators. However, fishing selectively removes predators that are overrepresented in strongly interacting chains. Hence, the potential for strong community-wide effects remains a threat.

Interaction strength combinations and the overfishing of a marine food web

PubMed Central

Bascompte, Jordi; Melián, Carlos J.; Sala, Enric

2005-01-01

The stability of ecological communities largely depends on the strength of interactions between predators and their prey. Here we show that these interaction strengths are structured nonrandomly in a large Caribbean marine food web. Specifically, the cooccurrence of strong interactions on two consecutive levels of food chains occurs less frequently than expected by chance. Even when they occur, these strongly interacting chains are accompanied by strong omnivory more often than expected by chance. By using a food web model, we show that these interaction strength combinations reduce the likelihood of trophic cascades after the overfishing of top predators. However, fishing selectively removes predators that are overrepresented in strongly interacting chains. Hence, the potential for strong community-wide effects remains a threat. PMID:15802468

Fluorescence correlation spectroscopy as a method for assessment of interactions between phage displaying antibodies and soluble antigen

PubMed Central

Lagerkvist, Ann Catrin; Földes-Papp, Zeno; Persson, Mats A.A.; Rigler, Rudolf

2001-01-01

Phage display is widely used for expression of combinatorial libraries, not least for protein engineering purposes. Precise selection at the single molecule level will provide an improved tool for generating proteins with complex and distinct properties from large molecular libraries. To establish such an improved selection system, we here report the detection of specific interactions between phage with displayed antibody fragments and fluorescently labeled soluble antigen based on Fluorescence Correlation Spectroscopy (FCS). Our novel strategy comprises the use of two separate fluorochromes for detection of the phage–antigen complex, either with labeled antiphage antibody or using a labeled antigen. As a model system, we studied a human monoclonal antibody to the hepatitis-C virus (HCV) envelope protein E2 and its cognate antigen (rE2 or rE1/E2). We could thus assess the specific interactions and determine the fraction of specific versus background phage (26% specific phage). Aggregation of these particular antigens made it difficult to reliably utilize the full potential of cross-correlation studies using the two labels simultaneously. However, with true monomeric proteins, this will certainly be possible, offering a great advantage in a safer and highly specific detection system. PMID:11468349

Chromatin immunoprecipitation (ChIP) method for non-model fruit flies (Diptera: Tephritidae) and evidence of histone modifications.

PubMed

Nagalingam, Kumaran; Lorenc, Michał T; Manoli, Sahana; Cameron, Stephen L; Clarke, Anthony R; Dudley, Kevin J

2018-01-01

Interactions between DNA and proteins located in the cell nucleus play an important role in controlling physiological processes by specifying, augmenting and regulating context-specific transcription events. Chromatin immunoprecipitation (ChIP) is a widely used methodology to study DNA-protein interactions and has been successfully used in various cell types for over three decades. More recently, by combining ChIP with genomic screening technologies and Next Generation Sequencing (e.g. ChIP-seq), it has become possible to profile DNA-protein interactions (including covalent histone modifications) across entire genomes. However, the applicability of ChIP-chip and ChIP-seq has rarely been extended to non-model species because of a number of technical challenges. Here we report a method that can be used to identify genome wide covalent histone modifications in a group of non-model fruit fly species (Diptera: Tephritidae). The method was developed by testing and refining protocols that have been used in model organisms, including Drosophila melanogaster. We demonstrate that this method is suitable for a group of economically important pest fruit fly species, viz., Bactrocera dorsalis, Ceratitis capitata, Zeugodacus cucurbitae and Bactrocera tryoni. We also report an example ChIP-seq dataset for B. tryoni, providing evidence for histone modifications in the genome of a tephritid fruit fly for the first time. Since tephritids are major agricultural pests globally, this methodology will be a valuable resource to study taxa-specific evolutionary questions and to assist with pest management. It also provides a basis for researchers working with other non-model species to undertake genome wide DNA-protein interaction studies.

Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.

PubMed

Moënne-Loccoz, Cristóbal; Vergara, Rodrigo C; López, Vladimir; Mery, Domingo; Cosmelli, Diego

2017-01-01

Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

A new approach in the design of an interactive environment for teaching Hamiltonian digraphs

NASA Astrophysics Data System (ADS)

Iordan, A. E.; Panoiu, M.

2014-03-01

In this article the authors present the necessary steps in object orientated design of an interactive environment that is dedicated to the process of acquaintances assimilation in Hamiltonian graphs theory domain, especially for the simulation of algorithms which determine the Hamiltonian trails and circuits. The modelling of the interactive environment is achieved through specific UML diagrams representing the steps of analysis, design and implementation. This interactive environment is very useful for both students and professors, because computer programming domain, especially digraphs theory domain is comprehended and assimilated with difficulty by students.

Shock competition and circulation deposition in shock interactions with heavy prolate cylinders

NASA Astrophysics Data System (ADS)

Ray, Jaideep; Samtaney, R.; Zabusky, Norman J.

1998-11-01

We investigate the interaction of a shock wave with elliptical heavier-than-ambient gaseous cylinders. We identify two different modes of interaction between the incident and transmitted shocks on the leeward side of the cylinder which yeild different mechanisms for the baroclinic vorticity generation. We model the net baroclinic circulation generated on the interface by both the shocks and validate the model via numerical simulations of the Euler equations. The principal parameters governing the interaction are the Mach number of the shock (M), the density ratio of the two gases (η, η > 1), λ (the aspect ratio) and the ratio of specific heats of the two gases. We derive a time ratio which uniquely characterizes the mode of interaction. In the range 1.2 <= M <= 3.5, 1.54 <= η <= 5.04 and λ = 1.5 and 3.0, our model predicts circulation within 10 % of the simulation results. Further developments on this topic will be posted on the Web at http://www.caip.rutgers.edu/ ~jaray/ellipse/RM_ellipse.html.

Promoting Scientist Communications Through Graduate Summer School in Heliophysics and Space Physics

NASA Astrophysics Data System (ADS)

Gross, N. A.; Schrijver, K.; Bagenal, F.; Sojka, J. J.; Wiltberger, M. J.

2014-12-01

edagogical tools that promote student interaction can be applied successfully during graduate workshops to enhance community and communication among the participants and instructors. The NASA/LWS funded Heliophysics Summer School and the NSF funded Space Weather Summer School provide graduate students starting research in the field, and others who are involved in space physics, an opportunity to learn from and interact with leaders in the field and each other. These interactions can happen casually, but there are a number of programatic aspects that foster the interaction so that they can be as fruitful as possible during the short period. These include: specific "ice-breaker" activities, practicing "elevator speeches", embedded lecture questions, question cards, discussion questions, interactive lab activities, structured lab groups, and use of social media. We are continuing to develop new ways to foster profession interaction during these short courses. Along with enhancing their own learning, the inclusion of these strategies provides both the participants and the instructors with models of good pedagogical tools and builds community among the students. Our specific implementation of these strategies and evidence of success will be presented.

RNA degradation and models for post-transcriptional gene-silencing.

PubMed

Meins, F

2000-06-01

Post-transcriptional gene silencing (PTGS) is a form of stable but potentially reversible epigenetic modification, which frequently occurs in transgenic plants. The interaction in trans of genes with similar transcribed sequences results in sequence-specific degradation of RNAs derived from the genes involved. Highly expressed single-copy loci, transcribed inverted repeats, and poorly transcribed complex loci can act as sources of signals that trigger PTGS. In some cases, mobile, sequence-specific silencing signals can move from cell to cell or even over long distances in the plant. Several current models hold that silencing signals are 'aberrant' RNAs (aRNA), which differ in some way from normal mRNAs. The most likely candidates are small antisense RNAs (asRNA) and double-stranded RNAs (dsRNA). Direct evidence that these or other aRNAs found in silent tissues can induce PTGS is still lacking. Most current models assume that silencing signals interact with target RNAs in a sequence-specific fashion. This results in degradation, usually in the cytoplasm, by exonucleolytic as well as endonucleolytic pathways, which are not necessarily PTGS-specific. Biochemical-switch models hold that the silent state is maintained by a positive auto-regulatory loop. One possibility is that concentrations of hypothetical silencing signals above a critical threshold trigger their own production by self-replication, by degradation of target RNAs, or by a combination of both mechanisms. These models can account for the stability, reversibility and multiplicity of silent states; the strong influence of transcription rate of target genes on the incidence and stability of silencing, and the amplification and systemic propagation of motile silencing signals.

Monitoring Retroviral RNA Dimerization In Vivo via Hammerhead Ribozyme Cleavage

PubMed Central

Pal, Bijay K.; Scherer, Lisa; Zelby, Laurie; Bertrand, Edouard; Rossi, John J.

1998-01-01

We have used a strategy for colocalization of Psi (Ψ)-tethered ribozymes and targets to demonstrate that Ψ sequences are capable of specific interaction in the cytoplasm of both packaging and nonpackaging cells. These results indicate that current in vitro dimerization models may have in vivo counterparts. The methodology used may be applied to further genetic analyses on Ψ domain interactions in vivo. PMID:9733882

Interactive computer modeling of combustion chemistry and coalescence-dispersion modeling of turbulent combustion

NASA Technical Reports Server (NTRS)

Pratt, D. T.

1984-01-01

An interactive computer code for simulation of a high-intensity turbulent combustor as a single point inhomogeneous stirred reactor was developed from an existing batch processing computer code CDPSR. The interactive CDPSR code was used as a guide for interpretation and direction of DOE-sponsored companion experiments utilizing Xenon tracer with optical laser diagnostic techniques to experimentally determine the appropriate mixing frequency, and for validation of CDPSR as a mixing-chemistry model for a laboratory jet-stirred reactor. The coalescence-dispersion model for finite rate mixing was incorporated into an existing interactive code AVCO-MARK I, to enable simulation of a combustor as a modular array of stirred flow and plug flow elements, each having a prescribed finite mixing frequency, or axial distribution of mixing frequency, as appropriate. Further increase the speed and reliability of the batch kinetics integrator code CREKID was increased by rewriting in vectorized form for execution on a vector or parallel processor, and by incorporating numerical techniques which enhance execution speed by permitting specification of a very low accuracy tolerance.

More Precise Estimation of Lower-Level Interaction Effects in Multilevel Models.

PubMed

Loeys, Tom; Josephy, Haeike; Dewitte, Marieke

2018-01-01

In hierarchical data, the effect of a lower-level predictor on a lower-level outcome may often be confounded by an (un)measured upper-level factor. When such confounding is left unaddressed, the effect of the lower-level predictor is estimated with bias. Separating this effect into a within- and between-component removes such bias in a linear random intercept model under a specific set of assumptions for the confounder. When the effect of the lower-level predictor is additionally moderated by another lower-level predictor, an interaction between both lower-level predictors is included into the model. To address unmeasured upper-level confounding, this interaction term ought to be decomposed into a within- and between-component as well. This can be achieved by first multiplying both predictors and centering that product term next, or vice versa. We show that while both approaches, on average, yield the same estimates of the interaction effect in linear models, the former decomposition is much more precise and robust against misspecification of the effects of cross-level and upper-level terms, compared to the latter.

Coupling fluid-structure interaction with phase-field fracture

NASA Astrophysics Data System (ADS)

Wick, Thomas

2016-12-01

In this work, a concept for coupling fluid-structure interaction with brittle fracture in elasticity is proposed. The fluid-structure interaction problem is modeled in terms of the arbitrary Lagrangian-Eulerian technique and couples the isothermal, incompressible Navier-Stokes equations with nonlinear elastodynamics using the Saint-Venant Kirchhoff solid model. The brittle fracture model is based on a phase-field approach for cracks in elasticity and pressurized elastic solids. In order to derive a common framework, the phase-field approach is re-formulated in Lagrangian coordinates to combine it with fluid-structure interaction. A crack irreversibility condition, that is mathematically characterized as an inequality constraint in time, is enforced with the help of an augmented Lagrangian iteration. The resulting problem is highly nonlinear and solved with a modified Newton method (e.g., error-oriented) that specifically allows for a temporary increase of the residuals. The proposed framework is substantiated with several numerical tests. In these examples, computational stability in space and time is shown for several goal functionals, which demonstrates reliability of numerical modeling and algorithmic techniques. But also current limitations such as the necessity of using solid damping are addressed.

Hemodynamic Assessment of Compliance of Pre-Stressed Pulmonary Valve-Vasculature in Patient Specific Geometry Using an Inverse Algorithm

NASA Astrophysics Data System (ADS)

Hebbar, Ullhas; Paul, Anup; Banerjee, Rupak

2016-11-01

Image based modeling is finding increasing relevance in assisting diagnosis of Pulmonary Valve-Vasculature Dysfunction (PVD) in congenital heart disease patients. This research presents compliant artery - blood interaction in a patient specific Pulmonary Artery (PA) model. This is an improvement over our previous numerical studies which assumed rigid walled arteries. The impedance of the arteries and the energy transfer from the Right Ventricle (RV) to PA is governed by compliance, which in turn is influenced by the level of pre-stress in the arteries. In order to evaluate the pre-stress, an inverse algorithm was developed using an in-house script written in MATLAB and Python, and implemented using the Finite Element Method (FEM). This analysis used a patient specific material model developed by our group, in conjunction with measured pressure (invasive) and velocity (non-invasive) values. The analysis was performed on an FEM solver, and preliminary results indicated that the Main PA (MPA) exhibited higher compliance as well as increased hysteresis over the cardiac cycle when compared with the Left PA (LPA). The computed compliance values for the MPA and LPA were 14% and 34% lesser than the corresponding measured values. Further, the computed pressure drop and flow waveforms were in close agreement with the measured values. In conclusion, compliant artery - blood interaction models of patient specific geometries can play an important role in hemodynamics based diagnosis of PVD.

(Fish) Food for Thought: Authority Shifts in the Interaction between Mathematics and Reality

ERIC Educational Resources Information Center

Peled, Irit

2010-01-01

This theoretical paper explores the decision-making process involved in modelling and mathematizing situations during problem solving. Specifically, it focuses on the authority behind these choices (i.e., what or who determines the chosen mathematical models). We show that different types of situations involve different sources of authority,…

Silencing the Center: Local Knowledge and Imported Model in Learning Disabilities

ERIC Educational Resources Information Center

Bazna, Maysaa

2009-01-01

This qualitative study investigates the interaction between local and imported knowledges in a specific case of transnational importation; the whole-sale importation of the American medical learning disabilities (LDs) model in Kuwait. A discourse analysis of the narratives of local educators at the only school for LDs in the country reveals a…

A Professional Learning Community Activity for Science Teachers: How to Incorporate Discourse-Rich Instructional Strategies into Science Lessons

ERIC Educational Resources Information Center

Lewis, Elizabeth; Baker, Dale; Watts, Nievita Bueno; Lang, Michael

2014-01-01

In this article we describe current educational research underlying a comprehensive model for building a scientific classroom discourse community. We offer a professional development activity for a school-based professional learning community, providing specific science instructional strategies within this interactive teaching model. This design…

Understanding the Behaviors of Stealth Applicants in the College Search Process

ERIC Educational Resources Information Center

Dupaul, Stephanie

2010-01-01

Successful enrollment management uses predictive modeling to achieve specific goals for admission rates, yield rates, and class size. Many of these models rely on evaluating an applicant's interest in the institution through measures of pre-application engagement. Recent increases in the number of applicants who do not visibly interact with…

Using the [beta][subscript 2]-Adrenoceptor for Structure-Based Drug Design

ERIC Educational Resources Information Center

Manallack, David T.; Chalmers, David K.; Yuriev, Elizabeth

2010-01-01

The topics of molecular modeling and drug design are studied in a medicinal chemistry course. The recently reported structures of several G protein-coupled receptors (GPCR) with bound ligands have been used to develop a simple computer-based experiment employing molecular-modeling software. Knowledge of the specific interactions between a ligand…

Methods for integrated modeling of landscape change: Interior Northwest Landscape Analysis System.

Treesearch

Jane L. Hayes; Alan. A. Ager; R. James Barbour

2004-01-01

The Interior Northwest Landscape Analysis System (INLAS) links a number of resource, disturbance, and landscape simulations models to examine the interactions of vegetative succession, management, and disturbance with policy goals. The effects of natural disturbance like wildfire, herbivory, forest insects and diseases, as well as specific management actions are...

Using Five Stage Model to Design of Collaborative Learning Environments in Second Life

ERIC Educational Resources Information Center

Orhan, Sevil; Karaman, M. Kemal

2014-01-01

Specifically Second Life (SL) among virtual worlds draws attention of researchers to form collaborative learning environments (Sutcliffe & Alrayes, 2012) since it could be used as a rich platform to simulate a real environment containing many collaborative learning characteristics and interaction tools within itself. Five Stage Model (FSM)…

Meeting the Deadline: Why, When and How

NASA Technical Reports Server (NTRS)

Dignum, Frank; Broersen, Jan; Dignum, Virginia; Meyer, John-Jules

2004-01-01

A normative system is defined as any set of interacting agents whose behavior can usefully be regarded as norm-directed. Most organizations, and more specifically institutions, fall under this definition. Interactions in these normative systems are regulated by normative templates that describe desired behavior in terms of deontic concepts (obligations, prohibitions and permissions), deadlines, violations and sanctions. Agreements between agents, and between an agent and the society, can then be specified by means of contracts. Contracts provide flexible but verifiable means to integrate society requirements and agent autonomy. and are an adequate means for the explicit specification of interactions. From the society perspective, it is important that these contracts adhere to the specifications described in the model of the organization. If we want to automate such verifications, we have to formalize the languages used for contracts and for the specification of organizations. The logic LCR is based on deontic temporal logic. LCR is an expressive language for describing interaction in multi-agent systems, including obligations with deadlines. Deadlines are important norms in most interactions between agents. Intuitively, a deadline states that an agent should perform an action before a certain point in time. The obligation to perform the action starts at the moment the deadline becomes active. E.g. when a contract is signed or approved. If the action is not performed in time a violation of the deadline occurs. It can be specified independently what measure has to be taken in this case. In this paper we investigate the deadline concept in more detail. The paper is organized as follows. Section 2 defines the variant of CTL we use. In section 3, we discuss the basic intuitions of deadlines. Section 4 presents a first intuitive formalization for deadlines. In section 5, we look at a more complex model for deadlines trying to catch some more practical aspects. Finally, in section 6 we present issues for future work and our conciusions.

Modelling the Transport of Nanoparticles under Blood Flow using an Agent-based Approach.

PubMed

Fullstone, Gavin; Wood, Jonathan; Holcombe, Mike; Battaglia, Giuseppe

2015-06-10

Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow.

Large Advanced Space Systems (LASS) computer-aided design program additions

NASA Technical Reports Server (NTRS)

Farrell, C. E.

1982-01-01

The LSS preliminary and conceptual design requires extensive iteractive analysis because of the effects of structural, thermal, and control intercoupling. A computer aided design program that will permit integrating and interfacing of required large space system (LSS) analyses is discussed. The primary objective of this program is the implementation of modeling techniques and analysis algorithms that permit interactive design and tradeoff studies of LSS concepts. Eight software modules were added to the program. The existing rigid body controls module was modified to include solar pressure effects. The new model generator modules and appendage synthesizer module are integrated (interfaced) to permit interactive definition and generation of LSS concepts. The mass properties module permits interactive specification of discrete masses and their locations. The other modules permit interactive analysis of orbital transfer requirements, antenna primary beam n, and attitude control requirements.

Gene by environment interactions influencing reading disability and the inattentive symptom dimension of attention deficit/hyperactivity disorder.

PubMed

Rosenberg, Jenni; Pennington, Bruce F; Willcutt, Erik G; Olson, Richard K

2012-03-01

Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G × E) interactions. This study used behavioral genetic methods to replicate these opposite G × E interactions in a sample of same-sex monozygotic and dizygotic twin pairs from the Colorado Learning Disabilities Research Center (CLDRC; DeFries et al., 1997) and to test a genetic hypothesis for why these opposite interactions occur. We replicated opposite G × E interactions for RD (bioecological) and ADHD-I (diathesis-stress) with parental education in the same sample of participants. The genetic hypothesis for this opposite pattern of interactions is that only genes specific to each disorder enter into these opposite interactions, not the shared genes underlying their comorbidity. To test this hypothesis, we used single models with an exploratory three-way interaction, in which the G × E interactions for each disorder were moderated by comorbidity. Neither three-way interaction was significant. The heritability of RD did not vary as a function of parental education and ADHD-I. Similarly, the heritability of ADHD-I did not vary as a function of parental education and RD. We documented opposite G × E interactions in RD and ADHD-I in the same overall twin sample, but the explanation for this apparent paradox remains unclear. Examining specific genes and more specific environmental factors may help resolve the paradox. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.

LEOrbit: A program to calculate parameters relevant to modeling Low Earth Orbit spacecraft-plasma interaction

NASA Astrophysics Data System (ADS)

Marchand, R.; Purschke, D.; Samson, J.

2013-03-01

Understanding the physics of interaction between satellites and the space environment is essential in planning and exploiting space missions. Several computer models have been developed over the years to study this interaction. In all cases, simulations are carried out in the reference frame of the spacecraft and effects such as charging, the formation of electrostatic sheaths and wakes are calculated for given conditions of the space environment. In this paper we present a program used to compute magnetic fields and a number of space plasma and space environment parameters relevant to Low Earth Orbits (LEO) spacecraft-plasma interaction modeling. Magnetic fields are obtained from the International Geophysical Reference Field (IGRF) and plasma parameters are obtained from the International Reference Ionosphere (IRI) model. All parameters are computed in the spacecraft frame of reference as a function of its six Keplerian elements. They are presented in a format that can be used directly in most spacecraft-plasma interaction models. Catalogue identifier: AENY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 270308 No. of bytes in distributed program, including test data, etc.: 2323222 Distribution format: tar.gz Programming language: FORTRAN 90. Computer: Non specific. Operating system: Non specific. RAM: 7.1 MB Classification: 19, 4.14. External routines: IRI, IGRF (included in the package). Nature of problem: Compute magnetic field components, direction of the sun, sun visibility factor and approximate plasma parameters in the reference frame of a Low Earth Orbit satellite. Solution method: Orbit integration, calls to IGRF and IRI libraries and transformation of coordinates from geocentric to spacecraft frame reference. Restrictions: Low Earth orbits, altitudes between 150 and 2000 km. Running time: Approximately two seconds to parameterize a full orbit with 1000 points.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm

PubMed Central

Yu, Isseki; Mori, Takaharu; Ando, Tadashi; Harada, Ryuhei; Jung, Jaewoon; Sugita, Yuji; Feig, Michael

2016-01-01

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology. DOI: http://dx.doi.org/10.7554/eLife.19274.001 PMID:27801646

Inferring Interaction Force from Visual Information without Using Physical Force Sensors.

PubMed

Hwang, Wonjun; Lim, Soo-Chul

2017-10-26

In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating the interaction force against a target object, where the shape of the object is changed by an external force. The force applied to the target can be estimated by means of the visual shape changes. However, the shape differences in the images are not very clear. To address this problem, we formulate a recurrent neural network-based deep model with fully-connected layers, which models complex temporal dynamics from the visual representations. Extensive evaluations show that the proposed learning models successfully estimate the interaction forces using only the corresponding sequential images, in particular in the case of three objects made of different materials, a sponge, a PET bottle, a human arm, and a tube. The forces predicted by the proposed method are very similar to those measured by force sensors.

Phase relations in a forced turbulent boundary layer: implications for modelling of high Reynolds number wall turbulence.

PubMed

Duvvuri, Subrahmanyam; McKeon, Beverley

2017-03-13

Phase relations between specific scales in a turbulent boundary layer are studied here by highlighting the associated nonlinear scale interactions in the flow. This is achieved through an experimental technique that allows for targeted forcing of the flow through the use of a dynamic wall perturbation. Two distinct large-scale modes with well-defined spatial and temporal wavenumbers were simultaneously forced in the boundary layer, and the resulting nonlinear response from their direct interactions was isolated from the turbulence signal for the study. This approach advances the traditional studies of large- and small-scale interactions in wall turbulence by focusing on the direct interactions between scales with triadic wavenumber consistency. The results are discussed in the context of modelling high Reynolds number wall turbulence.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

Patient-specific surgical planning and hemodynamic computational fluid dynamics optimization through free-form haptic anatomy editing tool (SURGEM).

PubMed

Pekkan, Kerem; Whited, Brian; Kanter, Kirk; Sharma, Shiva; de Zelicourt, Diane; Sundareswaran, Kartik; Frakes, David; Rossignac, Jarek; Yoganathan, Ajit P

2008-11-01

The first version of an anatomy editing/surgical planning tool (SURGEM) targeting anatomical complexity and patient-specific computational fluid dynamics (CFD) analysis is presented. Novel three-dimensional (3D) shape editing concepts and human-shape interaction technologies have been integrated to facilitate interactive surgical morphology alterations, grid generation and CFD analysis. In order to implement "manual hemodynamic optimization" at the surgery planning phase for patients with congenital heart defects, these tools are applied to design and evaluate possible modifications of patient-specific anatomies. In this context, anatomies involve complex geometric topologies and tortuous 3D blood flow pathways with multiple inlets and outlets. These tools make it possible to freely deform the lumen surface and to bend and position baffles through real-time, direct manipulation of the 3D models with both hands, thus eliminating the tedious and time-consuming phase of entering the desired geometry using traditional computer-aided design (CAD) systems. The 3D models of the modified anatomies are seamlessly exported and meshed for patient-specific CFD analysis. Free-formed anatomical modifications are quantified using an in-house skeletization based cross-sectional geometry analysis tool. Hemodynamic performance of the systematically modified anatomies is compared with the original anatomy using CFD. CFD results showed the relative importance of the various surgically created features such as pouch size, vena cave to pulmonary artery (PA) flare and PA stenosis. An interactive surgical-patch size estimator is also introduced. The combined design/analysis cycle time is used for comparing and optimizing surgical plans and improvements are tabulated. The reduced cost of patient-specific shape design and analysis process, made it possible to envision large clinical studies to assess the validity of predictive patient-specific CFD simulations. In this paper, model anatomical design studies are performed on a total of eight different complex patient specific anatomies. Using SURGEM, more than 30 new anatomical designs (or candidate configurations) are created, and the corresponding user times presented. CFD performances for eight of these candidate configurations are also presented.

Probing the tides in interacting galaxy pairs

NASA Technical Reports Server (NTRS)

Borne, Kirk D.

1990-01-01

Detailed spectroscopic and imaging observations of colliding elliptical galaxies revealed unmistakable diagnostic signatures of the tidal interactions. It is possible to compare both the distorted luminosity distributions and the disturbed internal rotation profiles with numerical simulations in order to model the strength of the tidal gravitational field acting within a given pair of galaxies. Using the best-fit numerical model, one can then measure directly the mass of a specific interacting binary system. This technique applies to individual pairs and therefore complements the classical methods of measuring the masses of galaxy pairs in well-defined statistical samples. The 'personalized' modeling of galaxy pairs also permits the derivation of each binary's orbit, spatial orientation, and interaction timescale. Similarly, one can probe the tides in less-detailed observations of disturbed galaxies in order to estimate some of the physical parameters for larger samples of interacting galaxy pairs. These parameters are useful inputs to the more universal problems of (1) the galaxy merger rate, (2) the strength and duration of the driving forces behind tidally stimulated phenomena (e.g., starbursts and maybe quasi steller objects), and (3) the identification of long-lived signatures of interaction/merger events.

Reputation Effects in Social Networks Do Not Promote Cooperation: An Experimental Test of the Raub & Weesie Model.

PubMed

Corten, Rense; Rosenkranz, Stephanie; Buskens, Vincent; Cook, Karen S

2016-01-01

Despite the popularity of the notion that social cohesion in the form of dense social networks promotes cooperation in Prisoner's Dilemmas through reputation, very little experimental evidence for this claim exists. We address this issue by testing hypotheses from one of the few rigorous game-theoretic models on this topic, the Raub & Weesie model, in two incentivized lab experiments. In the experiments, 156 subjects played repeated two-person PDs in groups of six. In the "atomized interactions" condition, subjects were only informed about the outcomes of their own interactions, while in the "embedded" condition, subjects were informed about the outcomes of all interactions in their group, allowing for reputation effects. The design of the experiments followed the specification of the RW model as closely as possible. For those aspects of the model that had to be modified to allow practical implementation in an experiment, we present additional analyses that show that these modifications do not affect the predictions. Contrary to expectations, we do not find that cooperation is higher in the embedded condition than in the atomized interaction. Instead, our results are consistent with an interpretation of the RW model that includes random noise, or with learning models of cooperation in networks.

Introductory lecture: interpreting and predicting Hofmeister salt ion and solute effects on biopolymer and model processes using the solute partitioning model.

PubMed

Record, M Thomas; Guinn, Emily; Pegram, Laurel; Capp, Michael

2013-01-01

Understanding how Hofmeister salt ions and other solutes interact with proteins, nucleic acids, other biopolymers and water and thereby affect protein and nucleic acid processes as well as model processes (e.g. solubility of model compounds) in aqueous solution is a longstanding goal of biophysical research. Empirical Hofmeister salt and solute "m-values" (derivatives of the observed standard free energy change for a model or biopolymer process with respect to solute or salt concentration m3) are equal to differences in chemical potential derivatives: m-value = delta(dmu2/dm3) = delta mu23, which quantify the preferential interactions of the solute or salt with the surface of the biopolymer or model system (component 2) exposed or buried in the process. Using the solute partitioning model (SPM), we dissect mu23 values for interactions of a solute or Hofmeister salt with a set of model compounds displaying the key functional groups of biopolymers to obtain interaction potentials (called alpha-values) that quantify the interaction of the solute or salt per unit area of each functional group or type of surface. Interpreted using the SPM, these alpha-values provide quantitative information about both the hydration of functional groups and the competitive interaction of water and the solute or salt with functional groups. The analysis corroborates and quantifies previous proposals that the Hofmeister anion and cation series for biopolymer processes are determined by ion-specific, mostly unfavorable interactions with hydrocarbon surfaces; the balance between these unfavorable nonpolar interactions and often-favorable interactions of ions with polar functional groups determine the series null points. The placement of urea and glycine betaine (GB) at opposite ends of the corresponding series of nonelectrolytes results from the favorable interactions of urea, and unfavorable interactions of GB, with many (but not all) biopolymer functional groups. Interaction potentials and local-bulk partition coefficients quantifying the distribution of solutes (e.g. urea, glycine betaine) and Hofmeister salt ions in the vicinity of each functional group make good chemical sense when interpreted in terms of competitive noncovalent interactions. These interaction potentials allow solute and Hofmeister (noncoulombic) salt effects on protein and nucleic acid processes to be interpreted or predicted, and allow the use of solutes and salts as probes of

Self-assembly kinetics of microscale components: A parametric evaluation

NASA Astrophysics Data System (ADS)

Carballo, Jose M.

The goal of the present work is to develop, and evaluate a parametric model of a basic microscale Self-Assembly (SA) interaction that provides scaling predictions of process rates as a function of key process variables. At the microscale, assembly by "grasp and release" is generally challenging. Recent research efforts have proposed adapting nanoscale self-assembly (SA) processes to the microscale. SA offers the potential for reduced equipment cost and increased throughput by harnessing attractive forces (most commonly, capillary) to spontaneously assemble components. However, there are challenges for implementing microscale SA as a commercial process. The existing lack of design tools prevents simple process optimization. Previous efforts have characterized a specific aspect of the SA process. However, the existing microscale SA models do not characterize the inter-component interactions. All existing models have simplified the outcome of SA interactions as an experimentally-derived value specific to a particular configuration, instead of evaluating it outcome as a function of component level parameters (such as speed, geometry, bonding energy and direction). The present study parameterizes the outcome of interactions, and evaluates the effect of key parameters. The present work closes the gap between existing microscale SA models to add a key piece towards a complete design tool for general microscale SA process modeling. First, this work proposes a simple model for defining the probability of assembly of basic SA interactions. A basic SA interaction is defined as the event where a single part arrives on an assembly site. The model describes the probability of assembly as a function of kinetic energy, binding energy, orientation and incidence angle for the component and the assembly site. Secondly, an experimental SA system was designed, and implemented to create individual SA interactions while controlling process parameters independently. SA experiments measured the outcome of SA interactions, while studying the independent effects of each parameter. As a first step towards a complete scaling model, experiments were performed to evaluate the effects of part geometry and part travel direction under low kinetic energy conditions. Experimental results show minimal dependence of assembly yield on the incidence angle of the parts, and significant effects induced by changes in part geometry. The results from this work indicate that SA could be modeled as an energy-based process due to the small path dependence effects. Assembly probability is linearly related to the orientation probability. The proportionality constant is based on the area fraction of the sites with an amplification factor. This amplification factor accounts for the ability of capillary forces to align parts with only very small areas of contact when they have a low kinetic energy. Results provide unprecedented insight about SA interactions. The present study is a key step towards completing a basic model of a general SA process. Moreover, the outcome from this work can complement existing SA process models, in order to create a complete design tool for microscale SA systems. In addition to SA experiments, Monte Carlo simulations of experimental part-site interactions were conducted. This study confirmed that a major contributor to experimental variation is the stochastic nature of experimental SA interactions and the limited sample size of the experiments. Furthermore, the simulations serve as a tool for defining an optimum sampling strategy to minimize the uncertainty in future SA experiments.

Electrostatic interaction map reveals a new binding position for tropomyosin on F-actin.

PubMed

Rynkiewicz, Michael J; Schott, Veronika; Orzechowski, Marek; Lehman, William; Fischer, Stefan

2015-12-01

Azimuthal movement of tropomyosin around the F-actin thin filament is responsible for muscle activation and relaxation. Recently a model of αα-tropomyosin, derived from molecular-mechanics and electron microscopy of different contractile states, showed that tropomyosin is rather stiff and pre-bent to present one specific face to F-actin during azimuthal transitions. However, a new model based on cryo-EM of troponin- and myosin-free filaments proposes that the interacting-face of tropomyosin can differ significantly from that in the original model. Because resolution was insufficient to assign tropomyosin side-chains, the interacting-face could not be unambiguously determined. Here, we use structural analysis and energy landscapes to further examine the proposed models. The observed bend in seven crystal structures of tropomyosin is much closer in direction and extent to the original model than to the new model. Additionally, we computed the interaction map for repositioning tropomyosin over the F-actin surface, but now extended over a much larger surface than previously (using the original interacting-face). This map shows two energy minima-one corresponding to the "blocked-state" as in the original model, and the other related by a simple 24 Å translation of tropomyosin parallel to the F-actin axis. The tropomyosin-actin complex defined by the second minimum fits perfectly into the recent cryo-EM density, without requiring any change in the interacting-face. Together, these data suggest that movement of tropomyosin between regulatory states does not require interacting-face rotation. Further, they imply that thin filament assembly may involve an interplay between initially seeded tropomyosin molecules growing from distinct binding-site regions on actin.

Specificity in transition state binding: the Pauling model revisited.

PubMed

Amyes, Tina L; Richard, John P

2013-03-26

Linus Pauling proposed that the large rate accelerations for enzymes are caused by the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogues of the transition states for enzymatic reactions often act as tight-binding inhibitors provided early support for this simple and elegant proposal. We review experimental results that support the proposal that Pauling's model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high-energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies that aimed to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-coenzyme A:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of coenzyme A (CoA) are responsible for a rate increase of 3 × 10(12)-fold, which is close to the estimated total 5 × 10(13)-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide an ~12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5'-monophosphate decarboxylase, and α-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6-8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared with that of the free enzyme. Evidence is presented that supports a model in which the binding energy of the phosphite dianion piece, or the phosphodianion group of the whole substrate, is utilized to drive an enzyme conformational change from an inactive open form E(O) to an active closed form E(C), by closure of a phosphodianion gripper loop. Members of the enolase and haloalkanoic acid dehalogenase superfamilies use variable capping domains to interact with nonreacting portions of the substrate and sequester the substrate from interaction with bulk solvent. Interactions of this capping domain with the phenyl group of mandelate have been shown to activate mandelate racemase for catalysis of deprotonation of α-carbonyl carbon. We propose that an important function of these capping domains is to utilize the binding interactions with nonreacting portions of the substrate to activate the enzyme for catalysis.

Specificity in Transition State Binding: The Pauling Model Revisited

PubMed Central

Amyes, Tina L.; Richard, John P.

2013-01-01

Linus Pauling proposed that the large rate accelerations for enzymes are due to the high specificity of the protein catalyst for binding the reaction transition state. The observation that stable analogs of the transition states for enzymatic reactions often act as tight-binding binding inhibitors provided early support for this simple and elegant proposal. We review experimental results which support the proposal that Pauling’s model provides a satisfactory explanation for the rate accelerations for many heterolytic enzymatic reactions through high energy reaction intermediates, such as proton transfer and decarboxylation. Specificity in transition state binding is obtained when the total intrinsic binding energy of the substrate is significantly larger than the binding energy observed at the Michaelis complex. The results of recent studies to characterize the specificity in binding of the enolate oxygen at the transition state for the 1,3-isomerization reaction catalyzed by ketosteroid isomerase are reviewed. Interactions between pig heart succinyl-CoA:3-oxoacid coenzyme A transferase (SCOT) and the nonreacting portions of CoA are responsible for a rate increase of 3 × 1012-fold, which is close to the estimated total 5 × 1013-fold enzymatic rate acceleration. Studies that partition the interactions between SCOT and CoA into their contributing parts are reviewed. Interactions of the protein with the substrate phosphodianion group provide a ca. 12 kcal/mol stabilization of the transition state for the reactions catalyzed by triosephosphate isomerase, orotidine 5′-monophosphate decarboxylase and α-glycerol phosphate dehydrogenase. The interactions of these enzymes with the substrate piece phosphite dianion provide a 6 – 8 kcal/mol stabilization of the transition state for reaction of the appropriate truncated substrate. Enzyme activation by phosphite dianion reflects the higher dianion affinity for binding to the enzyme-transition state complex compared with the free enzyme. Evidence is presented that supports a model in which the binding energy of the phosphite dianion piece, or the phosphodianion group of the whole substrate, is utilized to drive an enzyme conformational change from an inactive open form EO to an active closed form EC, by closure of a phosphodianion gripper loop. Members of the enolase and haloalkanoic acid dehalogenase superfamilies use variable capping domains to interact with nonreacting portions of the substrate and sequester the substrate from interaction with bulk solvent. Interactions of this capping domain with the phenyl group of mandelate have been shown to activate mandelate racemase for catalysis of deprotonation of α-carbonyl carbon. We propose that an important function of these capping domains is to utilize the binding interactions with nonreacting portions of the substrate to activate the enzyme for catalysis. PMID:23327224

Computer display and manipulation of biological molecules

NASA Technical Reports Server (NTRS)

Coeckelenbergh, Y.; Macelroy, R. D.; Hart, J.; Rein, R.

1978-01-01

This paper describes a computer model that was designed to investigate the conformation of molecules, macromolecules and subsequent complexes. Utilizing an advanced 3-D dynamic computer display system, the model is sufficiently versatile to accommodate a large variety of molecular input and to generate data for multiple purposes such as visual representation of conformational changes, and calculation of conformation and interaction energy. Molecules can be built on the basis of several levels of information. These include the specification of atomic coordinates and connectivities and the grouping of building blocks and duplicated substructures using symmetry rules found in crystals and polymers such as proteins and nucleic acids. Called AIMS (Ames Interactive Molecular modeling System), the model is now being used to study pre-biotic molecular evolution toward life.

Self-determination and sexual experience in dating relationships.

PubMed

Brunell, Amy B; Webster, Gregory D

2013-07-01

The authors propose the Model of Self-Determined Sexual Motivation to examine sexual motivation in dating relationships using a Self-Determination Theory (SDT) framework. This model predicted that sexual need satisfaction would mediate the association between self-determined sexual motives and the outcome variables of psychological well-being and relational quality. Three studies tested this model. Study 1 was a cross-sectional study that investigated sexual motivation in dating relationships. Study 2 was an event-contingent interaction record study that investigated specific sexual interactions over 2 weeks. Study 3 combined event- and interval-contingent methods using a daily diary to examine the model for both partners to enable examination of actor and partner effects. Discussion section focuses on the power of examining SDT in the sexual domain.

Identification of the HIV-1 Vif and Human APOBEC3G Protein Interface.

PubMed

Letko, Michael; Booiman, Thijs; Kootstra, Neeltje; Simon, Viviana; Ooms, Marcel

2015-12-01

Human cells express natural antiviral proteins, such as APOBEC3G (A3G), that potently restrict HIV replication. As a counter-defense, HIV encodes the accessory protein Vif, which binds A3G and mediates its proteasomal degradation. Our structural knowledge on how Vif and A3G interact is limited, because a co-structure is not available. We identified specific points of contact between Vif and A3G by using functional assays with full-length A3G, patient-derived Vif variants, and HIV forced evolution. These anchor points were used to model and validate the Vif-A3G interface. The resultant co-structure model shows that the negatively charged β4-α4 A3G loop, which contains primate-specific variation, is the core Vif binding site and forms extensive interactions with a positively charged pocket in HIV Vif. Our data present a functional map of this viral-host interface and open avenues for targeted approaches to block HIV replication by obstructing the Vif-A3G interaction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Integration of Tmc1/2 into the mechanotransduction complex in zebrafish hair cells is regulated by Transmembrane O-methyltransferase (Tomt)

PubMed Central

Erickson, Timothy; Morgan, Clive P; Olt, Jennifer; Hardy, Katherine; Busch-Nentwich, Elisabeth; Maeda, Reo; Clemens, Rachel; Krey, Jocelyn F; Nechiporuk, Alex; Barr-Gillespie, Peter G; Marcotti, Walter; Nicolson, Teresa

2017-01-01

Transmembrane O-methyltransferase (TOMT/LRTOMT) is responsible for non-syndromic deafness DFNB63. However, the specific defects that lead to hearing loss have not been described. Using a zebrafish model of DFNB63, we show that the auditory and vestibular phenotypes are due to a lack of mechanotransduction (MET) in Tomt-deficient hair cells. GFP-tagged Tomt is enriched in the Golgi of hair cells, suggesting that Tomt might regulate the trafficking of other MET components to the hair bundle. We found that Tmc1/2 proteins are specifically excluded from the hair bundle in tomt mutants, whereas other MET complex proteins can still localize to the bundle. Furthermore, mouse TOMT and TMC1 can directly interact in HEK 293 cells, and this interaction is modulated by His183 in TOMT. Thus, we propose a model of MET complex assembly where Tomt and the Tmcs interact within the secretory pathway to traffic Tmc proteins to the hair bundle. DOI: http://dx.doi.org/10.7554/eLife.28474.001 PMID:28534737

Interactions of information transfer along separable causal paths

NASA Astrophysics Data System (ADS)

Jiang, Peishi; Kumar, Praveen

2018-04-01

Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.

Micropatterned Cell–Cell Interactions Enable Functional Encapsulation of Primary Hepatocytes in Hydrogel Microtissues

PubMed Central

Li, Cheri Y.; Stevens, Kelly R.; Schwartz, Robert E.; Alejandro, Brian S.; Huang, Joanne H.

2014-01-01

Drug-induced liver injury is a major cause of drug development failures and postmarket withdrawals. In vitro models that incorporate primary hepatocytes have been shown to be more predictive than model systems which rely on liver microsomes or hepatocellular carcinoma cell lines. Methods to phenotypically stabilize primary hepatocytes ex vivo often rely on mimicry of hepatic microenvironmental cues such as cell–cell interactions and cell–matrix interactions. In this work, we sought to incorporate phenotypically stable hepatocytes into three-dimensional (3D) microtissues, which, in turn, could be deployed in drug-screening platforms such as multiwell plates and diverse organ-on-a-chip devices. We first utilize micropatterning on collagen I to specify cell–cell interactions in two-dimensions, followed by collagenase digestion to produce well-controlled aggregates for 3D encapsulation in polyethylene glycol (PEG) diacrylate. Using this approach, we examined the influence of homotypic hepatocyte interactions and composition of the encapsulating hydrogel, and achieved the maintenance of liver-specific function for over 50 days. Optimally preaggregated structures were subsequently encapsulated using a microfluidic droplet-generator to produce 3D microtissues. Interactions of engineered hepatic microtissues with drugs was characterized by flow cytometry, and yielded both induction of P450 enzymes in response to prototypic small molecules and drug–drug interactions that give rise to hepatotoxicity. Collectively, this study establishes a pipeline for the manufacturing of 3D hepatic microtissues that exhibit stabilized liver-specific functions and can be incorporated into a wide array of emerging drug development platforms. PMID:24498910

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PubMed Central

Engin, H. Billur; Guney, Emre; Keskin, Ozlem; Oliva, Baldo; Gursoy, Attila

2013-01-01

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis. PMID:24278371

Specificity of cell–cell adhesion by classical cadherins: Critical role for low-affinity dimerization through β-strand swapping

PubMed Central

Chen, Chien Peter; Posy, Shoshana; Ben-Shaul, Avinoam; Shapiro, Lawrence; Honig, Barry H.

2005-01-01

Cadherins constitute a family of cell-surface proteins that mediate intercellular adhesion through the association of protomers presented from juxtaposed cells. Differential cadherin expression leads to highly specific intercellular interactions in vivo. This cell–cell specificity is difficult to understand at the molecular level because individual cadherins within a given subfamily are highly similar to each other both in sequence and structure, and they dimerize with remarkably low binding affinities. Here, we provide a molecular model that accounts for these apparently contradictory observations. The model is based in part on the fact that cadherins bind to one another by “swapping” the N-terminal β-strands of their adhesive domains. An inherent feature of strand swapping (or, more generally, the domain swapping phenomenon) is that “closed” monomeric conformations act as competitive inhibitors of dimer formation, thus lowering affinities even when the dimer interface has the characteristics of high-affinity complexes. The model describes quantitatively how small affinity differences between low-affinity cadherin dimers are amplified by multiple cadherin interactions to establish large specificity effects at the cellular level. It is shown that cellular specificity would not be observed if cadherins bound with high affinities, thus emphasizing the crucial role of strand swapping in cell–cell adhesion. Numerical estimates demonstrate that the strength of cellular adhesion is extremely sensitive to the concentration of cadherins expressed at the cell surface. We suggest that the domain swapping mechanism is used by a variety of cell-adhesion proteins and that related mechanisms to control affinity and specificity are exploited in other systems. PMID:15937105

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.

Modelling the Impact of Soil Management on Soil Functions

NASA Astrophysics Data System (ADS)

Vogel, H. J.; Weller, U.; Rabot, E.; Stößel, B.; Lang, B.; Wiesmeier, M.; Urbanski, L.; Wollschläger, U.

2017-12-01

Due to an increasing soil loss and an increasing demand for food and energy there is an enormous pressure on soils as the central resource for agricultural production. Besides the importance of soils for biomass production there are other essential soil functions, i.e. filter and buffer for water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these functions have a direct feed back to biogeochemical cycles and climate. To render agricultural production efficient and sustainable we need to develop model tools that are capable to predict quantitatively the impact of a multitude of management measures on these soil functions. These functions are considered as emergent properties produced by soils as complex systems. The major challenge is to handle the multitude of physical, chemical and biological processes interacting in a non-linear manner. A large number of validated models for specific soil processes are available. However, it is not possible to simulate soil functions by coupling all the relevant processes at the detailed (i.e. molecular) level where they are well understood. A new systems perspective is required to evaluate the ensemble of soil functions and their sensitivity to external forcing. Another challenge is that soils are spatially heterogeneous systems by nature. Soil processes are highly dependent on the local soil properties and, hence, any model to predict soil functions needs to account for the site-specific conditions. For upscaling towards regional scales the spatial distribution of functional soil types need to be taken into account. We propose a new systemic model approach based on a thorough analysis of the interactions between physical, chemical and biological processes considering their site-specific characteristics. It is demonstrated for the example of soil compaction and the recovery of soil structure, water capacity and carbon stocks as a result of plant growth and biological activity. Coupling of the observed nonlinear interactions allows for modeling the stability and resilience of soil systems in terms of their essential functions.

Modeling conflict : research methods, quantitative modeling, and lessons learned.

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

Rexroth, Paul E.; Malczynski, Leonard A.; Hendrickson, Gerald A.

2004-09-01

This study investigates the factors that lead countries into conflict. Specifically, political, social and economic factors may offer insight as to how prone a country (or set of countries) may be for inter-country or intra-country conflict. Largely methodological in scope, this study examines the literature for quantitative models that address or attempt to model conflict both in the past, and for future insight. The analysis concentrates specifically on the system dynamics paradigm, not the political science mainstream approaches of econometrics and game theory. The application of this paradigm builds upon the most sophisticated attempt at modeling conflict as a resultmore » of system level interactions. This study presents the modeling efforts built on limited data and working literature paradigms, and recommendations for future attempts at modeling conflict.« less

Conformational Heterogeneity of the HIV Envelope Glycan Shield.

PubMed

Yang, Mingjun; Huang, Jing; Simon, Raphael; Wang, Lai-Xi; MacKerell, Alexander D

2017-06-30

To better understand the conformational properties of the glycan shield covering the surface of the HIV gp120/gp41 envelope (Env) trimer, and how the glycan shield impacts the accessibility of the underlying protein surface, we performed enhanced sampling molecular dynamics (MD) simulations of a model glycosylated HIV Env protein and related systems. Our simulation studies revealed a conformationally heterogeneous glycan shield with a network of glycan-glycan interactions more extensive than those observed to date. We found that partial preorganization of the glycans potentially favors binding by established broadly neutralizing antibodies; omission of several specific glycans could increase the accessibility of other glycans or regions of the protein surface to antibody or CD4 receptor binding; the number of glycans that can potentially interact with known antibodies is larger than that observed in experimental studies; and specific glycan conformations can maximize or minimize interactions with individual antibodies. More broadly, the enhanced sampling MD simulations described here provide a valuable tool to guide the engineering of specific Env glycoforms for HIV vaccine design.

Finding the target sites of RNA-binding proteins

PubMed Central

Li, Xiao; Kazan, Hilal; Lipshitz, Howard D; Morris, Quaid D

2014-01-01

RNA–protein interactions differ from DNA–protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA. WIREs RNA 2014, 5:111–130. doi: 10.1002/wrna.1201 PMID:24217996

Comment on "Many-body localization in Ising models with random long-range interactions"

NASA Astrophysics Data System (ADS)

Maksymov, Andrii O.; Rahman, Noah; Kapit, Eliot; Burin, Alexander L.

2017-11-01

This Comment is dedicated to the investigation of many-body localization in a quantum Ising model with long-range power-law interactions r-α, relevant for a variety of systems ranging from electrons in Anderson insulators to spin excitations in chains of cold atoms. It has earlier been argued [arXiv:cond-mat/0611387 (2005); Phys. Rev. B 91, 094202 (2015), 10.1103/PhysRevB.91.094202] that this model obeys the dimensional constraint suggesting the delocalization of all finite-temperature states in the thermodynamic limit for α ≤2 d in a d -dimensional system. This expectation conflicts with the recent numerical studies of the specific interacting spin model of Li et al. [Phys. Rev. A 94, 063625 (2016), 10.1103/PhysRevA.94.063625]. To resolve this controversy we reexamine the model of Li et al. [Phys. Rev. A 94, 063625 (2016), 10.1103/PhysRevA.94.063625] and demonstrate that the infinite-temperature states there obey the dimensional constraint. The earlier developed scaling theory for the critical system size required for delocalization is extended to small exponents 0 ≤α ≤d . The disagreements between the two works are explained by the nonstandard selection of investigated states in the ordered phase in the work of Li et al. [Phys. Rev. A 94, 063625 (2016)10.1103/PhysRevA.94.063625].

Investigation of Carbohydrate Recognition via Computer Simulation

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

Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas

Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

Investigation of Carbohydrate Recognition via Computer Simulation

DOE PAGES

Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; ...

2015-04-28

Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Regional and climate forcing on forage fish and apex predators in the California Current: new insights from a fully coupled ecosystem model.

NASA Astrophysics Data System (ADS)

Fiechter, J.; Rose, K.; Curchitser, E. N.; Huckstadt, L. A.; Costa, D. P.; Hedstrom, K.

2016-12-01

A fully coupled ecosystem model is used to describe the impact of regional and climate variability on changes in abundance and distribution of forage fish and apex predators in the California Current Large Marine Ecosystem. The ecosystem model consists of a biogeochemical submodel (NEMURO) embedded in a regional ocean circulation submodel (ROMS), and both coupled with a multi-species individual-based submodel for two forage fish species (sardine and anchovy) and one apex predator (California sea lion). Sardine and anchovy are specifically included in the model as they exhibit significant interannual and decadal variability in population abundances, and are commonly found in the diet of California sea lions. Output from the model demonstrates how regional-scale (i.e., upwelling intensity) and basin-scale (i.e., PDO and ENSO signals) physical processes control species distributions and predator-prey interactions on interannual time scales. The results also illustrate how variability in environmental conditions leads to the formation of seasonal hotspots where prey and predator spatially overlap. While specifically focused on sardine, anchovy and sea lions, the modeling framework presented here can provide new insights into the physical and biological mechanisms controlling trophic interactions in the California Current, or other regions where similar end-to-end ecosystem models may be implemented.

Bioinformatic prediction and in vivo validation of residue-residue interactions in human proteins

NASA Astrophysics Data System (ADS)

Jordan, Daniel; Davis, Erica; Katsanis, Nicholas; Sunyaev, Shamil

2014-03-01

Identifying residue-residue interactions in protein molecules is important for understanding both protein structure and function in the context of evolutionary dynamics and medical genetics. Such interactions can be difficult to predict using existing empirical or physical potentials, especially when residues are far from each other in sequence space. Using a multiple sequence alignment of 46 diverse vertebrate species we explore the space of allowed sequences for orthologous protein families. Amino acid changes that are known to damage protein function allow us to identify specific changes that are likely to have interacting partners. We fit the parameters of the continuous-time Markov process used in the alignment to conclude that these interactions are primarily pairwise, rather than higher order. Candidates for sites under pairwise epistasis are predicted, which can then be tested by experiment. We report the results of an initial round of in vivo experiments in a zebrafish model that verify the presence of multiple pairwise interactions predicted by our model. These experimentally validated interactions are novel, distant in sequence, and are not readily explained by known biochemical or biophysical features.

Investigation of specific interactions between T7 promoter and T7 RNA polymerase by force spectroscopy using atomic force microscope.

PubMed

Zhang, Xiaojuan; Yao, Zhixuan; Duan, Yanting; Zhang, Xiaomei; Shi, Jinsong; Xu, Zhenghong

2018-01-11

The specific recognition and binding of promoter and RNA polymerase is the first step of transcription initiation in bacteria and largely determines transcription activity. Therefore, direct analysis of the interaction between promoter and RNA polymerase in vitro may be a new strategy for promoter characterization, to avoid interference due to the cell's biophysical condition and other regulatory elements. In the present study, the specific interaction between T7 promoter and T7 RNA polymerase was studied as a model system using force spectroscopy based on atomic force microscope (AFM). The specific interaction between T7 promoter and T7 RNA polymerase was verified by control experiments, and the rupture force in this system was measured as 307.2 ± 6.7 pN. The binding between T7 promoter mutants with various promoter activities and T7 RNA polymerase was analyzed. Interaction information including rupture force, rupture distance and binding percentage were obtained in vitro , and reporter gene expression regulated by these promoters was also measured according to a traditional promoter activity characterization method in vivo Using correlation analysis, it was found that the promoter strength characterized by reporter gene expression was closely correlated with rupture force and the binding percentage by force spectroscopy. These results indicated that the analysis of the interaction between promoter and RNA polymerase using AFM-based force spectroscopy was an effective and valid approach for the quantitative characterization of promoters. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Modeling receptor kinetics in the analysis of survival data for organophosphorus pesticides.

PubMed

Jager, Tjalling; Kooijman, Sebastiaan A L M

2005-11-01

Acute ecotoxicological tests usually focus on survival at a standardized exposure time. However, LC50's decrease in time in a manner that depends both on the chemical and on the organism. DEBtox is an existing approach to analyze toxicity data in time, based on hazard modeling (the internal concentration increases the probability to die). However, certain chemicals elicit their response through (irreversible) interaction with a specific receptor, such as inhibition of acetylcholinesterase (AChE). Effects therefore do not solely depend on the actual internal concentration, but also on its (recent) past. In this paper, the DEBtox method is extended with a simple mechanistic model to deal with receptor interactions. We analyzed data from the literature for organophosphorus pesticides in guppies, fathead minnows, and springtails. Overall, the observed survival patterns do not clearly differ from those of chemicals with a less-specific mode of action. However, using the receptor model, resulting parameter estimates are easier to interpret in terms of underlying mechanisms and reveal similarities between the various pesticides. We observed thatthe no-effect concentration estimated from the receptor model is basically identical to the value from standard DEBtox, illustrating the robustness of this summary statistic.

Simple processes drive unpredictable differences in estuarine fish assemblages: Baselines for understanding site-specific ecological and anthropogenic impacts

NASA Astrophysics Data System (ADS)

Sheaves, Marcus

2016-03-01

Predicting patterns of abundance and composition of biotic assemblages is essential to our understanding of key ecological processes, and our ability to monitor, evaluate and manage assemblages and ecosystems. Fish assemblages often vary from estuary to estuary in apparently unpredictable ways, making it challenging to develop a general understanding of the processes that determine assemblage composition. This makes it problematic to transfer understanding from one estuary situation to another and therefore difficult to assemble effective management plans or to assess the impacts of natural and anthropogenic disturbance. Although system-to-system variability is a common property of ecological systems, rather than being random it is the product of complex interactions of multiple causes and effects at a variety of spatial and temporal scales. I investigate the drivers of differences in estuary fish assemblages, to develop a simple model explaining the diversity and complexity of observed estuary-to-estuary differences, and explore its implications for management and conservation. The model attributes apparently unpredictable differences in fish assemblage composition from estuary to estuary to the interaction of species-specific, life history-specific and scale-specific processes. In explaining innate faunal differences among estuaries without the need to invoke complex ecological or anthropogenic drivers, the model provides a baseline against which the effects of additional natural and anthropogenic factors can be evaluated.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Determinants of BH3 Binding Specificity for Mcl-1 versus Bcl-x[subscript L

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

Dutta, Sanjib; Gullá, Stefano; Chen, T. Scott

2010-06-25

Interactions among Bcl-2 family proteins are important for regulating apoptosis. Prosurvival members of the family interact with proapoptotic BH3 (Bcl-2-homology-3)-only members, inhibiting execution of cell death through the mitochondrial pathway. Structurally, this interaction is mediated by binding of the {alpha}-helical BH3 region of the proapoptotic proteins to a conserved hydrophobic groove on the prosurvival proteins. Native BH3-only proteins exhibit selectivity in binding prosurvival members, as do small molecules that block these interactions. Understanding the sequence and structural basis of interaction specificity in this family is important, as it may allow the prediction of new Bcl-2 family associations and/or the designmore » of new classes of selective inhibitors to serve as reagents or therapeutics. In this work, we used two complementary techniques - yeast surface display screening from combinatorial peptide libraries and SPOT peptide array analysis - to elucidate specificity determinants for binding to Bcl-x{sub L} versus Mcl-1, two prominent prosurvival proteins. We screened a randomized library and identified BH3 peptides that bound to either Mcl-1 or Bcl-x{sub L} selectively or to both with high affinity. The peptides competed with native ligands for binding into the conserved hydrophobic groove, as illustrated in detail by a crystal structure of a specific peptide bound to Mcl-1. Mcl-1-selective peptides from the screen were highly specific for binding Mcl-1 in preference to Bcl-x{sub L}, Bcl-2, Bcl-w, and Bfl-1, whereas Bcl-x{sub L}-selective peptides showed some cross-interaction with related proteins Bcl-2 and Bcl-w. Mutational analyses using SPOT arrays revealed the effects of 170 point mutations made in the background of a peptide derived from the BH3 region of Bim, and a simple predictive model constructed using these data explained much of the specificity observed in our Mcl-1 versus Bcl-x{sub L} binders.« less

REEPs Are Membrane Shaping Adapter Proteins That Modulate Specific G Protein-Coupled Receptor Trafficking by Affecting ER Cargo Capacity

PubMed Central

Ho, Vincent K.; Angelotti, Timothy

2013-01-01

Receptor expression enhancing proteins (REEPs) were identified by their ability to enhance cell surface expression of a subset of G protein-coupled receptors (GPCRs), specifically GPCRs that have proven difficult to express in heterologous cell systems. Further analysis revealed that they belong to the Yip (Ypt-interacting protein) family and that some REEP subtypes affect ER structure. Yip family comparisons have established other potential roles for REEPs, including regulation of ER-Golgi transport and processing/neuronal localization of cargo proteins. However, these other potential REEP functions and the mechanism by which they selectively enhance GPCR cell surface expression have not been clarified. By utilizing several REEP family members (REEP1, REEP2, and REEP6) and model GPCRs (α2A and α2C adrenergic receptors), we examined REEP regulation of GPCR plasma membrane expression, intracellular processing, and trafficking. Using a combination of immunolocalization and biochemical methods, we demonstrated that this REEP subset is localized primarily to ER, but not plasma membranes. Single cell analysis demonstrated that these REEPs do not specifically enhance surface expression of all GPCRs, but affect ER cargo capacity of specific GPCRs and thus their surface expression. REEP co-expression with α2 adrenergic receptors (ARs) revealed that this REEP subset interacts with and alter glycosidic processing of α2C, but not α2A ARs, demonstrating selective interaction with cargo proteins. Specifically, these REEPs enhanced expression of and interacted with minimally/non-glycosylated forms of α2C ARs. Most importantly, expression of a mutant REEP1 allele (hereditary spastic paraplegia SPG31) lacking the carboxyl terminus led to loss of this interaction. Thus specific REEP isoforms have additional intracellular functions besides altering ER structure, such as enhancing ER cargo capacity, regulating ER-Golgi processing, and interacting with select cargo proteins. Therefore, some REEPs can be further described as ER membrane shaping adapter proteins. PMID:24098485

Determinants of BH3 binding specificity for Mcl-1 vs. Bcl-xL

PubMed Central

Dutta, Sanjib; Gullá, Stefano; Chen, T. Scott; Fire, Emiko; Grant, Robert A.; Keating, Amy E.

2010-01-01

Interactions among Bcl-2 family proteins are important for regulating apoptosis. Pro-survival members of the family interact with pro-apoptotic BH3-only members, inhibiting execution of cell death through the mitochondrial pathway. Structurally, this interaction is mediated by binding of the alpha-helical BH3 region of the pro-apoptotic proteins to a conserved hydrophobic groove on the pro-survival proteins. Native BH3-only proteins exhibit selectivity in binding pro-survival members, as do small molecules that block these interactions. Understanding the sequence and structural basis of interaction specificity in this family is important, as it may allow the prediction of new Bcl-2 family associations and/or the design of new classes of selective inhibitors to serve as reagents or therapeutics. In this work we used two complementary techniques, yeast surface display screening from combinatorial peptide libraries and SPOT peptide array analysis, to elucidate specificity determinants for binding to Bcl-xL vs. Mcl-1, two prominent pro-survival proteins. We screened a randomized library and identified BH3 peptides that bound to either Mcl-1 or Bcl-xL selectively, or to both with high affinity. The peptides competed with native ligands for binding into the conserved hydrophobic groove, as illustrated in detail by a crystal structure of a specific peptide bound to Mcl-1. Mcl-1 selective peptides from the screen were highly specific for binding Mcl-1 in preference to Bcl-xL, Bcl-2, Bcl-w and Bfl-1, whereas Bcl-xL selective peptides showed some cross-interaction with related proteins Bcl-2 and Bcl-w. Mutational analyses using SPOT arrays revealed the effects of 170 point mutations made in the background of a peptide derived from the BH3 region of Bim, and a simple predictive model constructed using these data explained much of the specificity observed in our Mcl-1 vs. Bcl-xL binders. PMID:20363230

Models of inhibitory control

PubMed Central

Logan, Gordon D.

2017-01-01

We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’. PMID:28242727

Models and applications for space weather forecasting and analysis at the Community Coordinated Modeling Center.

NASA Astrophysics Data System (ADS)

Kuznetsova, Maria

The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) was established at the dawn of the new millennium as a long-term flexible solution to the problem of transition of progress in space environment modeling to operational space weather forecasting. CCMC hosts an expanding collection of state-of-the-art space weather models developed by the international space science community. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment and developing and maintaining custom displays and powerful web-based systems and tools ready to be used by researchers, space weather service providers and decision makers. In support of space weather needs of NASA users CCMC is developing highly-tailored applications and services that target specific orbits or locations in space and partnering with NASA mission specialists on linking CCMC space environment modeling with impacts on biological and technological systems in space. Confidence assessment of model predictions is an essential element of space environment modeling. CCMC facilitates interaction between model owners and users in defining physical parameters and metrics formats relevant to specific applications and leads community efforts to quantify models ability to simulate and predict space environment events. Interactive on-line model validation systems developed at CCMC make validation a seamless part of model development circle. The talk will showcase innovative solutions for space weather research, validation, anomaly analysis and forecasting and review on-going community-wide model validation initiatives enabled by CCMC applications.

Trans-Homolog Interactions Facilitating Paramutation in Maize

PubMed Central

2015-01-01

Paramutations represent locus-specific trans-homolog interactions affecting the heritable silencing properties of endogenous alleles. Although examples of paramutation are well studied in maize (Zea mays), the responsible mechanisms remain unclear. Genetic analyses indicate roles for plant-specific DNA-dependent RNA polymerases that generate small RNAs, and current working models hypothesize that these small RNAs direct heritable changes at sequences often acting as transcriptional enhancers. Several studies have defined specific sequences that mediate paramutation behaviors, and recent results identify a diversity of DNA-dependent RNA polymerase complexes operating in maize. Other reports ascribe broader roles for some of these complexes in normal genome function. This review highlights recent research to understand the molecular mechanisms of paramutation and examines evidence relevant to small RNA-based modes of transgenerational epigenetic inheritance. PMID:26149572

SH3 interactome conserves general function over specific form

PubMed Central

Xin, Xiaofeng; Gfeller, David; Cheng, Jackie; Tonikian, Raffi; Sun, Lin; Guo, Ailan; Lopez, Lianet; Pavlenco, Alevtina; Akintobi, Adenrele; Zhang, Yingnan; Rual, Jean-François; Currell, Bridget; Seshagiri, Somasekar; Hao, Tong; Yang, Xinping; Shen, Yun A; Salehi-Ashtiani, Kourosh; Li, Jingjing; Cheng, Aaron T; Bouamalay, Dryden; Lugari, Adrien; Hill, David E; Grimes, Mark L; Drubin, David G; Grant, Barth D; Vidal, Marc; Boone, Charles; Sidhu, Sachdev S; Bader, Gary D

2013-01-01

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form. PMID:23549480

Interplay of Laser-Plasma Interactions and Inertial Fusion Hydrodynamics.

PubMed

Strozzi, D J; Bailey, D S; Michel, P; Divol, L; Sepke, S M; Kerbel, G D; Thomas, C A; Ralph, J E; Moody, J D; Schneider, M B

2017-01-13

The effects of laser-plasma interactions (LPI) on the dynamics of inertial confinement fusion hohlraums are investigated via a new approach that self-consistently couples reduced LPI models into radiation-hydrodynamics numerical codes. The interplay between hydrodynamics and LPI-specifically stimulated Raman scatter and crossed-beam energy transfer (CBET)-mostly occurs via momentum and energy deposition into Langmuir and ion acoustic waves. This spatially redistributes energy coupling to the target, which affects the background plasma conditions and thus, modifies laser propagation. This model shows reduced CBET and significant laser energy depletion by Langmuir waves, which reduce the discrepancy between modeling and data from hohlraum experiments on wall x-ray emission and capsule implosion shape.

Transition to parenthood: the role of social interaction and endogenous networks.

PubMed

Diaz, Belinda Aparicio; Fent, Thomas; Prskawetz, Alexia; Bernardi, Laura

2011-05-01

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdependencies across individuals' transition to parenthood and its timing, we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics: age, intended education, and parity. Agents endogenously form their network based on social closeness. Network members may then influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social interactions can explain the shift of first-birth probabilities in Austria during the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Multiscale modeling and simulation of microtubule-motor-protein assemblies

NASA Astrophysics Data System (ADS)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2015-12-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule-motor-protein assemblies.

PubMed

Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J

2015-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Insights in connecting phenotypes in bacteria to coevolutionary information

NASA Astrophysics Data System (ADS)

Cheng, Ryan; Morcos, Faruck; Hayes, Ryan; Helm, Rodney; Levine, Herbert; Onuchic, Jose

It has long been known that protein sequences are far from random. These sequences have been evolutionarily selected to maintain their ability to fold into stable, three-dimensional folded structures as well as their ability to form macromolecular assemblies, perform catalytic functions, etc. For these reasons, there exist quantifiable mutational patterns in the collection of sequence data for a protein family arising from the need to maintain favorable residue-residue interactions to facilitate folding as well as cellular function. Here, we focus on studying the correlated mutational patterns that give rise to interaction specificity in bacterial two-component signaling (TCS) systems. TCS proteins have evolved to be able to preferentially bind and transfer a phosphate group to their signaling partner while avoiding phosphotransfer with non-partners. We infer a Potts model Hamiltonian governing the correlated mutational patterns that are observed in the sequence data of TCS partners and apply this model to recently published in vivo mutational data. Our findings further support the notion that statistical models built from sequence data can be used to predict bacterial phenotypes as well as engineer interaction specificity between non-partner TCS proteins. This research has been supported by the NSF INSPIRE Award (MCB-1241332) and by the CTBP sponsored by the NSF (Grant PHY- 1427654).

Life course perspectives on the epidemiology of depression.

PubMed

Colman, Ian; Ataullahjan, Anushka

2010-10-01

Life course epidemiology seeks to understand how determinants of health and disease interact across the span of a human life, and has made significant contributions to understanding etiological mechanisms in many chronic diseases, including schizophrenia. The life course approach is ideal for understanding depression: causation in depression appears to be multifactorial, including interactions between genes and stressful events, or between early life trauma and later stress in life; timing of onset and remission of depression varies widely, indicating differing trajectories of symptoms over long periods of time, with possible differing causes and differing outcomes; and early life events and development appear to be important risk factors for depression, including exposure to acute and chronic stress in the first years of life. To better understand etiology and outcome of depression, future research must move beyond basic epidemiologic techniques that link specific exposures to specific outcomes and embrace life course principles and methods. Time-sensitive modelling techniques that are able to incorporate multiple interacting factors across long periods of time, such as structural equation models, will be critical in understanding the complexity of causal and influencing factors from early development to the end stages of life. Using these models to identify key pathways that influence trajectories of depression across the life course will help guide prevention and intervention.

Multiscale modeling and simulation of microtubule–motor-protein assemblies

PubMed Central

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2016-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

Interaction studies reveal specific recognition of an anti-inflammatory polyphosphorhydrazone dendrimer by human monocytes

NASA Astrophysics Data System (ADS)

Ledall, Jérémy; Fruchon, Séverine; Garzoni, Matteo; Pavan, Giovanni M.; Caminade, Anne-Marie; Turrin, Cédric-Olivier; Blanzat, Muriel; Poupot, Rémy

2015-10-01

Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes.Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03884g

Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas

2015-01-01

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.

Do responses to different anthropogenic forcings add linearly in climate models?

DOE PAGES

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...

2015-10-14

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

PubMed Central

2010-01-01

Background Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. Results The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the FcγRIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Conclusions Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/ PMID:20691091

JETSPIN: A specific-purpose open-source software for simulations of nanofiber electrospinning

NASA Astrophysics Data System (ADS)

Lauricella, Marco; Pontrelli, Giuseppe; Coluzza, Ivan; Pisignano, Dario; Succi, Sauro

2015-12-01

We present the open-source computer program JETSPIN, specifically designed to simulate the electrospinning process of nanofibers. Its capabilities are shown with proper reference to the underlying model, as well as a description of the relevant input variables and associated test-case simulations. The various interactions included in the electrospinning model implemented in JETSPIN are discussed in detail. The code is designed to exploit different computational architectures, from single to parallel processor workstations. This paper provides an overview of JETSPIN, focusing primarily on its structure, parallel implementations, functionality, performance, and availability.

Study of vibrational modes and specific heat of wurtzite phase of BN

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

Singh, Daljit, E-mail: daljit.jt@gmail.com; Sinha, M. M.

2016-05-06

In these days of nanotechnology the materials like BN is of utmost importance as in hexagonal phase it is among hardest materials. The phonon mode study of the materials is most important factor to find structural and thermodynamcal properties. To study the phonons de launey angular force (DAF) constant model is best suited as it involves many particle interactions. Therefore in this presentation we have studied the lattice dynamical properties and specific heat of BN in wurtzite phase using DAF model. The obtained results are in excellent agreement with existing results.

Thermophysical properties of liquid rare earth metals

NASA Astrophysics Data System (ADS)

Thakor, P. B.; Sonvane, Y. A.; Patel, H. P.; Jani, A. R.

2013-06-01

The thermodynamical properties like long wavelength limit S(0), iso-thermal compressibility (χT), thermal expansion coefficient (αV), thermal pressure coefficient (γV), specific heat at constant volume (CV) and specific heat at constant pressure (CP) are calculated for liquid rare earth metals. Our newly constructed parameter free model potential is used to describe the electron ion interaction due to Sarkar et al (S) local field correction function. Lastly, we conclude that our newly constructed model potential is capable to explain the thermophysical properties of liquid rare earth metals.

Automatic determination of fault effects on aircraft functionality

NASA Technical Reports Server (NTRS)

Feyock, Stefan

1989-01-01

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

MSX-3D: a tool to validate 3D protein models using mass spectrometry.

PubMed

Heymann, Michaël; Paramelle, David; Subra, Gilles; Forest, Eric; Martinez, Jean; Geourjon, Christophe; Deléage, Gilbert

2008-12-01

The technique of chemical cross-linking followed by mass spectrometry has proven to bring valuable information about the protein structure and interactions between proteic subunits. It is an effective and efficient way to experimentally investigate some aspects of a protein structure when NMR and X-ray crystallography data are lacking. We introduce MSX-3D, a tool specifically geared to validate protein models using mass spectrometry. In addition to classical peptides identifications, it allows an interactive 3D visualization of the distance constraints derived from a cross-linking experiment. Freely available at http://proteomics-pbil.ibcp.fr

Towards Co-Engineering Communicating Autonomous Cyber-Physical Systems

NASA Technical Reports Server (NTRS)

Bujorianu, Marius C.; Bujorianu, Manuela L.

2009-01-01

In this paper, we sketch a framework for interdisciplinary modeling of space systems, by proposing a holistic view. We consider different system dimensions and their interaction. Specifically, we study the interactions between computation, physics, communication, uncertainty and autonomy. The most comprehensive computational paradigm that supports a holistic perspective on autonomous space systems is given by cyber-physical systems. For these, the state of art consists of collaborating multi-engineering efforts that prompt for an adequate formal foundation. To achieve this, we propose a leveraging of the traditional content of formal modeling by a co-engineering process.

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm.

PubMed

Lamonica, Dominique; Clément, Bernard; Charles, Sandrine; Lopes, Christelle

2016-06-01

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 μg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning. Copyright © 2016 Elsevier Inc. All rights reserved.

Group Facilitation: Functions and Skills.

ERIC Educational Resources Information Center

Anderson, L. Frances; Robertson, Sharon E.

1985-01-01

Discusses a model based on a specific set of assumptions about causality and effectiveness in interactional groups. Discusses personal qualities of group facilitators and proposes five major functions and seven skill clusters central to effective group facilitation. (Author/BH)

ACID RAIN MODELING

EPA Science Inventory

This paper provides an overview of existing statistical methodologies for the estimation of site-specific and regional trends in wet deposition. The interaction of atmospheric processes and emissions tend to produce wet deposition data patterns that show large spatial and tempora...

A Hypermedia Representation of a Taxonomy of Usability Characteristics in Virtual Environments

DTIC Science & Technology

2003-03-01

user, organization, and social workflow; needs analysis; and user modeling. A user task analysis generates critical information used throughout all...exist specific to VE user interaction [Gabbard and others, 1999]. Typically more than one person performs guidelines-based evaluations, since it’s...unlikely that any one person could identify all if not most of an interaction design’s usability problems. Nielsen [1994] recommends three to five

Effect of mutation at the interface of Trp-repressor dimeric protein: a steered molecular dynamics simulation.

PubMed

Miño, German; Baez, Mauricio; Gutierrez, Gonzalo

2013-09-01

The strength of key interfacial contacts that stabilize protein-protein interactions have been studied by computer simulation. Experimentally, changes in the interface are evaluated by generating specific mutations at one or more points of the protein structure. Here, such an evaluation is performed by means of steered molecular dynamics and use of a dimeric model of tryptophan repressor and in-silico mutants as a test case. Analysis of four particular cases shows that, in principle, it is possible to distinguish between wild-type and mutant forms by examination of the total energy and force-extension profiles. In particular, detailed atomic level structural analysis indicates that specific mutations at the interface of the dimeric model (positions 19 and 39) alter interactions that appear in the wild-type form of tryptophan repressor, reducing the energy and force required to separate both subunits.

Electronic excitation of molecules in solution calculated using the symmetry-adapted cluster–configuration interaction method in the polarizable continuum model

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

Fukuda, Ryoichi, E-mail: fukuda@ims.ac.jp; Ehara, Masahiro; Elements Strategy Initiative for Catalysts and Batteries

2015-12-31

The effects from solvent environment are specific to the electronic states; therefore, a computational scheme for solvent effects consistent with the electronic states is necessary to discuss electronic excitation of molecules in solution. The PCM (polarizable continuum model) SAC (symmetry-adapted cluster) and SAC-CI (configuration interaction) methods are developed for such purposes. The PCM SAC-CI adopts the state-specific (SS) solvation scheme where solvent effects are self-consistently considered for every ground and excited states. For efficient computations of many excited states, we develop a perturbative approximation for the PCM SAC-CI method, which is called corrected linear response (cLR) scheme. Our test calculationsmore » show that the cLR PCM SAC-CI is a very good approximation of the SS PCM SAC-CI method for polar and nonpolar solvents.« less

A Dynamic Network Model to Explain the Development of Excellent Human Performance

PubMed Central

Den Hartigh, Ruud J. R.; Van Dijk, Marijn W. G.; Steenbeek, Henderien W.; Van Geert, Paul L. C.

2016-01-01

Across different domains, from sports to science, some individuals accomplish excellent levels of performance. For over 150 years, researchers have debated the roles of specific nature and nurture components to develop excellence. In this article, we argue that the key to excellence does not reside in specific underlying components, but rather in the ongoing interactions among the components. We propose that excellence emerges out of dynamic networks consisting of idiosyncratic mixtures of interacting components such as genetic endowment, motivation, practice, and coaching. Using computer simulations we demonstrate that the dynamic network model accurately predicts typical properties of excellence reported in the literature, such as the idiosyncratic developmental trajectories leading to excellence and the highly skewed distributions of productivity present in virtually any achievement domain. Based on this novel theoretical perspective on excellent human performance, this article concludes by suggesting policy implications and directions for future research. PMID:27148140

Theory and modeling of particles with DNA-mediated interactions

NASA Astrophysics Data System (ADS)

Licata, Nicholas A.

2008-05-01

In recent years significant attention has been attracted to proposals which utilize DNA for nanotechnological applications. Potential applications of these ideas range from the programmable self-assembly of colloidal crystals, to biosensors and nanoparticle based drug delivery platforms. In Chapter I we introduce the system, which generically consists of colloidal particles functionalized with specially designed DNA markers. The sequence of bases on the DNA markers determines the particle type. Due to the hybridization between complementary single-stranded DNA, specific, type-dependent interactions can be introduced between particles by choosing the appropriate DNA marker sequences. In Chapter II we develop a statistical mechanical description of the aggregation and melting behavior of particles with DNA-mediated interactions. In Chapter III a model is proposed to describe the dynamical departure and diffusion of particles which form reversible key-lock connections. In Chapter IV we propose a method to self-assemble nanoparticle clusters using DNA scaffolds. A natural extension is discussed in Chapter V, the programmable self-assembly of nanoparticle clusters where the desired cluster geometry is encoded using DNA-mediated interactions. In Chapter VI we consider a nanoparticle based drug delivery platform for targeted, cell specific chemotherapy. In Chapter VII we present prospects for future research: the connection between DNA-mediated colloidal crystallization and jamming, and the inverse problem in self-assembly.

Mechanisms of triggering H1 helix in prion proteins unfolding revealed by molecular dynamic simulation

NASA Astrophysics Data System (ADS)

Tseng, Chih-Yuan; Lee, H. C.

2006-03-01

In template-assistance model, normal Prion protein (PrP^C), the pathogen to cause several prion diseases such as Creutzfeldt-Jakob (CJD) in human, Bovine Spongiform Encephalopathy (BSE) in cow, and scrapie in sheep, converts to infectious prion (PrP^Sc) through a transient interaction with PrP^Sc. Furthermore, conventional studies showed S1-H1-S2 region in PrP^C to be the template of S1-S2 β-sheet in PrP^Sc, and Prion protein's conformational conversion may involve an unfolding of H1 and refolding into β-sheet. Here we prepare several mouse prion peptides that contain S1-H1-S2 region with specific different structures, which are corresponding to specific interactions, to investigate possible mechanisms to trigger H1 α-helix unfolding process via molecular dynamic simulation. Three properties, conformational transition, salt-bridge in H1, and hydrophobic solvent accessible surface (SAS) are analyzed. From these studies, we found the interaction that triggers H1 unfolding to be the one that causes dihedral angle at residue Asn^143 changes. Whereas interactions that cause S1 segment's conformational changes play a minor in this process. These studies offers an additional evidence for template-assistance model.

Ovariectomy results in inbred strain-specific increases in anxiety-like behavior in mice

PubMed Central

Schoenrock, Sarah Adams; Oreper, Daniel; Young, Nancy; Ervin, Robin Betsch; Bogue, Molly A.; Valdar, William; Tarantino, Lisa M.

2017-01-01

Women are at an increased risk for developing affective disorders during times of hormonal flux, including menopause when the ovaries cease production of estrogen. However, while all women undergo menopause, not all develop an affective disorder. Increased vulnerability can result from genetic predisposition, environmental factors and gene by environment interactions. In order to investigate interactions between genetic background and estrogen depletion, we performed bilateral ovariectomy, a surgical procedure that results in estrogen depletion and is thought to model the post-menopausal state, in a genetically defined panel of 37 inbred mouse strains. Seventeen days post-ovariectomy, we assessed behavior in two standard rodent assays of anxiety- and depressive-like behavior, the open field and forced swim tests. We detected a significant interaction between ovariectomy and genetic background on anxiety-like behavior in the open field. No strain specific effects of ovariectomy were observed in the forced swim assay. However, we did observe significant strain effects for all behaviors in both the open field and forced swim tests. This study is the largest to date to look at the effects of ovariectomy on behavior and provides evidence that ovariectomy interacts with genetic background to alter anxiety-like behavior in an animal model of menopause. PMID:27693591

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

PubMed

Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

2014-07-01

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts

NASA Astrophysics Data System (ADS)

Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em

2017-01-01

Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

Modelling non-linear effects of dark energy

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Baldi, Marco; Pourtsidou, Alkistis

2018-04-01

We investigate the capabilities of perturbation theory in capturing non-linear effects of dark energy. We test constant and evolving w models, as well as models involving momentum exchange between dark energy and dark matter. Specifically, we compare perturbative predictions at 1-loop level against N-body results for four non-standard equations of state as well as varying degrees of momentum exchange between dark energy and dark matter. The interaction is modelled phenomenologically using a time dependent drag term in the Euler equation. We make comparisons at the level of the matter power spectrum and the redshift space monopole and quadrupole. The multipoles are modelled using the Taruya, Nishimichi and Saito (TNS) redshift space spectrum. We find perturbation theory does very well in capturing non-linear effects coming from dark sector interaction. We isolate and quantify the 1-loop contribution coming from the interaction and from the non-standard equation of state. We find the interaction parameter ξ amplifies scale dependent signatures in the range of scales considered. Non-standard equations of state also give scale dependent signatures within this same regime. In redshift space the match with N-body is improved at smaller scales by the addition of the TNS free parameter σv. To quantify the importance of modelling the interaction, we create mock data sets for varying values of ξ using perturbation theory. This data is given errors typical of Stage IV surveys. We then perform a likelihood analysis using the first two multipoles on these sets and a ξ=0 modelling, ignoring the interaction. We find the fiducial growth parameter f is generally recovered even for very large values of ξ both at z=0.5 and z=1. The ξ=0 modelling is most biased in its estimation of f for the phantom w=‑1.1 case.

On the validity of specific rate constants (kSA) in Fe0/H2O systems.

PubMed

Noubactep, C

2009-05-30

The validity of the specific reaction rate constants (k(SA)) in modelling contaminant removal in Fe(0)/H(2)O systems is questioned. It is shown that the current k(SA)-model does not consider the large reactive surface area provided by the in-situ formed oxide film, and thus the adsorptive interactions between contaminants and film materials. Furthermore, neither the dynamic nature of film formation nor the fact that the Fe(0) surface is shielded by the film is considered. Suggestions are made how the k(SA)-model could be further developed to meet its original goal.

Emergence of Alpha and Gamma Like Rhythms in a Large Scale Simulation of Interacting Neurons

NASA Astrophysics Data System (ADS)

Gaebler, Philipp; Miller, Bruce

2007-10-01

In the normal brain, at first glance the electrical activity appears very random. However, certain frequencies emerge during specific stages of sleep or between quiet wake states. This raises the question of whether current mathematical and computational models of interacting neurons can display similar behavior. A recent model developed by Eugene Izhikevich appears to succeed. However, early dynamical simulations used to detect these patterns were possibly compromised by an over-simplified initial condition and evolution algorithm. Utilizing the same model, but a more robust algorithm, here we present our initial results, showing that these patterns persist under a wide range of initial conditions. We employ spectral analysis of the firing patterns of a system of interacting excitatory and inhibitory neurons to demonstrate a bimodal spectrum centered on two frequencies in the range characteristic of alpha and gamma rhythms in the human brain.

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

Update - Concept of Operations for Integrated Model-Centric Engineering at JPL

NASA Technical Reports Server (NTRS)

Bayer, Todd J.; Bennett, Matthew; Delp, Christopher L.; Dvorak, Daniel; Jenkins, Steven J.; Mandutianu, Sanda

2011-01-01

The increasingly ambitious requirements levied on JPL's space science missions, and the development pace of such missions, challenge our current engineering practices. All the engineering disciplines face this growth in complexity to some degree, but the challenges are greatest in systems engineering where numerous competing interests must be reconciled and where complex system level interactions must be identified and managed. Undesired system-level interactions are increasingly a major risk factor that cannot be reliably exposed by testing, and natural-language single-viewpoint specifications areinadequate to capture and expose system level interactions and characteristics. Systems engineering practices must improve to meet these challenges, and the most promising approach today is the movement toward a more integrated and model-centric approach to mission conception, design, implementation and operations. This approach elevates engineering models to a principal role in systems engineering, gradually replacing traditional document centric engineering practices.

Some improvements in DNA interaction calculations

NASA Technical Reports Server (NTRS)

Egan, J. T.; Swissler, T. J.; Rein, R.

1974-01-01

Calculations are made on specific DNA-type complexes using refined expressions for electrostatic and polarization energies. Dispersion and repulsive terms are included in the evaluation of the total interaction energy. It is shown that the expansion of the electrostatic potential to include multipole moments up to octopole is necessary to achieve convergence of first-order energies. Polarization energies are not as sensitive to this expansion. The calculations also support the usefulness of the hard sphere model for DNA hydrogen bonds and indicate how stacking interactions are influenced by second-order energies.

UV-Visible and Infrared Methods for Investigating Lipid-Rhodopsin Membrane Interactions

PubMed Central

Brown, Michael F.

2017-01-01

Summary Experimental UV-visible and Fourier transform infrared (FTIR) spectroscopic methods are described for characterizing lipid-protein interactions for the example of rhodopsin in a membrane bilayer environment. The combined use of FTIR and UV-visible difference spectroscopy monitors the structural and functional changes during rhodopsin activation. Such studies investigate how membrane lipids stabilize the various rhodopsin photoproducts, analogous to mutating the protein. Interpretation of the results entails a non-specific flexible surface model for explaining the role of membrane lipid-protein interactions in biological functions. PMID:22976026

Radiative interactions in transient energy transfer in gaseous systems

NASA Technical Reports Server (NTRS)

Tiwari, S. N.

1985-01-01

Analyses and numerical procedures are presented to investigate the radiative interactions in transient energy transfer processes in gaseous systems. The nongray radiative formulations are based on the wide-band model correlations for molecular absorption. Various relations for the radiative flux are developed; these are useful for different flow conditions and physical problems. Specific plans for obtaining extensive results for different cases are presented. The methods presented in this study can be extended easily to investigate the radiative interactions in realistic flows of hydrogen-air species in the scramjet engine.

Mechanistic investigation of a hemostatic keratin biomaterial

NASA Astrophysics Data System (ADS)

Rahmany, Maria Bahawdory

Traumatic injury leads to more productive years lost than heart disease, cancer and stroke combined. Trauma is often accompanied and complicated by uncontrolled bleeding. Human hair keratin biomaterials have demonstrated efficacy in controlling hemorrhage in both small and large animal models; however little is known about the mechanism by which these proteins aid in blood clotting. Inspection of the amino acid sequence of known keratins shows the presence of several cellular binding motifs, suggesting a possible mechanism and potentially eliminating the need to functionalize the material's surface for cellular interaction. In addition to small animal studies, the hemostatic activity of keratin hydrogels was explored through porcine hemorrhage models representing both a high flow and low flow bleed. In both studies, keratin hydrogels appeared to lead to a significant reduction in blood loss. The promising results from these in vivo studies provided the motivation for this project. The objective of this dissertation work was to assess the mechanism of action of a hemostatic keratin biomaterial, and more broadly assess the biomaterial-cellular interaction(s). It is our hypothesis that keratin biomaterials have the capacity to specifically interact with cells and lead to propagation of intracellular signaling pathway, specifically contributing to hemostasis. Through application of biochemical and molecular tools, we demonstrate here that keratin biomaterials contribute to hemostasis through two probable mechanisms; integrin mediated platelet adhesion and increased fibrin polymerization. Platelets are the major cell type involved in coagulation both by acting as a catalytic surface for the clotting cascade and adhering to extracellular matrix (ECM) proteins providing a soft platelet plug. Because keratin biomaterials have structural and biochemical characteristics similar to ECM proteins, we utilized several adhesion assays to investigate platelet adhesion to keratin biomaterial surfaces. While other groups have discussed keratin's capacity to specifically adhere cells, this work was the first to utilize function blocking antibodies to deduce the specific receptors involved in mediating the cell-keratin interaction. To explore keratin's role in the second arm of coagulation, the clotting cascade, we followed the kinetic behavior of fibrin generation in the presence and absence of keratin. Confirmed with samples of plasma and a purified system of fibrinogen and thrombin, we observed an increased rate of fibrin polymerization in the presence of keratin proteins. The final goal of this project was to utilize a Chinese hamster ovary cell line to more specifically explore integrin-mediated cell interactions with keratin biomaterials in a controlled, biologically relevant system. Together, this work provides key details regarding keratin's hemostatic characteristics, providing the foundations for further development and optimizing of the material's unique characteristics for use as a hemostatic agent. More broadly, application of the CHO cell model could provide a useful tool for developing a receptor-ligand profile for keratin biomaterials.

Modeling the interaction between the intra-aortic balloon pump and the cardiovascular system: the effect of timing.

PubMed

Schampaert, Stéphanie; Rutten, Marcel C M; van T Veer, Marcel; van Nunen, Lokien X; Tonino, Pim A L; Pijls, Nico H J; van de Vosse, Frans N

2013-01-01

Because of the large number of interaction factors involved, the effects of the intra-aortic balloon pump (IABP) have not been investigated deeply. To enhance its clinical efficiency and to better define indications for use, advanced models are required to test the interaction between the IABP and the cardiovascular system. A patient with mild blood pressure depression and a lowered cardiac output is modeled in a lumped parameter computational model, developed with physiologically representative elements for relevant components of circulation and device. IABP support is applied, and the moments of balloon inflation and deflation are varied around their conventional timing modes. For validation purposes, timing is adapted within acceptable ranges in ten patients undergoing IABP therapy for typical clinical indications. In both model and patients, the IABP induces a diastolic blood pressure augmentation as well as a systolic reduction in afterload. The support capabilities of the IABP benefit the most when the balloon is deflated simultaneously with ventricular contraction, whereas inflation before onset of diastole unconditionally interferes with ejection. The physiologic response makes the model an excellent tool for testing the interaction between the IABP and the cardiovascular system, and how alterations of specific IABP parameters (i.e., timing) affect this coupling.

A latent modeling approach to genotype–phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype

PubMed Central

Mustanski, B.; Metzger, A.; Pine, D. S.; Kistner-Griffin, E.; Cook, E.; Wakschlag, L. S.

2013-01-01

This study illustrates the application of a latent modeling approach to genotype–phenotype relationships and gene×environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the mono-amine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N=192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA× physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA. PMID:22610759

GiPSi:a framework for open source/open architecture software development for organ-level surgical simulation.

PubMed

Cavuşoğlu, M Cenk; Göktekin, Tolga G; Tendick, Frank

2006-04-01

This paper presents the architectural details of an evolving open source/open architecture software framework for developing organ-level surgical simulations. Our goal is to facilitate shared development of reusable models, to accommodate heterogeneous models of computation, and to provide a framework for interfacing multiple heterogeneous models. The framework provides an application programming interface for interfacing dynamic models defined over spatial domains. It is specifically designed to be independent of the specifics of the modeling methods used, and therefore facilitates seamless integration of heterogeneous models and processes. Furthermore, each model has separate geometries for visualization, simulation, and interfacing, allowing the model developer to choose the most natural geometric representation for each case. Input/output interfaces for visualization and haptics for real-time interactive applications have also been provided.

Hostile Intent Attributions and Relational Aggression: The Moderating Roles of Emotional Sensitivity, Gender, and Victimization

ERIC Educational Resources Information Center

Mathieson, Lindsay C.; Murray-Close, Dianna; Crick, Nicki R.; Woods, Kathleen E.; Zimmer-Gembeck, Melanie; Geiger, Tasha C.; Morales, Julie R.

2011-01-01

The current study adopts a relational vulnerability model to examine the association between hostile attribution bias and relational aggression. Specifically, the relational vulnerability model implicates the interactive effects of a number of relational risk factors in the development of relational aggression. A sample of 635 3rd, 4th, and 5th…

Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures

NASA Astrophysics Data System (ADS)

Fujikake, So; Deringer, Volker L.; Lee, Tae Hoon; Krynski, Marcin; Elliott, Stephen R.; Csányi, Gábor

2018-06-01

We demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with graphene, graphite, and disordered carbon nanostructures, based on reference density functional theory data. Rather than treating the full Li-C system, we demonstrate how the energy and force differences arising from Li intercalation can be modeled and then added to a (prexisting and unmodified) GAP model of pure elemental carbon. Furthermore, we show the benefit of using an explicit pair potential fit to capture "effective" Li-Li interactions and to improve the performance of the GAP model. This provides proof-of-concept for modeling guest atoms in host frameworks with machine-learning based potentials and in the longer run is promising for carrying out detailed atomistic studies of battery materials.

Using machine learning tools to model complex toxic interactions with limited sampling regimes.

PubMed

Bertin, Matthew J; Moeller, Peter; Guillette, Louis J; Chapman, Robert W

2013-03-19

A major impediment to understanding the impact of environmental stress, including toxins and other pollutants, on organisms, is that organisms are rarely challenged by one or a few stressors in natural systems. Thus, linking laboratory experiments that are limited by practical considerations to a few stressors and a few levels of these stressors to real world conditions is constrained. In addition, while the existence of complex interactions among stressors can be identified by current statistical methods, these methods do not provide a means to construct mathematical models of these interactions. In this paper, we offer a two-step process by which complex interactions of stressors on biological systems can be modeled in an experimental design that is within the limits of practicality. We begin with the notion that environment conditions circumscribe an n-dimensional hyperspace within which biological processes or end points are embedded. We then randomly sample this hyperspace to establish experimental conditions that span the range of the relevant parameters and conduct the experiment(s) based upon these selected conditions. Models of the complex interactions of the parameters are then extracted using machine learning tools, specifically artificial neural networks. This approach can rapidly generate highly accurate models of biological responses to complex interactions among environmentally relevant toxins, identify critical subspaces where nonlinear responses exist, and provide an expedient means of designing traditional experiments to test the impact of complex mixtures on biological responses. Further, this can be accomplished with an astonishingly small sample size.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait.

PubMed

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E; Del-Ama, Antonio J; Dimbwadyo, Iris; Moreno, Juan C; Florez, Julian; Pons, Jose L

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait

PubMed Central

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E.; del-Ama, Antonio J.; Dimbwadyo, Iris; Moreno, Juan C.; Florez, Julian; Pons, Jose L.

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton. PMID:29755336

Fulde-Ferrell-Larkin-Ovchinnikov correlation and free fluids in the one-dimensional attractive Hubbard model

NASA Astrophysics Data System (ADS)

Cheng, Song; Yu, Yi-Cong; Batchelor, M. T.; Guan, Xi-Wen

2018-03-01

In this Rapid Communication, we show that low-energy macroscopic properties of the one-dimensional (1D) attractive Hubbard model exhibit two fluids of bound pairs and of unpaired fermions. Using the thermodynamic Bethe ansatz equations of the model, we first determine the low-temperature phase diagram and analytically calculate the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) pairing correlation function for the partially polarized phase. We then show that for such an FFLO-like state in the low-density regime the effective chemical potentials of bound pairs and unpaired fermions behave like two free fluids. Consequently, the susceptibility, compressibility, and specific heat obey simple additivity rules, indicating the "free" particle nature of interacting fermions on a 1D lattice. In contrast to the continuum Fermi gases, the correlation critical exponents and thermodynamics of the attractive Hubbard model essentially depend on two lattice interacting parameters. Finally, we study scaling functions, the Wilson ratio and susceptibility, which provide universal macroscopic properties and dimensionless constants of interacting fermions at low energy.

Modelling the effect of GRP78 on anti-oestrogen sensitivity and resistance in breast cancer

PubMed Central

Parmar, Jignesh H.; Cook, Katherine L.; Shajahan-Haq, Ayesha N.; Clarke, Pamela A. G.; Tavassoly, Iman; Clarke, Robert; Tyson, John J.; Baumann, William T.

2013-01-01

Understanding the origins of resistance to anti-oestrogen drugs is of critical importance to many breast cancer patients. Recent experiments show that knockdown of GRP78, a key gene in the unfolded protein response (UPR), can re-sensitize resistant cells to anti-oestrogens, and overexpression of GRP78 in sensitive cells can cause them to become resistant. These results appear to arise from the operation and interaction of three cellular systems: the UPR, autophagy and apoptosis. To determine whether our current mechanistic understanding of these systems is sufficient to explain the experimental results, we built a mathematical model of the three systems and their interactions. We show that the model is capable of reproducing previously published experimental results and some new data gathered specifically for this paper. The model provides us with a tool to better understand the interactions that bring about anti-oestrogen resistance and the effects of GRP78 on both sensitive and resistant breast cancer cells. PMID:24511377

Developmental fate and lineage commitment of singled mouse blastomeres.

PubMed

Lorthongpanich, Chanchao; Doris, Tham Puay Yoke; Limviphuvadh, Vachiranee; Knowles, Barbara B; Solter, Davor

2012-10-01

The inside-outside model has been invoked to explain cell-fate specification of the pre-implantation mammalian embryo. Here, we investigate whether cell-cell interaction can influence the fate specification of embryonic blastomeres by sequentially separating the blastomeres in two-cell stage mouse embryos and continuing separation after each cell division throughout pre-implantation development. This procedure eliminates information provided by cell-cell interaction and cell positioning. Gene expression profiles, polarity protein localization and functional tests of these separated blastomeres reveal that cell interactions, through cell position, influence the fate of the blastomere. Blastomeres, in the absence of cell contact and inner-outer positional information, have a unique pattern of gene expression that is characteristic of neither inner cell mass nor trophectoderm, but overall they have a tendency towards a 'trophectoderm-like' gene expression pattern and preferentially contribute to the trophectoderm lineage.

Interaction of cytoplasmic dehydrogenases: quantitation of pathways of ethanol metabolism.

PubMed

Vind, C; Grunnet, N

1983-01-01

The interaction between xylitol, alcohol and lactate dehydrogenase has been studied in hepatocytes from rats by applying specifically tritiated substrates. A simple model, describing the metabolic fate of tritium from [2-3H] xylitol and (1R) [1-3H]ethanol is presented. The model allows calculation of the specific radioactivity of free, cytosolic NADH, based on transfer of tritium to lactate, glucose and water. From the initial labelling rate of lactate and the specific radioactivity of cytosolic NADH, we have determined the reversible flow through the lactate dehydrogenase catalyzed reaction to 1-5 mumol/min . g wet wt. The results suggest that xylitol, alcohol and lactate dehydrogenase share the same pool of NAD(H) in the cytoplasma. This finding allows estimation of the ethanol oxidation rate by the non-alcohol dehydrogenase pathways from the relative yield of tritium in water and glucose. The calculations are based on a comparison of the fate of the 1-pro-R hydrogen of ethanol and the hydrogen bound to carbon 2 of xylitol or carbon 2 of lactate under identical conditions.